Sample records for xrcc3 genes predictive

  1. [Relationship between XRCC3 gene polymorphism and susceptibility to lead poisoning in male lead-exposed workers].

    PubMed

    Liu, Xiang-quan; Zhang, Zhong

    2013-06-01

    To investigate the relationship between genetic polymorphism of X-ray repair cross-complementing gene 3 (XRCC3) and susceptibility to lead poisoning in male lead-exposed workers. Peripheral venous blood and morning urine samples were collected from 326 male lead-exposed workers in a storage battery factory in Fuzhou. Blood lead, urine lead, blood zinc protoporphyrin (ZPP), blood calcium, and blood iron were measured. The genotype of XRCC3 was determined by polymerase chain reaction-restriction fragment length polymorphism method. The relationship between XRCC3 gene polymorphism and susceptibility to lead poisoning in male lead-exposed workers was analyzed. Genetic polymorphism of XRCC3 was seen in the 326 subjects. The frequency distribution of XRCC3 genotypes, XRCC3-241CC (wild type), XRCC3-241CT (heterozygous mutation), and XRCC3-241TT (homozygous mutation), was in accordance with the Hardy-Weinberg equilibrium (P > 0.05). There were no significant differences in urine lead, blood ZPP, blood calcium, and blood iron between the lead-exposed workers with different XRCC3 genotypes (P > 0.05). The workers with XRCC3-241CT/TT had a significantly higher mean blood lead level than those with XRCC3-241CC (P < 0.05). With a blood lead level of 1.90 µmol/L as the cutoff value, the chi-square test and logistic regression analysis showed that the proportion of workers with XRCC3-241CT/TT was significantly higher than that of workers with XRCC3-241CC in the subjects with high blood leads (P < 0.05) and that the risk of high blood lead was significantly higher in the workers with XRCC3-241CT/TT than in those with XRCC3-241CC (OR = 2.34, 95%CI = 1.61 ∼ 5.13); the multivariate linear regression analysis showed that the workers with XRCC3-241CT/TT had high blood lead levels (β = 0.116, P < 0.05), the workers with smoking habit demonstrated marked lead absorption (β = 0.188, P < 0.05), good individual protection could reduce lead absorption (β = -0.247, P < 0.05), and the

  2. Association between polymorphisms at promoters of XRCC5 and XRCC6 genes and risk of breast cancer.

    PubMed

    Rajaei, Mehrdad; Saadat, Iraj; Omidvari, Shahpour; Saadat, Mostafa

    2014-04-01

    Variation in DNA repair genes is one of the mechanisms that may lead to variation in DNA repair capacity. Ku, a heterodimeric DNA-binding complex, is directly involved in repair of DNA double-strand breaks. Ku consists of two subunits, Ku70 and Ku80, which are encoded by the XRCC6 and XRCC5 genes, respectively. In the present study, we investigated whether common genetic variant in variable number of tandem repeats (VNTR) XRCC5 and T-991C XRCC6 was associated with an altered risk of breast cancer. The present study included 407 females with breast cancer and 395 age frequency-matched controls which were randomly selected from the healthy female blood donors. The XRCC5 and XRCC6 polymorphisms were determined using PCR-based methods. For XRCC5 polymorphism, in comparison with the 1R/1R genotype, the 0R/0R genotype increased breast cancer risk (OR 9.55, 95%CI 1.19-76.64, P = 0.034). The 1R/3R genotype compared with 1R/1R genotype decreased the risk of breast cancer (Fisher's exact test P = 0.015). There was no association between T-991C polymorphism of XRCC6 and breast cancer risk. Mean of age at diagnosis of breast cancer for 0, 1, 2, 3, and >4 repeat in XRCC5 were 39.2, 41.9, 44.3, 45.8, and 47.3 years, respectively. The Kaplan-Meier survival analysis revealed that the number of repeat was associated with age at diagnosis of breast cancer (log rank statistic = 13.90, df = 4, P = 0.008). The findings of the present study revealed that either breast cancer risk or age at diagnosis of breast cancer was associated with the VNTR polymorphism at promoter region of XRCC5.

  3. Contribution of DNA double-strand break repair gene XRCC3 genotypes to oral cancer susceptibility in Taiwan.

    PubMed

    Tsai, Chia-Wen; Chang, Wen-Shin; Liu, Juhn-Cherng; Tsai, Ming-Hsui; Lin, Cheng-Chieh; Bau, Da-Tian

    2014-06-01

    The DNA repair gene X-ray repair cross complementing protein 3 (XRCC3) is thought to play a major role in double-strand break repair and in maintaining genomic stability. Very possibly, defective double-strand break repair of cells can lead to carcinogenesis. Therefore, a case-control study was performed to reveal the contribution of XRCC3 genotypes to individual oral cancer susceptibility. In this hospital-based research, the association of XRCC3 rs1799794, rs45603942, rs861530, rs3212057, rs1799796, rs861539, rs28903081 genotypes with oral cancer risk in a Taiwanese population was investigated. In total, 788 patients with oral cancer and 956 age- and gender-matched healthy controls were genotyped. The results showed that there was significant differential distribution among oral cancer and controls in the genotypic (p=0.001428) and allelic (p=0.0013) frequencies of XRCC3 rs861539. As for the other polymorphisms, there was no difference between case and control groups. In gene-lifestyle interaction analysis, we have provided the first evidence showing that there is an obvious joint effect of XRCC3 rs861539 genotype with individual areca chewing habits on oral cancer risk. In conclusion, the T allele of XRCC3 rs861539, which has an interaction with areca chewing habit in oral carcinogenesis, may be an early marker for oral cancer in Taiwanese. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  4. Association between genetic polymorphisms in the XRCC1, XRCC3, XPD, GSTM1, GSTT1, MSH2, MLH1, MSH3, and MGMT genes and radiosensitivity in breast cancer patients.

    PubMed

    Mangoni, Monica; Bisanzi, Simonetta; Carozzi, Francesca; Sani, Cristina; Biti, Giampaolo; Livi, Lorenzo; Barletta, Emanuela; Costantini, Adele Seniori; Gorini, Giuseppe

    2011-09-01

    Clinical radiosensitivity varies considerably among patients, and radiation-induced side effects developing in normal tissue can be therapy limiting. Some single nucleotide polymorphisms (SNPs) have been shown to correlate with hypersensitivity to radiotherapy. We conducted a prospective study of 87 female patients with breast cancer who received radiotherapy after breast surgery. We evaluated the association between acute skin reaction following radiotherapy and 11 genetic polymorphisms in DNA repair genes: XRCC1 (Arg399Gln and Arg194Trp), XRCC3 (Thr241Met), XPD (Asp312Asn and Lys751Gln), MSH2 (gIVS12-6T>C), MLH1 (Ile219Val), MSH3 (Ala1045Thr), MGMT (Leu84Phe), and in damage-detoxification GSTM1 and GSTT1 genes (allele deletion). Individual genetic polymorphisms were determined by polymerase chain reaction and single nucleotide primer extension for single nucleotide polymorphisms or by a multiplex polymerase chain reaction assay for deletion polymorphisms. The development of severe acute skin reaction (moist desquamation or interruption of radiotherapy due to toxicity) associated with genetic polymorphisms was modeled using Cox proportional hazards, accounting for cumulative biologically effective radiation dose. Radiosensitivity developed in eight patients and was increased in carriers of variants XRCC3-241Met allele (hazard ratio [HR] unquantifiably high), MSH2 gIVS12-6nt-C allele (HR=53.36; 95% confidence intervals [95% CI], 3.56-798.98), and MSH3-1045Ala allele (HR unquantifiably high). Carriers of XRCC1-Arg194Trp variant allele in combination with XRCC1-Arg399Gln wild-type allele had a significant risk of radiosensitivity (HR=38.26; 95% CI, 1.19-1232.52). To our knowledge, this is the first report to find an association between MSH2 and MSH3 genetic variants and the development of radiosensitivity in breast cancer patients. Our findings suggest the hypothesis that mismatch repair mechanisms may be involved in cellular response to radiotherapy. Genetic

  5. [Association between genetic polymorphisms of DNA repair genes XRCC1, XPD, XRCC3 and the capacity of DNA repair induce by benzene].

    PubMed

    Xu, Jianning; Yang, Min; Huang, Huilong; Wang, Quankai

    2007-09-01

    To explore the correlation between genetic polymorphisms of XRCC1, XPD, XRCC3 and DNA repair capacity induced by benzene. Eighty patients suffered from chronic benzene poisoning were investigated. PCR-RFLP was applied to detect the single nucleotide polymorphisms on C26304T, G27466A, G28152A, G36189A of XRCC1, C22541A, C23591T, A35931C of XPD, C18067T of XRCC3. Cytokinesis-block micronucleus (CBMN) and alkaline comet were applied to detect the DNA repair capacity. The DNA repair capacity of the subjects carrying XPD 35931C variant allele or carrying XRCC3 18067 C/T variant genotype were higher than those carrying corresponding mild genotype. There could be a correlation between polymorphisms of XRCC3 and DNA repair capacity of DNA damage induced by benzene.

  6. XRCC3 Thr241Met Polymorphism is not Associated with Lung Cancer Risk in a Romanian Population.

    PubMed

    Catana, Andreea; Pop, Monica; Marginean, Dragos Horea; Blaga, Ioana Cristina; Porojan, Mihai Dumitru; Popp, Radu Anghel; Pop, Ioan Victor

    2016-01-01

    Deoxyribonucleic Acid (DNA) repair mechanisms play a critical role in protecting the cellular genome against carcinogens. X-ray cross-complementing gene 3 (XRCC3) is involved in DNA repair and therefore certain genetic polymorphisms that occur in DNA repair genes may affect the ability to repair DNA defects and may represent a risk factor in carcinogenesis. The purpose of our study was to investigate the association between XRCC3 gene substitution of Threonine with Methionine in codon 241 of XRCC3 gene (Thr241Met) polymorphism and the risk of lung cancer, in a Romanian population. We recruited 93 healthy controls and 85 patients with lung cancer, all smokers. Thr241Met, XRCC3 gene genotyping was determined by multiplex Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). Statistical analysis (OR, recessive model), did not revealed an increased risk for lung cancer, for the variant 241Met allele and Thr241Met genotypes (p=0.138, OR=0.634, CI=0.348-1.157; p=0.023, OR=0.257, CI=0.085-6.824). Also, there were no positive statistical associations between Thr241Met polymorphism of XRCC3 gene, gender, tobacco and various histopathological tumor type of lung cancer. In conclusion, the results of the study suggest that the XRCC3 gene Thr241Met polymorphism is not associated with an increased risk for the development of lung cancer in this Romanian group.

  7. Genetic polymorphisms in DNA double-strand break repair genes XRCC5, XRCC6 and susceptibility to hepatocellular carcinoma.

    PubMed

    Li, Rui; Yang, Yuan; An, Yu; Zhou, Yun; Liu, Yanhong; Yu, Qing; Lu, Daru; Wang, Hongyang; Jin, Li; Zhou, Weiping; Qian, Ji; Shugart, Yin Yao

    2011-04-01

    Environmental risk factors cause DNA damages. Imprecise DNA repair leads to chromosome aberrations, genome destabilization and hepatocarcinogenesis. Ku is a key DNA double-strand break repair protein. We hypothesized that the genetic variants in Ku subunits encoding genes, XRCC5/XRCC6, may contribute to hepatocellular carcinoma (HCC) susceptibility. We genotyped 13 common single nucleotide polymorphisms (SNPs) in XRCC5 and XRCC6 and evaluated their associations with HCC risk in 689 pathologically confirmed cases and 690 cancer-free controls from a Chinese population. We found that a significantly reduced risk for HCC was associated with XRCC5 rs16855458 [odds ratio (OR)=0.59; 95% confidence interval (CI)=0.43-0.81; CA+AA versus CC] and a significantly increased risk for HCC was associated with XRCC5 rs9288516 (OR=2.02; 95% CI=1.42-2.86; TA+AA versus TT) even after Bonferroni correction (Pcorrected=0.026 and 0.002, respectively). The effects of rs16855458 (OR=0.57; 95% CI=0.37-0.86, P=0.008) and rs9288516 (OR=1.86; 95% CI=1.19-2.90, P=0.007) were more significant in hepatitis B surface antigen-infected subjects than non-infected subjects. The haplotype-based analysis revealed that in XRCC5, AA in block 1 (OR=0.63; 95% CI=0.48-0.83) and CGGTT in block 2 (OR=0.52; 95% CI=0.39-0.69) were associated with decreased HCC risk (Pcorrected=0.013 and <0.001, respectively). The aforementioned two SNPs exhibited a significant cumulative risk effect (Ptrend<0.001). Additionally, potential interaction among XRCC5 rs9288516 and rs2267437, rs5751131 in XRCC6 was indicated by the multifactor dimensionality reduction analysis. In conclusion, XRCC5 variants may play a role in determining individual's HCC susceptibility, which warranted validation in larger studies.

  8. Functional Polymorphisms of Base Excision Repair Genes XRCC1 and APEX1 Predict Risk of Radiation Pneumonitis in Patients With Non-Small Cell Lung Cancer Treated With Definitive Radiation Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yin Ming; Liao Zhongxing; Liu Zhensheng

    2011-11-01

    Purpose: To explore whether functional single nucleotide polymorphisms (SNPs) of base-excision repair genes are predictors of radiation treatment-related pneumonitis (RP), we investigated associations between functional SNPs of ADPRT, APEX1, and XRCC1 and RP development. Methods and Materials: We genotyped SNPs of ADPRT (rs1136410 [V762A]), XRCC1 (rs1799782 [R194W], rs25489 [R280H], and rs25487 [Q399R]), and APEX1 (rs1130409 [D148E]) in 165 patients with non-small cell lung cancer (NSCLC) who received definitive chemoradiation therapy. Results were assessed by both Logistic and Cox regression models for RP risk. Kaplan-Meier curves were generated for the cumulative RP probability by the genotypes. Results: We found that SNPsmore » of XRCC1 Q399R and APEX1 D148E each had a significant effect on the development of Grade {>=}2 RP (XRCC1: AA vs. GG, adjusted hazard ratio [HR] = 0.48, 95% confidence interval [CI], 0.24-0.97; APEX1: GG vs. TT, adjusted HR = 3.61, 95% CI, 1.64-7.93) in an allele-dose response manner (Trend tests: p = 0.040 and 0.001, respectively). The number of the combined protective XRCC1 A and APEX1 T alleles (from 0 to 4) also showed a significant trend of predicting RP risk (p = 0.001). Conclusions: SNPs of the base-excision repair genes may be biomarkers for susceptibility to RP. Larger prospective studies are needed to validate our findings.« less

  9. Contribution of X-Ray Repair Complementing Defective Repair in Chinese Hamster Cells 3 (XRCC3) Genotype to Leiomyoma Risk.

    PubMed

    Chang, Wen-Shin; Tsai, Chia-Wen; Wang, Ju-Yu; Ying, Tsung-Ho; Hsiao, Tsan-Seng; Chuang, Chin-Liang; Yueh, Te-Cheng; Liao, Cheng-Hsi; Hsu, Chin-Mu; Liu, Shih-Ping; Gong, Chi-Li; Tsai, Chang-Hai; Bau, Da-Tian

    2015-09-01

    The present study aimed at investigating whether X-ray repair cross complementing protein 3 (XRCC3) genotype may serve as a useful marker for detecting leiomyoma and predicting risk. A total of 640 women (166 patients with leiomyoma and 474 healthy controls) were examined for their XRCC3 rs1799794, rs45603942, rs861530, rs3212057, rs1799796, rs861539, rs28903081 genotype. The distributions of genotypic and allelic frequencies between the two groups were compared. The results showed that the CT and TT genotypes of XRCC3 rs861539 were associated with increased leiomyoma risk (odds ratio=2.19, 95% confidence interval=1.23-3.90; odds ratio=3.72, 95% confidence interval=1.23-11.26, respectively). On allelic frequency analysis, we found a significant difference in the distribution of the T allelic frequency of the XRCC3 rs861539 (p=5.88 × 10(-5)). None of the other six single nucleotide polymorphisms were associated with altered leiomyoma susceptibility. The T allele (CT and TT genotypes) of XRCC3 rs861539 contributes to increased risk of leiomyoma among Taiwanese women and may serve as a early detection and predictive marker. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  10. Tetratricopeptide-motif-mediated interaction of FANCG with recombination proteins XRCC3 and BRCA2.

    PubMed

    Hussain, Shobbir; Wilson, James B; Blom, Eric; Thompson, Larry H; Sung, Patrick; Gordon, Susan M; Kupfer, Gary M; Joenje, Hans; Mathew, Christopher G; Jones, Nigel J

    2006-05-10

    Fanconi anaemia is an inherited chromosomal instability disorder characterised by cellular sensitivity to DNA interstrand crosslinkers, bone-marrow failure and a high risk of cancer. Eleven FA genes have been identified, one of which, FANCD1, is the breast cancer susceptibility gene BRCA2. At least eight FA proteins form a nuclear core complex required for monoubiquitination of FANCD2. The BRCA2/FANCD1 protein is connected to the FA pathway by interactions with the FANCG and FANCD2 proteins, both of which co-localise with the RAD51 recombinase, which is regulated by BRCA2. These connections raise the question of whether any of the FANC proteins of the core complex might also participate in other complexes involved in homologous recombination repair. We therefore tested known FA proteins for direct interaction with RAD51 and its paralogs XRCC2 and XRCC3. FANCG was found to interact with XRCC3, and this interaction was disrupted by the FA-G patient derived mutation L71P. FANCG was co-immunoprecipitated with both XRCC3 and BRCA2 from extracts of human and hamster cells. The FANCG-XRCC3 and FANCG-BRCA2 interactions did not require the presence of other FA proteins from the core complex, suggesting that FANCG also participates in a DNA repair complex that is downstream and independent of FANCD2 monoubiquitination. Additionally, XRCC3 and BRCA2 proteins co-precipitate in both human and hamster cells and this interaction requires FANCG. The FANCG protein contains multiple tetratricopeptide repeat motifs (TPRs), which function as scaffolds to mediate protein-protein interactions. Mutation of one or more of these motifs disrupted all of the known interactions of FANCG. We propose that FANCG, in addition to stabilising the FA core complex, may have a role in building multiprotein complexes that facilitate homologous recombination repair.

  11. Predictive assessment in pharmacogenetics of XRCC1 gene on clinical outcomes of advanced lung cancer patients treated with platinum-based chemotherapy

    PubMed Central

    Yuan, Zhengrong; Li, Jiao; Hu, Ruiqi; Jiao, Yang; Han, Yingying; Weng, Qiang

    2015-01-01

    Published data have shown inconsistent results about the pharmacogenetics of XRCC1 gene on clinical outcomes of advanced lung cancer patients treated with platinum-based chemotherapy. This meta-analysis aimed to summarize published findings and provide more reliable association. A total of 53 eligible studies including 7433 patients were included. Patients bearing the favorable TrpTrp and TrpArg genotypes of Arg194Trp were more likely to better response rates to platinum-based chemotherapy compared to those with the unfavorable ArgArg genotype (TrpTrp+TrpArg vs. ArgArg: odds ratio (OR) = 2.02, 95% CI, 1.66–2.45). The GlnGln and GlnArg genotypes of Arg399Gln were significantly associated with the poorer response rates compared to those with the ArgArg genotype (GlnGln +GlnArg vs. ArgArg: OR = 0.68, 95% CI, 0.54–0.86). The GlnGln genotype might be more closely associated with shorter survival time and higher risks of death for patients (GlnGln vs. ArgArg: hazard ratio (HR) = 1.14, 95% CI, 0.75–1.75). Our cumulative meta-analyses indicated a distinct apparent trend toward a better response rate for Arg194Trp, but a poorer response rate in Arg399Gln. These findings indicate a predictive role of XRCC1 polymorphisms in clinical outcomes. The use of XRCC1 polymorphisms as predictive factor of clinical outcomes in personalized chemotherapy treatment requires further verification from large well-designed pharmacogenetics studies. PMID:26585370

  12. Complementation of hypersensitivity to DNA interstrand crosslinking agents demonstrates that XRCC2 is a Fanconi anaemia gene.

    PubMed

    Park, Jung-Young; Virts, Elizabeth L; Jankowska, Anna; Wiek, Constanze; Othman, Mohamed; Chakraborty, Sujata C; Vance, Gail H; Alkuraya, Fowzan S; Hanenberg, Helmut; Andreassen, Paul R

    2016-10-01

    Fanconi anaemia (FA) is a heterogeneous inherited disorder clinically characterised by progressive bone marrow failure, congenital anomalies and a predisposition to malignancies. Determine, based on correction of cellular phenotypes, whether XRCC2 is a FA gene. Cells (900677A) from a previously identified patient with biallelic mutation of XRCC2, among other mutations, were genetically complemented with wild-type XRCC2. Wild-type XRCC2 corrects each of three phenotypes characteristic of FA cells, all related to the repair of DNA interstrand crosslinks, including increased sensitivity to mitomycin C (MMC), chromosome breakage and G2-M accumulation in the cell cycle. Further, the p.R215X mutant of XRCC2, which is harboured by the patient, is unstable. This provides an explanation for the pathogenesis of this mutant, as does the fact that 900677A cells have reduced levels of other proteins in the XRCC2-RAD51B-C-D complex. Also, FANCD2 monoubiquitination and foci formation, but not assembly of RAD51 foci, are normal in 900677A cells. Thus, XRCC2 acts late in the FA-BRCA pathway as also suggested by hypersensitivity of 900677A cells to ionising radiation. These cells also share milder sensitivities towards olaparib and formaldehyde with certain other FA cells. XRCC2/FANCU is a FA gene, as is another RAD51 paralog gene, RAD51C/FANCO. Notably, similar to a subset of FA genes that act downstream of FANCD2, biallelic mutation of XRCC2/FANCU has not been associated with bone marrow failure. Taken together, our results yield important insights into phenotypes related to FA and its genetic origins. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  13. XRCC1 suppresses somatic hypermutation and promotes alternative nonhomologous end joining in Igh genes.

    PubMed

    Saribasak, Huseyin; Maul, Robert W; Cao, Zheng; McClure, Rhonda L; Yang, William; McNeill, Daniel R; Wilson, David M; Gearhart, Patricia J

    2011-10-24

    Activation-induced deaminase (AID) deaminates cytosine to uracil in immunoglobulin genes. Uracils in DNA can be recognized by uracil DNA glycosylase and abasic endonuclease to produce single-strand breaks. The breaks are repaired either faithfully by DNA base excision repair (BER) or mutagenically to produce somatic hypermutation (SHM) and class switch recombination (CSR). To unravel the interplay between repair and mutagenesis, we decreased the level of x-ray cross-complementing 1 (XRCC1), a scaffold protein involved in BER. Mice heterozygous for XRCC1 showed a significant increase in the frequencies of SHM in Igh variable regions in Peyer's patch cells, and of double-strand breaks in the switch regions during CSR. Although the frequency of CSR was normal in Xrcc1(+/-) splenic B cells, the length of microhomology at the switch junctions decreased, suggesting that XRCC1 also participates in alternative nonhomologous end joining. Furthermore, Xrcc1(+/-) B cells had reduced Igh/c-myc translocations during CSR, supporting a role for XRCC1 in microhomology-mediated joining. Our results imply that AID-induced single-strand breaks in Igh variable and switch regions become substrates simultaneously for BER and mutagenesis pathways.

  14. XRCC3 polymorphism is associated with hypertension-induced left ventricular hypertrophy.

    PubMed

    Ariyandy, Andi; Sakai, Chiemi; Ishida, Mari; Mizuta, Ryusei; Miyagawa, Kiyoshi; Tashiro, Satoshi; Kinomura, Aiko; Hiraaki, Koji; Ueda, Keitaro; Yoshizumi, Masao; Ishida, Takafumi

    2018-06-01

    Deficiency of X-ray repair cross-complementing protein 3 (XRCC3), a DNA-damage repair molecule, and the 241Met variant of XRCC3 have been reported to increase endoreduplication, which induces polyploidy. The aims of this study were to determine the impact of the XRCC3 polymorphism on the incidence of hypertension-induced left ventricular hypertrophy (LVH) and to investigate the mechanisms underlying any potential relationship. Patients undergoing chronic hemodialysis (n = 77) were genotyped to assess for the XRCC3 Thr241Met polymorphism. The XRCC3 241Thr/Met genotype was more frequent in the LVH (+) group than in the LVH (-) group (42.3 vs. 13.7%, χ2 = 7.85, p = 0.0051). To investigate possible mechanisms underlying these observations, human XRCC3 cDNA of 241Thr or that of 241Met was introduced into cultured CHO cells. The surface area of CHO cells expressing XRCC3 241Met was larger than that expressing 241Thr. Spontaneous DNA double-strand breaks accumulated to a greater degree in NIH3T3 cells expressing 241Met (3T3-241Met) than in those expressing 241Thr (3T3-241Thr). DNA damage caused by radiation induced cell senescence more frequently in 3T3-241Met. The levels of basal and TNF-α-stimulated MCP-1 mRNA and protein secretion were higher in 3T3-241Met. Finally, FACS analysis revealed that the cell percentage in G2/M phase including polyploidy was significantly higher in 3T3-241Met than in 3T3-241Thr. Furthermore, the basal level of MCP-1 mRNA positively correlated with the cell percentage in G2/M phase and polyploidy. These data suggest that the XRCC3 241Met increases the risk of LVH via accumulation of DNA damage, thereby altering cell cycle progression and inducing cell senescence and a proinflammatory phenotype.

  15. Genetic variation in DNA repair gene XRCC7 (G6721T) and susceptibility to breast cancer.

    PubMed

    Nasiri, Meysam; Saadat, Iraj; Omidvari, Shahpour; Saadat, Mostafa

    2012-08-15

    The human XRCC7 is a DNA double-strand break (DSBs) repair gene, involved in non-homologous end joining (NHEJ). It is speculated that DNA DSBs repair have an important role during development of breast cancer. The human XRCC7 is a NHEJ DSBs repair gene. Genetic variation G6721T of XRCC7 (rs7003908) is located in the intron 8 of the gene. This polymorphism may regulate splicing and cause mRNA instability. In the present study, we specifically investigated whether common G6721T genetic variant of XRCC7 was associated with an altered risk of breast cancer. The present study included 362 females with breast cancer. Age frequency-matched controls (362 persons) were randomly selected from the healthy female blood donors, according to the age distribution of the cases. Using RFLP-PCR based method, the polymorphism of XRCC7 was determined. The TG (OR=1.20, 95% CI: 0.83-1.74, P=0.320) and TT (OR=1.01, 95% CI: 0.67-1.53, P=0.933) genotypes had no significant effect on risk of breast cancer, in comparison with the GG genotype. Our present findings indicate that the TT and TG genotypes were not associated with an altered breast cancer risk. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. Impact of DNA repair genes polymorphism (XPD and XRCC1) on the risk of breast cancer in Egyptian female patients.

    PubMed

    Hussien, Yousry Mostafa; Gharib, Amal F; Awad, Hanan A; Karam, Rehab A; Elsawy, Wael H

    2012-02-01

    The genes involved in DNA repair system play a crucial role in the protection against mutations. It has been hypothesized that functional deficiencies in highly conserved DNA repair processes resulting from polymorphic variation may increase genetic susceptibility to breast cancer (BC). The aim of the present study was to evaluate the association of genetic polymorphisms in 2 DNA repair genes, XPD (Asp312Asn) and XRCC1 (A399G), with BC susceptibility. We further investigated the potential combined effect of these DNA repair variants on BC risk. Both XPD (xeroderma pigmentosum group D) and XRCC1 (X-ray repair cross-complementing group 1) polymorphisms were characterized in 100 BC Egyptian females and 100 healthy women who had no history of any malignancy by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) method and PCR with confronting two-pair primers (PCR-CTPP), using DNA from peripheral blood in a case control study. Our results revealed that the frequencies of AA genotype of XPD codon 312 polymorphism were significantly higher in the BC patients than in the normal individuals (P ≤ 0.003), and did not observe any association between the XRCC1 Arg399Gln polymorphism and risk of developing BC. Also, no association between both XPD Asp312Asn and XRCC1 A399G polymorphisms and the clinical characteristics of disease. Finally, the combination of AA(XPD) + AG(XRCC1) were significantly associated with BC risk. Our results suggested that, XPD gene is an important candidate gene for susceptibility to BC. Also, gene-gene interaction between XPD(AA) + XRCC1(AG) polymorphism may be associated with increased risk of BC in Egyptian women.

  17. Oxidative Stress in Mammalian Cells Impinges on the Cysteines Redox State of Human XRCC3 Protein and on Its Cellular Localization

    PubMed Central

    Girard, Pierre-Marie; Graindorge, Dany; Smirnova, Violetta; Rigolet, Pascal; Francesconi, Stefania; Scanlon, Susan; Sage, Evelyne

    2013-01-01

    In vertebrates, XRCC3 is one of the five Rad51 paralogs that plays a central role in homologous recombination (HR), a key pathway for maintaining genomic stability. While investigating the potential role of human XRCC3 (hXRCC3) in the inhibition of DNA replication induced by UVA radiation, we discovered that hXRCC3 cysteine residues are oxidized following photosensitization by UVA. Our in silico prediction of the hXRCC3 structure suggests that 6 out of 8 cysteines are potentially accessible to the solvent and therefore potentially exposed to ROS attack. By non-reducing SDS-PAGE we show that many different oxidants induce hXRCC3 oxidation that is monitored in Chinese hamster ovarian (CHO) cells by increased electrophoretic mobility of the protein and in human cells by a slight decrease of its immunodetection. In both cell types, hXRCC3 oxidation was reversed in few minutes by cellular reducing systems. Depletion of intracellular glutathione prevents hXRCC3 oxidation only after UVA exposure though depending on the type of photosensitizer. In addition, we show that hXRCC3 expressed in CHO cells localizes both in the cytoplasm and in the nucleus. Mutating all hXRCC3 cysteines to serines (XR3/S protein) does not affect the subcellular localization of the protein even after exposure to camptothecin (CPT), which typically induces DNA damages that require HR to be repaired. However, cells expressing mutated XR3/S protein are sensitive to CPT, thus highlighting a defect of the mutant protein in HR. In marked contrast to CPT treatment, oxidative stress induces relocalization at the chromatin fraction of both wild-type and mutated protein, even though survival is not affected. Collectively, our results demonstrate that the DNA repair protein hXRCC3 is a target of ROS induced by environmental factors and raise the possibility that the redox environment might participate in regulating the HR pathway. PMID:24116071

  18. Interactions involving the Rad51 paralogs Rad51C and XRCC3 in human cells

    NASA Technical Reports Server (NTRS)

    Wiese, Claudia; Collins, David W.; Albala, Joanna S.; Thompson, Larry H.; Kronenberg, Amy; Schild, David; Chatterjee, A. (Principal Investigator)

    2002-01-01

    Homologous recombinational repair of DNA double-strand breaks and crosslinks in human cells is likely to require Rad51 and the five Rad51 paralogs (XRCC2, XRCC3, Rad51B/Rad51L1, Rad51C/Rad51L2 and Rad51D/Rad51L3), as has been shown in chicken and rodent cells. Previously, we reported on the interactions among these proteins using baculovirus and two- and three-hybrid yeast systems. To test for interactions involving XRCC3 and Rad51C, stable human cell lines have been isolated that express (His)6-tagged versions of XRCC3 or Rad51C. Ni2+-binding experiments demonstrate that XRCC3 and Rad51C interact in human cells. In addition, we find that Rad51C, but not XRCC3, interacts directly or indirectly with Rad51B, Rad51D and XRCC2. These results argue that there are at least two complexes of Rad51 paralogs in human cells (Rad51C-XRCC3 and Rad51B-Rad51C-Rad51D-XRCC2), both containing Rad51C. Moreover, Rad51 is not found in these complexes. X-ray treatment did not alter either the level of any Rad51 paralog or the observed interactions between paralogs. However, the endogenous level of Rad51C is moderately elevated in the XRCC3-overexpressing cell line, suggesting that dimerization between these proteins might help stabilize Rad51C.

  19. [Analysis for the association between genetic polymorphisms of XRCC1, XPD, XRCC3, CCND1 and the latency of the occupational chronic benzene poisoning].

    PubMed

    Xu, Jian-ning; Huang, Hui-long; Wang, Quan-kai; Wang, Ya-wen; Yang, Min; Zheng, Yu-xin

    2007-03-01

    To explore the association between genetic polymorphisms of XRCC1, XPD, XRCC3 and CCND1 and latency of occupational chronic benzene poisoning. 80 patients diagnosed with occupational chronic benzene poisoning were investigated. PCR-RFLP was applied to detect the single nucleotide polymorphisms of C26304T, G27466A, G28152A, G36189A of XRCC1, C22541A, C23591T, A35931C of XPD, C18067T of XRCC3 and G870A of CCND1. Their relationship with the latency of chronic benzene poisoning was analyzed by Kaplan-Meier method. The association of XRCC1 G27466A subgroup with the latency of chronic benzene poisoning was observed, as well as that of CCDN1G870A subgroup. The benzene-exposed workers with XRCC1 27466G/G homozygous wild genotype developed chronic benzene poisoning 6.9 years later than those had homozygous (27466A/A) or heterozygous (27466G/A) mutant alleles. On the other hand, the latency developing chronic benzene poisoning was longer in workers with homozygous (CCND1 870A/A) or heterozygous (CCND1 870G/A) mutant alleles than in those carrying 870G/G homozygous wild genotype (14.9 vs. 8.7 years). The polymorphisms of XRCC1 and CCND1 potentially modify the latency of the chronic benzene poisoning among workers exposed to benzene.

  20. Exploring the deleterious SNPs in XRCC4 gene using computational approach and studying their association with breast cancer in the population of West India.

    PubMed

    Singh, Preety K; Mistry, Kinnari N; Chiramana, Haritha; Rank, Dharamshi N; Joshi, Chaitanya G

    2018-05-20

    Non-homologous end joining (NHEJ) pathway has pivotal role in repair of double-strand DNA breaks that may lead to carcinogenesis. XRCC4 is one of the essential proteins of this pathway and single-nucleotide polymorphisms (SNPs) of this gene are reported to be associated with cancer risks. In our study, we first used computational approaches to predict the damaging variants of XRCC4 gene. Tools predicted rs79561451 (S110P) nsSNP as the most deleterious SNP. Along with this SNP, we analysed other two SNPs (rs3734091 and rs6869366) to study their association with breast cancer in population of West India. Variant rs3734091 was found to be significantly associated with breast cancer while rs6869366 variant did not show any association. These SNPs may influence the susceptibility of individuals to breast cancer in this population. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Analysis of difference of association between polymorphisms in the XRCC5, RPA3 and RTEL1 genes and glioma, astrocytoma and glioblastoma.

    PubMed

    Jin, Tianbo; Wang, Yuan; Li, Gang; Du, Shuli; Yang, Hua; Geng, Tingting; Hou, Peng; Gong, Yongkuan

    2015-01-01

    Gliomas are the most common aggressive brain tumors and have many complex pathological types. Previous reports have discovered that genetic mutations are associated with the risk of glioma. However, it is unclear whether uniform genetic mutations exist difference between glioma and its two pathological types in the Han Chinese population. We evaluated 20 SNPs of 703 glioma cases (338 astrocytoma cases, 122 glioblastoma cases) and 635 controls in a Han Chinese population using χ(2) test and genetic model analysis. In three case-control studies, we found rs9288516 in XRCC5 gene showed a decreased risk of glioma (OR, 0.85; 95% CI, 0.73-0.99; P = 0.042) and glioblastoma (OR, 0.70; 95% CI, 0.52-0.92; P = 0.001) in the allele model. We identified rs414805 in RPA3 gene showed an increased risk of glioblastoma in allele model (OR, 1.38; 95% CI, 1.00-1.89; P = 0.047) and dominant model (OR, 1.57; 95% CI, 1.05-2.35; P = 0.027), analysis respectively. Meanwhile, rs2297440 in RTEL1 gene showed an increased risk of glioma (OR, 1.30; 95% CI, 1.10-1.54; P = 0.002) and astrocytoma (OR, 1.26; 95% CI, 1.02-1.54; P = 0.029) in the allele model. In addition, we also observed a haplotype of "GCT" in the RTEL1 gene with an increased risk of astrocytoma (P = 0.005). Polymorphisms in the XRCC5, RPA3 and RTEL1 genes, combinating with previous reaserches, are associated with glioma developing. However, those genes mutations may play different roles in the glioma, astrocytoma and glioblastoma, respectively.

  2. DNA repair gene XRCC1 polymorphisms, smoking, and bladder cancer risk.

    PubMed

    Stern, M C; Umbach, D M; van Gils, C H; Lunn, R M; Taylor, J A

    2001-02-01

    Bladder cancer is the sixth most common cancer in the United States. The main identified risk factor is cigarette smoking, which is estimated to contribute to up to 50% of new cases in men and 20% in women. Besides containing other carcinogens, cigarette smoke is a rich source of reactive oxygen species (ROS) that can induce a variety of DNA damage, some of which is repaired by the base excision repair (BER) pathway. The XRCC1 gene protein plays an important role in BER by serving as a scaffold for other repair enzymes and by recognizing single-strand DNA breaks. Three polymorphisms that induce amino acid changes have been found in codon 194 (exon 6), codon 280 (exon 9), and codon 399 (exon 10) of this gene. We tested whether polymorphisms in XRCC1 were associated with bladder cancer risk and whether this association was modified by cigarette smoking. Therefore, we genotyped for the three polymorphisms in 235 bladder cancer cases and 213 controls who had been frequency matched to cases on age, sex, and ethnicity. We found no evidence of an association between the codon 280 variant and bladder cancer risk [odds ratio (OR), 1.2; 95% confidence interval (CI), 0.6-2.6]. We found some evidence of a protective effect for subjects that carried at least one copy of the codon 194 variant allele relative to those homozygous for the common allele (OR, 0.59; 95% CI, 0.3-1.0). The combined analysis with smoking history suggested a possible gene-exposure interaction; however, the results were not statistically significant. Similarly, for the codon 399 polymorphism, our data suggested a protective effect of the homozygous variant genotype relative to carriers of either one or two copies of the common allele (OR, 0.70; 95% CI, 0.4-1.3), and provided limited evidence, albeit not statistically significant, for a gene-smoking interaction.

  3. Analysis of difference of association between polymorphisms in the XRCC5, RPA3 and RTEL1 genes and glioma, astrocytoma and glioblastoma

    PubMed Central

    Jin, Tianbo; Wang, Yuan; Li, Gang; Du, Shuli; Yang, Hua; Geng, Tingting; Hou, Peng; Gong, Yongkuan

    2015-01-01

    Background: Gliomas are the most common aggressive brain tumors and have many complex pathological types. Previous reports have discovered that genetic mutations are associated with the risk of glioma. However, it is unclear whether uniform genetic mutations exist difference between glioma and its two pathological types in the Han Chinese population. Materials and methods: We evaluated 20 SNPs of 703 glioma cases (338 astrocytoma cases, 122 glioblastoma cases) and 635 controls in a Han Chinese population using χ2 test and genetic model analysis. Results: In three case-control studies, we found rs9288516 in XRCC5 gene showed a decreased risk of glioma (OR, 0.85; 95% CI, 0.73-0.99; P = 0.042) and glioblastoma (OR, 0.70; 95% CI, 0.52-0.92; P = 0.001) in the allele model. We identified rs414805 in RPA3 gene showed an increased risk of glioblastoma in allele model (OR, 1.38; 95% CI, 1.00-1.89; P = 0.047) and dominant model (OR, 1.57; 95% CI, 1.05-2.35; P = 0.027), analysis respectively. Meanwhile, rs2297440 in RTEL1 gene showed an increased risk of glioma (OR, 1.30; 95% CI, 1.10-1.54; P = 0.002) and astrocytoma (OR, 1.26; 95% CI, 1.02-1.54; P = 0.029) in the allele model. In addition, we also observed a haplotype of “GCT” in the RTEL1 gene with an increased risk of astrocytoma (P = 0.005). Conclusions: Polymorphisms in the XRCC5, RPA3 and RTEL1 genes, combinating with previous reaserches, are associated with glioma developing. However, those genes mutations may play different roles in the glioma, astrocytoma and glioblastoma, respectively. PMID:26328260

  4. Homologous recombination as a potential target for caffeine radiosensitization in mammalian cells: reduced caffeine radiosensitization in XRCC2 and XRCC3 mutants

    NASA Technical Reports Server (NTRS)

    Asaad, N. A.; Zeng, Z. C.; Guan, J.; Thacker, J.; Iliakis, G.

    2000-01-01

    The radiosensitizing effect of caffeine has been associated with the disruption of multiple DNA damage-responsive cell cycle checkpoints, but several lines of evidence also implicate inhibition of DNA repair. The role of DNA repair inhibition in caffeine radiosensitization remains uncharacterized, and it is unknown which repair process, or lesion, is affected. We show that a radiosensitive cell line, mutant for the RAD51 homolog XRCC2 and defective in homologous recombination repair (HRR), displays significantly diminished caffeine radiosensitization that can be restored by expression of XRCC2. Despite the reduced radiosensitization, caffeine effectively abrogates checkpoints in S and G2 phases in XRCC2 mutant cells indicating that checkpoint abrogation is not sufficient for radiosensitization. Another radiosensitive line, mutant for XRCC3 and defective in HRR, similarly shows reduced caffeine radiosensitization. On the other hand, a radiosensitive mutant (irs-20) of DNA-PKcs with a defect in non-homologous end-joining (NHEJ) is radiosensitized by caffeine to an extent comparable to wild-type cells. In addition, rejoining of radiation-induced DNA DSBs, that mainly reflects NHEJ, remains unaffected by caffeine in XRCC2 and XRCC3 mutants, or their wild-type counterparts. These observations suggest that caffeine targets steps in HRR but not in NHEJ and that abrogation of checkpoint response is not sufficient to explain radiosensitization. Indeed, immortalized fibroblasts from AT patients show caffeine radiosensitization despite the checkpoint defects associated with ATM mutation. We propose that caffeine radiosensitization is mediated by inhibition of stages in DNA DSB repair requiring HRR and that checkpoint disruption contributes by allowing these DSBs to transit into irreparable states. Thus, checkpoints may contribute to genomic stability by promoting error-free HRR.

  5. Implications of XRCC1, XPD and APE1 gene polymorphism in North Indian population: a comparative approach in different ethnic groups worldwide.

    PubMed

    Gangwar, Ruchika; Manchanda, Parmeet Kaur; Mittal, Rama Devi

    2009-05-01

    Identifying risk factors for human cancers should consider combinations of genetic variations and environmental exposures. Several polymorphisms in DNA repair genes have impact on repair and cancer susceptibility. We focused on X-ray repair cross-complementing group 1 (XRCC1), Xeroderma pigmentosum D (XPD) and apurinic/apyrimidinic endonuclease (APE1) as these are most extensively studied in cancer. Present study was conducted to determine distribution of XRCC1 C26304T, G27466A, G23591A, APE1 T2197G and XPD A35931C gene polymorphisms in North Indian population and compare with different populations globally. PCR-based analysis was conducted in 209 normal healthy individuals of similar ethnicity. Allelic frequencies in wild type of XRCC1 C26304T were 91.1% C(Arg); G27466A 62.9% G(Arg); G23591A 60.3% G(Arg); APE1 T2197G 75.1% T(Asp) and XPD A35931C 71.8% A(Lys). The variant allele frequency were 8.9% T(Trp) in XRCC1 C26304T; 37.1% A(His) in G27466A; 39.7% A(Gln) in G23591A; 24.9% G(Glu) in APE1 and 28.2% C(Gln) in XPD respectively. We further compared frequency distribution for these genes with various published studies in different ethnicity. Our results suggest that frequency in these DNA repair genes exhibit distinctive pattern in India that could be attributed to ethnicity variation. This could assist in high-risk screening of humans exposed to environmental carcinogens and cancer predisposition in different ethnic groups.

  6. Evaluation of Prediction of Polymorphisms of DNA Repair Genes on the Efficacy of Platinum-Based Chemotherapy in Patients With Non-Small Cell Lung Cancer: A Network Meta-Analysis.

    PubMed

    Yu, Shao-Nan; Liu, Gui-Feng; Li, Xue-Feng; Fu, Bao-Hong; Dong, Li-Xin; Zhang, Shu-Hua

    2017-12-01

    This network meta-analysis (NMA) was conducted to compare the predictive value of 14 SNPs in eight DNA repair genes on the efficacy of platinum-based chemotherapy in patients with non-small cell lung cancer (NSCLC). These included ERCC1 (rs11615, rs3212986, rs3212948), XRCC1 (rs25487, rs25489, rs1799782), XPD (rs13181, rs1799793), XPG (rs1047768, rs17655), XPA (rs1800975), XRCC3 (rs861539), APE1 (rs3136820), and RRM1 (rs1042858). The PubMed and Cochrane library databases were reviewed from their inception to February 2017 and studies which met our inclusion criteria were included in our investigation. This network meta-analysis combines direct and indirect evidence to assess the predictive value of 14 SNPs in eight DNA repair genes on the efficacy of platinum-based chemotherapy in NSCLC. We evaluated the predictive value through the use of the odd ratios (OR) and drawing surface under the cumulative ranking curves (SUCRA). A total of 26 eligible cohort studies were enrolled in this NMA. The pairwise meta-analysis indicated that in terms of overall response ratio (ORR), ERCC1 (rs11615), XRCC1 (rs25487, rs1799782), and XPD (rs13181) polymorphisms are associated with the efficacy of platinum-based chemotherapy in NSCLC. The result of this NMA suggests that there is no significant difference in predictive value of 8 DNA repair genes on the efficacy of platinum-based chemotherapy in NSCLC patients. The rank of SUCRA values of the 14 SNPs in the eight DNA repair genes were: XPD (rs1799793)→ERCC1 (rs3212986)→XPA(rs1800975)→ERCC1(rs3212948)→XRCC1(rs25487)→XRCC3(rs861539)→APE1(rs3136820)→ERCC1(rs11615)→XRCC1(rs1799782)→RRM1(rs1042858)→XPD(rs13181)→XPG (rs1047768)→XPG(rs17655)→XRCC1(rs25489). ERCC1(rs11615), XRCC1(rs25487, rs1799782) and XPD(rs13181) polymorphisms were better predictors in evaluating the efficacy of platinum-based chemotherapy in NSCLC patients. J. Cell. Biochem. 118: 4782-4791, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley

  7. Mutations in XRCC4 cause primordial dwarfism without causing immunodeficiency.

    PubMed

    Saito, Shinta; Kurosawa, Aya; Adachi, Noritaka

    2016-08-01

    In successive reports from 2014 to 2015, X-ray repair cross-complementing protein 4 (XRCC4) has been identified as a novel causative gene of primordial dwarfism. XRCC4 is indispensable for non-homologous end joining (NHEJ), the major pathway for repairing DNA double-strand breaks. As NHEJ is essential for V(D)J recombination during lymphocyte development, it is generally believed that abnormalities in XRCC4 cause severe combined immunodeficiency. Contrary to expectations, however, no overt immunodeficiency has been observed in patients with primordial dwarfism harboring XRCC4 mutations. Here, we describe the various XRCC4 mutations that lead to disease and discuss their impact on NHEJ and V(D)J recombination.

  8. Prospective assessment of XRCC3, XPD and Aurora kinase A single-nucleotide polymorphisms in advanced lung cancer.

    PubMed

    Provencio, M; Camps, C; Cobo, M; De las Peñas, R; Massuti, B; Blanco, R; Alberola, V; Jimenez, U; Delgado, J R; Cardenal, F; Tarón, M; Ramírez, J L; Sanchez, A; Rosell, R

    2012-12-01

    New therapeutic approaches are being developed based on findings that several genetic abnormalities underlying non-small-cell lung cancer (NSCLC) can influence chemosensitivity. The identification of molecular markers, useful for therapeutic decisions in lung cancer, is thus crucial for disease management. The present study evaluated single-nucleotide polymorphisms (SNPs) in XRCC3, XPD and Aurora kinase A in NSCLC patients in order to assess whether these biomarkers were able to predict the outcomes of the patients. The Spanish Lung Cancer Group prospectively assessed this clinical study. Eligible patients had histologically confirmed stage IV or IIIB (with malignant pleural effusion) NSCLC, which had not previously been treated with chemotherapy, and a World Health Organization performance status (PS) of 0-1. Patients received intravenous doses of vinorelbine 25 mg/m(2) on days 1 and 8, and cisplatin 75 mg/m(2) on day 1, every 21 days for a maximum of 6 cycles. Venous blood was collected from each, and genomic DNA was isolated. SNPs in XRCC3 T241M, XPD K751Q, XPD D312N, AURORA 91, AURORA 169 were assessed. The study included 180 patients. Median age was 62 years; 87 % were male; 34 % had PS 0; and 83 % had stage IV disease. The median number of cycles was 4. Time to progression was 5.1 months (95 % CI, 4.2-5.9). Overall median survival was 8.6 months (95 % CI, 7.1-10.1). There was no significant association between SNPs in XRCC3 T241M, XPD K751Q, XPD D312N, AURORA 91, AURORA 169 in outcome or toxicity. Our findings indicate that SNPs in XRCC3, XPD or Aurora kinase A cannot predict outcomes in advanced NSCLC patients treated with platinum-based chemotherapy.

  9. Reduced expression of DNA repair genes (XRCC1, XPD, and OGG1) in squamous cell carcinoma of head and neck in North India.

    PubMed

    Kumar, Anil; Pant, Mohan Chand; Singh, Hirdya Shanker; Khandelwal, Shashi

    2012-02-01

    Squamous cell carcinoma of head and neck (SCCHN) is the sixth most common cancer globally, and in India, it accounts for 30% of all cancer cases. Epidemiological studies have shown a positive association between defective DNA repair capacity and SCCHN. The underlying mechanism of their involvement is not well understood. In the present study, we have analyzed the relationship between SCCHN and the expression of DNA repair genes namely X-ray repair cross-complementing group 1 (XRCC1), xeroderma pigmentosum group D (XPD), and 8-oxoguanine DNA glycosylase (OGG1) in 75 SCCHN cases and equal number of matched healthy controls. Additionally, levels of DNA adduct [8-hydroxyguanine (8-OHdG)] in 45 SCCHN cases and 45 healthy controls were also determined, to ascertain a link between mRNA expression of these three genes and DNA adducts. The relative expression of XRCC1, XPD, and OGG1 in head and neck cancer patients was found to be significantly low as compared to controls. The percent difference of mean relative expression between cases and controls demonstrated maximum lowering in OGG1 (47.3%) > XPD (30.7%) > XRCC1 (25.2%). A negative Spearmen correlation between XRCC1 vs. 8-OHdG in cases was observed. In multivariate logistic regression analysis (adjusting for age, gender, smoking status, and alcohol use), low expression of XRCC1, XPD, and OGG1 was associated with a statistically significant increased risk of SCCHN [crude odds ratios (ORs) (95%CI) OR 2.10; (1.06-4.17), OR 2.76; (1.39-5.49), and 5.24 (2.38-11.52), respectively]. In conclusion, our study demonstrated that reduced expression of XRCC1, XPD, and OGG1 is associated with more than twofold increased risk in SCCHN.

  10. Genetic variants of SULT1A1 and XRCC1 genes and risk of lung cancer in Bangladeshi population.

    PubMed

    Tasnim, Tasnova; Al-Mamun, Mir Md Abdullah; Nahid, Noor Ahmed; Islam, Md Reazul; Apu, Mohd Nazmul Hasan; Bushra, Most Umme; Rabbi, Sikder Nahidul Islam; Nahar, Zabun; Chowdhury, Jakir Ahmed; Ahmed, Maizbha Uddin; Islam, Mohammad Safiqul; Hasnat, Abul

    2017-11-01

    Lung cancer is one of the most frequently occurring cancers throughout the world as well as in Bangladesh. This study aimed to correlate the prognostic and/or predictive value of functional polymorphisms in SULT1A1 (rs9282861) and XRCC1 (rs25487) genes and lung cancer risk in Bangladeshi population. A case-control study was conducted which comprises 202 lung cancer patients and 242 healthy volunteers taking into account the age, sex, and smoking status. After isolation of genomic DNA, genotyping was done by polymerase chain reaction-restriction fragment length polymorphism method and the lung cancer risk was evaluated as odds ratio that was adjusted for age, sex, and smoking status. A significant association was found between SULT1A1 rs9282861 and XRCC1 rs25487 polymorphisms and lung cancer risk. In case of rs9282861 polymorphism, Arg/His (adjusted odds ratio = 5.06, 95% confidence interval = 3.05-8.41, p < 0.05) and His/His (adjusted odds ratio = 3.88, 95% confidence interval = 2.20-6.82, p < 0.05) genotypes were strongly associated with increased risk of lung cancer in comparison to the Arg/Arg genotype. In case of rs25487 polymorphism, Arg/Gln heterozygote (adjusted odds ratio = 4.57, 95% confidence interval = 2.79-7.46, p < 0.05) and Gln/Gln mutant homozygote (adjusted odds ratio = 4.99, 95% confidence interval = 2.66-9.36, p < 0.05) were also found to be significantly associated with increased risk of lung cancer. This study demonstrates that the presence of His allele and Gln allele in case of SULT1A1 rs9282861 and XRCC1 rs25487, respectively, involve in lung cancer prognosis in Bangladeshi population.

  11. XRCC1 Arg194Trp and Arg399Gln polymorphisms and arsenic methylation capacity are associated with urothelial carcinoma

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Chiang, Chien-I; Huang, Ya-Li; Chen, Wei-Jen

    The association between DNA repair gene polymorphisms and bladder cancer has been widely studied. However, few studies have examined the correlation between urothelial carcinoma (UC) and arsenic or its metabolites. The aim of this study was to examine the association between polymorphisms of the DNA repair genes, XRCC1 Arg194Trp, XRCC1 Arg399Gln, XRCC3 Thr241Met, and XPD Lys751Gln, with urinary arsenic profiles and UC. To this end, we conducted a hospital-based case–control study with 324 UC patients and 647 age- and gender-matched non-cancer controls. Genomic DNA was used to examine the genotype of XRCC1 Arg194Trp, XRCC1 Arg399Gln, XRCC3 Thr241Met, and XPD Lys751Glnmore » by PCR-restriction fragment length polymorphism analysis (PCR-RFLP). Urinary arsenic profiles were measured by high performance liquid chromatography (HPLC) linked with hydride generator and atomic absorption spectrometry. The XRCC1 399 Gln/Gln and 194 Arg/Trp and Trp/Trp genotypes were significantly related to UC, and the odds ratio (OR) and 95% confidence interval (95%CI) were 1.68 (1.03–2.75) and 0.66 (0.48–0.90), respectively. Participants with higher total urinary arsenic levels, a higher percentage of inorganic arsenic (InAs%) and a lower percentage of dimethylarsinic acid (DMA%) had a higher OR of UC. Participants carrying XRCC1 risk diplotypes G-C/G-C, A-C/A-C, and A-T/G-T, and who had higher total arsenic levels, higher InAs%, or lower DMA% compared to those with other XRCC1 diplotypes had a higher OR of UC. Our results suggest that the XRCC1 399 Gln/Gln and 194 Arg/Arg DNA repair genes play an important role in poor arsenic methylation capacity, thereby increasing the risk of UC in non-obvious arsenic exposure areas. - Highlights: • The XRCC1 399Gln/Gln genotype was significantly associated with increased OR of UC. • The XRCC1 194 Arg/Trp and Trp/Trp genotype had a significantly decreased OR of UC. • Combined effect of the XRCC1 genotypes and poor arsenic methylation

  12. Association study between XRCC1 gene polymorphisms and sporadic amyotrophic lateral sclerosis.

    PubMed

    Coppedè, Fabio; Migheli, Francesca; Lo Gerfo, Annalisa; Fabbrizi, Maria Rita; Carlesi, Cecilia; Mancuso, Michelangelo; Corti, Stefania; Mezzina, Nicoletta; del Bo, Roberto; Comi, Giacomo P; Siciliano, Gabriele; Migliore, Lucia

    2010-01-01

    The aim of the present study was to investigate the possible contribution of three common functional polymorphisms in the DNA repair protein X-ray repair cross-complementing group 1 (XRCC1), namely Arg194Trp (rs1799782), Arg280His (rs25489) and Arg399Gln (rs25487), to sporadic amyotrophic lateral sclerosis (SALS). We genotyped 206 Italian SALS patients and 203 matched controls for XRCC1 Arg194Trp, Arg280His and Arg399Gln polymorphisms by means of PCR/RFLP technique, searching for association between any of the studied polymorphisms and disease risk, age and site of onset. We observed a statistically significant difference in XRCC1 Gln399 allele frequencies between SALS cases and controls (0.39/0.28; p=0.001). The present study suggests that the XRCC1 Arg399Gln polymorphism might contribute to SALS risk.

  13. Lysine 271 but not lysine 210 of XRCC4 is required for the nuclear localization of XRCC4 and DNA ligase IV

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Fukuchi, Mikoto; Wanotayan, Rujira; Liu, Sicheng

    2015-06-12

    XRCC4 and DNA Ligase IV (LIG4) cooperate to join two DNA ends at the final step of DNA double-strand break (DSB) repair through non-homologous end-joining (NHEJ). However, it is not fully understood how these proteins are localized to the nucleus. Here we created XRCC4{sup K271R} mutant, as Lys271 lies within the putative nuclear localization signal (NLS), and XRCC4{sup K210R} mutant, as Lys210 was reported to undergo SUMOylation, implicated in the nuclear localization of XRCC4. Wild-type and mutated XRCC4 with EGFP tag were introduced into HeLa cell, in which endogenous XRCC4 had been knocked down using siRNA directed to 3′-untranslated region,more » and tested for the nuclear localization function by fluorescence microscopy. XRCC4{sup K271R} was defective in the nuclear localization of itself and LIG4, whereas XRCC4{sup K210R} was competent for the nuclear localization with LIG4. To examine DSB repair function, wild-type and mutated XRCC4 were introduced into XRCC4-deficient M10. M10-XRCC4{sup K271R}, but not M10-XRCC4{sup K210R}, showed significantly reduced surviving fraction after 2 Gy γ-ray irradiation as compared to M10-XRCC4{sup WT}. The number of γ-H2AX foci remaining 2 h after 2 Gy γ-ray irradiation was significantly greater in M10-XRCC4{sup K271R} than in M10-XRCC4{sup WT}, whereas it was only marginally increased in M10-XRCC4{sup K210R} as compared to M10-XRCC4{sup WT}. The present results collectively indicated that Lys271, but not Lys210, of XRCC4 is required for the nuclear localization of XRCC4 and LIG4 and that the nuclear localizing ability is essential for DSB repair function of XRCC4. - Highlights: • XRCC4{sup K271R} is defective in the nuclear localization of itself and LIG4. • XRCC4{sup K210R} is competent for the nuclear localization of itself and LIG4. • XRCC4{sup K271R} is deficient in DSB repair function. • XRCC4{sup K210R} is mostly normal in DSB repair function.« less

  14. XRCC4 suppresses medulloblastomas with recurrent translocations in p53-deficient mice

    PubMed Central

    Yan, Catherine T.; Kaushal, Dhruv; Murphy, Michael; Zhang, Yu; Datta, Abhishek; Chen, Changzhong; Monroe, Brianna; Mostoslavsky, Gustavo; Coakley, Kristen; Gao, Yijie; Mills, Kevin D.; Fazeli, Alex P.; Tepsuporn, Suprawee; Hall, Giles; Mulligan, Richard; Fox, Edward; Bronson, Roderick; De Girolami, Umberto; Lee, Charles; Alt, Frederick W.

    2006-01-01

    Inactivation of the XRCC4 nonhomologous end-joining factor in the mouse germ line leads to embryonic lethality, in association with apoptosis of newly generated, postmitotic neurons. We now show that conditional inactivation of the XRCC4 in nestin-expressing neuronal progenitor cells, although leading to no obvious phenotype in a WT background, leads to early onset of neuronally differentiated medulloblastomas (MBs) in a p53-deficient background. A substantial proportion of the XRCC4/p53-deficient MBs have high-level N-myc gene amplification, often intrachromosomally in the context of complex translocations or other alterations of chromosome 12, on which N-myc resides, or extrachromosomally within double minutes. In addition, most XRCC4/p53-deficient MBs harbor clonal translocations of chromosome 13, which frequently involve chromosome 6 as a partner. One copy of the patched gene (Ptc), which lies on chromosome 13, was deleted in all tested XRCC4/p53-deficient MBs in the context of translocations or interstitial deletions. In addition, Cyclin D2, a chromosome 6 gene, was amplified in a subset of tumors. Notably, amplification of Myc-family or Cyclin D2 genes and deletion of Ptc also have been observed in human MBs. We therefore conclude that, in neuronal cells of mice, the nonhomologous end-joining pathway plays a critical role in suppressing genomic instability that, in a p53-deficient background, routinely contributes to genesis of MBs with recurrent chromosomal alterations. PMID:16670198

  15. [Association of XRCC1 genetic polymorphism with susceptibility to non-Hodgkin's lymphoma].

    PubMed

    Li, Su-Xia; Zhu, Hong-Li; Guo, Bo; Yang, Yang; Wang, Hong-Yan; Sun, Jing-Fen; Cao, Yong-Bin

    2014-08-01

    The purpose of this study was to explore the association between X-ray repair cross-complementing group 1 (XRCC1)gene polymorphism and non-Hodgkin's lymphoma risk. A total of 282 non-Hodgkin's lymphoma (NHL) patients and 231 normal controls were used to investigate the effect of three XRCC1 gene polymorphisms (rs25487, rs25489, rs1799782) on susceptibility to non-Hodgkin's lymphoma. Genotyping was performed by using SNaPshot method. All statistical analyses were done with R software. Genotype and allele frequencies of XRCC1 were compared between the patients and controls by using the chi-square test. Crude and adjusted odd ratios and 95% confidence intervals were calculated by using logistic regression on the basis of genetic different models. For four kinds of NHL, subgroup analyses were also conducted. Combined genotype analyses of the three XRCC1 polymorphisms were also done by using logistic regression. The results showed that the variant genotype frequency was not significantly different between the controls and NHL or NHL subtype cases. Combined genotype analyses of XRCC1 399-280-194 results showed that the combined genotype was not associated with risk of NHL overall, but the VT-WT-WT combined genotype was associated with the decreased risk of T-NHL (OR: 0.21; 95%CI (0.06-0.8); P = 0.022), and the WT-VT-WT combined genotype was associated with the increased risk of FL(OR:15.23; 95%CI (1.69-137.39); P = 0.015). It is concluded that any studied polymorphism (rs25487, rs25489, rs1799782) alone was not shown to be rela-ted with the risk of NHL or each histologic subtype of NHL. The combined genotype with mutation of three SNP of XRCC1 was not related to the risk of NHL. However, further large-scale studies would be needed to confirm the association of decreased or increased risk for T-NHL and FL with the risk 3 combined SNP mutants of XRCC1 polymorphism.

  16. FANCG promotes formation of a newly identified protein complex containing BRCA2, FANCD2 and XRCC3.

    PubMed

    Wilson, J B; Yamamoto, K; Marriott, A S; Hussain, S; Sung, P; Hoatlin, M E; Mathew, C G; Takata, M; Thompson, L H; Kupfer, G M; Jones, N J

    2008-06-12

    Fanconi anemia (FA) is a human disorder characterized by cancer susceptibility and cellular sensitivity to DNA crosslinks and other damages. Thirteen complementation groups and genes are identified, including BRCA2, which is defective in the FA-D1 group. Eight of the FA proteins, including FANCG, participate in a nuclear core complex that is required for the monoubiquitylation of FANCD2 and FANCI. FANCD2, like FANCD1/BRCA2, is not part of the core complex, and we previously showed direct BRCA2-FANCD2 interaction using yeast two-hybrid analysis. We now show in human and hamster cells that expression of FANCG protein, but not the other core complex proteins, is required for co-precipitation of BRCA2 and FANCD2. We also show that phosphorylation of FANCG serine 7 is required for its co-precipitation with BRCA2, XRCC3 and FANCD2, as well as the direct interaction of BRCA2-FANCD2. These results argue that FANCG has a role independent of the FA core complex, and we propose that phosphorylation of serine 7 is the signalling event required for forming a discrete complex comprising FANCD1/BRCA2-FANCD2-FANCG-XRCC3 (D1-D2-G-X3). Cells that fail to express either phospho-Ser7-FANCG, or full length BRCA2 protein, lack the interactions amongst the four component proteins. A role for D1-D2-G-X3 in homologous recombination repair (HRR) is supported by our finding that FANCG and the RAD51-paralog XRCC3 are epistatic for sensitivity to DNA crosslinking compounds in DT40 chicken cells. Our findings further define the intricate interface between FANC and HRR proteins in maintaining chromosome stability.

  17. XRCC3 polymorphisms are associated with the risk of developing radiation-induced late xerostomia in nasopharyngeal carcinoma patients treated with intensity modulation radiated therapy.

    PubMed

    Zou, Yan; Song, Tao; Yu, Wei; Zhao, Ruping; Wang, Yong; Xie, Ruifei; Chen, Tian; Wu, Bo; Wu, Shixiu

    2014-03-01

    The incidence of radiation-induced late xerostomia varies greatly in nasopharyngeal carcinoma patients treated with radiotherapy. The single-nucleotide polymorphisms in genes involved in DNA repair and fibroblast proliferation may be correlated with such variability. The purpose of this paper was to evaluate the association between the risk of developing radiation-induced late xerostomia and four genetic polymorphisms: TGFβ1 C-509T, TGFβ1 T869C, XRCC3 722C>T and ATM 5557G>A in nasopharyngeal carcinoma patients treated with Intensity Modulation Radiated Therapy. The severity of late xerostomia was assessed using a patient self-reported validated xerostomia questionnaire. Polymerase chain reaction-ligation detection reaction methods were performed to determine individual genetic polymorphism. The development of radiation-induced xerostomia associated with genetic polymorphisms was modeled using Cox proportional hazards, accounting for equivalent uniform dose. A total of 43 (41.7%) patients experienced radiation-induced late xerostomia. Univariate Cox proportional hazard analyses showed a higher risk of late xerostomia for patients with XRCC3 722 TT/CT alleles. In multivariate analysis adjusted for clinical and dosimetric factors, XRCC3 722C>T polymorphisms remained a significant factor for higher risk of late xerostomia. To our knowledge, this is the first study that demonstrated an association between genetic polymorphisms and the risk of radiation-induced late xerostomia in nasopharyngeal carcinoma patients treated with Intensity Modulation Radiated Therapy. Our findings suggest that the polymorphisms in XRCC3 are significantly associated with the risk of developing radiation-induced late xerostomia.

  18. A prospective study of XRCC1 haplotypes and their interaction with plasma carotenoids on breast cancer risk

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mohrenweiser, H W; Han, J; Hankinson, S E

    2004-01-15

    The XRCC1 protein is involved in the base excision repair pathway through interactions with other proteins. Polymorphisms in the XRCC1 gene may lead to variation in repair proficiency and confer inherited predisposition to cancer. We prospectively assessed the associations between polymorphisms and haplotypes in XRCC1 and breast cancer risk in a nested case-control study within the Nurses' Health Study (incident cases, n 1004; controls, n 1385). We further investigated gene-environment interactions between the XRCC1 variations and plasma carotenoids on breast cancer risk. We genotyped four haplotype-tagging single nucleotide polymorphisms Arg {sup 194}Trp, C26602T, Arg{sup 399}Gln, and Gln{sup 632}Gln in themore » XRCC1 gene. Five common haplotypes accounted for 99% of the chromosomes in the present study population of mostly Caucasian women. We observed a marginally significant reduction in the risk of breast cancer among {sup 194}Trp carriers. As compared with no-carriers, women with at least one {sup 194}Trp allele had a multivariate odds ratio of 0.79 (95% of the confidence interval, 0.60 -1.04). The inferred haplotype harboring the {sup 194}Trp allele was more common in controls than in cases (6.6 versus 5.3%, P 0.07). We observed that the Arg {sup 194}Trp modified the inverse associations of plasma -carotene level (P, ordinal test for interaction 0.02) and plasma -carotene level (P, ordinal test for interaction 0.003) with breast cancer risk. No suggestion of an interaction was observed between the Arg {sup 194}Trp and cigarette smoking. Our results suggest an inverse association between XRCC1 {sup 194}Trp allele and breast cancer risk. The findings of the effect modification of the Arg {sup 194}Trp on the relations of plasma -and -carotene levels with breast cancer risk suggest a potential protective effect of carotenoids in breast carcinogenesis by preventing oxidative DNA damage.« less

  19. Prognostic significance of XRCC4 expression in hepatocellular carcinoma

    PubMed Central

    Huang, Xiao-Ying; Yao, Jin-Guang; Wang, Chao; Wei, Zhong-Hong; Ma, Yun; Wu, Xue-Min; Luo, Chun-Ying; Xia, Qiang; Long, Xi-Dai

    2017-01-01

    Background Our previous investigations have shown that the variants of X-ray repair complementing 4 (XRCC4) may be involved in hepatocellular carcinoma (hepatocarcinoma) tumorigenesis. This study aimed to investigate the possible prognostic significance of XRCC4 expression for hepatocarcinoma patients and possible value for the selection of transarterial chemoembolization (TACE) treatment. Materials and Methods We conducted a hospital-based retrospective analysis (including 421 hepatocarcinoma cases) to analyze the effects of XRCC4 on hepatocarcinoma prognosis and TACE. The levels of XRCC4 expression were tested using immunohistochemistry. The sensitivity of cancer cells to anti-cancer drug doxorubicin was evaluated using the half-maximal inhibitory concentration (IC50). Results XRCC4 expression was significantly correlated with pathological features including tumor stage, liver cirrhosis, and micro-vessel density. XRCC4 expression was an independent prognostic factor of hepatocarcinoma, and TACE treatments had no effects on prognosis of hepatocarcinoma patients with high XRCC4 expression. More intriguingly, TACE improved the prognosis of hepatocarcinoma patients with low XRCC4 expression. Functionally, XRCC4 overexpression increased while XRCC4 knockdown reduced the IC50 of cancer cells to doxorubicin. Conclusions These results suggest that XRCC4 may be an independent prognostic factor for hepatocarcinoma patients, and that decreasing XRCC4 expression may be beneficial for post-operative adjuvant TACE treatment in hepatocarcinoma. PMID:29152133

  20. The impact of homologous recombination repair deficiency on depleted uranium clastogenicity in Chinese hamster ovary cells: XRCC3 protects cells from chromosome aberrations, but increases chromosome fragmentation.

    PubMed

    Holmes, Amie L; Joyce, Kellie; Xie, Hong; Falank, Carolyne; Hinz, John M; Wise, John Pierce

    2014-04-01

    Depleted uranium (DU) is extensively used in both industry and military applications. The potential for civilian and military personnel exposure to DU is rising, but there are limited data on the potential health hazards of DU exposure. Previous laboratory research indicates DU is a potential carcinogen, but epidemiological studies remain inconclusive. DU is genotoxic, inducing DNA double strand breaks, chromosome damage and mutations, but the mechanisms of genotoxicity or repair pathways involved in protecting cells against DU-induced damage remain unknown. The purpose of this study was to investigate the effects of homologous recombination repair deficiency on DU-induced genotoxicity using RAD51D and XRCC3-deficient Chinese hamster ovary (CHO) cell lines. Cells deficient in XRCC3 (irs1SF) exhibited similar cytotoxicity after DU exposure compared to wild-type (AA8) and XRCC3-complemented (1SFwt8) cells, but DU induced more break-type and fusion-type lesions in XRCC3-deficient cells compared to wild-type and XRCC3-complemented cells. Surprisingly, loss of RAD51D did not affect DU-induced cytotoxicity or genotoxicity. DU induced selective X-chromosome fragmentation irrespective of RAD51D status, but loss of XRCC3 nearly eliminated fragmentation observed after DU exposure in wild-type and XRCC3-complemented cells. Thus, XRCC3, but not RAD51D, protects cells from DU-induced breaks and fusions and also plays a role in DU-induced chromosome fragmentation. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Structural and functional characterization of the PNKP–XRCC4–LigIV DNA repair complex

    DOE PAGES

    Aceytuno, R.  Daniel; Piett, Cortt G.; Havali-Shahriari, Zahra; ...

    2017-04-27

    Non-homologous end joining (NHEJ) repairs DNA double strand breaks in non-cycling eukaryotic cells. NHEJ relies on polynucleotide kinase/phosphatase (PNKP), which generates 5'-phosphate/3'-hydroxyl DNA termini that are critical for ligation by the NHEJ DNA ligase, LigIV. PNKP and LigIV require the NHEJ scaffolding protein, XRCC4. The PNKP FHA domain binds to the CK2-phosphorylated XRCC4 C-terminal tail, while LigIV uses its tandem BRCT repeats to bind the XRCC4 coiled-coil. Yet, the assembled PNKP-XRCC4-LigIV complex remains uncharacterized. Here, we report purification and characterization of a recombinant PNKP-XRCC4-LigIV complex. We show that the stable binding of PNKP in this complex requires XRCC4 phosphorylation andmore » that only one PNKP protomer binds per XRCC4 dimer. Small angle X-ray scattering (SAXS) reveals a flexiblemultistate complex that suggests that both the PNKP FHA and catalytic domains contact the XRCC4 coiled-coil and LigIV BRCT repeats. Hydrogen-deuterium exchange indicates protection of a surface on the PNKP phosphatase domain that may contact XRCC4-LigIV. Amutation on this surface (E326K) causes the hereditary neuro-developmental disorder, MCSZ. This mutation impairs PNKP recruitment to damaged DNA in human cells and provides a possible disease mechanism. Together, this work unveils multipoint contacts between PNKP and XRCC4-LigIV that regulate PNKP recruitment and activity within NHEJ.« less

  2. Structural and functional characterization of the PNKP–XRCC4–LigIV DNA repair complex

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aceytuno, R.  Daniel; Piett, Cortt G.; Havali-Shahriari, Zahra

    Non-homologous end joining (NHEJ) repairs DNA double strand breaks in non-cycling eukaryotic cells. NHEJ relies on polynucleotide kinase/phosphatase (PNKP), which generates 5'-phosphate/3'-hydroxyl DNA termini that are critical for ligation by the NHEJ DNA ligase, LigIV. PNKP and LigIV require the NHEJ scaffolding protein, XRCC4. The PNKP FHA domain binds to the CK2-phosphorylated XRCC4 C-terminal tail, while LigIV uses its tandem BRCT repeats to bind the XRCC4 coiled-coil. Yet, the assembled PNKP-XRCC4-LigIV complex remains uncharacterized. Here, we report purification and characterization of a recombinant PNKP-XRCC4-LigIV complex. We show that the stable binding of PNKP in this complex requires XRCC4 phosphorylation andmore » that only one PNKP protomer binds per XRCC4 dimer. Small angle X-ray scattering (SAXS) reveals a flexiblemultistate complex that suggests that both the PNKP FHA and catalytic domains contact the XRCC4 coiled-coil and LigIV BRCT repeats. Hydrogen-deuterium exchange indicates protection of a surface on the PNKP phosphatase domain that may contact XRCC4-LigIV. Amutation on this surface (E326K) causes the hereditary neuro-developmental disorder, MCSZ. This mutation impairs PNKP recruitment to damaged DNA in human cells and provides a possible disease mechanism. Together, this work unveils multipoint contacts between PNKP and XRCC4-LigIV that regulate PNKP recruitment and activity within NHEJ.« less

  3. XRCC5 cooperates with p300 to promote cyclooxygenase-2 expression and tumor growth in colon cancers

    PubMed Central

    Hao, Jiajiao; Chen, Miao; Yu, Wendan; Guo, Wei; Chen, Yiming; Huang, Wenlin; Deng, Wuguo

    2017-01-01

    Cyclooxygenase (COX) is the rate-limiting enzyme in prostaglandins (PGs) biosynthesis. Previous studies indicate that COX-2, one of the isoforms of COX, is highly expressed in colon cancers and plays a key role in colon cancer carcinogenesis. Thus, searching for novel transcription factors regulating COX-2 expression will facilitate drug development for colon cancer. In this study, we identified XRCC5 as a binding protein of the COX-2 gene promoter in colon cancer cells with streptavidin-agarose pulldown assay and mass spectrometry analysis, and found that XRCC5 promoted colon cancer growth through modulation of COX-2 signaling. Knockdown of XRCC5 by siRNAs inhibited the growth of colon cancer cells in vitro and of tumor xenografts in a mouse model in vivo by suppressing COX-2 promoter activity and COX-2 protein expression. Conversely, overexpression of XRCC5 promoted the growth of colon cancer cells by activating COX-2 promoter and increasing COX-2 protein expression. Moreover, the role of p300 (a transcription co-activator) in acetylating XRCC5 to co-regulate COX-2 expression was also evaluated. Immunofluorescence assay and confocal microscopy showed that XRCC5 and p300 proteins were co-located in the nucleus of colon cancer cells. Co-immunoprecipitation assay also proved the interaction between XRCC5 and p300 in nuclear proteins of colon cancer cells. Cell viability assay indicated that the overexpression of wild-type p300, but not its histone acetyltransferase (HAT) domain deletion mutant, increased XRCC5 acetylation, thereby up-regulated COX-2 expression and promoted the growth of colon cancer cells. In contrast, suppression of p300 by a p300 HAT-specific inhibitor (C646) inhibited colon cancer cell growth by suppressing COX-2 expression. Taken together, our results demonstrated that XRCC5 promoted colon cancer growth by cooperating with p300 to regulate COX-2 expression, and suggested that the XRCC5/p300/COX-2 signaling pathway was a potential target in the

  4. XRCC1 Polymorphism Associated With Late Toxicity After Radiation Therapy in Breast Cancer Patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Seibold, Petra; Behrens, Sabine; Schmezer, Peter

    Purpose: To identify single-nucleotide polymorphisms (SNPs) in oxidative stress–related genes associated with risk of late toxicities in breast cancer patients receiving radiation therapy. Methods and Materials: Using a 2-stage design, 305 SNPs in 59 candidate genes were investigated in the discovery phase in 753 breast cancer patients from 2 prospective cohorts from Germany. The 10 most promising SNPs in 4 genes were evaluated in the replication phase in up to 1883 breast cancer patients from 6 cohorts identified through the Radiogenomics Consortium. Outcomes of interest were late skin toxicity and fibrosis of the breast, as well as an overall toxicity score (Standardized Totalmore » Average Toxicity). Multivariable logistic and linear regression models were used to assess associations between SNPs and late toxicity. A meta-analysis approach was used to summarize evidence. Results: The association of a genetic variant in the base excision repair gene XRCC1, rs2682585, with normal tissue late radiation toxicity was replicated in all tested studies. In the combined analysis of discovery and replication cohorts, carrying the rare allele was associated with a significantly lower risk of skin toxicities (multivariate odds ratio 0.77, 95% confidence interval 0.61-0.96, P=.02) and a decrease in Standardized Total Average Toxicity scores (−0.08, 95% confidence interval −0.15 to −0.02, P=.016). Conclusions: Using a stage design with replication, we identified a variant allele in the base excision repair gene XRCC1 that could be used in combination with additional variants for developing a test to predict late toxicities after radiation therapy in breast cancer patients.« less

  5. DNA Repair Gene (XRCC1) Polymorphism (Arg399Gln) Associated with Schizophrenia in South Indian Population: A Genotypic and Molecular Dynamics Study

    PubMed Central

    Sujitha, S. P.; Kumar, D. Thirumal; Doss, C. George Priya; Aavula, K.; Ramesh, R.; Lakshmanan, S.; Gunasekaran, S.; Anilkumar, G.

    2016-01-01

    This paper depicts the first report from an Indian population on the association between the variant Arg399Gln of XRCC1 locus in the DNA repair system and schizophrenia, the debilitating disease that affects 1% of the world population. Genotypic analysis of a total of 523 subjects (260 patients and 263 controls) revealed an overwhelming presence of Gln399Gln in the case subjects against the controls (P < 0.0068), indicating significant level of association of this nsSNP with schizophrenia; the Gln399 allele frequency was also perceptibly more in cases than in controls (p < 0.003; OR = 1.448). The results of the genotypic studies were further validated using pathogenicity and stability prediction analysis employing computational tools [I-Mutant Suite, iStable, PolyPhen2, SNAP, and PROVEAN], with a view toassess the magnitude of deleteriousness of the mutation. The pathogenicity analysis reveals that the nsSNP could be deleterious inasmuch as it could affect the functionality of the gene, and interfere with protein function. Molecular dynamics simulation of 60ns was performed using GROMACS to analyse structural change due to a mutation (Arg399Gln) that was never examined before. RMSD, RMSF, hydrogen bonds, radius of gyration and SASA analysis showedthe existence of asignificant difference between the native and the mutant protein. The present study gives astrong indication that the XRCC1 locus deserves serious attention, as it could be a potential candidatecontributing to the etio-pathogenesis of the disease. PMID:26824244

  6. DNA Repair Gene (XRCC1) Polymorphism (Arg399Gln) Associated with Schizophrenia in South Indian Population: A Genotypic and Molecular Dynamics Study.

    PubMed

    Sujitha, S P; Kumar, D Thirumal; Doss, C George Priya; Aavula, K; Ramesh, R; Lakshmanan, S; Gunasekaran, S; Anilkumar, G

    2016-01-01

    This paper depicts the first report from an Indian population on the association between the variant Arg399Gln of XRCC1 locus in the DNA repair system and schizophrenia, the debilitating disease that affects 1% of the world population. Genotypic analysis of a total of 523 subjects (260 patients and 263 controls) revealed an overwhelming presence of Gln399Gln in the case subjects against the controls (P < 0.0068), indicating significant level of association of this nsSNP with schizophrenia; the Gln399 allele frequency was also perceptibly more in cases than in controls (p < 0.003; OR = 1.448). The results of the genotypic studies were further validated using pathogenicity and stability prediction analysis employing computational tools [I-Mutant Suite, iStable, PolyPhen2, SNAP, and PROVEAN], with a view toassess the magnitude of deleteriousness of the mutation. The pathogenicity analysis reveals that the nsSNP could be deleterious inasmuch as it could affect the functionality of the gene, and interfere with protein function. Molecular dynamics simulation of 60ns was performed using GROMACS to analyse structural change due to a mutation (Arg399Gln) that was never examined before. RMSD, RMSF, hydrogen bonds, radius of gyration and SASA analysis showedthe existence of asignificant difference between the native and the mutant protein. The present study gives astrong indication that the XRCC1 locus deserves serious attention, as it could be a potential candidatecontributing to the etio-pathogenesis of the disease.

  7. Susceptibility to Colorectal Cancer and Two Genetic Polymorphisms of XRCC4.

    PubMed

    Emami, Naghmeh; Saadat, Iraj; Omidvari, Shahpour

    2015-09-01

    The X-ray complementing group 4 (XRCC4, OMIM: 194363) plays a key role in non-homologous end-joining DNA repair pathway in mammalian cells. This pathway is believed to help maintain genomic stability. In the present study, it is hypothesized that genetic polymorphisms in the NHEJ repair XRCC4 gene may be associated with an increased risk in developing colorectal cancer (CRC). We genotyped two polymorphisms of XRCC4, G-1394T (rs6869366) and intron 3 insertion/deletion (I/D; rs28360071) in 200 colorectal cancer patients as well as 256 healthy individuals, and evaluated their association with CRC. We found that in G-1394T polymorphism, neither the TG nor the GG genotypes (versus the TT genotype) were associated with the risk of developing CRC. The results of our study indicate that in comparison with the II genotype, ID and DD genotypes had no significant association with the risk of developing CRC. Subjects with TT genotype and positive family history in colorectal cancer were found to be at a much lower risk of developing CRC in comparison with the reference group (OR = 0.31, 95%CI: 0.11-0.85, P =  .023). It should be noted that participants having at least one G allele (TG+GG genotypes) were at a significantly higher risk to develop the disease compared with the reference group (OR = 9.10, 95%CI: 2.00-41.3, P = 0.004). In relation to I/D polymorphism, among participants, those with positive family history, either with ID (OR =  .78, 95%CI: 2.26-10.0, P < 0.001) or DD genotypes (OR = 5.73, 95%CI: 1.99-16.4, P = 0.001) had a significantly association with the disease. Among participants with a positive family history in CRC, the haplotype GD dramatically increased the risk of developing CRC (OR = 10.2, 95%CI: 2.28-46, P = 0.002). The results of this study indicate that G-1394T and I/D polymorphisms of XRCC4 among individuals with positive family history for colorectal cancer substantially increase the risk factor for developing colorectal cancers.

  8. Genetic Polymorphisms in XRCC1, CD3EAP, PPP1R13L, XPB, XPC, and XPF and the Risk of Chronic Benzene Poisoning in a Chinese Occupational Population.

    PubMed

    Xue, Ping; Gao, Lin; Xiao, Sha; Zhang, Guopei; Xiao, Mingyang; Zhang, Qianye; Zheng, Xiao; Cai, Yuan; Jin, Cuihong; Yang, Jinghua; Wu, Shengwen; Lu, Xiaobo

    2015-01-01

    the rs25487 and rs1799782 polymorphisms of XRCC1 may contribute to an individual's susceptibility to CBP and may be used as valid biomarkers. Overall, the genes on chromosome 19q13.2-3 may have a special significance in the development of CBP in occupationally exposed Chinese populations.

  9. Genetic Polymorphisms in XRCC1, CD3EAP, PPP1R13L, XPB, XPC, and XPF and the Risk of Chronic Benzene Poisoning in a Chinese Occupational Population

    PubMed Central

    Xiao, Sha; Zhang, Guopei; Xiao, Mingyang; Zhang, Qianye; Zheng, Xiao; Cai, Yuan; Jin, Cuihong; Yang, Jinghua; Wu, Shengwen; Lu, Xiaobo

    2015-01-01

    risk of CBP. Conclusions The findings showed that the rs25487 and rs1799782 polymorphisms of XRCC1 may contribute to an individual’s susceptibility to CBP and may be used as valid biomarkers. Overall, the genes on chromosome 19q13.2–3 may have a special significance in the development of CBP in occupationally exposed Chinese populations. PMID:26681190

  10. Influence of XRCC1 Genetic Polymorphisms on Ionizing Radiation-Induced DNA Damage and Repair.

    PubMed

    Sterpone, Silvia; Cozzi, Renata

    2010-07-25

    It is well known that ionizing radiation (IR) can damage DNA through a direct action, producing single- and double-strand breaks on DNA double helix, as well as an indirect effect by generating oxygen reactive species in the cells. Mammals have evolved several and distinct DNA repair pathways in order to maintain genomic stability and avoid tumour cell transformation. This review reports important data showing a huge interindividual variability on sensitivity to IR and in susceptibility to developing cancer; this variability is principally represented by genetic polymorphisms, that is, DNA repair gene polymorphisms. In particular we have focussed on single nucleotide polymorphisms (SNPs) of XRCC1, a gene that encodes for a scaffold protein involved basically in Base Excision Repair (BER). In this paper we have reported and presented recent studies that show an influence of XRCC1 variants on DNA repair capacity and susceptibility to breast cancer.

  11. Rare, protein-truncating variants in ATM, CHEK2 and PALB2, but not XRCC2, are associated with increased breast cancer risks

    PubMed Central

    Decker, Brennan; Allen, Jamie; Luccarini, Craig; Pooley, Karen A; Shah, Mitul; Bolla, Manjeet K; Wang, Qin; Ahmed, Shahana; Baynes, Caroline; Conroy, Don M; Brown, Judith; Luben, Robert; Ostrander, Elaine A; Pharoah, Paul DP; Dunning, Alison M; Easton, Douglas F

    2017-01-01

    Background Breast cancer (BC) is the most common malignancy in women and has a major heritable component. The risks associated with most rare susceptibility variants are not well estimated. To better characterise the contribution of variants in ATM, CHEK2, PALB2 and XRCC2, we sequenced their coding regions in 13 087 BC cases and 5488 controls from East Anglia, UK. Methods Gene coding regions were enriched via PCR, sequenced, variant called and filtered for quality. ORs for BC risk were estimated separately for carriers of truncating variants and of rare missense variants, which were further subdivided by functional domain and pathogenicity as predicted by four in silico algorithms. Results Truncating variants in PALB2 (OR=4.69, 95% CI 2.27 to 9.68), ATM (OR=3.26; 95% CI 1.82 to 6.46) and CHEK2 (OR=3.11; 95% CI 2.15 to 4.69), but not XRCC2 (OR=0.94; 95% CI 0.26 to 4.19) were associated with increased BC risk. Truncating variants in ATM and CHEK2 were more strongly associated with risk of oestrogen receptor (ER)-positive than ER-negative disease, while those in PALB2 were associated with similar risks for both subtypes. There was also some evidence that missense variants in ATM, CHEK2 and PALB2 may contribute to BC risk, but larger studies are necessary to quantify the magnitude of this effect. Conclusions Truncating variants in PALB2 are associated with a higher risk of BC than those in ATM or CHEK2. A substantial risk of BC due to truncating XRCC2 variants can be excluded. PMID:28779002

  12. Assessment of genetic mutations in the XRCC2 coding region by high resolution melting curve analysis and the risk of differentiated thyroid carcinoma in Iran

    PubMed Central

    Fayaz, Shima; Fard-Esfahani, Pezhman; Fard-Esfahani, Armaghan; Mostafavi, Ehsan; Meshkani, Reza; Mirmiranpour, Hossein; Khaghani, Shahnaz

    2012-01-01

    Homologous recombination (HR) is the major pathway for repairing double strand breaks (DSBs) in eukaryotes and XRCC2 is an essential component of the HR repair machinery. To evaluate the potential role of mutations in gene repair by HR in individuals susceptible to differentiated thyroid carcinoma (DTC) we used high resolution melting (HRM) analysis, a recently introduced method for detecting mutations, to examine the entire XRCC2 coding region in an Iranian population. HRM analysis was used to screen for mutations in three XRCC2 coding regions in 50 patients and 50 controls. There was no variation in the HRM curves obtained from the analysis of exons 1 and 2 in the case and control groups. In exon 3, an Arg188His polymorphism (rs3218536) was detected as a new melting curve group (OR: 1.46; 95%CI: 0.432–4.969; p = 0.38) compared with the normal melting curve. We also found a new Ser150Arg polymorphism in exon 3 of the control group. These findings suggest that genetic variations in the XRCC2 coding region have no potential effects on susceptibility to DTC. However, further studies with larger populations are required to confirm this conclusion. PMID:22481871

  13. XRCC2 Polymorphisms and Environmental Factors Predict High Risk of Colorectal Cancer.

    PubMed

    Wang, Lijie; Ma, Junxun; Yang, Bo; Jing, Fangfang; Hu, Yi

    2018-05-07

    BACKGROUND This case-control study aimed to analyze the association of [i]XRCC2[/i] polymorphisms (rs3218408 and rs3218384) with colorectal cancer (CRC) risk. The interaction of [i]XRCC2[/i] polymorphisms with environmental factors was investigated as well. MATERIAL AND METHODS We enrolled 147 CRC patients and 114 healthy individuals into the study. Polymerase chain reaction (PCR)-sequencing method was performed to detect rs3218408 and rs3218384 polymorphisms. Hardy-Weinberg equilibrium (HWE) was checked in the control group. Odds ratio (OR) with 95% confidence interval (CI) represented the risk of CRC. Cross-table method was used in analyzing the interaction effects. RESULTS Compared to the control group, the frequency of smokers was much higher in the case group ([i]P[/i]<0.001). A similar result was observed in drinkers (55.8% [i]vs.[/i] 40.4%, [i]P[/i]=0.013). Dietary habits of all subjects were investigated as well, showing that CRC patients ate fewer vegetables than did healthy controls (P<0.001). In the analysis of polymorphisms, rs3218408 appeared to be an independent risk factor of CRC (GG: OR=2.048, 95%CI=1.032-4.061; G allele: OR=1.445, 95%CI=1.019-2.049). There were 68 (76.4%) C allele carriers (rs3218384) among smokers, which was higher than the number of G allele carriers ([i]P[/i]<0.001). A similar outcome was observed for alcohol drinkers ([i]P[/i]=0.048), which suggests a relationship of rs3218384 with smoking and drinking. Further analysis indicated that interaction of rs3218384 with smoking increased the risk of CRC (GG and smoking: OR=3.250, 95%CI=1.235-8.556; GC+CC and smoking: OR=2.167, 95%CI=1.175-3.996). CONCLUSIONS We found that rs3218408 was related with increased risk of CRC, and the interaction of rs3218384 with smoking increased the risk of CRC.

  14. Rare, protein-truncating variants in ATM, CHEK2 and PALB2, but not XRCC2, are associated with increased breast cancer risks.

    PubMed

    Decker, Brennan; Allen, Jamie; Luccarini, Craig; Pooley, Karen A; Shah, Mitul; Bolla, Manjeet K; Wang, Qin; Ahmed, Shahana; Baynes, Caroline; Conroy, Don M; Brown, Judith; Luben, Robert; Ostrander, Elaine A; Pharoah, Paul Dp; Dunning, Alison M; Easton, Douglas F

    2017-11-01

    Breast cancer (BC) is the most common malignancy in women and has a major heritable component. The risks associated with most rare susceptibility variants are not well estimated. To better characterise the contribution of variants in ATM , CHEK2 , PALB2 and XRCC2 , we sequenced their coding regions in 13 087 BC cases and 5488 controls from East Anglia, UK. Gene coding regions were enriched via PCR, sequenced, variant called and filtered for quality. ORs for BC risk were estimated separately for carriers of truncating variants and of rare missense variants, which were further subdivided by functional domain and pathogenicity as predicted by four in silico algorithms. Truncating variants in PALB2 (OR=4.69, 95% CI 2.27 to 9.68), ATM (OR=3.26; 95% CI 1.82 to 6.46) and CHEK2 (OR=3.11; 95% CI 2.15 to 4.69), but not XRCC2 (OR=0.94; 95% CI 0.26 to 4.19) were associated with increased BC risk. Truncating variants in ATM and CHEK2 were more strongly associated with risk of oestrogen receptor (ER)-positive than ER-negative disease, while those in PALB2 were associated with similar risks for both subtypes. There was also some evidence that missense variants in ATM , CHEK2 and PALB2 may contribute to BC risk, but larger studies are necessary to quantify the magnitude of this effect. Truncating variants in PALB2 are associated with a higher risk of BC than those in ATM or CHEK2 . A substantial risk of BC due to truncating XRCC2 variants can be excluded. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  15. Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tucker, Susan L., E-mail: sltucker@mdanderson.org; Li Minghuan; Xu Ting

    2013-01-01

    Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk ofmore » severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.« less

  16. Xrcc2 deficiency sensitizes cells to apoptosis by MNNG and the alkylating anticancer drugs temozolomide, fotemustine and mafosfamide.

    PubMed

    Tsaryk, Roman; Fabian, Kerstin; Thacker, John; Kaina, Bernd

    2006-08-08

    DNA double-strand breaks (DSBs) are potent killing lesions, and inefficient repair of DSBs does not only lead to cell death but also to genomic instability and tumorigenesis. DSBs are repaired by non-homologous end-joining and homologous recombination (HR). A key player in HR is Xrcc2, a Rad51-like protein. Cells deficient in Xrcc2 are hypersensitive to X-rays and mitomycin C and display increased chromosomal aberration frequencies. In order to elucidate the role of Xrcc2 in resistance to anticancer drugs, we compared Xrcc2 knockout (Xrcc2-/-) mouse embryonic fibroblasts with the corresponding isogenic wild-type and Xrcc2 complemented knockout cells. We show that Xrcc2-/- cells are hypersensitive to the killing effect of the simple methylating agent N-methyl-N'-nitro-N-nitrosoguanidine (MNNG). They undergo apoptosis after MNNG treatment while necrosis is only marginally enhanced. Complementation of Xrcc2 deficient cells by Xrcc2 cDNA transfection conferred resistance to the cytotoxic and apoptosis-inducing effect of MNNG. The hypersensitivity of Xrcc2-/- cells to MNNG prompted us to investigate their killing and apoptotic response to various methylating, chloroethylating and crosslinking drugs used in anticancer therapy. Xrcc2 deficient cells were found to be hypersensitive to temozolomide, fotemustine and mafosfamide. They were also hypersensitive to cisplatin but not to taxol. The data reveal that Xrcc2 plays a role in the protection against a wide range of anticancer drugs and, therefore, suggest Xrcc2 to be a determinant of anticancer drug resistance. They also indicate that HR is involved in the processing of DNA damage induced by simple alkylating agents.

  17. The XRCC1 Arg194Trp polymorphism is significantly associated with lung adenocarcinoma: a case-control study in an Eastern European Caucasian group.

    PubMed

    Cătană, Andreea; Pop, Monica; Hincu, Bianca Domokos; Pop, Ioan V; Petrişor, Felicia M; Porojan, Mihai D; Popp, Radu A

    2015-01-01

    DNA repair plays an important role in maintaining the integrity of the genome by repairing DNA damage induced by carcinogens. Certain genetic polymorphisms that occur in DNA-repair genes may affect the ability to repair DNA defects, and may represent a risk factor in carcinogenesis. The gene XRCC1 is involved in DNA repair. The purpose of our study was to investigate the association between XRCC1 Arg194Trp and Arg399Gln polymorphisms and the risk of lung cancer in a Romanian population. We recruited 222 healthy controls and 102 patients with lung cancer. Genotypes were determined by multiplex polymerase chain-reaction restriction fragment-length polymorphism. Statistical analysis (odds ratio, recessive model) revealed an increased risk for lung cancer for the homozygous 194Trp genotype (χ (2)=0.186, odds ratio 10.667, 95% confidence interval 1.309-86.933; P=0.007). Also, we found an association between the 194Trp allele and women with lung adenocarcinoma. In conclusion, the results of the study place the XRCC1 Arg194Trp polymorphism among independent risk factors for developing lung cancer.

  18. Modulation of DNA repair capacity and mRNA expression levels of XRCC1, hOGG1 and XPC genes in styrene-exposed workers.

    PubMed

    Hanova, Monika; Stetina, Rudolf; Vodickova, Ludmila; Vaclavikova, Radka; Hlavac, Pavel; Smerhovsky, Zdenek; Naccarati, Alessio; Polakova, Veronika; Soucek, Pavel; Kuricova, Miroslava; Manini, Paola; Kumar, Rajiv; Hemminki, Kari; Vodicka, Pavel

    2010-11-01

    Decreased levels of single-strand breaks in DNA (SSBs), reflecting DNA damage, have previously been observed with increased styrene exposure in contrast to a dose-dependent increase in the base-excision repair capacity. To clarify further the above aspects, we have investigated the associations between SSBs, micronuclei, DNA repair capacity and mRNA expression in XRCC1, hOGG1 and XPC genes on 71 styrene-exposed and 51 control individuals. Styrene concentrations at workplace and in blood characterized occupational exposure. The workers were divided into low (below 50 mg/m³) and high (above 50 mg/m³)) styrene exposure groups. DNA damage and DNA repair capacity were analyzed in peripheral blood lymphocytes by Comet assay. The mRNA expression levels were determined by qPCR. A significant negative correlation was observed between SSBs and styrene concentration at workplace (R=-0.38, p=0.001); SSBs were also significantly higher in men (p=0.001). The capacity to repair irradiation-induced DNA damage was the highest in the low exposure group (1.34±1.00 SSB/10⁹ Da), followed by high exposure group (0.72±0.81 SSB/10⁹ Da) and controls (0.65±0.82 SSB/10⁹ Da). The mRNA expression levels of XRCC1, hOGG1 and XPC negatively correlated with styrene concentrations in blood and at workplace (p<0.001) and positively with SSBs (p<0.001). Micronuclei were not affected by styrene exposure, but were higher in older persons and in women (p<0.001). In this study, we did not confirm previous findings on an increased DNA repair response to styrene-induced genotoxicity. However, negative correlations of SSBs and mRNA expression levels of XRCC1, hOGG1 and XPC with styrene exposure warrant further highly-targeted study. Copyright © 2010 Elsevier Inc. All rights reserved.

  19. [Polymorphism of genes encoding proteins of DNA repair vs. occupational and environmental exposure to lead, arsenic and pesticides].

    PubMed

    Bukowski, Karol; Woźniak, Katarzyna

    2018-03-09

    Genetic polymorphism is associated with the occurrence of at least 2 different alleles in the locus with a frequency higher than 1% in the population. Among polymorphisms we can find single nucleotide polymorphism (SNP) and polymorphism of variable number of tandem repeats. The presence of certain polymorphisms in genes encoding DNA repair enzymes is associated with the speed and efficiency of DNA repair and can protect or expose humans to the effects provoked by xenobiotics. Chemicals, such as lead, arsenic pesticides are considered to exhibit strong toxicity. There are many different polymorphisms in genes encoding DNA repair enzymes, which determine the speed and efficiency of DNA damage repair induced by these xenobiotics. In the case of lead, the influence of various polymorphisms, such as APE1 (apurinic/apyrimidinic endonuclease 1) (rs1130409), hOGG1 (human 8-oxoguanine glycosylase) (rs1052133), XRCC1 (X-ray repair cross-complementing protein group 1) (rs25487), XRCC1 (rs1799782) and XRCC3 (X-ray repair cross-complementing protein group 3) (rs861539) were described. For arsenic polymorphisms, such as ERCC2 (excision repair cross-complementing) (rs13181), XRCC3 (rs861539), APE1 (rs1130409) and hOGG1 (rs1052133) were examined. As to pesticides, separate and combined effects of polymorphisms in genes encoding DNA repair enzymes, such as XRCC1 (rs1799782), hOGG1 (rs1052133), XRCC4 (X-ray repair cross-complementing protein group 4) (rs28360135) and the gene encoding the detoxification enzyme PON1 paraoxonase (rs662) were reported. Med Pr 2018;69(2):225-235. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

  20. XRCC1 Arg399Gln was associated with repair capacity for DNA damage induced by occupational chromium exposure

    PubMed Central

    2012-01-01

    Background Occupational chromium exposure may induce DNA damage and lead to lung cancer and other work-related diseases. DNA repair gene polymorphisms, which may alter the efficiency of DNA repair, thus may contribute to genetic susceptibility of DNA damage. The aim of this study was to test the hypothesis that the genetic variations of 9 major DNA repair genes could modulate the hexavalent chromium (Cr (VI))-induced DNA damage. Findings The median (P25-P75) of Olive tail moment was 0.93 (0.58–1.79) for individuals carrying GG genotype of XRCC1 Arg399Gln (G/A), 0.73 (0.46–1.35) for GA heterozygote and 0.50 (0.43–0.93) for AA genotype. Significant difference was found among the subjects with three different genotypes (P = 0.048) after adjusting the confounding factors. The median of Olive tail moment of the subjects carrying A allele (the genotypes of AA and GA) was 0.66 (0.44–1.31), which was significantly lower than that of subjects with GG genotype (P = 0.043). The A allele conferred a significantly reduced risk of DNA damage with the OR of 0.39 (95% CI: 0.15–0.99, P = 0.048). No significant association was found between the XRCC1Arg194Trp, ERCC1 C8092A, ERCC5 His1104Asp, ERCC6 Gly399Asp, GSTP1 Ile105Val, OGG1 Ser326Cys, XPC Lys939Gln, XPD Lys751Gln and DNA damage. Conclusion The polymorphism of Arg399Gln in XRCC1 was associated with the Cr (VI)- induced DNA damage. XRCC1 Arg399Gln may serve as a genetic biomarker of susceptibility for Cr (VI)- induced DNA damage. PMID:22642904

  1. Worldwide Distribution of Four SNPs in X‐Ray and Repair and Cross‐Complementing Group 1 (XRCC1)

    PubMed Central

    Takeshita, Haruo; Yasuda, Toshihiro; Kimura‐Kataoka, Kaori

    2014-01-01

    Abstract Purpose X‐ray repair cross‐complementing group 1 (XRCC1) repairs single‐strand breaks in DNA. Several reports have shown the association of single nucleotide polymorphisms (SNPs) (Arg194Trp, Pro206Pro, Arg280His, Arg399Gln) in XRCC1 to diseases. Limited population data are available regarding SNPs in XRCC1, especially in African populations. In this study, genotype distributions of four SNPs in worldwide populations were examined and compared with those reported previously. Materials and Methods Four SNPs (Arg194Trp, Pro206Pro, Arg280His, Arg399Gln) in XRCC1 from genomic DNA samples of 10 populations were evaluated by using polymerase chain reaction followed by restriction fragment length polymorphism analysis. Results The frequency of the minor allele corresponding to the Trp allele of XRCC1Arg194Trp was higher in Asian populations than in African and Caucasian populations. As for XRCC1Pro206Pro, Africans showed higher minor allele frequencies than did Asian populations, except for Tamils and Sinhalese. XRCC1 Arg280His frequencies were similar among Africans and Caucasians but differed among Asian populations. Similarly, lower mutant XRCC1 Arg399Gln frequencies were observed in Africans. Conclusions This study is the first to show the existence of a certain genetic heterogeneity in the worldwide distribution of four SNPs in XRCC1. PMID:25387884

  2. Polymorphic Variation in Double Strand Break Repair Gene in Indian Population: A Comparative Approach with Worldwide Ethnic Group Variations.

    PubMed

    Mandal, Raju Kumar; Mittal, Rama Devi

    2018-04-01

    DNA repair capacity is essential in maintaining cellular functions and homeostasis. Identification of genetic polymorphisms responsible for reduced DNA repair capacity may allow better cancer prevention. Double strand break repair pathway plays critical roles in maintaining genome stability. Present study was conducted to determine distribution of XRCC3 Exon 7 (C18067T, rs861539) and XRCC7 Intron 8 (G6721T, rs7003908) gene polymorphisms in North Indian population and compare with different populations globally. The genotype assays were performed in 224 normal healthy individuals of similar ethnicity using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Allelic frequencies of wild type were 79% (C) in XRCC3 Exon 7 C > T and 57% (G) in XRCC7 Intron 8 (G > T) 57% (G) observed. On the other hand, the variant allele frequency were 21% (T) in XRCC3 Exon 7 C > T and 43% (T) in XRCC7 Intron 8 G > T respectively. Major differences from other ethnic populations were observed. Our results suggest that frequency in these DNA repair genes exhibit distinctive pattern in India that could be attributed to ethnicity variation. This could assist in high-risk screening of humans exposed to environmental carcinogens and cancer predisposition in different ethnic groups.

  3. The XRCC1 Arg194Trp polymorphism is significantly associated with lung adenocarcinoma: a case-control study in an Eastern European Caucasian group

    PubMed Central

    Cătană, Andreea; Pop, Monica; Hincu, Bianca Domokos; Pop, Ioan V; Petrişor, Felicia M; Porojan, Mihai D; Popp, Radu A

    2015-01-01

    DNA repair plays an important role in maintaining the integrity of the genome by repairing DNA damage induced by carcinogens. Certain genetic polymorphisms that occur in DNA-repair genes may affect the ability to repair DNA defects, and may represent a risk factor in carcinogenesis. The gene XRCC1 is involved in DNA repair. The purpose of our study was to investigate the association between XRCC1 Arg194Trp and Arg399Gln polymorphisms and the risk of lung cancer in a Romanian population. We recruited 222 healthy controls and 102 patients with lung cancer. Genotypes were determined by multiplex polymerase chain-reaction restriction fragment-length polymorphism. Statistical analysis (odds ratio, recessive model) revealed an increased risk for lung cancer for the homozygous 194Trp genotype (χ2=0.186, odds ratio 10.667, 95% confidence interval 1.309–86.933; P=0.007). Also, we found an association between the 194Trp allele and women with lung adenocarcinoma. In conclusion, the results of the study place the XRCC1 Arg194Trp polymorphism among independent risk factors for developing lung cancer. PMID:26664136

  4. X-Ray Cross-Complementing Group 1 and Thymidylate Synthase Polymorphisms Might Predict Response to Chemoradiotherapy in Rectal Cancer Patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lamas, Maria J., E-mail: mlamasd@yahoo.es; Duran, Goretti; Gomez, Antonio

    2012-01-01

    Purpose: 5-Fluorouracil-based chemoradiotherapy before total mesorectal excision is currently the standard treatment of Stage II and III rectal cancer patients. We used known predictive pharmacogenetic biomarkers to identify the responders to preoperative chemoradiotherapy in our series. Methods and Materials: A total of 93 Stage II-III rectal cancer patients were genotyped using peripheral blood samples. The genes analyzed were X-ray cross-complementing group 1 (XRCC1), ERCC1, MTHFR, EGFR, DPYD, and TYMS. The patients were treated with 225 mg/m{sup 2}/d continuous infusion of 5-fluorouracil concomitantly with radiotherapy (50.4 Gy) followed by total mesorectal excision. The outcomes were measured by tumor regression grade (TRG)more » as a major response (TRG 1 and TRG 2) or as a poor response (TRG3, TRG4, and TRG5). Results: The major histopathologic response rate was 47.3%. XRCC1 G/G carriers had a greater probability of response than G/A carriers (odds ratio, 4.18; 95% confidence interval, 1.62-10.74, p = .003) Patients with polymorphisms associated with high expression of thymidylate synthase (2R/3G, 3C/3G, and 3G/3G) showed a greater pathologic response rate compared with carriers of low expression (odds ratio, 2.65; 95% confidence interval, 1.10-6.39, p = .02) No significant differences were seen in the response according to EGFR, ERCC1, MTHFR{sub C}677 and MTHFR{sub A}1298 expression. Conclusions: XRCC1 G/G and thymidylate synthase (2R/3G, 3C/3G, and 3G/3G) are independent factors of a major response. Germline thymidylate synthase and XRCC1 polymorphisms might be useful as predictive markers of rectal tumor response to neoadjuvant chemoradiotherapy with 5-fluorouracil.« less

  5. Functional characterization of polymorphisms in DNA repair genes using cytogenetic challenge assays.

    PubMed

    Au, William W; Salama, Salama A; Sierra-Torres, Carlos H

    2003-11-01

    A major barrier to understanding the role of polymorphic DNA repair genes for environmental cancer is that the functions of variant genotypes are largely unknown. Using our cytogenetic challenge assays, we conducted an investigation to address the deficiency. Using X-rays or ultraviolet (UV) light, we irradiated blood lymphocytes from 80 nonsmoking donors to challenge the cells to repair the induced DNA damage, and we analyzed expression of chromosome aberrations (CA) specific to the inducing agents. We have genotyped polymorphic DNA repair genes preferentially involved with base excision repair (BER) and nucleotide excision repair (NER) activities (XRCC1, XRCC3, APE1, XPD) corresponding to the repair of X-ray- and UV light-induced DNA damage, respectively. We expected that defects in specific DNA repair pathways due to polymorphisms would cause corresponding increases of specific CA. From our data, XRCC1 399Gln and XRCC3 241Met were associated with significant increases in chromosome deletions compared with the corresponding homozygous wild types (18.27 1.1 vs 14.79 1.2 and 18.22 0.99 vs 14.20 1.39, respectively); XPD 312Asn and XPD 751Gln were associated with significant increases in chromatid breaks compared with wild types (16.09 1.36 vs 11.41 0.98 and 16.87 1.27 vs 10.54 0.87, respectively), p < 0.05. The data indicate that XRCC1 399Gln and XRCC3 241Met are significantly defective in BER, and the XPD 312Asn and XPD 751Gln are significantly defective in NER. In addition, the variant genotypes interact significantly, with limited overlap of the two different repair pathways.

  6. Polymorphisms in DNA double-strand break repair genes and risk of breast cancer: two population-based studies in USA and Poland, and meta-analyses.

    PubMed

    García-Closas, Montserrat; Egan, Kathleen M; Newcomb, Polly A; Brinton, Louise A; Titus-Ernstoff, Linda; Chanock, Stephen; Welch, Robert; Lissowska, Jolanta; Peplonska, Beata; Szeszenia-Dabrowska, Neonila; Zatonski, Witold; Bardin-Mikolajczak, Alicja; Struewing, Jeffery P

    2006-05-01

    The double-strand break DNA repair pathway has been implicated in breast carcinogenesis. We evaluated the association between 19 polymorphisms in seven genes in this pathway (XRCC2, XRCC3, BRCA2, ZNF350, BRIP1, XRCC4, LIG4) and breast cancer risk in two population-based studies in USA (3,368 cases and 2,880 controls) and Poland (1,995 cases and 2,296 controls). These data suggested weak associations with breast cancer risk for XRCC3 T241M and IVS7-14A>G (pooled odds ratio (95% confidence interval): 1.18 (1.04-1.34) and 0.85 (0.73-0.98) for homozygous variant vs wild-type genotypes, respectively), and for an uncommon variant in ZNF350 S472P (1.24 (1.05-1.48)), with no evidence for study heterogeneity. The remaining variants examined had no significant relationships to breast cancer risk. Meta-analyses of studies in Caucasian populations, including ours, provided some support for a weak association for homozygous variants for XRCC3 T241M (1.16 (1.04-1.30); total of 10,979 cases and 10,423 controls) and BRCA2 N372H (1.13 (1.10-1.28); total of 13,032 cases and 13,314 controls), and no support for XRCC2 R188H (1.06 (0.59-1.91); total of 8,394 cases and 8,404 controls). In conclusion, the genetic variants evaluated are unlikely to have a substantial overall association with breast cancer risk; however, weak associations are possible for XRCC3 (T241M and IVS7-14A>G), BRCA2 N372H, and ZNF350 S472P. Evaluation of potential underlying gene-gene interactions or associations in population subgroups will require even larger sample sizes.

  7. Asparagine 326 in the extremely C-terminal region of XRCC4 is essential for the cell survival after irradiation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wanotayan, Rujira; Fukuchi, Mikoto; Imamichi, Shoji

    2015-02-20

    XRCC4 is one of the crucial proteins in the repair of DNA double-strand break (DSB) through non-homologous end-joining (NHEJ). As XRCC4 consists of 336 amino acids, N-terminal 200 amino acids include domains for dimerization and for association with DNA ligase IV and XLF and shown to be essential for XRCC4 function in DSB repair and V(D)J recombination. On the other hand, the role of the remaining C-terminal region of XRCC4 is not well understood. In the present study, we noticed that a stretch of ∼20 amino acids located at the extreme C-terminus of XRCC4 is highly conserved among vertebrate species.more » To explore its possible importance, series of mutants in this region were constructed and assessed for the functionality in terms of ability to rescue radiosensitivity of M10 cells lacking XRCC4. Among 13 mutants, M10 transfectant with N326L mutant (M10-XRCC4{sup N326L}) showed elevated radiosensitivity. N326L protein showed defective nuclear localization. N326L sequence matched the consensus sequence of nuclear export signal. Leptomycin B treatment accumulated XRCC4{sup N326L} in the nucleus but only partially rescued radiosensitivity of M10-XRCC4{sup N326L}. These results collectively indicated that the functional defects of XRCC4{sup N326L} might be partially, but not solely, due to its exclusion from nucleus by synthetic nuclear export signal. Further mutation of XRCC4 Asn326 to other amino acids, i.e., alanine, aspartic acid or glutamine did not affect the nuclear localization but still exhibited radiosensitivity. The present results indicated the importance of the extremely C-terminal region of XRCC4 and, especially, Asn326 therein. - Highlights: • Extremely C-terminal region of XRCC4 is highly conserved among vertebrate species. • XRCC4 C-terminal point mutants, R325F and N326L, are functionally deficient in terms of survival after irradiation. • N326L localizes to the cytoplasm because of synthetic nuclear export signal. • Leptomycin B

  8. Characterization of the APLF FHA–XRCC1 phosphopeptide interaction and its structural and functional implications

    PubMed Central

    Kim, Kyungmin; Pedersen, Lars C.; Kirby, Thomas W.; DeRose, Eugene F.

    2017-01-01

    Abstract Aprataxin and PNKP-like factor (APLF) is a DNA repair factor containing a forkhead-associated (FHA) domain that supports binding to the phosphorylated FHA domain binding motifs (FBMs) in XRCC1 and XRCC4. We have characterized the interaction of the APLF FHA domain with phosphorylated XRCC1 peptides using crystallographic, NMR, and fluorescence polarization studies. The FHA–FBM interactions exhibit significant pH dependence in the physiological range as a consequence of the atypically high pK values of the phosphoserine and phosphothreonine residues and the preference for a dianionic charge state of FHA-bound pThr. These high pK values are characteristic of the polyanionic peptides typically produced by CK2 phosphorylation. Binding affinity is greatly enhanced by residues flanking the crystallographically-defined recognition motif, apparently as a consequence of non-specific electrostatic interactions, supporting the role of XRCC1 in nuclear cotransport of APLF. The FHA domain-dependent interaction of XRCC1 with APLF joins repair scaffolds that support single-strand break repair and non-homologous end joining (NHEJ). It is suggested that for double-strand DNA breaks that have initially formed a complex with PARP1 and its binding partner XRCC1, this interaction acts as a backup attempt to intercept the more error-prone alternative NHEJ repair pathway by recruiting Ku and associated NHEJ factors. PMID:29059378

  9. The cAMP signaling system inhibits the repair of {gamma}-ray-induced DNA damage by promoting Epac1-mediated proteasomal degradation of XRCC1 protein in human lung cancer cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Cho, Eun-Ah; Juhnn, Yong-Sung, E-mail: juhnn@snu.ac.kr

    2012-06-01

    Highlights: Black-Right-Pointing-Pointer cAMP signaling system inhibits repair of {gamma}-ray-induced DNA damage. Black-Right-Pointing-Pointer cAMP signaling system inhibits DNA damage repair by decreasing XRCC1 expression. Black-Right-Pointing-Pointer cAMP signaling system decreases XRCC1 expression by promoting its proteasomal degradation. Black-Right-Pointing-Pointer The promotion of XRCC1 degradation by cAMP signaling system is mediated by Epac1. -- Abstract: Cyclic AMP is involved in the regulation of metabolism, gene expression, cellular growth and proliferation. Recently, the cAMP signaling system was found to modulate DNA-damaging agent-induced apoptosis by regulating the expression of Bcl-2 family proteins and inhibitors of apoptosis. Thus, we hypothesized that the cAMP signaling may modulate DNAmore » repair activity, and we investigated the effects of the cAMP signaling system on {gamma}-ray-induced DNA damage repair in lung cancer cells. Transient expression of a constitutively active mutant of stimulatory G protein (G{alpha}sQL) or treatment with forskolin, an adenylyl cyclase activator, augmented radiation-induced DNA damage and inhibited repair of the damage in H1299 lung cancer cells. Expression of G{alpha}sQL or treatment with forskolin or isoproterenol inhibited the radiation-induced expression of the XRCC1 protein, and exogenous expression of XRCC1 abolished the DNA repair-inhibiting effect of forskolin. Forskolin treatment promoted the ubiquitin and proteasome-dependent degradation of the XRCC1 protein, resulting in a significant decrease in the half-life of the protein after {gamma}-ray irradiation. The effect of forskolin on XRCC1 expression was not inhibited by PKA inhibitor, but 8-pCPT-2 Prime -O-Me-cAMP, an Epac-selective cAMP analog, increased ubiquitination of XRCC1 protein and decreased XRCC1 expression. Knockdown of Epac1 abolished the effect of 8-pCPT-2 Prime -O-Me-cAMP and restored XRCC1 protein level following {gamma

  10. An XRCC4 Splice Mutation Associated With Severe Short Stature, Gonadal Failure, and Early-Onset Metabolic Syndrome

    PubMed Central

    de Bruin, Christiaan; Mericq, Verónica; Andrew, Shayne F.; van Duyvenvoorde, Hermine A.; Verkaik, Nicole S.; Losekoot, Monique; Porollo, Aleksey; Garcia, Hernán; Kuang, Yi; Hanson, Dan; Clayton, Peter; van Gent, Dik C.; Wit, Jan M.; Hwa, Vivian

    2015-01-01

    Context: Severe short stature can be caused by defects in numerous biological processes including defects in IGF-1 signaling, centromere function, cell cycle control, and DNA damage repair. Many syndromic causes of short stature are associated with medical comorbidities including hypogonadism and microcephaly. Objective: To identify an underlying genetic etiology in two siblings with severe short stature and gonadal failure. Design: Clinical phenotyping, genetic analysis, complemented by in vitro functional studies of the candidate gene. Setting: An academic pediatric endocrinology clinic. Patients or Other Participants: Two adult siblings (male patient [P1] and female patient 2 [P2]) presented with a history of severe postnatal growth failure (adult heights: P1, −6.8 SD score; P2, −4 SD score), microcephaly, primary gonadal failure, and early-onset metabolic syndrome in late adolescence. In addition, P2 developed a malignant gastrointestinal stromal tumor at age 28. Intervention(s): Single nucleotide polymorphism microarray and exome sequencing. Results: Combined microarray analysis and whole exome sequencing of the two affected siblings and one unaffected sister identified a homozygous variant in XRCC4 as the probable candidate variant. Sanger sequencing and mRNA studies revealed a splice variant resulting in an in-frame deletion of 23 amino acids. Primary fibroblasts (P1) showed a DNA damage repair defect. Conclusions: In this study we have identified a novel pathogenic variant in XRCC4, a gene that plays a critical role in non-homologous end-joining DNA repair. This finding expands the spectrum of DNA damage repair syndromes to include XRCC4 deficiency causing severe postnatal growth failure, microcephaly, gonadal failure, metabolic syndrome, and possibly tumor predisposition. PMID:25742519

  11. SNPs in DNA repair or oxidative stress genes and late subcutaneous fibrosis in patients following single shot partial breast irradiation

    PubMed Central

    2012-01-01

    Background The aim of this study was to evaluate the potential association between single nucleotide polymorphisms related response to radiotherapy injury, such as genes related to DNA repair or enzymes involved in anti-oxidative activities. The paper aims to identify marker genes able to predict an increased risk of late toxicity studying our group of patients who underwent a Single Shot 3D-CRT PBI (SSPBI) after BCS (breast conserving surgery). Methods A total of 57 breast cancer patients who underwent SSPBI were genotyped for SNPs (single nucleotide polymorphisms) in XRCC1, XRCC3, GST and RAD51 by Pyrosequencing technology. Univariate analysis (ORs and 95% CI) was performed to correlate SNPs with the risk of developing ≥ G2 fibrosis or fat necrosis. Results A higher significant risk of developing ≥ G2 fibrosis or fat necrosis in patients with: polymorphic variant GSTP1 (Ile105Val) (OR = 2.9; 95%CI, 0.88-10.14, p = 0.047). Conclusions The presence of some SNPs involved in DNA repair or response to oxidative stress seem to be able to predict late toxicity. Trial Registration ClinicalTrials.gov: NCT01316328 PMID:22272830

  12. Genetic polymorphisms and expression of minisatellite mutations in a 3-generation population around the Semipalatinsk nuclear explosion test-site, Kazakhstan.

    PubMed

    Bolegenova, N K; Bekmanov, B O; Djansugurova, L B; Bersimbaev, R I; Salama, S A; Au, W W

    2009-11-01

    We have reported previously that a population near the Semipalatinsk nuclear explosion test site had significantly increased minisatellite mutations (MM), suggesting increased germ-line mutation rates from the exposure in 3 generations. We hypothesize that the MM can be used as a surrogate biomarker for functional genetic alterations, e.g. gene mutations and chromosome aberrations. Therefore, we have investigated the influence of polymorphisms in genes on the expression of MM in the same two populations (247 and 172 individuals, for exposed and control, respectively, in 3 generations), and their relationships with radiation exposure. We have chosen the analyses of three polymorphic DNA - repair genes (XRCC1, XRCC1 and XRCC3) and two xenobiotic detoxification genes (GSTT1 and GSTM1). Among the exposed and in comparison with the wild-type gene, the functionally active XRCC1 Arg194Trp was significantly associated with low MM and over-represented in the exposed compared with the control populations. In a similar analysis, the functionally deficient XRCC1 Arg399Glu and XRCC3 Trp241Met were associated with increased and significantly reduced MM, respectively, but these variant genes were under-represented in the exposed population. Both GSTT1 and GSTM1 nulls were significantly associated with increased MM. The former was under-represented but the latter was significantly over-represented in the exposed compared with the control populations. In summary, the data indicate that the expected enzymatic functions of the polymorphic genes are consistent with the MM expression, except the XRCC1 Arg399Glu variant gene. In addition, the variant genes were retained in the three generations in association with their useful function, except for the GSTM1 null. However, the MM frequencies in the exposed were not consistently and significantly higher than those in the control populations, radiation exposure may therefore not have been the only cause for the high MM frequency among the

  13. Characterization of the APLF FHA-XRCC1 phosphopeptide interaction and its structural and functional implications.

    PubMed

    Kim, Kyungmin; Pedersen, Lars C; Kirby, Thomas W; DeRose, Eugene F; London, Robert E

    2017-12-01

    Aprataxin and PNKP-like factor (APLF) is a DNA repair factor containing a forkhead-associated (FHA) domain that supports binding to the phosphorylated FHA domain binding motifs (FBMs) in XRCC1 and XRCC4. We have characterized the interaction of the APLF FHA domain with phosphorylated XRCC1 peptides using crystallographic, NMR, and fluorescence polarization studies. The FHA-FBM interactions exhibit significant pH dependence in the physiological range as a consequence of the atypically high pK values of the phosphoserine and phosphothreonine residues and the preference for a dianionic charge state of FHA-bound pThr. These high pK values are characteristic of the polyanionic peptides typically produced by CK2 phosphorylation. Binding affinity is greatly enhanced by residues flanking the crystallographically-defined recognition motif, apparently as a consequence of non-specific electrostatic interactions, supporting the role of XRCC1 in nuclear cotransport of APLF. The FHA domain-dependent interaction of XRCC1 with APLF joins repair scaffolds that support single-strand break repair and non-homologous end joining (NHEJ). It is suggested that for double-strand DNA breaks that have initially formed a complex with PARP1 and its binding partner XRCC1, this interaction acts as a backup attempt to intercept the more error-prone alternative NHEJ repair pathway by recruiting Ku and associated NHEJ factors. Published by Oxford University Press on behalf of Nucleic Acids Research 2017.

  14. The cAMP signaling system inhibits the repair of γ-ray-induced DNA damage by promoting Epac1-mediated proteasomal degradation of XRCC1 protein in human lung cancer cells.

    PubMed

    Cho, Eun-Ah; Juhnn, Yong-Sung

    2012-06-01

    Cyclic AMP is involved in the regulation of metabolism, gene expression, cellular growth and proliferation. Recently, the cAMP signaling system was found to modulate DNA-damaging agent-induced apoptosis by regulating the expression of Bcl-2 family proteins and inhibitors of apoptosis. Thus, we hypothesized that the cAMP signaling may modulate DNA repair activity, and we investigated the effects of the cAMP signaling system on γ-ray-induced DNA damage repair in lung cancer cells. Transient expression of a constitutively active mutant of stimulatory G protein (GαsQL) or treatment with forskolin, an adenylyl cyclase activator, augmented radiation-induced DNA damage and inhibited repair of the damage in H1299 lung cancer cells. Expression of GαsQL or treatment with forskolin or isoproterenol inhibited the radiation-induced expression of the XRCC1 protein, and exogenous expression of XRCC1 abolished the DNA repair-inhibiting effect of forskolin. Forskolin treatment promoted the ubiquitin and proteasome-dependent degradation of the XRCC1 protein, resulting in a significant decrease in the half-life of the protein after γ-ray irradiation. The effect of forskolin on XRCC1 expression was not inhibited by PKA inhibitor, but 8-pCPT-2'-O-Me-cAMP, an Epac-selective cAMP analog, increased ubiquitination of XRCC1 protein and decreased XRCC1 expression. Knockdown of Epac1 abolished the effect of 8-pCPT-2'-O-Me-cAMP and restored XRCC1 protein level following γ-ray irradiation. From these results, we conclude that the cAMP signaling system inhibits the repair of γ-ray-induced DNA damage by promoting the ubiquitin-proteasome dependent degradation of XRCC1 in an Epac-dependent pathway in lung cancer cells. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Mutations in the NHEJ component XRCC4 cause primordial dwarfism.

    PubMed

    Murray, Jennie E; van der Burg, Mirjam; IJspeert, Hanna; Carroll, Paula; Wu, Qian; Ochi, Takashi; Leitch, Andrea; Miller, Edward S; Kysela, Boris; Jawad, Alireza; Bottani, Armand; Brancati, Francesco; Cappa, Marco; Cormier-Daire, Valerie; Deshpande, Charu; Faqeih, Eissa A; Graham, Gail E; Ranza, Emmanuelle; Blundell, Tom L; Jackson, Andrew P; Stewart, Grant S; Bicknell, Louise S

    2015-03-05

    Non-homologous end joining (NHEJ) is a key cellular process ensuring genome integrity. Mutations in several components of the NHEJ pathway have been identified, often associated with severe combined immunodeficiency (SCID), consistent with the requirement for NHEJ during V(D)J recombination to ensure diversity of the adaptive immune system. In contrast, we have recently found that biallelic mutations in LIG4 are a common cause of microcephalic primordial dwarfism (MPD), a phenotype characterized by prenatal-onset extreme global growth failure. Here we provide definitive molecular genetic evidence supported by biochemical, cellular, and immunological data for mutations in XRCC4, encoding the obligate binding partner of LIG4, causing MPD. We report the identification of biallelic mutations in XRCC4 in five families. Biochemical and cellular studies demonstrate that these alterations substantially decrease XRCC4 protein levels leading to reduced cellular ligase IV activity. Consequently, NHEJ-dependent repair of ionizing-radiation-induced DNA double-strand breaks is compromised in XRCC4 cells. Similarly, immunoglobulin junctional diversification is impaired in cells. However, immunoglobulin levels are normal, and individuals lack overt signs of immunodeficiency. Additionally, in contrast to individuals with LIG4 mutations, pancytopenia leading to bone marrow failure has not been observed. Hence, alterations that alter different NHEJ proteins give rise to a phenotypic spectrum, from SCID to extreme growth failure, with deficiencies in certain key components of this repair pathway predominantly exhibiting growth deficits, reflecting differential developmental requirements for NHEJ proteins to support growth and immune maturation. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

  16. Mutations in the NHEJ Component XRCC4 Cause Primordial Dwarfism

    PubMed Central

    Murray, Jennie E.; van der Burg, Mirjam; IJspeert, Hanna; Carroll, Paula; Wu, Qian; Ochi, Takashi; Leitch, Andrea; Miller, Edward S.; Kysela, Boris; Jawad, Alireza; Bottani, Armand; Brancati, Francesco; Cappa, Marco; Cormier-Daire, Valerie; Deshpande, Charu; Faqeih, Eissa A.; Graham, Gail E.; Ranza, Emmanuelle; Blundell, Tom L.; Jackson, Andrew P.; Stewart, Grant S.; Bicknell, Louise S.

    2015-01-01

    Non-homologous end joining (NHEJ) is a key cellular process ensuring genome integrity. Mutations in several components of the NHEJ pathway have been identified, often associated with severe combined immunodeficiency (SCID), consistent with the requirement for NHEJ during V(D)J recombination to ensure diversity of the adaptive immune system. In contrast, we have recently found that biallelic mutations in LIG4 are a common cause of microcephalic primordial dwarfism (MPD), a phenotype characterized by prenatal-onset extreme global growth failure. Here we provide definitive molecular genetic evidence supported by biochemical, cellular, and immunological data for mutations in XRCC4, encoding the obligate binding partner of LIG4, causing MPD. We report the identification of biallelic mutations in XRCC4 in five families. Biochemical and cellular studies demonstrate that these alterations substantially decrease XRCC4 protein levels leading to reduced cellular ligase IV activity. Consequently, NHEJ-dependent repair of ionizing-radiation-induced DNA double-strand breaks is compromised in XRCC4 cells. Similarly, immunoglobulin junctional diversification is impaired in cells. However, immunoglobulin levels are normal, and individuals lack overt signs of immunodeficiency. Additionally, in contrast to individuals with LIG4 mutations, pancytopenia leading to bone marrow failure has not been observed. Hence, alterations that alter different NHEJ proteins give rise to a phenotypic spectrum, from SCID to extreme growth failure, with deficiencies in certain key components of this repair pathway predominantly exhibiting growth deficits, reflecting differential developmental requirements for NHEJ proteins to support growth and immune maturation. PMID:25728776

  17. Association between XRCC1 polymorphisms and laryngeal cancer susceptibility in a Chinese sample population.

    PubMed

    Wu, W Q; Zhang, L S; Liao, S P; Lin, X L; Zeng, J; Du, D

    2016-10-05

    Laryngeal cancer is the major malignant tumor affecting the upper respiratory tract. Previous studies have reported on the association between XRCC1 genetic polymorphisms and risk of laryngeal cancer, but with conflicting results. In this study, we attempted to assess the association between XRCC1 Arg194Trp, Arg280His and Arg399Gln polymorphisms and risk of laryngeal cancer in a Chinese population. A total of 126 laryngeal cancer patients and 254 control subjects were recruited to this study from the Second Medical College of Jinan University between December 2013 and May 2015. The XRCC1 Arg194Trp, Arg280His, and Arg399Gln polymorphic sites were genotyped by polymerase chain reaction-restriction fragment length polymorphism. Our results revealed a significant association between the AA genotype of XRCC1 Arg280His [odds ratio (OR) = 2.51, 95% confidence interval (CI) = 1.29-4.87, P = 0.01] and an increased risk of laryngeal cancer susceptibility compared to the GG genotype. Moreover, the A allele showed a higher risk of laryngeal cancer susceptibility compared to the G allele (OR = 1.63, 95%CI = 1.19-2.50, P = 0.002). In conclusion, the results of our study suggest that the AA genotype and A allele of the XRCC1 Arg280His polymorphism are associated with an increased laryngeal cancer risk in a Chinese population.

  18. Structure-Based Virtual Ligand Screening on the XRCC4/DNA Ligase IV Interface

    NASA Astrophysics Data System (ADS)

    Menchon, Grégory; Bombarde, Oriane; Trivedi, Mansi; Négrel, Aurélie; Inard, Cyril; Giudetti, Brigitte; Baltas, Michel; Milon, Alain; Modesti, Mauro; Czaplicki, Georges; Calsou, Patrick

    2016-03-01

    The association of DNA Ligase IV (Lig4) with XRCC4 is essential for repair of DNA double-strand breaks (DSBs) by Non-homologous end-joining (NHEJ) in humans. DSBs cytotoxicity is largely exploited in anticancer therapy. Thus, NHEJ is an attractive target for strategies aimed at increasing the sensitivity of tumors to clastogenic anticancer treatments. However the high affinity of the XRCC4/Lig4 interaction and the extended protein-protein interface make drug screening on this target particularly challenging. Here, we conducted a pioneering study aimed at interfering with XRCC4/Lig4 assembly. By Molecular Dynamics simulation using the crystal structure of the complex, we first delineated the Lig4 clamp domain as a limited suitable target. Then, we performed in silico screening of ~95,000 filtered molecules on this Lig4 subdomain. Hits were evaluated by Differential Scanning Fluorimetry, Saturation Transfer Difference - NMR spectroscopy and interaction assays with purified recombinant proteins. In this way we identified the first molecule able to prevent Lig4 binding to XRCC4 in vitro. This compound has a unique tripartite interaction with the Lig4 clamp domain that suggests a starting chemotype for rational design of analogous molecules with improved affinity.

  19. Polymorphisms in nonhomologous end-joining genes associated with breast cancer risk and chromosomal radiosensitivity.

    PubMed

    Willems, Petra; Claes, Kathleen; Baeyens, Ans; Vandersickel, Veerle; Werbrouck, Joke; De Ruyck, Kim; Poppe, Bruce; Van den Broecke, Rudy; Makar, Amin; Marras, Emanuela; Perletti, Gianpaolo; Thierens, Hubert; Vral, Anne

    2008-02-01

    As enhanced chromosomal radiosensitivity (CRS) results from non- or misrepaired double strand breaks (DSBs) and is a hallmark for breast cancer and single nucleotide polymorphisms (SNPs) in DSB repair genes, such as non homologous end-joining (NHEJ) genes, could be involved in CRS and genetic predisposition to breast cancer. In this study, we investigated the association of five SNPs in three different NHEJ genes with breast cancer in a population-based case-control setting. The total patient population composed of a selected group of patients with a family history of the disease and an unselected group, consisting mainly of sporadic cases. SNP analysis showed that the c.2099-2408G>A SNP (XRCC5Ku80) [corrected] has a significant, positive odds ratio (OR) of 2.81 (95% confidence interval (CI): 1.30-6.05) for the heterozygous (He) and homozygous variant (HV) genotypes in the selected patient group. For the c.-1310 C>G SNP (XRCC6Ku70)[corrected] a significant OR of 1.85 (95%CI: 1.01-3.41) was found for the He genotype in the unselected patient group. On the contrary, the HV genotype of c.1781G>T (XRCC6Ku70) [corrected] displays a significant, negative OR of 0.43 (95%CI: 0.18-0.99) in the total patient population. The He+HV genotypes of the c.2099-2408G>A SNP (XRCC5Ku80) [corrected] also showed high and significant ORs in the group of "radiosensitive," familial breast cancer patients. In conclusion, our results provide preliminary evidence that the variant allele of c.-1310C>G (XRCC6Ku70) [corrected]and c.2099-2408G>A (XRCC5Ku80) [corrected] are risk alleles for breast cancer as well as CRS. The HV genotype of c.1781G>T (XRCC6Ku70) [corrected] on the contrary, seems to protect against breast cancer and ionizing radiation induced micronuclei. (c) 2007 Wiley-Liss, Inc.

  20. Genetic variation in a DNA double strand break repair gene in saudi population: a comparative study with worldwide ethnic groups.

    PubMed

    Areeshi, Mohammed Yahya

    2013-01-01

    DNA repair capacity is crucial in maintaining cellular functions and homeostasis. However, it can be altered based on DNA sequence variations in DNA repair genes and this may lead to the development of many diseases including malignancies. Identification of genetic polymorphisms responsible for reduced DNA repair capacity is necessary for better prevention. Homologous recombination (HR), a major double strand break repair pathway, plays a critical role in maintaining the genome stability. The present study was performed to determine the frequency of the HR gene XRCC3 Exon 7 (C18067T, rs861539) polymorphisms in Saudi Arabian population in comparison with epidemiological studies by "MEDLINE" search to equate with global populations. The variant allelic (T) frequency of XRCC3 (C>T) was found to be 39%. Our results suggest that frequency of XRCC3 (C>T) DNA repair gene exhibits distinctive patterns compared with the Saudi Arabian population and this might be attributed to ethnic variation. The present findings may help in high-risk screening of humans exposed to environmental carcinogens and cancer predisposition in different ethnic groups.

  1. Retraction RETRACTION of "Association between polymorphisms in the XRCC1 gene and the risk of non-small cell lung cancer", by Han JC, Zhang YJ and Li XD - Genet. Mol. Res. 14 (4): 12888-12893 (2015).

    PubMed

    Han, J C; Zhang, Y J; Li, X D

    2016-10-07

    The retracted article is: Han JC, Zhang YJ and Li XD (2015). Association between polymorphisms in the XRCC1 gene and the risk of non-small cell lung cancer. Genet. Mol. Res. 14: 12888-12893. The GMR editorial staff was alerted about this article (received on May 3, 2015; accepted on August 18, 2015) published on October 21, 2015 (DOI: 10.4238/2015.October.21.9) that was found to be substantially similar to the publication of "Association of XRCC1 gene polymorphisms with risk of non-small cell lung cancer" (received on January 25, 2015; accepted on March 23, 2015; e-published on April 1, 2015) by Kang et al., published in the International Journal of Clinical Experimental Pathology 8 (4): 4171-4176. The authors were aware of the Kang et al.'s paper, since they cite it several times in the manuscript published in GMR. Some of the language is similar between the two manuscripts, but what is the most concerning is that several of the tables in the papers are nearly identical. Tables 2 and 3 are exactly identical between the two articles, suggesting that the publication in GMR was plagiarized from the publication in the International Journal of Clinical Experimental Pathology. The Publisher and Editor decided to retract these articles in accordance with the recommendations of the Committee on Publication Ethics (COPE). After a thorough investigation, we have strong reason to believe that the peer review process was failure and, after review and contacting the authors, the editors of Genetics and Molecular Research decided to retract the article. The authors and their institutions were advised of this serious breach of ethics.

  2. Association of XRCC1 Trp194 allele with risk of breast cancer, and Ki67 protein status in breast tumor tissues

    PubMed Central

    Jalali, Chiya; Ghaderi, Bayazid; Amini, Sabrieh; Abdi, Mohammad; Roshani, Daem

    2016-01-01

    Objectives: To evaluate the role of this polymorphism as a risk factor for breast cancer in Kurdish patients and to investigate the possible association between Arg194Trp x-ray repair cross-complementing group 1 (XRCC1) gene polymorphisms with clinical and histopathological outcomes of patients with breast cancer. Methods: A total of 100 breast cancer patients and 200 cancer-free controls in Kurdish population of Kurdistan state admitted to Tohid Hospital, Sanandaj, Kurdistan, Iran between January 2012 and May 2015 were enrolled in this cross-sectional study. Tissue expression of estrogen receptor (ER), progesteron receptor (PR), human epidermal growth factor receptor 2 (Her2/neu), and Ki67 were evaluated by immunohistochemistry (IHC). The Arg194Trp genotypes were determined by polymerase chain reaction- restriction fragment length polymorphism method. Results: Our data showed that the risk for breast cancer increased significantly among the Trp variant of XRCC1. Statistically significant association was found between codon 194 polymorphisms and tissue expression of Ki67. Conclusion: The Trp allele of codon 194 XRCC1 is a potential risk factor for breast cancer in Kurdish ethnicity. Furthermore, effect of this polymorphism on clinical and histological features of breast cancer was significant. PMID:27279507

  3. MTHFR, TS and XRCC1 genetic variants may affect survival in patients with myelodysplastic syndromes treated with supportive care or azacitidine.

    PubMed

    Visani, G; Loscocco, F; Ruzzo, A; Galimberti, S; Graziano, F; Voso, M T; Giacomini, E; Finelli, C; Ciabatti, E; Fabiani, E; Barulli, S; Volpe, A; Magro, D; Piccaluga, P; Fuligni, F; Vignetti, M; Fazi, P; Piciocchi, A; Gabucci, E; Rocchi, M; Magnani, M; Isidori, A

    2017-12-05

    We evaluated the impact of genomic polymorphisms in folate-metabolizing, DNA synthesis and DNA repair enzymes on the clinical outcome of 108 patients with myelodysplastic syndromes (MDS) receiving best supportive care (BSC) or azacitidine. A statistically significant association between methylenetetrahydrofolate reductase (MTHFR) 677T/T, thymidylate synthase (TS) 5'-untranslated region (UTR) 3RG, TS 3'-UTR -6 bp/-6 bp, XRCC1 399G/G genotypes and short survival was found in patients receiving BSC by multivariate analysis (P<0.001; P=0.026; P=0.058; P=0.024). MTHFR 677T/T, TS 3'-UTR -6 bp/-6 bp and XRCC1 399G/G genotypes were associated with short survival in patients receiving azacitidine by multivariate analysis (P<0.001; P=0.004; P=0.002). We then performed an exploratory analysis to evaluate the effect of the simultaneous presence of multiple adverse variant genotypes. Interestingly, patients with ⩾1 adverse genetic variants had a short survival, independently from their International Prognostic Scoring System (IPSS) and therapy received. To our knowledge, this is the first study showing that polymorphisms in folate-metabolizing pathway, DNA synthesis and DNA repair genes could influence survival of MDS patients.The Pharmacogenomics Journal advance online publication, 5 December 2017; doi:10.1038/tpj.2017.48.

  4. Genetic polymorphisms in 19q13.3 genes associated with alteration of repair capacity to BPDE-DNA adducts in primary cultured lymphocytes.

    PubMed

    Xiao, Mingyang; Xiao, Sha; Straaten, Tahar van der; Xue, Ping; Zhang, Guopei; Zheng, Xiao; Zhang, Qianye; Cai, Yuan; Jin, Cuihong; Yang, Jinghua; Wu, Shengwen; Zhu, Guolian; Lu, Xiaobo

    2016-12-01

    Benzo[a]pyrene(B[a]P), and its ultimate metabolite Benzo[a]pyrene 7,8-diol 9,10-epoxide (BPDE), are classic DNA damaging carcinogens. DNA damage in cells caused by BPDE is normally repaired by Nucleotide Excision Repair (NER) and Base Excision Repair (BER). Genetic variations in NER and BER can change individual DNA repair capacity to DNA damage induced by BPDE. In the present study we determined the number of in vitro induced BPDE-DNA adducts in lymphocytes, to reflect individual susceptibility to Polycyclic aromatic hydrocarbons (PAHs)-induced carcinogenesis. The BPDE-DNA adduct level in lymphocytes were assessed by high performance liquid chromatography (HPLC) in 281 randomly selected participants. We genotyped for 9 single nucleotide polymorphisms (SNPs) in genes involved in NER (XPB rs4150441, XPC rs2228001, rs2279017 and XPF rs4781560), BER (XRCC1 rs25487, rs25489 and rs1799782) and genes located on chromosome 19q13.2-3 (PPP1R13L rs1005165 and CAST rs967591). We found that 3 polymorphisms in chromosome 19q13.2-3 were associated with lower levels of BPDE-DNA adducts (MinorT allele in XRCC1 rs1799782, minor T allele in PPP1R13L rs1005165 and minor A allele in CAST rs967571). In addition, a modified comet assay was performed to further confirm the above conclusions. We found both minor T allele in PPP1R13L rs1005165 and minor A allele in CAST rs967571 were associated with the lower levels of BPDE-adducts. Our data suggested that the variant genotypes of genes in chromosome 19q13.2-3 are associated with the alteration of repair efficiency to DNA damage caused by Benzo[a]pyrene, and may contribute to enhance predictive value for individual's DNA repair capacity in response to environmental carcinogens. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. XRCC1 Polymorphisms and Pancreatic Cancer: A Meta-Analysis

    PubMed Central

    Shen, Wei-dong; Chen, Hong-lin; Liu, Peng-fei

    2011-01-01

    Objective To assess the association between X-ray repair cross-complementating group 1 (XRCC1) polymorphisms and pancreatic cancer. Methods We searched MEDLINE, Web of Science and HuGE Navigator at June 2010, and then quantitatively summarized associations of the XRCC1 polymorphisms with pancreatic cancer risk using meta-analysis. Results Four studies with 1343 cases and 2302 controls were included. Our analysis found: at codon 194, the Trp allele did not decrease pancreatic cancer risk (Arg/Arg versus Trp/Trp: OR=0.97; 95% CI: 0.48-1.96; P=0.97; Arg/Arg versus Arg/Trp: OR=0.89; 95% CI: 0.70-1.13; P=0.55; Arg/Trp versus Trp/Trp: OR=1.06; 95% CI: 0.52-2.16; P=0.90); at codon 280, only a study showed a nonsignificant association between single nucleotide polymorphism with pancreatic cancer risk; at codon 399, the Gln allele also showed no significant effect on pancreatic cancer compared to Arg allele (Arg/Arg versus Gln/Gln: OR=0.94; 95% CI: 0.74-1.18; Arg/Arg versus Arg/Gln: OR=0.97; 95% CI: 0.83-1.13; Arg/Gln versus Gln/Gln: OR=0.97; 95% CI: 0.77-1.22). The shape of the funnel plot and the Egger’s test did not detect any publication bias. Conclusion There is no evidence that XRCC1 polymorphisms (Arg194Trp, Arg280His, and Arg399Gln) are associated with pancreatic cancer risk. PMID:23467456

  6. Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia

    PubMed Central

    LI, CHENGLONG; ZHU, BIAO; CHEN, JIAO; HUANG, XIAOBING

    2016-01-01

    In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation-positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the micro-array data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML. PMID:27177049

  7. Feature genes predicting the FLT3/ITD mutation in acute myeloid leukemia.

    PubMed

    Li, Chenglong; Zhu, Biao; Chen, Jiao; Huang, Xiaobing

    2016-07-01

    In the present study, gene expression profiles of acute myeloid leukemia (AML) samples were analyzed to identify feature genes with the capacity to predict the mutation status of FLT3/ITD. Two machine learning models, namely the support vector machine (SVM) and random forest (RF) methods, were used for classification. Four datasets were downloaded from the European Bioinformatics Institute, two of which (containing 371 samples, including 281 FLT3/ITD mutation-negative and 90 mutation‑positive samples) were randomly defined as the training group, while the other two datasets (containing 488 samples, including 350 FLT3/ITD mutation-negative and 138 mutation-positive samples) were defined as the test group. Differentially expressed genes (DEGs) were identified by significance analysis of the microarray data by using the training samples. The classification efficiency of the SCM and RF methods was evaluated using the following parameters: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and the area under the receiver operating characteristic curve. Functional enrichment analysis was performed for the feature genes with DAVID. A total of 585 DEGs were identified in the training group, of which 580 were upregulated and five were downregulated. The classification accuracy rates of the two methods for the training group, the test group and the combined group using the 585 feature genes were >90%. For the SVM and RF methods, the rates of correct determination, specificity and PPV were >90%, while the sensitivity and NPV were >80%. The SVM method produced a slightly better classification effect than the RF method. A total of 13 biological pathways were overrepresented by the feature genes, mainly involving energy metabolism, chromatin organization and translation. The feature genes identified in the present study may be used to predict the mutation status of FLT3/ITD in patients with AML.

  8. TXNL1-XRCC1 pathway regulates cisplatin-induced cell death and contributes to resistance in human gastric cancer

    PubMed Central

    Xu, W; Wang, S; Chen, Q; Zhang, Y; Ni, P; Wu, X; Zhang, J; Qiang, F; Li, A; Røe, O D; Xu, S; Wang, M; Zhang, R; Zhou, J

    2014-01-01

    Cisplatin is a cytotoxic platinum compound that triggers DNA crosslinking induced cell death, and is one of the reference drugs used in the treatment of several types of human cancers including gastric cancer. However, intrinsic or acquired drug resistance to cisplatin is very common, and leading to treatment failure. We have recently shown that reduced expression of base excision repair protein XRCC1 (X-ray repair cross complementing group1) in gastric cancerous tissues correlates with a significant survival benefit from adjuvant first-line platinum-based chemotherapy. In this study, we demonstrated the role of XRCC1 in repair of cisplatin-induced DNA lesions and acquired cisplatin resistance in gastric cancer by using cisplatin-sensitive gastric cancer cell lines BGC823 and the cisplatin-resistant gastric cancer cell lines BGC823/cis-diamminedichloridoplatinum(II) (DDP). Our results indicated that the protein expression of XRCC1 was significantly increased in cisplatin-resistant cells and independently contributed to cisplatin resistance. Irinotecan, another chemotherapeutic agent to induce DNA damaging used to treat patients with advanced gastric cancer that progressed on cisplatin, was found to inhibit the expression of XRCC1 effectively, and leading to an increase in the sensitivity of resistant cells to cisplatin. Our proteomic studies further identified a cofactor of 26S proteasome, the thioredoxin-like protein 1 (TXNL1) that downregulated XRCC1 in BGC823/DDP cells via the ubiquitin-proteasome pathway. In conclusion, the TXNL1-XRCC1 is a novel regulatory pathway that has an independent role in cisplatin resistance, indicating a putative drug target for reversing cisplatin resistance in gastric cancer. PMID:24525731

  9. Human XPA and XRCC1 DNA repair proteins expressed in yeast, Saccharomyces cerevisiae.

    PubMed

    Pushnova, E A; Ostanin, K; Thelen, M P

    2001-11-01

    Human XPA and XRCC1 DNA repair proteins have been expressed in a series of novel yeast episomal vectors. Expression of XPA cDNA resulted in synthesis of anti-XPA crossreacting polypeptides of 40 and 42 kDa, the status of the native protein found in human cells. Likewise, the majority of the recombinant XRCC1 found in the yeast intracellular fraction corresponded to the molecular mass of the full-length human protein. Recombinant XPA protein expressed as an NH(2)-terminal polyhistidine fusion could be affinity purified using Ni(2+) agarose. Copyright 2001 Academic Press.

  10. The Human Ligase IIIα-XRCC1 Protein Complex Performs DNA Nick Repair after Transient Unwrapping of Nucleosomal DNA*

    PubMed Central

    Rashid, Ishtiaque; Tomkinson, Alan E.; Pederson, David S.

    2017-01-01

    Reactive oxygen species generate potentially cytotoxic and mutagenic lesions in DNA, both between and within the nucleosomes that package DNA in chromatin. The vast majority of these lesions are subject to base excision repair (BER). Enzymes that catalyze the first three steps in BER can act at many sites in nucleosomes without the aid of chromatin-remodeling agents and without irreversibly disrupting the host nucleosome. Here we show that the same is true for a protein complex comprising DNA ligase IIIα and the scaffolding protein X-ray repair cross-complementing protein 1 (XRCC1), which completes the fourth and final step in (short-patch) BER. Using in vitro assembled nucleosomes containing discretely positioned DNA nicks, our evidence indicates that the ligase IIIα-XRCC1 complex binds to DNA nicks in nucleosomes only when they are exposed by periodic, spontaneous partial unwrapping of DNA from the histone octamer; that the scaffolding protein XRCC1 enhances the ligation; that the ligation occurs within a complex that ligase IIIα-XRCC1 forms with the host nucleosome; and that the ligase IIIα-XRCC1-nucleosome complex decays when ligation is complete, allowing the host nucleosome to return to its native configuration. Taken together, our results illustrate ways in which dynamic properties intrinsic to nucleosomes may contribute to the discovery and efficient repair of base damage in chromatin. PMID:28184006

  11. Curcumin downregulates p38 MAPK-dependent X-ray repair cross-complement group 1 (XRCC1) expression to enhance cisplatin-induced cytotoxicity in human lung cancer cells.

    PubMed

    Tung, Chun-Liang; Jian, Yi-Jun; Chen, Jyh-Cheng; Wang, Tai-Jing; Chen, Wen-Ching; Zheng, Hao-Yu; Chang, Po-Yuan; Liao, Kai-Sheng; Lin, Yun-Wei

    2016-06-01

    Cisplatin is a well-studied and widely used chemotherapeutic agent and is effective in the treatment of the advanced human non-small cell lung cancer (NSCLC). Curcumin is a yellow pigment derived from the rhizome of Curcuma longa and has been proved to have antioxidant and antitumor properties. XRCC1 is an important scaffold protein involved in base excision repair and plays an important role in the development of lung cancer. In this study, we characterize the role of curcumin in the cytotoxicity, p38 MAPK activation, and XRCC1 expression affected by cisplatin in NSCLC cells. We show that curcumin enhanced the cytotoxicity induced by cisplatin in two NSCLC cells, A549 and H1703. Treatment with cisplatin alone increased XRCC1 mRNA and protein expression through p38 MAPK activation. Moreover, SB2023580 (p38 inhibitor) decreased the XRCC1 mRNA and protein stability upon cisplatin treatment. Knockdown of XRCC1 in NSCLC cells by transfection of XRCC1 siRNA or inactivation of p38 MAPK resulted in enhancing the cytotoxicity and cell growth inhibition induced by cisplatin. Curcumin inhibited the expression of XRCC1 in cisplatin-exposed NSCLC cells. Furthermore, transfection with constitutive active MKK6 or HA-p38 MAPK vectors rescued the XRCC1 protein level and also the cell survival suppressed by cisplatin and curcumin combination in A549 and H1703 cells. These findings suggested that the downregulation of XRCC1 expression by curcumin can enhance the chemosensitivity of cisplatin in NSCLC cells.

  12. The association of six non-synonymous variants in three DNA repair genes with hepatocellular carcinoma risk: a meta-analysis.

    PubMed

    Shi, Yan-Hui; Wang, Bin; Xu, Bai-Ping; Jiang, Dan-Na; Zhao, Dong-Mei; Ji, Man-Ru; Zhou, Li; Li, Xue; Lu, Chang-Zhu

    2016-11-01

    Hepatocellular carcinoma is a complex polygenic disease. Despite the huge advances in genetic epidemiology, it still remains a challenge to unveil the genetic architecture of hepatocellular carcinoma. We, therefore, decided to meta-analytically assess the association of six non-synonymous coding variants from XRCC1, XRCC3 and XPD genes with hepatocellular carcinoma risk by pooling the results of 20 English articles. This meta-analysis was conducted according to the PRISMA statement, and data collection was independently completed in duplicate. In overall analyses, the minor alleles of four variants, Arg280His (odds ratio, 95% confidence interval, P: 1.37, 1.13-1.66, 0.001), Thr241Met (1.93, 1.17-3.20, 0.011), Asp312Asn (1.22, 1.08-1.38, 0.001) and Lys751Gln (1.42, 1.02-1.97, 0.038), were associated with the significant risk for hepatocellular carcinoma. There were low probabilities of publication bias for all variants. Subgroup analyses revealed significant association of XRCC1 gene Arg399Gln with hepatocellular carcinoma in Chinese especially from south China (odds ratio, 95% confidence interval, P: 1.57, 1.16-2.14, 0.004), in larger studies (1.48, 1.11-1.98, 0.007) and in studies with population-based controls (1.33, 1.06-1.68, 0.016). Taken together, our findings demonstrated that XPD gene Asp312Asn and XRCC1 gene Arg399Gln might be candidate susceptibility loci for hepatocellular carcinoma. Considering the ubiquity of genetic heterogeneity, further validation in a broad range of ethnic populations is warranted. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  13. Requirement for Parp-1 and DNA ligases 1 or 3 but not of Xrcc1 in chromosomal translocation formation by backup end joining

    PubMed Central

    Soni, Aashish; Siemann, Maria; Grabos, Martha; Murmann, Tamara; Pantelias, Gabriel E.; Iliakis, George

    2014-01-01

    In mammalian cells, ionizing radiation (IR)-induced DNA double-strand breaks (DSBs) are repaired in all phases of the cell cycle predominantly by classical, DNA-PK-dependent nonhomologous end joining (D-NHEJ). Homologous recombination repair (HRR) is functional during the S- and G2-phases, when a sister chromatid becomes available. An error-prone, alternative form of end joining, operating as backup (B-NHEJ) functions robustly throughout the cell cycle and particularly in the G2-phase and is thought to backup predominantly D-NHEJ. Parp-1, DNA-ligases 1 (Lig1) and 3 (Lig3), and Xrcc1 are implicated in B-NHEJ. Chromosome and chromatid translocations are manifestations of erroneous DSB repair and are crucial culprits in malignant transformation and IR-induced cell lethality. We analyzed shifts in translocation formation deriving from defects in D-NHEJ or HRR in cells irradiated in the G2-phase and identify B-NHEJ as the main DSB repair pathway backing up both of these defects at the cost of a large increase in translocation formation. Our results identify Parp-1 and Lig1 and 3 as factors involved in translocation formation and show that Xrcc1 reinforces the function of Lig3 in the process without being required for it. Finally, we demonstrate intriguing connections between B-NHEJ and DNA end resection in translocation formation and show that, as for D-NHEJ and HRR, the function of B-NHEJ facilitates the recovery from the G2-checkpoint. These observations advance our understanding of chromosome aberration formation and have implications for the mechanism of action of Parp inhibitors. PMID:24748665

  14. Search for novel remedies to augment radiation resistance of inhabitants of Fukushima and Chernobyl disasters: identifying DNA repair protein XRCC4 inhibitors.

    PubMed

    Sun, Mao-Feng; Chen, Hsin-Yi; Tsai, Fuu-Jen; Lui, Shu-Hui; Chen, Chih-Yi; Chen, Calvin Yu-Chian

    2011-10-01

    Two nuclear plant disasters occurring within a span of 25 years threaten health and genome integrity both in Fukushima and Chernobyl. Search for remedies capable of enhancing DNA repair efficiency and radiation resistance in humans appears to be a urgent problem for now. XRCC4 is an important enhancer in promoting repair pathway triggered by DNA double-strand break (DSB). In the context of radiation therapy, active XRCC4 could reduce DSB-mediated apoptotic effect on cancer cells. Hence, developing XRCC4 inhibitors could possibly enhance radiotherapy outcomes. In this study, we screened traditional Chinese medicine (TCM) database, TCM Database@Taiwan, and have identified three potent inhibitor agents against XRCC4. Through molecular dynamics simulation, we have determined that the protein-ligand interactions were focused at Lys188 on chain A and Lys187 on chain B. Intriguingly, the hydrogen bonds for all three ligands fluctuated frequently but were held at close approximation. The pi-cation interactions and ionic interactions mediated by o-hydroxyphenyl and carboxyl functional groups respectively have been demonstrated to play critical roles in stabilizing binding conformations. Based on these results, we reported the identification of potential radiotherapy enhancers from TCM. We further characterized the key binding elements for inhibiting the XRCC4 activities.

  15. DNA repair genes polymorphisms and genetic susceptibility to Philadelphia-negative myeloproliferative neoplasms in a Portuguese population: The role of base excision repair genes polymorphisms.

    PubMed

    Azevedo, Ana P; Silva, Susana N; De Lima, João P; Reichert, Alice; Lima, Fernando; Júnior, Esmeraldina; Rueff, José

    2017-06-01

    The role of base excision repair (BER) genes in Philadelphia-negative (PN)-myeloproliferative neoplasms (MPNs) susceptibility was evaluated by genotyping eight polymorphisms [apurinic/apyrimidinic endodeoxyribonuclease 1, mutY DNA glycosylase, earlier mutY homolog ( E. coli ) (MUTYH), 8-oxoguanine DNA glycosylase 1, poly (ADP-ribose) polymerase (PARP) 1, PARP4 and X-ray repair cross-complementing 1 (XRCC1)] in a case-control study involving 133 Caucasian Portuguese patients. The results did not reveal a correlation between individual BER polymorphisms and PN-MPNs when considered as a whole. However, stratification for essential thrombocythaemia revealed i) borderline effect/tendency to increased risk when carrying at least one variant allele for XRCC1_399 single-nucleotide polymorphism (SNP); ii) decreased risk for Janus kinase 2-positive patients carrying at least one variant allele for XRCC1_399 SNP; and iii) decreased risk in females carrying at least one variant allele for MUTYH SNP. Combination of alleles demonstrated an increased risk to PN-MPNs for one specific haplogroup. These findings may provide evidence for gene variants in susceptibility to MPNs. Indeed, common variants in DNA repair genes may hamper the capacity to repair DNA, thus increasing cancer susceptibility.

  16. DNA repair genes polymorphisms and genetic susceptibility to Philadelphia-negative myeloproliferative neoplasms in a Portuguese population: The role of base excision repair genes polymorphisms

    PubMed Central

    Azevedo, Ana P.; Silva, Susana N.; De Lima, João P.; Reichert, Alice; Lima, Fernando; Júnior, Esmeraldina; Rueff, José

    2017-01-01

    The role of base excision repair (BER) genes in Philadelphia-negative (PN)-myeloproliferative neoplasms (MPNs) susceptibility was evaluated by genotyping eight polymorphisms [apurinic/apyrimidinic endodeoxyribonuclease 1, mutY DNA glycosylase, earlier mutY homolog (E. coli) (MUTYH), 8-oxoguanine DNA glycosylase 1, poly (ADP-ribose) polymerase (PARP) 1, PARP4 and X-ray repair cross-complementing 1 (XRCC1)] in a case-control study involving 133 Caucasian Portuguese patients. The results did not reveal a correlation between individual BER polymorphisms and PN-MPNs when considered as a whole. However, stratification for essential thrombocythaemia revealed i) borderline effect/tendency to increased risk when carrying at least one variant allele for XRCC1_399 single-nucleotide polymorphism (SNP); ii) decreased risk for Janus kinase 2-positive patients carrying at least one variant allele for XRCC1_399 SNP; and iii) decreased risk in females carrying at least one variant allele for MUTYH SNP. Combination of alleles demonstrated an increased risk to PN-MPNs for one specific haplogroup. These findings may provide evidence for gene variants in susceptibility to MPNs. Indeed, common variants in DNA repair genes may hamper the capacity to repair DNA, thus increasing cancer susceptibility. PMID:28599464

  17. Nuclear localization of the DNA repair scaffold XRCC1: Uncovering the functional role of a bipartite NLS

    DOE PAGES

    Kirby, Thomas W.; Gassman, Natalie R.; Smith, Cassandra E.; ...

    2015-08-25

    We have characterized the nuclear localization signal (NLS) of XRCC1 structurally using X-ray crystallography and functionally using fluorescence imaging. Crystallography and binding studies confirm the bipartite nature of the XRCC1 NLS interaction with Importin α (Impα) in which the major and minor binding motifs are separated by >20 residues, and resolve previous inconsistent determinations. Binding studies of peptides corresponding to the bipartite NLS, as well as its major and minor binding motifs, to both wild-type and mutated forms of Impα reveal pronounced cooperative binding behavior that is generated by the proximity effect of the tethered major and minor motifs ofmore » the NLS. The cooperativity stems from the increased local concentration of the second motif near its cognate binding site that is a consequence of the stepwise binding behavior of the bipartite NLS. We predict that the stepwise dissociation of the NLS from Impα facilitates unloading by providing a partially complexed intermediate that is available for competitive binding by Nup50 or the Importin β binding domain. This behavior gives a basis for meeting the intrinsically conflicting high affinity and high flux requirements of an efficient nuclear transport system.« less

  18. Requirement for Parp-1 and DNA ligases 1 or 3 but not of Xrcc1 in chromosomal translocation formation by backup end joining.

    PubMed

    Soni, Aashish; Siemann, Maria; Grabos, Martha; Murmann, Tamara; Pantelias, Gabriel E; Iliakis, George

    2014-06-01

    In mammalian cells, ionizing radiation (IR)-induced DNA double-strand breaks (DSBs) are repaired in all phases of the cell cycle predominantly by classical, DNA-PK-dependent nonhomologous end joining (D-NHEJ). Homologous recombination repair (HRR) is functional during the S- and G2-phases, when a sister chromatid becomes available. An error-prone, alternative form of end joining, operating as backup (B-NHEJ) functions robustly throughout the cell cycle and particularly in the G2-phase and is thought to backup predominantly D-NHEJ. Parp-1, DNA-ligases 1 (Lig1) and 3 (Lig3), and Xrcc1 are implicated in B-NHEJ. Chromosome and chromatid translocations are manifestations of erroneous DSB repair and are crucial culprits in malignant transformation and IR-induced cell lethality. We analyzed shifts in translocation formation deriving from defects in D-NHEJ or HRR in cells irradiated in the G2-phase and identify B-NHEJ as the main DSB repair pathway backing up both of these defects at the cost of a large increase in translocation formation. Our results identify Parp-1 and Lig1 and 3 as factors involved in translocation formation and show that Xrcc1 reinforces the function of Lig3 in the process without being required for it. Finally, we demonstrate intriguing connections between B-NHEJ and DNA end resection in translocation formation and show that, as for D-NHEJ and HRR, the function of B-NHEJ facilitates the recovery from the G2-checkpoint. These observations advance our understanding of chromosome aberration formation and have implications for the mechanism of action of Parp inhibitors. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. Xrcc1-dependent and Ku-dependent DNA double-strand break repair kinetics in Arabidopsis plants.

    PubMed

    Charbonnel, Cyril; Gallego, Maria E; White, Charles I

    2010-10-01

    Double-strand breakage (DSB) of DNA involves loss of information on the two strands of the DNA fibre and thus cannot be repaired by simple copying of the complementary strand which is possible with single-strand DNA damage. Homologous recombination (HR) can precisely repair DSB using another copy of the genome as template and non-homologous recombination (NHR) permits repair of DSB with little or no dependence on DNA sequence homology. In addition to the well-characterised Ku-dependent non-homologous end-joining (NHEJ) pathway, much recent attention has been focused on Ku-independent NHR. The complex interrelationships and regulation of NHR pathways remain poorly understood, even more so in the case of plants, and we present here an analysis of Ku-dependent and Ku-independent repair of DSB in Arabidopsis thaliana. We have characterised an Arabidopsis xrcc1 mutant and developed quantitative analysis of the kinetics of appearance and loss of γ-H2AX foci as a tool to measure DSB repair in dividing root tip cells of γ-irradiated plants in vivo. This approach has permitted determination of DSB repair kinetics in planta following a short pulse of γ-irradiation, establishing the existence of a Ku-independent, Xrcc1-dependent DSB repair pathway. Furthermore, our data show a role for Ku80 during the first minutes post-irradiation and that Xrcc1 also plays such a role, but only in the absence of Ku. The importance of Xrcc1 is, however, clearly visible at later times in the presence of Ku, showing that alternative end-joining plays an important role in DSB repair even in the presence of active NHEJ. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

  20. Acute Normal Tissue Reactions in Head-and-Neck Cancer Patients Treated With IMRT: Influence of Dose and Association With Genetic Polymorphisms in DNA DSB Repair Genes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Werbrouck, Joke; Ruyck, Kim de; Duprez, Frederic

    2009-03-15

    Purpose: To investigate the association between dose-related parameters and polymorphisms in DNA DSB repair genes XRCC3 (c.-1843A>G, c.562-14A>G, c.722C>T), Rad51 (c.-3429G>C, c.-3392G>T), Lig4 (c.26C>T, c.1704T>C), Ku70 (c.-1310C>G), and Ku80 (c.2110-2408G>A) and the occurrence of acute reactions after radiotherapy. Materials and Methods: The study population consisted of 88 intensity-modulated radiation therapy (IMRT)-treated head-and-neck cancer patients. Mucositis, dermatitis, and dysphagia were scored using the Common Terminology Criteria (CTC) for Adverse Events v.3.0 scale. The population was divided into a CTC0-2 and CTC3+ group for the analysis of each acute effect. The influence of the dose on critical structures was analyzed using dose-volumemore » histograms. Genotypes were determined by polymerase chain reaction (PCR) combined with restriction fragment length polymorphism or PCR-single base extension assays. Results: The mean dose (D{sub mean}) to the oral cavity and constrictor pharyngeus (PC) muscles was significantly associated with the development of mucositis and dysphagia, respectively. These parameters were considered confounding factors in the radiogenomics analyses. The XRCC3c.722CT/TT and Ku70c.-1310CG/GG genotypes were significantly associated with the development of severe dysphagia (CTC3+). No association was found between the investigated polymorphisms and the development of mucositis or dermatitis. A risk analysis model for severe dysphagia, which was developed based on the XRCC3c.722CT/TT and Ku70c.-1310CG/GG genotypes and the PC dose, showed a sensitivity of 78.6% and a specificity of 77.6%. Conclusions: The XRCC3c.722C>T and Ku70c.-1310C>G polymorphisms as well as the D{sub mean} to the PC muscles were highly associated with the development of severe dysphagia after IMRT. The prediction model developed using these parameters showed a high sensitivity and specificity.« less

  1. GeneBuilder: interactive in silico prediction of gene structure.

    PubMed

    Milanesi, L; D'Angelo, D; Rogozin, I B

    1999-01-01

    Prediction of gene structure in newly sequenced DNA becomes very important in large genome sequencing projects. This problem is complicated due to the exon-intron structure of eukaryotic genes and because gene expression is regulated by many different short nucleotide domains. In order to be able to analyse the full gene structure in different organisms, it is necessary to combine information about potential functional signals (promoter region, splice sites, start and stop codons, 3' untranslated region) together with the statistical properties of coding sequences (coding potential), information about homologous proteins, ESTs and repeated elements. We have developed the GeneBuilder system which is based on prediction of functional signals and coding regions by different approaches in combination with similarity searches in proteins and EST databases. The potential gene structure models are obtained by using a dynamic programming method. The program permits the use of several parameters for gene structure prediction and refinement. During gene model construction, selecting different exon homology levels with a protein sequence selected from a list of homologous proteins can improve the accuracy of the gene structure prediction. In the case of low homology, GeneBuilder is still able to predict the gene structure. The GeneBuilder system has been tested by using the standard set (Burset and Guigo, Genomics, 34, 353-367, 1996) and the performances are: 0.89 sensitivity and 0.91 specificity at the nucleotide level. The total correlation coefficient is 0.88. The GeneBuilder system is implemented as a part of the WebGene a the URL: http://www.itba.mi. cnr.it/webgene and TRADAT (TRAncription Database and Analysis Tools) launcher URL: http://www.itba.mi.cnr.it/tradat.

  2. Influence of allelic Variations of hypoxia-related and DNA repair genes on patient outcome and toxicity in head and neck cancer treated with radiotherapy plus cetuximab.

    PubMed

    Muñoz, Carmen; Caballero, Miguel; Hakim, Sofia; Verger, Eugenia; Grau, Juan Jose

    2016-08-01

    Although cetuximab plus radiotherapy is a standard treatment for patients with inoperable head and neck squamous cell carcinoma (HNSCC), its efficacy varies greatly among individuals. To identify predictive markers of efficacy, we examined the effects of single nucleotide polymorphisms (SNPs) in hypoxia-related and DNA repair genes on the clinical outcome and occurrence of skin toxicity. We analyzed 61 consecutive patients with HNSCC for the presence of specific SNPs (HIF-1α, HIF-2α, HIF-1β, VHL, FIH-1, XRCC1, and XRCC5). The results were then correlated with time to progression (TTP), overall survival (OS), and toxicity (epithelitis, mucositis, and folliculitis). The median TTP and OS were better in patients with severe vs mild mucositis (17 vs 7 months, p = 0.03; and 26 vs 12 months, p = 0.016, respectively) and folliculitis (10 vs 7 months, p = 0.01, and 26 vs 10 months, p < 0.001, respectively). Patients with the HIF-1α CT/TT genotype had better OS than those with the wild-type HIF-1α CC genotype (28 vs 13 months, p = 0.035). Patients with the XRCC5 GG/AA genotype had longer TTP than patients with the XRCC5 AG genotype (11 vs 7 months, p = 0.035). Severe skin toxicity and SNPs of HIF-1α and XRCC5 were associated with different outcomes among patients treated with radiotherapy plus cetuximab.

  3. Evaluation of candidate genes associated with hepatitis A and E virus infection in Chinese Han population.

    PubMed

    Gu, Maolin; Qiu, Jing; Guo, Daoxia; Xu, Yunfang; Liu, Xingxiang; Shen, Chong; Dong, Chen

    2018-03-20

    Recent GWAS-associated studies reported that single nucleotide polymorphisms (SNPs) in ABCB1, TGFβ1, XRCC1 genes were associated with hepatitis A virus (HAV) infection, and variants of APOA4 and APOE genes were associated with and hepatitis E virus (HEV) infection in US population. However, the associations of these loci with HAV or HEV infection in Chinese Han population remain unclear. A total of 3082 Chinese Han persons were included in this study. Anti-HAV IgG and anti-HEV IgG were detected by enzyme-linked immunosorbent assay (ELISA). Genotypes in ABCB1, TGFβ1, XRCC1, APOA4 and APOE SNPs were determined by TaqMan MGB technology. In Chinese Han population, rs1045642 C to T variation in ABCB1 was significantly associated with the decreased risk of HAV infection (P < 0.05). However, the effect direction was different with the previous US study. Rs1001581 A to G variation in XRCC1, which was not identified in US population, was significantly associated with the protection against HAV infection in our samples (P < 0.05). In addition, our results suggested that rs7412 C to T variation in APOE was significantly associated with lower risk of HEV infection in males (adjusted OR < 1.0, P < 0.05) but not in females. ABCB1 and XRCC1 genes variants are significantly associated with the protection against HAV infection. Additionally, Chinese Han males with rs7412 C to T variation in APOE gene are less prone to be infected by HEV.

  4. Polymorphisms in DNA repair genes and MDR1 and the risk for non-Hodgkin lymphoma.

    PubMed

    Kim, Hee Nam; Kim, Nan Young; Yu, Li; Kim, Yeo-Kyeoung; Lee, Il-Kwon; Yang, Deok-Hwan; Lee, Je-Jung; Shin, Min-Ho; Park, Kyeong-Soo; Choi, Jin-Su; Kim, Hyeoung-Joon

    2014-04-21

    The damage caused by oxidative stress and exposure to cigarette smoke and alcohol necessitate DNA damage repair and transport by multidrug resistance-1 (MDR1). To explore the association between polymorphisms in these genes and non-Hodgkin lymphoma risk, we analyzed 15 polymorphisms of 12 genes in a population-based study in Korea (694 cases and 1700 controls). Four genotypes of DNA repair pathway genes (XRCC1 399 GA, OGG1 326 GG, BRCA1 871 TT, and WRN 787 TT) were associated with a decreased risk for NHL [odds ratio (OR)XRCC1 GA=0.80, p=0.02; OROGG1 GG=0.70, p=0.008; ORBRCA1 TT=0.71, p=0.048; ORWRN TT=0.68, p=0.01]. Conversely, the MGMT 115 CT genotype was associated with an increased risk for NHL (OR=1.25, p=0.04). In the MDR1 gene, the 1236 CC genotype was associated with a decreased risk for NHL (OR=0.74, p=0.04), and the 3435 CT and TT genotypes were associated with an increased risk (OR3435CT=1.50, p<0.0001; OR3435TT=1.43, p=0.02). These results suggest that polymorphisms in the DNA repair genes XRCC1, OGG1, BRCA1, WRN1, and MGMT and in the MDR1 gene may affect the risk for NHL in Korean patients.

  5. Variable continental distribution of polymorphisms in the coding regions of DNA-repair genes.

    PubMed

    Mathonnet, Géraldine; Labuda, Damian; Meloche, Caroline; Wambach, Tina; Krajinovic, Maja; Sinnett, Daniel

    2003-01-01

    DNA-repair pathways are critical for maintaining the integrity of the genetic material by protecting against mutations due to exposure-induced damages or replication errors. Polymorphisms in the corresponding genes may be relevant in genetic epidemiology by modifying individual cancer susceptibility or therapeutic response. We report data on the population distribution of potentially functional variants in XRCC1, APEX1, ERCC2, ERCC4, hMLH1, and hMSH3 genes among groups representing individuals of European, Middle Eastern, African, Southeast Asian and North American descent. The data indicate little interpopulation differentiation in some of these polymorphisms and typical FST values ranging from 10 to 17% at others. Low FST was observed in APEX1 and hMSH3 exon 23 in spite of their relatively high minor allele frequencies, which could suggest the effect of balancing selection. In XRCC1, hMSH3 exon 21 and hMLH1 Africa clusters either with Middle East and Europe or with Southeast Asia, which could be related to the demographic history of human populations, whereby human migrations and genetic drift rather than selection would account for the observed differences.

  6. Cobalt-induced genotoxicity in male zebrafish (Danio rerio), with implications for reproduction and expression of DNA repair genes.

    PubMed

    Reinardy, Helena C; Syrett, James R; Jeffree, Ross A; Henry, Theodore B; Jha, Awadhesh N

    2013-01-15

    Although cobalt (Co) is an environmental contaminant of surface waters in both radioactive (e.g. (60)Co) and non-radioactive forms, there is relatively little information about Co toxicity in fishes. The objective of this study was to investigate acute and chronic toxicity of Co in zebrafish, with emphasis on male genotoxicity and implications for reproductive success. The lethal concentration for 50% mortality (LC(50)) in larval zebrafish exposed (96 h) to 0-50 mg l(-1) Co was 35.3 ± 1.1 (95%C.I.) mg l(-1) Co. Adult zebrafish were exposed (13 d) to sub-lethal (0-25 mg l(-1)) Co and allowed to spawn every 4 d and embryos were collected. After 12-d exposure, fertilisation rate was reduced (6% total eggs fertilised, 25 mg l(-1)) and embryo survival to hatching decreased (60% fertilised eggs survived, 25 mg l(-1)). A concentration-dependent increase in DNA strand breaks was detected in sperm from males exposed (13 d) to Co, and DNA damage in sperm returned to control levels after males recovered for 6 d in clean water. Induction of DNA repair genes (rad51, xrcc5, and xrcc6) in testes was complex and not directly related to Co concentration, although there was significant induction in fish exposed to 15 and 25 mg l(-1) Co relative to controls. Induction of 4.0 ± 0.9, 2.5 ± 0.7, and 3.1 ± 0.7-fold change (mean ± S.E.M. for rad51, xrcc5, and xrcc6, respectively) was observed in testes at the highest Co concentration (25 mg l(-1)). Expression of these genes was not altered in offspring (larvae) spawned after 12-d exposure. Chronic exposure to Co resulted in DNA damage in sperm, induction of DNA repair genes in testes, and indications of reduced reproductive success. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. Partial loss of the DNA repair scaffolding protein, Xrcc1, results in increased brain damage and reduced recovery from ischemic stroke in mice

    PubMed Central

    Ghosh, Somnath; Canugovi, Chandrika; Yoon, Jeong Seon; Wilson, David M.; Croteau, Deborah L.; Mattson, Mark P.; Bohr, Vilhelm A.

    2017-01-01

    Oxidative DNA damage is mainly repaired by base excision repair (BER). Previously, our lab showed that mice lacking the BER glycosylases Ogg1 or Neil1 recover more poorly from focal ischemic stroke than wild-type mice. Here, a mouse model was used to investigate whether loss of one of the two alleles of Xrcc1, which encodes a non-enzymatic scaffold protein required for BER, alters recovery from stroke. Ischemia and reperfusion caused higher brain damage and lower functional recovery in Xrcc1+/− mice than in wild-type mice. Additionally, a greater percentage of Xrcc1+/− mice died as a result of the stroke. Brain samples from human individuals who died of stroke and individuals who died of non-neurological causes were assayed for various steps of BER. Significant losses of thymine glycol incision, abasic endonuclease incision and single nucleotide incorporation activities were identified, as well as lower expression of XRCC1 and NEIL1 proteins in stroke brains compared to controls. Together, these results suggest that impaired BER is a risk factor in ischemic brain injury and contributes to its recovery. PMID:25971543

  8. Down-regulation of ERK1/2 and AKT-mediated X-ray repair cross-complement group 1 protein (XRCC1) expression by Hsp90 inhibition enhances the gefitinib-induced cytotoxicity in human lung cancer cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tung, Chun-Liang; Jian, Yi-Jun; Department of Biochemical Science and Technology, National Chiayi University, 300 Syuefu Road, Chiayi 600, Taiwan

    2015-05-15

    Gefitinib (Iressa{sup R}, ZD1839) is a selective epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) that blocks growth factor-mediated cell proliferation and extracellular signal-regulated kinases 1/2 (ERK1/2) and AKT signaling activation. It has been shown that inhibition of Hsp90 function can enhance antitumor activity of EGFR-TKI. XRCC1 is an important scaffold protein in base excision repair, which could be regulated by ERK1/2 and AKT pathways. However, the role of ERK1/2 and AKT-mediated XRCC1 expression in gefitinib alone or combination with an Hsp90 inhibitor-induced cytotoxicity in non-small cell lung cancer (NSCLC) cells has not been identified. In this study, gefitinib treatment decreasedmore » XRCC1 mRNA and protein expression through ERK1/2 and AKT inactivation in two NSCLC cells, A549 and H1975. Knocking down XRCC1 expression by transfection with small interfering RNA of XRCC1 enhanced the cytotoxicity and cell growth inhibition of gefitinib. Combining treatment of gefitinib with an Hsp90 inhibitor resulted in enhancing the reduction of XRCC1 protein and mRNA levels in gefitinib-exposed A549 and H1975 cells. Compared to a single agent alone, gefitinib combined with an Hsp90 inhibitor resulted in cytotoxicity and cell growth inhibition synergistically in NSCLC cells. Furthermore, transfection with constitutive active MKK1 or AKT vectors rescued the XRCC1 protein level as well as the cell survival suppressed by an Hsp90 inhibitor and gefitinib. These findings suggested that down-regulation of XRCC1 can enhance the sensitivity of gefitinib for NSCLC cells. - Highlights: • Gefitinib treatment decreased XRCC1 mRNA and protein expression in NSCLC cells. • Knocking down XRCC1 expression enhanced the cytotoxic effect of gefitinib. • Gefitinib combined with an Hsp90 inhibitor resulted in synergistically cytotoxicity.« less

  9. Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival.

    PubMed

    Azad, Tej D; Donato, Michele; Heylen, Line; Liu, Andrew B; Shen-Orr, Shai S; Sweeney, Timothy E; Maltzman, Jonathan Scott; Naesens, Maarten; Khatri, Purvesh

    2018-01-25

    Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

  10. Brca2 (XRCC11) Deficiency Results in Radioresistant DNA Synthesis and a Higher Frequency of Spontaneous Deletions

    PubMed Central

    Kraakman-van der Zwet, Maria; Overkamp, Wilhelmina J. I.; van Lange, Rebecca E. E.; Essers, Jeroen; van Duijn-Goedhart, Annemarie; Wiggers, Ingrid; Swaminathan, Srividya; van Buul, Paul P. W.; Errami, Abdellatif; Tan, Raoul T. L.; Jaspers, Nicolaas G. J.; Sharan, Shyam K.; Kanaar, Roland; Zdzienicka, Małgorzata Z.

    2002-01-01

    We show here that the radiosensitive Chinese hamster cell mutant (V-C8) of group XRCC11 is defective in the breast cancer susceptibility gene Brca2. The very complex phenotype of V-C8 cells is complemented by a single human chromosome 13 providing the BRCA2 gene, as well as by the murine Brca2 gene. The Brca2 deficiency in V-C8 cells causes hypersensitivity to various DNA-damaging agents with an extreme sensitivity toward interstrand DNA cross-linking agents. Furthermore, V-C8 cells show radioresistant DNA synthesis after ionizing radiation, suggesting that Brca2 deficiency affects cell cycle checkpoint regulation. In addition, V-C8 cells display tremendous chromosomal instability and a high frequency of abnormal centrosomes. The mutation spectrum at the hprt locus showed that the majority of spontaneous mutations in V-C8 cells are deletions, in contrast to wild-type V79 cells. A mechanistic explanation for the genome instability phenotype of Brca2-deficient cells is provided by the observation that the nuclear localization of the central DNA repair protein in homologous recombination, Rad51, is reduced in V-C8 cells. PMID:11756561

  11. Significant interactions between maternal PAH exposure and haplotypes in candidate genes on B[a]P-DNA adducts in a NYC cohort of non-smoking African-American and Dominican mothers and newborns

    PubMed Central

    Tang, Deliang

    2014-01-01

    Polycyclic aromatic hydrocarbons (PAH) are a class of chemicals common in the environment. Certain PAH are carcinogenic, although the degree to which genetic variation influences susceptibility to carcinogenic PAH remains unclear. Also unknown is the influence of genetic variation on the procarcinogenic effect of in utero exposures to PAH. Benzo[a]pyrene (B[a]P) is a well-studied PAH that is classified as a probable human carcinogen. Within our New York City-based cohort, we explored interactions between maternal exposure to airborne PAH during pregnancy and maternal and newborn haplotypes (and in one case, a single-nucleotide polymorphism) in key B[a]P metabolism genes on B[a]P-DNA adducts in paired cord blood samples. The study subjects included non-smoking African-American (n = 132) and Dominican (n = 235) women with available data on maternal PAH exposure, paired cord adducts and genetic data who resided in the Washington Heights, Central Harlem and South Bronx neighborhoods of New York City. We selected seven maternal and newborn genes related to B[a]P metabolism, detoxification and repair for our analyses: CYP1A1, CYP1A2, CYP1B1, GSTM3, GSTT2, NQO1 and XRCC1. We found significant interactions between maternal PAH exposure and haplotype on cord B[a]P-DNA adducts in the following genes: maternal CYP1B1, XRCC1 and GSTM3, and newborn CYP1A2 and XRCC1 in African-Americans; and maternal XRCC1 and newborn NQO1 in Dominicans. These novel findings highlight differences in maternal and newborn genetic contributions to B[a]P-DNA adduct formation, as well as ethnic differences in gene–environment interactions, and have the potential to identify at-risk subpopulations who are susceptible to the carcinogenic potential of B[a]P. PMID:24177223

  12. Systematic Characterization and Prediction of Human Hypertension Genes.

    PubMed

    Li, Yan-Hui; Zhang, Gai-Gai; Wang, Nanping

    2017-02-01

    Hypertension is a major cardiovascular risk factor and accounts for a large part of cardiovascular mortality. In this work, we analyzed the properties of hypertension genes and found that when compared with genes not yet known to be involved in hypertension regulation, known hypertension genes display distinguishing features: (1) hypertension genes tend to be located at network center; (2) hypertension genes tend to interact with each other; and (3) hypertension genes tend to enrich in certain biological processes and show certain phenotypes. Based on these features, we developed a machine-learning algorithm to predict new hypertension genes. One hundred and seventy-seven candidates were predicted with a posterior probability >0.9. Evidence supporting 17 of the predictions has been found. © 2016 American Heart Association, Inc.

  13. Environmental exposure and HPV infection may act synergistically to induce lung tumorigenesis in nonsmokers

    PubMed Central

    Cheng, Ya-Wen; Lin, Frank Cheau-Feng; Chen, Chih-Yi; Hsu, Nan-Yung

    2016-01-01

    Most studies of lung tumorigenesis have focused on smokers rather than nonsmokers. In this study, we used human papillomavirus (HPV)-positive and HPV-negative lung cancer cells to test the hypothesis that HPV infection synergistically increases DNA damage induced by exposure to the carcinogen benzo[a]pyrene (B[a]P), and contributes to lung tumorigenesis in nonsmokers. DNA adduct levels induced by B[a]P in HPV-positive cells were significantly higher than in HPV-negative cells. The DNA adduct formation was dependent on HPV E6 oncoprotein expression. Gene and protein expression of two DNA repair genes, XRCC3 and XRCC5, were lower in B[a]P-treated E6-positive cells than in E6-negative lung cancer cells. The reduced expression was also detected immunohistochemically and was caused by increased promoter hypermethylation. Moreover, mutations of p53 and epidermal growth factor receptor (EGFR) genes in lung cancer patients were associated with XRCC5 inactivation. In sum, our study indicates that HPV E6-induced promoter hypermethylation of the XRCC3 and XRCC5 DNA repair genes and the resultant decrease in their expression increases B[a]P-induced DNA adducts and contributes to lung tumorigenesis in nonsmokers. PMID:26918347

  14. Hemoglobin level and XRCC1 polymorphisms to select patients with locally advanced rectal cancer candidate for neoadjuvant chemoradiotherapy with concurrent capecitabine and a platinum salt.

    PubMed

    Formica, Vincenzo; Benassi, Michaela; Del Vecchio Blanco, Giovanna; Doldo, Elena; Martano, Laura; Portarena, Ilaria; Nardecchia, Antonella; Lucchetti, Jessica; Morelli, Cristina; Giudice, Emilia; Rossi, Piero; Anselmo, Alessandro; Sileri, Pierpaolo; Sica, Giuseppe; Orlandi, Augusto; Santoni, Riccardo; Roselli, Mario

    2018-05-02

    A platinum salt (oxaliplatin or cisplatin) is widely used to enhance chemoradation (CRT) response. The potential of cisplatin in neoadjuvant CRT for locally advanced rectal cancer (LARC) has not been fully investigated. Consecutive patients with histologically confirmed LARC were treated with standard pelvic radiotherapy and concurrent cisplatin plus capecitabine (CisCape CRT). Surgery and eight cycles of adjuvant FOLFOX4 were offered to all patients after CRT. Common biochemical variables and key germline genetic polymorphisms were analyzed as predictors of pathological complete response (pCR). Fifty-one patients were enrolled. pCR (regression AJCC grade 0) was documented in 7 patients (14%), nearly complete response (AJCC grade 1) in 10 pts. There was a strong association between disease-free survival and AJCC grade (p 0.0047). Grade 3-4 toxicities (mainly diarrhea) was observed in 41% of patients. Among all analyzed variables, baseline hemoglobin (Hb) was significantly associated with AJCC grade 0-1 response (p 0.027). As for the pharmacogenetic analysis, XRCC1 rs25487 polymorphism was significantly associated with AJCC grade 0-1, Odds Ratio 25.8, p 0.049. AJCC grade 0-1 response rate for patients with high Hb and/or XRCC1 rs25487 G/G genotype was as high as 57%. Baseline Hb and XRCC1 polymorphisms are valuable selection criteria for the CisCape CRT regimen, given its otherwise meaningful toxicity.

  15. Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT).

    PubMed

    Saiag, P; Gutzmer, R; Ascierto, P A; Maio, M; Grob, J-J; Murawa, P; Dreno, B; Ross, M; Weber, J; Hauschild, A; Rutkowski, P; Testori, A; Levchenko, E; Enk, A; Misery, L; Vanden Abeele, C; Vojtek, I; Peeters, O; Brichard, V G; Therasse, P

    2016-10-01

    Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. An open-label prospective phase II trial ('PREDICT') in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS- populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS- patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS-). There was one complete response (GS-) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS- and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study.This study is registered at www.clinicatrials.gov NCT00942162. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

  16. Analysis and results of Ku and XRCC4 expression in hypopharyngeal cancer tissues treated with chemoradiotherapy

    PubMed Central

    HAYASHI, JYUNICHI; SAKATA, KOH-ICHI; SOMEYA, MASANORI; MATSUMOTO, YOSHIHISA; SATOH, MASAAKI; NAKATA, KENSEI; HORI, MASAKAZU; TAKAGI, MASARU; KONDOH, ATSUSHI; HIMI, TETSUO; HAREYAMA, MASATO

    2012-01-01

    DNA double-strand break (DSB) is one of the most serious forms of damage induced by ionizing irradiation. Non-homologous end-joining (NHEJ) is a key mechanism of DNA DSB repair. The immunohistochemical analysis of proteins involved in NHEJ may have potential as a predictive assay for tumor radiosensitivity. We examined the correlation between the expression of proteins involved in DNA DSB in biopsy specimens and the results of chemoradiotherapy in hypopharyngeal cancers. Fifty-seven patients with previously untreated squamous cell carcinoma of the hypopharynx were treated between March 2002 and December 2009. Most patients (75%) had stage III or IV disease. The chemotherapy consisted of cisplatin plus 5FU or S-1. A tumor dose of 50 Gy was usually administered to the primary tumor and regional lymph nodes. Doses of 10–20 Gy were usually added to the primary tumor with reduced fields after 50 Gy. The 5-year disease-free survival rate was 100% for patients in stage I, 90% in stage II, 64% in stage III and 50% in stage IV. In stages I-III, patients with a lower expression of Ku70 or XRCC4 tended to have better locoregional control. These results indicated that a lower expression of Ku70 or XRCC4 may be correlated with higher radiosensitivity. Two patients had distant metastasis alone, of which one had 0% expression of Ku70 and the other had 0% expression of Ku86. The absence of Ku70 or Ku86 expression indicates low DNA-PK activity. Low DNA-PK activity due to a low expression of Ku may result in the genetic alteration of cancer cells, leading to a higher tendency of distant metastasis. This finding suggests that proteins involved in NHEJ may have an impact on the treatment results of chemoradiotherapy in hypopharyngeal cancer. PMID:22807979

  17. Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

    PubMed Central

    2012-01-01

    Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

  18. Genetic polymorphisms of XRCC1 (codon 399) and susceptibility to breast cancer in Iranian women, a case-control study.

    PubMed

    Saadat, Mostafa; Kohan, Leila; Omidvari, Shahpour

    2008-10-01

    The X-ray repair cross-complementation group 1 (XRCC1) protein plays an important role in base excision repair. In the present study, we specifically investigated whether common genetic variant in XRCC1 (exon 10, codon Arg399Gln) was associated with an altered risk of breast cancer. The eligible cases were patients at chemotherapy unit of Nemazi hospital, Shiraz Iran, from October 1999 to August 2000 and from July 2004 to July 2005. The present study included 186 females with breast cancer. Age frequency-matched controls were randomly selected from the healthy females blood donor, according to the age distribution of the cases. A total of 187 healthy females included in the study. Using PCR-based method, the XRCC1 Arg399Gln polymorphism was determined. In control group the 399Gln allele frequency was 32.6%. The genotypic frequencies of the control subjects did not show significant deviation from Hardy-Weinberg equilibrium (chi(2) = 1.683, df = 1, P > 0.05). A statistically significant association was observed in comparison between Gln/Gln and Arg/Arg genotype (OR = 2.01, 95% CI:1.02-3.94, P = 0.041). There was no linear trend for presence of 0, 1, and 2 of the 399Gln allele and risk of breast cancer (chi(2) = 1.212, P = 0.271). In the recessive effect of the Gln allele (comparison between Gln/Gln vs. Arg/Arg+Arg/Gln), Gln/Gln genotype significantly increased the risk of breast cancer (OR = 2.31, 95% CI:1.21-4.35, P = 0.010). In the dominant effect of the Gln allele (comparison between Gln/Gln+Arg/Gln vs. Arg/Arg), Gln/Gln+Arg/Gln genotypes was not associated with the risk of breast cancer (OR = 0.95, 95% CI:0.63-1.42, P = 0.799). It is concluded that 399Gln allele may act as a recessive allele and increase the breast cancer risk.

  19. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

    PubMed

    Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

    2018-02-23

    Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Discovery of mutations in homologous recombination genes in African-American women with breast cancer.

    PubMed

    Ding, Yuan Chun; Adamson, Aaron W; Steele, Linda; Bailis, Adam M; John, Esther M; Tomlinson, Gail; Neuhausen, Susan L

    2018-04-01

    African-American women are more likely to develop aggressive breast cancer at younger ages and experience poorer cancer prognoses than non-Hispanic Caucasians. Deficiency in repair of DNA by homologous recombination (HR) is associated with cancer development, suggesting that mutations in genes that affect this process may cause breast cancer. Inherited pathogenic mutations have been identified in genes involved in repairing DNA damage, but few studies have focused on African-Americans. We screened for germline mutations in seven HR repair pathway genes in DNA of 181 African-American women with breast cancer, evaluated the potential effects of identified missense variants using in silico prediction software, and functionally characterized a set of missense variants by yeast two-hybrid assays. We identified five likely-damaging variants, including two PALB2 truncating variants (Q151X and W1038X) and three novel missense variants (RAD51C C135R, and XRCC3 L297P and V337E) that abolish protein-protein interactions in yeast two-hybrid assays. Our results add to evidence that HR gene mutations account for a proportion of the genetic risk for developing breast cancer in African-Americans. Identifying additional mutations that diminish HR may provide a tool for better assessing breast cancer risk and improving approaches for targeted treatment.

  1. Integrating alternative splicing detection into gene prediction.

    PubMed

    Foissac, Sylvain; Schiex, Thomas

    2005-02-10

    Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders. We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGENE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage). This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline.

  2. Training set selection for the prediction of essential genes.

    PubMed

    Cheng, Jian; Xu, Zhao; Wu, Wenwu; Zhao, Li; Li, Xiangchen; Liu, Yanlin; Tao, Shiheng

    2014-01-01

    Various computational models have been developed to transfer annotations of gene essentiality between organisms. However, despite the increasing number of microorganisms with well-characterized sets of essential genes, selection of appropriate training sets for predicting the essential genes of poorly-studied or newly sequenced organisms remains challenging. In this study, a machine learning approach was applied reciprocally to predict the essential genes in 21 microorganisms. Results showed that training set selection greatly influenced predictive accuracy. We determined four criteria for training set selection: (1) essential genes in the selected training set should be reliable; (2) the growth conditions in which essential genes are defined should be consistent in training and prediction sets; (3) species used as training set should be closely related to the target organism; and (4) organisms used as training and prediction sets should exhibit similar phenotypes or lifestyles. We then analyzed the performance of an incomplete training set and an integrated training set with multiple organisms. We found that the size of the training set should be at least 10% of the total genes to yield accurate predictions. Additionally, the integrated training sets exhibited remarkable increase in stability and accuracy compared with single sets. Finally, we compared the performance of the integrated training sets with the four criteria and with random selection. The results revealed that a rational selection of training sets based on our criteria yields better performance than random selection. Thus, our results provide empirical guidance on training set selection for the identification of essential genes on a genome-wide scale.

  3. Normal development of mice lacking PAXX, the paralogue of XRCC4 and XLF.

    PubMed

    Gago-Fuentes, Raquel; Xing, Mengtan; Sæterstad, Siri; Sarno, Antonio; Dewan, Alisa; Beck, Carole; Bradamante, Stefano; Bjørås, Magnar; Oksenych, Valentyn

    2018-03-01

    DNA repair consists of several cellular pathways which recognize and repair damaged DNA. The classical nonhomologous DNA end-joining (NHEJ) pathway repairs double-strand breaks in DNA. It is required for maturation of both B and T lymphocytes by supporting V(D)J recombination as well as B-cell differentiation during class switch recombination (CSR). Inactivation of NHEJ factors Ku70, Ku80, XRCC4, DNA ligase 4, DNA-PKcs, and Artemis impairs V(D)J recombination and blocks lymphocyte development. Paralogue of XRCC4 and XLF (PAXX) is an accessory NHEJ factor that has a significant impact on the repair of DNA lesions induced by ionizing radiation in human, murine, and chicken cells. However, the role of PAXX during development is poorly understood. To determine the physiological role of PAXX, we deleted part of the Paxx promoter and the first two exons in mice. Further, we compared Paxx -knockout mice with wild-type (WT) and NHEJ-deficient controls including Ku80- and Dna-pkcs -null and severe combined immunodeficiency mice. Surprisingly, Paxx -deficient mice were not distinguishable from the WT littermates; they were the same weight and size, fertility status, had normal spleen, thymus, and bone marrow. Paxx -deficient mice had the same number of chromosomal and chromatid breaks as WT mice. Moreover, Paxx -deficient primary B lymphocytes had the same level of CSR as lymphocytes isolated from WT mice. We concluded that PAXX is dispensable for normal mouse development.

  4. A 3' untranslated region polymorphism rs2304277 in the DNA repair pathway gene OGG1 is a novel risk modulator for urothelial bladder carcinoma.

    PubMed

    Ahmed, Tayyaba; Nawaz, Saira; Noreen, Rabia; Bangash, Kashif Sardar; Rauf, Abdur; Younis, Muhammad; Anwar, Khursheed; Khawaja, Muhammad Athar; Azam, Maleeha; Qureshi, Abid Ali; Akhter, Saeed; Kiemeney, Lambertus A; Qamar, Raheel; Ali, Syeda Hafiza Benish

    2018-03-01

    Altered DNA repair capacity may affect an individual's susceptibility to cancers due to compromised genomic integrity. This study was designed to elucidate the association of selected polymorphisms in DNA repair genes with urothelial bladder carcinoma (UBC). OGG1 rs1052133 and rs2304277, XRCC1 rs1799782 and rs25487, XRCC3 rs861539, XPC rs2228001, and XPD rs13181 were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in 200 UBC cases and 200 controls. We found association of OGG1 rs2304277 [odds ratio (OR) GG = 3.55, 95% confidence interval (CI) = 1.79-7.06] and XPC rs2228001 (OR AC = 2.38, 95% CI = 1.43-3.94) with UBC. In stratified analysis with respect to smoking status, OGG1 rs2304277 and XPC rs2228001 exhibited increased risk in smokers [(rs2304277 OR GG = 4.96, 95% CI = 1.51-16.30) (rs2228001 OR AC = 2.19, 95% CI = 1.02-4.72)] as well as nonsmokers [(rs2304277 OR GG = 2.95, 95% CI = 1.26-6.90) (rs2228001 OR AC = 2.57, 95% CI = 1.31-5.04)]. These polymorphisms were also associated with both low-grade [(rs2304277 OR GG = 3.73, 95% CI = 1.72-8.09) (rs2228001 OR AC = 2.18, 95% CI = 1.21-3.92)] and high-grade tumors [(rs2304277 OR GG = 3.45, 95% CI = 1.52-7.80) (rs2228001 OR AC = 2.81, 95% CI = 1.48-5.33)] as well as with non-muscle-invasive bladder cancer [(rs2304277 OR GG = 4.03, 95% CI = 1.87-8.67) (rs2228001 OR AC = 2.14, 95% CI = 1.20-3.81)] and muscle-invasive bladder cancer [(rs2304277 OR GG = 3.06, 95%CI = 1.31-7.13) (rs2228001 OR AC = 2.95, 95%CI = 1.51-5.75)]. This is the first study on DNA repair gene polymorphisms and UBC in the Pakistani population. It identifies OGG1 rs2304277 and replicates XPC rs2228001 as significant modulators of UBC susceptibility. © 2017 John Wiley & Sons Ltd/University College London.

  5. The Effect of Polymorphisms in DNA Repair Genes and Carcinogen Metabolizers on Leukocyte Telomere Length: A Cohort of Healthy Spanish Smokers.

    PubMed

    Verde, Zoraida; Reinoso-Barbero, Luis; Chicharro, Luis; Resano, Pilar; Sánchez-Hernández, Ignacio; Rodríguez González-Moro, Jose Miguel; Bandrés, Fernando; Gómez-Gallego, Félix; Santiago, Catalina

    2016-04-01

    Smoking implies exposure to carcinogenic agents that causes DNA damage, which could be suspected to enhance telomere attrition. To protect and deal with DNA damage, cells possess mechanisms that repair and neutralize harmful substances. Polymorphisms altering DNA repair capacity or carcinogen metabolism may lead to synergistic effects with tobacco carcinogen-induced shorter telomere length independently of cancer interaction. The aim of this study was to explore the association between leukocyte telomere length (LTL) and several genetic polymorphisms in DNA repair genes and carcinogen metabolizers in a cohort of healthy smokers. We evaluated the effect of six genetic polymorphisms in cytochrome P1A1 (Ile462Val), XRCC1 (Arg399Gln), APEX1 (Asp148Glu), XRCC3 (Thr241Met), and XPD (Asp312Asn; Lys751Gln) on LTL in a cohort of 145 healthy smokers in addition to smoking habits. Logistic regression analysis showed an association between XRCC1 399Gln allele and shorter telomere length (OR = 5.03, 95% CI = 1.08% to 23.36%). There were not association between the rest of polymorphisms analyzed and LTL. Continuous exposure to tobacco could overwhelm the DNA repair machinery, making the effect of the polymorphisms that reduce repair capacity more pronounced. Analyzing the function of smoking-induced DNA-repair genes and LTL is an important goal in order to identify therapeutic targets to treat smoking-induced diseases. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  6. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mangoni, Monica; Bisanzi, Simonetta; Carozzi, Francesca

    Purpose: Clinical radiosensitivity varies considerably among patients, and radiation-induced side effects developing in normal tissue can be therapy limiting. Some single nucleotide polymorphisms (SNPs) have been shown to correlate with hypersensitivity to radiotherapy. We conducted a prospective study of 87 female patients with breast cancer who received radiotherapy after breast surgery. We evaluated the association between acute skin reaction following radiotherapy and 11 genetic polymorphisms in DNA repair genes: XRCC1 (Arg399Gln and Arg194Trp), XRCC3 (Thr241Met), XPD (Asp312Asn and Lys751Gln), MSH2 (gIVS12-6T>C), MLH1 (Ile219Val), MSH3 (Ala1045Thr), MGMT (Leu84Phe), and in damage-detoxification GSTM1 and GSTT1 genes (allele deletion). Methods and Materials: Individualmore » genetic polymorphisms were determined by polymerase chain reaction and single nucleotide primer extension for single nucleotide polymorphisms or by a multiplex polymerase chain reaction assay for deletion polymorphisms. The development of severe acute skin reaction (moist desquamation or interruption of radiotherapy due to toxicity) associated with genetic polymorphisms was modeled using Cox proportional hazards, accounting for cumulative biologically effective radiation dose. Results: Radiosensitivity developed in eight patients and was increased in carriers of variants XRCC3-241Met allele (hazard ratio [HR] unquantifiably high), MSH2 gIVS12-6nt-C allele (HR = 53.36; 95% confidence intervals [95% CI], 3.56-798.98), and MSH3-1045Ala allele (HR unquantifiably high). Carriers of XRCC1-Arg194Trp variant allele in combination with XRCC1-Arg399Gln wild-type allele had a significant risk of radiosensitivity (HR = 38.26; 95% CI, 1.19-1232.52). Conclusions: To our knowledge, this is the first report to find an association between MSH2 and MSH3 genetic variants and the development of radiosensitivity in breast cancer patients. Our findings suggest the hypothesis that mismatch repair mechanisms may

  7. Extensive complementarity between gene function prediction methods.

    PubMed

    Vidulin, Vedrana; Šmuc, Tomislav; Supek, Fran

    2016-12-01

    The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions. Our pipeline amalgamates 5 133 543 genes from 2071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1227 Gene Ontology (GO) terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse genomic AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to rely on a single most-confident prediction per gene/function, rather than enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known Escherichia coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the Critical Assessment of Function Annotation 2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them. The individual and integrated GO predictions for the complete set of genes are available from http://gorbi.irb.hr/ CONTACT: fran.supek@irb.hrSupplementary information: Supplementary materials are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Incorrectly predicted genes in rice?

    PubMed

    Cruveiller, Stéphane; Jabbari, Kamel; Clay, Oliver; Bernardi, Giorgio

    2004-05-26

    Between one third and one half of the proposed rice genes appear to have no homologs in other species, including Arabidopsis. Compositional considerations, and a comparison of curated rice sequences with ex novo predictions, suggest that many or most of the putative genes without homologs may be false positive predictions, i.e., sequences that are never translated into functional proteins in vivo.

  9. PRGdb 3.0: a comprehensive platform for prediction and analysis of plant disease resistance genes.

    PubMed

    Osuna-Cruz, Cristina M; Paytuvi-Gallart, Andreu; Di Donato, Antimo; Sundesha, Vicky; Andolfo, Giuseppe; Aiese Cigliano, Riccardo; Sanseverino, Walter; Ercolano, Maria R

    2018-01-04

    The Plant Resistance Genes database (PRGdb; http://prgdb.org) has been redesigned with a new user interface, new sections, new tools and new data for genetic improvement, allowing easy access not only to the plant science research community but also to breeders who want to improve plant disease resistance. The home page offers an overview of easy-to-read search boxes that streamline data queries and directly show plant species for which data from candidate or cloned genes have been collected. Bulk data files and curated resistance gene annotations are made available for each plant species hosted. The new Gene Model view offers detailed information on each cloned resistance gene structure to highlight shared attributes with other genes. PRGdb 3.0 offers 153 reference resistance genes and 177 072 annotated candidate Pathogen Receptor Genes (PRGs). Compared to the previous release, the number of putative genes has been increased from 106 to 177 K from 76 sequenced Viridiplantae and algae genomes. The DRAGO 2 tool, which automatically annotates and predicts (PRGs) from DNA and amino acid with high accuracy and sensitivity, has been added. BLAST search has been implemented to offer users the opportunity to annotate and compare their own sequences. The improved section on plant diseases displays useful information linked to genes and genomes to connect complementary data and better address specific needs. Through, a revised and enlarged collection of data, the development of new tools and a renewed portal, PRGdb 3.0 engages the plant science community in developing a consensus plan to improve knowledge and strategies to fight diseases that afflict main crops and other plants. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. DNA Repair Mechanism Gene, XRCC1A ( Arg194Trp) but not XRCC3 ( Thr241Met) Polymorphism Increased the Risk of Breast Cancer in Premenopausal Females: A Case-Control Study in Northeastern Region of India.

    PubMed

    Devi, K Rekha; Ahmed, Jishan; Narain, Kanwar; Mukherjee, Kaustab; Majumdar, Gautam; Chenkual, Saia; Zonunmawia, Jason C

    2017-12-01

    X-ray repair cross complementary group gene is one of the most studied candidate gene involved in different types of cancers. Studies have shown that X-ray repair cross complementary genes are significantly associated with increased risk of breast cancer in females. Moreover, studies have revealed that X-ray repair cross complementary gene polymorphism significantly varies between and within different ethnic groups globally. The present case-control study was aimed to investigate the association of X-ray repair cross complementary 1A (Arg194Trp) and X-ray repair cross complementary 3 (Thr241Met) polymorphism with the risk of breast cancer in females from northeastern region of India. The present case-control study includes histopathologically confirmed and newly diagnosed 464 cases with breast cancer and 534 apparently healthy neighborhood community controls. Information on sociodemographic factors and putative risk factors were collected from each study participant by conducting face-to-face interviews. Genotyping of X-ray repair cross complementary 1A (Arg194Trp) and X-ray repair cross complementary 3 (Thr241Met) was carried out by polymerase chain reaction-restriction fragment length polymorphism. For statistical analysis, both univariate and multivariate logistic regression analyses were performed. We also performed stratified analysis to find out the association of X-ray repair cross complementary genes with the risk of breast cancer stratified based on menstrual status. This study revealed that tryptophan allele (R/W-W/W genotype) in X-ray repair cross complementary 1A (Arg194Trp) gene significantly increased the risk of breast cancer (adjusted odds ratio = 1.44, 95% confidence interval = 1.06-1.97, P < .05 for R/W-W/W genotype). Moreover, it was found that tryptophan allele (W/W genotype) at codon 194 of X-ray repair cross complementary 1A (Arg194Trp) gene significantly increased the risk of breast cancer in premenopausal females (crude odds ratio = 1.66, 95

  11. DNA Repair Mechanism Gene, XRCC1A (Arg194Trp) but not XRCC3 (Thr241Met) Polymorphism Increased the Risk of Breast Cancer in Premenopausal Females: A Case–Control Study in Northeastern Region of India

    PubMed Central

    Ahmed, Jishan; Narain, Kanwar; Mukherjee, Kaustab; Majumdar, Gautam; Chenkual, Saia; Zonunmawia, Jason C.

    2017-01-01

    X-ray repair cross complementary group gene is one of the most studied candidate gene involved in different types of cancers. Studies have shown that X-ray repair cross complementary genes are significantly associated with increased risk of breast cancer in females. Moreover, studies have revealed that X-ray repair cross complementary gene polymorphism significantly varies between and within different ethnic groups globally. The present case–control study was aimed to investigate the association of X-ray repair cross complementary 1A (Arg194Trp) and X-ray repair cross complementary 3 (Thr241Met) polymorphism with the risk of breast cancer in females from northeastern region of India. The present case–control study includes histopathologically confirmed and newly diagnosed 464 cases with breast cancer and 534 apparently healthy neighborhood community controls. Information on sociodemographic factors and putative risk factors were collected from each study participant by conducting face-to-face interviews. Genotyping of X-ray repair cross complementary 1A (Arg194Trp) and X-ray repair cross complementary 3 (Thr241Met) was carried out by polymerase chain reaction-restriction fragment length polymorphism. For statistical analysis, both univariate and multivariate logistic regression analyses were performed. We also performed stratified analysis to find out the association of X-ray repair cross complementary genes with the risk of breast cancer stratified based on menstrual status. This study revealed that tryptophan allele (R/W-W/W genotype) in X-ray repair cross complementary 1A (Arg194Trp) gene significantly increased the risk of breast cancer (adjusted odds ratio = 1.44, 95% confidence interval = 1.06-1.97, P < .05 for R/W-W/W genotype). Moreover, it was found that tryptophan allele (W/W genotype) at codon 194 of X-ray repair cross complementary 1A (Arg194Trp) gene significantly increased the risk of breast cancer in premenopausal females (crude odds ratio = 1

  12. A cluster of novel serotonin receptor 3-like genes on human chromosome 3.

    PubMed

    Karnovsky, Alla M; Gotow, Lisa F; McKinley, Denise D; Piechan, Julie L; Ruble, Cara L; Mills, Cynthia J; Schellin, Kathleen A B; Slightom, Jerry L; Fitzgerald, Laura R; Benjamin, Christopher W; Roberds, Steven L

    2003-11-13

    The ligand-gated ion channel family includes receptors for serotonin (5-hydroxytryptamine, 5-HT), acetylcholine, GABA, and glutamate. Drugs targeting subtypes of these receptors have proven useful for the treatment of various neuropsychiatric and neurological disorders. To identify new ligand-gated ion channels as potential therapeutic targets, drafts of human genome sequence were interrogated. Portions of four novel genes homologous to 5-HT(3A) and 5-HT(3B) receptors were identified within human sequence databases. We named the genes 5-HT(3C1)-5-HT(3C4). Radiation hybrid (RH) mapping localized these genes to chromosome 3q27-28. All four genes shared similar intron-exon organizations and predicted protein secondary structure with 5-HT(3A) and 5-HT(3B). Orthologous genes were detected by Southern blotting in several species including dog, cow, and chicken, but not in rodents, suggesting that these novel genes are not present in rodents or are very poorly conserved. Two of the novel genes are predicted to be pseudogenes, but two other genes are transcribed and spliced to form appropriate open reading frames. The 5-HT(3C1) transcript is expressed almost exclusively in small intestine and colon, suggesting a possible role in the serotonin-responsiveness of the gut.

  13. Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

    PubMed Central

    Danger, Richard; Royer, Pierre-Joseph; Reboulleau, Damien; Durand, Eugénie; Loy, Jennifer; Tissot, Adrien; Lacoste, Philippe; Roux, Antoine; Reynaud-Gaubert, Martine; Gomez, Carine; Kessler, Romain; Mussot, Sacha; Dromer, Claire; Brugière, Olivier; Mornex, Jean-François; Guillemain, Romain; Dahan, Marcel; Knoop, Christiane; Botturi, Karine; Foureau, Aurore; Pison, Christophe; Koutsokera, Angela; Nicod, Laurent P.; Brouard, Sophie; Magnan, Antoine; Jougon, J.

    2018-01-01

    Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS. PMID:29375549

  14. A link among DNA replication, recombination, and gene expression revealed by genetic and genomic analysis of TEBICHI gene of Arabidopsis thaliana.

    PubMed

    Inagaki, Soichi; Nakamura, Kenzo; Morikami, Atsushi

    2009-08-01

    Spatio-temporal regulation of gene expression during development depends on many factors. Mutations in Arabidopsis thaliana TEBICHI (TEB) gene encoding putative helicase and DNA polymerase domains-containing protein result in defects in meristem maintenance and correct organ formation, as well as constitutive DNA damage response and a defect in cell cycle progression; but the molecular link between these phenotypes of teb mutants is unknown. Here, we show that mutations in the DNA replication checkpoint pathway gene, ATR, but not in ATM gene, enhance developmental phenotypes of teb mutants, although atr suppresses cell cycle defect of teb mutants. Developmental phenotypes of teb mutants are also enhanced by mutations in RAD51D and XRCC2 gene, which are involved in homologous recombination. teb and teb atr double mutants exhibit defects in adaxial-abaxial polarity of leaves, which is caused in part by the upregulation of ETTIN (ETT)/AUXIN RESPONSIVE FACTOR 3 (ARF3) and ARF4 genes. The Helitron transposon in the upstream of ETT/ARF3 gene is likely to be involved in the upregulation of ETT/ARF3 in teb. Microarray analysis indicated that teb and teb atr causes preferential upregulation of genes nearby the Helitron transposons. Furthermore, interestingly, duplicated genes, especially tandemly arrayed homologous genes, are highly upregulated in teb or teb atr. We conclude that TEB is required for normal progression of DNA replication and for correct expression of genes during development. Interplay between these two functions and possible mechanism leading to altered expression of specific genes will be discussed.

  15. Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

    PubMed

    Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

    2018-03-01

    Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  16. A gene expression biomarker accurately predicts estrogen ...

    EPA Pesticide Factsheets

    The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

  17. A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

    PubMed

    Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

  18. A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

    PubMed Central

    Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

  19. Polymorphisms in arsenic(+III oxidation state) methyltransferase (AS3MT) predict gene expression of AS3MT as well as arsenic metabolism.

    PubMed

    Engström, Karin; Vahter, Marie; Mlakar, Simona Jurkovic; Concha, Gabriela; Nermell, Barbro; Raqib, Rubhana; Cardozo, Alejandro; Broberg, Karin

    2011-02-01

    Arsenic (As) occurs as monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) in humans, and the methylation pattern demonstrates large interindividual differences. The fraction of urinary MMA is a marker for susceptibility to As-related diseases. We evaluated the impact of polymorphisms in five methyltransferase genes on As metabolism in two populations, one in South America and one in Southeast Asia. The methyltransferase genes were arsenic(+III oxidation state) methyltransferase (AS3MT), DNA-methyltransferase 1a and 3b (DNMT1a and DNMT3b, respectively), phosphatidylethanolamine N-methyltransferase (PEMT), and betaine-homocysteine methyltransferase (BHMT). AS3MT expression was analyzed in peripheral blood. Subjects were women exposed to As in drinking water in the Argentinean Andes [n = 172; median total urinary As (U-As), 200 µg/L] and in rural Bangladesh (n = 361; U-As, 100 µg/L; all in early pregnancy). Urinary As metabolites were measured by high-pressure liquid chromatography/inductively coupled plasma mass spectrometry. Polymorphisms (n = 22) were genotyped with Sequenom, and AS3MT expression was measured by quantitative real-time polymerase chain reaction using TaqMan expression assays. Six AS3MT polymorphisms were significantly associated with As metabolite patterns in both populations (p ≤ 0.01). The most frequent AS3MT haplotype in Bangladesh was associated with a higher percentage of MMA (%MMA), and the most frequent haplotype in Argentina was associated with a lower %MMA and a higher percentage of DMA. Four polymorphisms in the DNMT genes were associated with metabolite patterns in Bangladesh. Noncoding AS3MT polymorphisms affected gene expression of AS3MT in peripheral blood, demonstrating that one functional impact of AS3MT polymorphisms may be altered levels of gene expression. Polymorphisms in AS3MT significantly predicted As metabolism across these two very different populations, suggesting that AS3MT may have an impact on As metabolite

  20. Polymorphisms in Arsenic(+III Oxidation State) Methyltransferase (AS3MT) Predict Gene Expression of AS3MT as Well as Arsenic Metabolism

    PubMed Central

    Engström, Karin; Vahter, Marie; Mlakar, Simona Jurkovic; Concha, Gabriela; Nermell, Barbro; Raqib, Rubhana; Cardozo, Alejandro; Broberg, Karin

    2011-01-01

    Background Arsenic (As) occurs as monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) in humans, and the methylation pattern demonstrates large interindividual differences. The fraction of urinary MMA is a marker for susceptibility to As-related diseases. Objectives We evaluated the impact of polymorphisms in five methyltransferase genes on As metabolism in two populations, one in South America and one in Southeast Asia. The methyltransferase genes were arsenic(+III oxidation state) methyltransferase (AS3MT), DNA-methyltransferase 1a and 3b (DNMT1a and DNMT3b, respectively), phosphatidylethanolamine N-methyltransferase (PEMT), and betaine-homocysteine methyltransferase (BHMT). AS3MT expression was analyzed in peripheral blood. Methods Subjects were women exposed to As in drinking water in the Argentinean Andes [n = 172; median total urinary As (U-As), 200 μg/L] and in rural Bangladesh (n = 361; U-As, 100 μg/L; all in early pregnancy). Urinary As metabolites were measured by high-pressure liquid chromatography/inductively coupled plasma mass spectrometry. Polymorphisms (n = 22) were genotyped with Sequenom, and AS3MT expression was measured by quantitative real-time polymerase chain reaction using TaqMan expression assays. Results Six AS3MT polymorphisms were significantly associated with As metabolite patterns in both populations (p ≤ 0.01). The most frequent AS3MT haplotype in Bangladesh was associated with a higher percentage of MMA (%MMA), and the most frequent haplotype in Argentina was associated with a lower %MMA and a higher percentage of DMA. Four polymorphisms in the DNMT genes were associated with metabolite patterns in Bangladesh. Noncoding AS3MT polymorphisms affected gene expression of AS3MT in peripheral blood, demonstrating that one functional impact of AS3MT polymorphisms may be altered levels of gene expression. Conclusions Polymorphisms in AS3MT significantly predicted As metabolism across these two very different populations

  1. Gene Expression Profiling Predicts the Development of Oral Cancer

    PubMed Central

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

    2011-01-01

    Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

  2. Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements.

    PubMed

    Lan, Hui; Carson, Rachel; Provart, Nicholas J; Bonner, Anthony J

    2007-09-21

    Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these genes is currently unknown. The purpose of this study is to infer gene function in Arabidopsis using machine-learning algorithms applied to large-scale gene expression data sets, with the goal of identifying genes that are potentially involved in plant response to abiotic stress. Using in house and publicly available data, we assembled a large set of gene expression measurements for A. thaliana. Using those genes of known function, we first evaluated and compared the ability of basic machine-learning algorithms to predict which genes respond to stress. Predictive accuracy was measured using ROC50 and precision curves derived through cross validation. To improve accuracy, we developed a method for combining these classifiers using a weighted-voting scheme. The combined classifier was then trained on genes of known function and applied to genes of unknown function, identifying genes that potentially respond to stress. Visual evidence corroborating the predictions was obtained using electronic Northern analysis. Three of the predicted genes were chosen for biological validation. Gene knockout experiments confirmed that all three are involved in a variety of stress responses. The biological analysis of one of these genes (At1g16850) is presented here, where it is shown to be necessary for the normal response to temperature and NaCl. Supervised learning methods applied to large-scale gene expression measurements can be used to predict gene function. However, the ability of basic learning methods to predict stress response varies widely and depends heavily on how much dimensionality reduction is used. Our method of combining classifiers can improve the accuracy of such predictions - in this case, predictions of genes involved in stress response in plants - and it effectively chooses the appropriate amount

  3. A comparative analysis of soft computing techniques for gene prediction.

    PubMed

    Goel, Neelam; Singh, Shailendra; Aseri, Trilok Chand

    2013-07-01

    The rapid growth of genomic sequence data for both human and nonhuman species has made analyzing these sequences, especially predicting genes in them, very important and is currently the focus of many research efforts. Beside its scientific interest in the molecular biology and genomics community, gene prediction is of considerable importance in human health and medicine. A variety of gene prediction techniques have been developed for eukaryotes over the past few years. This article reviews and analyzes the application of certain soft computing techniques in gene prediction. First, the problem of gene prediction and its challenges are described. These are followed by different soft computing techniques along with their application to gene prediction. In addition, a comparative analysis of different soft computing techniques for gene prediction is given. Finally some limitations of the current research activities and future research directions are provided. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. Inductive matrix completion for predicting gene-disease associations.

    PubMed

    Natarajan, Nagarajan; Dhillon, Inderjit S

    2014-06-15

    Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive. Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently reported in the literature

  5. Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.

    PubMed

    Chan, Kuang-Lim; Rosli, Rozana; Tatarinova, Tatiana V; Hogan, Michael; Firdaus-Raih, Mohd; Low, Eng-Ti Leslie

    2017-01-27

    Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion. We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure). Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

  6. Homologous Recombination Repair Protects Against Particulate Chromate-induced Chromosome Instability in Chinese Hamster Cells

    PubMed Central

    Stackpole, Megan M.; Wise, Sandra S.; Duzevik, Eliza Grlickova; Munroe, Ray C.; Thompson, W. Douglas; Thacker, John; Thompson, Larry H.; Hinz, John M.; Wise, John Pierce

    2008-01-01

    Particulate hexavalent chromium [Cr(VI)] compounds are well-established human carcinogens. Cr(VI)-induced tumors are characterized by chromosomal instability (CIN); however, the mechanisms of this effect are unknown. We investigated the hypothesis that homologous recombination (HR) repair of DNA double strand breaks protect cells from Cr(VI)-induced CIN by focusing on the XRCC3 and RAD51C genes, which play an important role in cellular resistance to DNA double strand breaks. We used Chinese hamster cells defective in each HR gene (irs3 for RAD51C and irs1SF for XRCC3) and compared with their wildtype parental and cDNA-complemented controls. We found that the intracellular Cr ion levels varied among the cell lines after particulate chromate treatment. Importantly, accounting for differences in Cr ion levels, we discovered that XRCC3 and RAD51C cells treated with lead chromate had increased cytotoxicity and chromosomal aberrations, relative to wild-type and cDNA-complimented cells. We also observed the emergence of high levels of chromatid exchanges in the two mutant cell lines. For example, 1 ug/cm2 lead chromate induced 20 and 32 exchanges in XRCC3- and RAD51C-deficient cells, respectively, whereas no exchanges were detected in the wildtype and cDNA-complemented cells. These observations suggest that HR protects cells from Cr(VI)-induced CIN, consistent with the ability of particulate Cr(VI) to induce double strand breaks. PMID:17662313

  7. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network

    PubMed Central

    Hwang, Sohyun; Rhee, Seung Y; Marcotte, Edward M; Lee, Insuk

    2012-01-01

    AraNet is a functional gene network for the reference plant Arabidopsis and has been constructed in order to identify new genes associated with plant traits. It is highly predictive for diverse biological pathways and can be used to prioritize genes for functional screens. Moreover, AraNet provides a web-based tool with which plant biologists can efficiently discover novel functions of Arabidopsis genes (http://www.functionalnet.org/aranet/). This protocol explains how to conduct network-based prediction of gene functions using AraNet and how to interpret the prediction results. Functional discovery in plant biology is facilitated by combining candidate prioritization by AraNet with focused experimental tests. PMID:21886106

  8. A new computational strategy for predicting essential genes.

    PubMed

    Cheng, Jian; Wu, Wenwu; Zhang, Yinwen; Li, Xiangchen; Jiang, Xiaoqian; Wei, Gehong; Tao, Shiheng

    2013-12-21

    Determination of the minimum gene set for cellular life is one of the central goals in biology. Genome-wide essential gene identification has progressed rapidly in certain bacterial species; however, it remains difficult to achieve in most eukaryotic species. Several computational models have recently been developed to integrate gene features and used as alternatives to transfer gene essentiality annotations between organisms. We first collected features that were widely used by previous predictive models and assessed the relationships between gene features and gene essentiality using a stepwise regression model. We found two issues that could significantly reduce model accuracy: (i) the effect of multicollinearity among gene features and (ii) the diverse and even contrasting correlations between gene features and gene essentiality existing within and among different species. To address these issues, we developed a novel model called feature-based weighted Naïve Bayes model (FWM), which is based on Naïve Bayes classifiers, logistic regression, and genetic algorithm. The proposed model assesses features and filters out the effects of multicollinearity and diversity. The performance of FWM was compared with other popular models, such as support vector machine, Naïve Bayes model, and logistic regression model, by applying FWM to reciprocally predict essential genes among and within 21 species. Our results showed that FWM significantly improves the accuracy and robustness of essential gene prediction. FWM can remarkably improve the accuracy of essential gene prediction and may be used as an alternative method for other classification work. This method can contribute substantially to the knowledge of the minimum gene sets required for living organisms and the discovery of new drug targets.

  9. Contrasting analytical and data-driven frameworks for radiogenomic modeling of normal tissue toxicities in prostate cancer.

    PubMed

    Coates, James; Jeyaseelan, Asha K; Ybarra, Norma; David, Marc; Faria, Sergio; Souhami, Luis; Cury, Fabio; Duclos, Marie; El Naqa, Issam

    2015-04-01

    We explore analytical and data-driven approaches to investigate the integration of genetic variations (single nucleotide polymorphisms [SNPs] and copy number variations [CNVs]) with dosimetric and clinical variables in modeling radiation-induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients. Sixty-two patients who underwent curative hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 and 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Fifty-four patients had full dosimetric profiles. Two parallel modeling approaches were compared to assess the risk of severe RB (Grade⩾3) and ED (Grade⩾1); Maximum likelihood estimated generalized Lyman-Kutcher-Burman (LKB) and logistic regression. Statistical resampling based on cross-validation was used to evaluate model predictive power and generalizability to unseen data. Integration of biological variables xrcc1 CNV and SNP improved the fit of the RB and ED analytical and data-driven models. Cross-validation of the generalized LKB models yielded increases in classification performance of 27.4% for RB and 14.6% for ED when xrcc1 CNV and SNP were included, respectively. Biological variables added to logistic regression modeling improved classification performance over standard dosimetric models by 33.5% for RB and 21.2% for ED models. As a proof-of-concept, we demonstrated that the combination of genetic and dosimetric variables can provide significant improvement in NTCP prediction using analytical and data-driven approaches. The improvement in prediction performance was more pronounced in the data driven approaches. Moreover, we have shown that CNVs, in addition to SNPs, may be useful structural genetic variants in predicting radiation toxicities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  10. Unstabilized DNA breaks in HTLV-1 Tax expressing cells correlate with functional targeting of Ku80, not PKcs, XRCC4, or H2AX

    PubMed Central

    2012-01-01

    Background Expression of the human T-cell leukemia virus type 1 (HTLV-1) Tax oncoprotein rapidily induces a significant increase of micronuclei (MN) and unstabilized DNA breaks in cells. Unstabilized DNA breaks can have free 3′-OH ends accessible to in situ addition of digoxygenin (DIG)-labeled dUTP using terminal deoxynucleotidyl transferase. In the present work, we used a GFP-Tax (green fluorescent protein) plasmid, which produces a functionally active GFP-tagged Tax protein, to detect the cellular target(s) for Tax which might mechanistically explain the clastogenic phenomenon. We examined the induction of MN and unstabilized DNA breaks in wild type cells and cells individually knocked out for Ku80, PKcs, XRCC4, and H2AX proteins. We also assessed in the same cells, the signal strengths produced by DIG-dUTP incorporation at the unstable DNA breaks in the presence and absence of Tax. Results Cells mutated for PKcs, XRCC4 and H2AX showed increased frequency of MN and unstabilized DNA breaks in response to the expression of Tax, while cells genetically mutated for Ku80 were refractory to Tax’s induction of these cytogenetic effects. Moreover, by measuring the size of DIG-dUTP incorporation signal, which indicates the extent of unstable DNA ends, we found that Tax induces larger signals than those in control cells. However, in xrs-6 cells deficient for Ku80, this Tax effect was not seen. Conclusions The data here demonstrate that clastogenic DNA damage in Tax expressing cells is explained by Tax targeting of Ku80, but not PKcs, XRCC4 or H2AX, which are all proteins directly or indirectly related to the non-homologous end-joining (NHEJ) repair system. Of note, the Ku80 protein plays an important role at the initial stage of the NHEJ repair system, protecting and stabilizing DNA-breaks. Accordingly, HTLV-1 Tax is shown to interfere with a normal cellular protective mechanism for stabilizing DNA breaks. These DNA breaks, unprotected by Ku80, are unstable and are

  11. Thyroid nodules, polymorphic variants in DNA repair and RET-related genes, and interaction with ionizing radiation exposure from nuclear tests in Kazakhstan

    PubMed Central

    Sigurdson, Alice J.; Land, Charles E.; Bhatti, Parveen; Pineda, Marbin; Brenner, Alina; Carr, Zhanat; Gusev, Boris I.; Zhumadilov, Zhaxibay; Simon, Steven L.; Bouville, Andre; Rutter, Joni L.; Ron, Elaine; Struewing, Jeffery P.

    2010-01-01

    Risk factors for thyroid cancer remain largely unknown except for ionizing radiation exposure during childhood and a history of benign thyroid nodules. Because thyroid nodules are more common than thyroid cancers and are associated with thyroid cancer risk, we evaluated several polymorphisms potentially relevant to thyroid tumors and assessed interaction with ionizing radiation exposure to the thyroid gland. Thyroid nodules were detected in 1998 by ultrasound screening of 2997 persons who lived near the Semipalatinsk nuclear test site in Kazakhstan when they were children (1949-62). Cases with thyroid nodules (n=907) were frequency matched (1:1) to those without nodules by ethnicity (Kazakh or Russian), gender, and age at screening. Thyroid gland radiation doses were estimated from fallout deposition patterns, residence history, and diet. We analyzed 23 polymorphisms in 13 genes and assessed interaction with ionizing radiation exposure using likelihood ratio tests (LRT). Elevated thyroid nodule risks were associated with the minor alleles of RET S836S (rs1800862, p = 0.03) and GFRA1 -193C>G (rs not assigned, p = 0.05) and decreased risk with XRCC1 R194W (rs1799782, p-trend = 0.03) and TGFB1 T263I (rs1800472, p = 0.009). Similar patterns of association were observed for a small number of papillary thyroid cancers (n=25). Ionizing radiation exposure to the thyroid gland was associated with significantly increased risk of thyroid nodules (age and gender adjusted excess odds ratio/Gy = 0.30, 95% confidence interval 0.05-0.56), with evidence for interaction by genotype found for XRCC1 R194W (LRT p value = 0.02). Polymorphisms in RET signaling, DNA repair, and proliferation genes may be related to risk of thyroid nodules, consistent with some previous reports on thyroid cancer. Borderline support for gene-radiation interaction was found for a variant in XRCC1, a key base excision repair protein. Other pathways, such as genes in double strand break repair, apoptosis, and

  12. Ecological transition predictably associated with gene degeneration.

    PubMed

    Wessinger, Carolyn A; Rausher, Mark D

    2015-02-01

    Gene degeneration or loss can significantly contribute to phenotypic diversification, but may generate genetic constraints on future evolutionary trajectories, potentially restricting phenotypic reversal. Such constraints may manifest as directional evolutionary trends when parallel phenotypic shifts consistently involve gene degeneration or loss. Here, we demonstrate that widespread parallel evolution in Penstemon from blue to red flowers predictably involves the functional inactivation and degeneration of the enzyme flavonoid 3',5'-hydroxylase (F3'5'H), an anthocyanin pathway enzyme required for the production of blue floral pigments. Other types of genetic mutations do not consistently accompany this phenotypic shift. This pattern may be driven by the relatively large mutational target size of degenerative mutations to this locus and the apparent lack of associated pleiotropic effects. The consistent degeneration of F3'5'H may provide a mechanistic explanation for the observed asymmetry in the direction of flower color evolution in Penstemon: Blue to red transitions are common, but reverse transitions have not been observed. Although phenotypic shifts in this system are likely driven by natural selection, internal constraints may generate predictable genetic outcomes and may restrict future evolutionary trajectories. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  13. Association of Arg194Trp, Arg280His and Arg399Gln Polymorphisms in X-ray Repair Cross-Complementing Group 1 Gene and Risk of Differentiated Thyroid Carcinoma in Iran

    PubMed Central

    Fard-Esfahani, Pezhman; Fard-Esfahani, Armaghan; Fayaz, Shima; Ghanbarzadeh, Bahareh; Saidi, Parinaz; Mohabati, Reyhaneh; Bidoki, Seyed Kazem; Majdi, Mina

    2011-01-01

    Background: X-ray repair cross-complementing group 1 (XRCC1) gene is a DNA repair gene and its non-synonymous single nucleotide polymorphisms (SNP) may influence DNA repair capacity which has been considered as a modifying risk factor for cancer development. Methods: A case-control study was conducted to investigate impact of three frequently studied polymorphisms (Arg194Trp, Arg280His and Arg399Gln) on developing differentiated thyroid carcinoma (DTC). Results: Increased risks for DTC were shown in homozygous (odds ratio [OR]: 3.66, 95% confidence interval [CI]: 0.38-35.60) and in dominant trait (OR: 1.22, 95% CI: 1.64-2.32) of Arg194Trp genotype. Also, for Arg280His genotype, an increased risk for DTC was shown in dominant trait (OR: 1.42, 95% confidence interval [CI]: 0.76-2.68), while a mildly reduction of risk for DTC (OR: 0.77, 95% [CI]: 0.50-1.17) was estimated in dominant Gln genotype of Arg399Gln. Considering combinatory effects of Arg194Trp and Arg280His genotypes on DTC, the calculated OR and 95% CI for being heterozygous for one of Arg194Trp or Arg280His genotypes were 1.57 and 0.90-2.74, respectively. Conclusion: Genotyping of codons 194, 280 and 399 in XRCC1 gene may use in risk assessment of DTC. PMID:21987112

  14. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    PubMed Central

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  15. Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

    PubMed

    Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

    2012-07-15

    Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary

  16. GenePRIMP: A Gene Prediction Improvement Pipeline For Prokaryotic Genomes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kyrpides, Nikos C.; Ivanova, Natalia N.; Pati, Amrita

    2010-07-08

    GenePRIMP (Gene Prediction Improvement Pipeline, Http://geneprimp.jgi-psf.org), a computational process that performs evidence-based evaluation of gene models in prokaryotic genomes and reports anomalies including inconsistent start sites, missing genes, and split genes. We show that manual curation of gene models using the anomaly reports generated by GenePRIMP improves their quality and demonstrate the applicability of GenePRIMP in improving finishing quality and comparing different genome sequencing and annotation technologies. Keywords in context: Gene model, Quality Control, Translation start sites, Automatic correction. Hardware requirements; PC, MAC; Operating System: UNIX/LINUX; Compiler/Version: Perl 5.8.5 or higher; Special requirements: NCBI Blast and nr installation; File Types:more » Source Code, Executable module(s), Sample problem input data; installation instructions other; programmer documentation. Location/transmission: http://geneprimp.jgi-psf.org/gp.tar.gz« less

  17. Reranking candidate gene models with cross-species comparison for improved gene prediction

    PubMed Central

    Liu, Qian; Crammer, Koby; Pereira, Fernando CN; Roos, David S

    2008-01-01

    Background Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patterns, etc). Competing models with similar state-based scores may be distinguishable with additional information. In particular, functional and comparative genomics datasets may help to select among competing models of comparable probability by exploiting features likely to be associated with the correct gene models, such as conserved exon/intron structure or protein sequence features. Results We have investigated the utility of a simple post-processing step for selecting among a set of alternative gene models, using global scoring rules to rerank competing models for more accurate prediction. For each gene locus, we first generate the K best candidate gene models using the gene finder Evigan, and then rerank these models using comparisons with putative orthologous genes from closely-related species. Candidate gene models with lower scores in the original gene finder may be selected if they exhibit strong similarity to probable orthologs in coding sequence, splice site location, or signal peptide occurrence. Experiments on Drosophila melanogaster demonstrate that reranking based on cross-species comparison outperforms the best gene models identified by Evigan alone, and also outperforms the comparative gene finders GeneWise and Augustus+. Conclusion Reranking gene models with cross-species comparison improves gene prediction accuracy. This straightforward method can be readily adapted to incorporate additional lines of evidence, as it requires only a ranked source of candidate gene models. PMID:18854050

  18. Identification and characterisation of the angiotensin converting enzyme-3 (ACE3) gene: a novel mammalian homologue of ACE

    PubMed Central

    Rella, Monika; Elliot, Joann L; Revett, Timothy J; Lanfear, Jerry; Phelan, Anne; Jackson, Richard M; Turner, Anthony J; Hooper, Nigel M

    2007-01-01

    Background Mammalian angiotensin converting enzyme (ACE) plays a key role in blood pressure regulation. Although multiple ACE-like proteins exist in non-mammalian organisms, to date only one other ACE homologue, ACE2, has been identified in mammals. Results Here we report the identification and characterisation of the gene encoding a third homologue of ACE, termed ACE3, in several mammalian genomes. The ACE3 gene is located on the same chromosome downstream of the ACE gene. Multiple sequence alignment and molecular modelling have been employed to characterise the predicted ACE3 protein. In mouse, rat, cow and dog, the predicted protein has mutations in some of the critical residues involved in catalysis, including the catalytic Glu in the HEXXH zinc binding motif which is Gln, and ESTs or reverse-transcription PCR indicate that the gene is expressed. In humans, the predicted ACE3 protein has an intact HEXXH motif, but there are other deletions and insertions in the gene and no ESTs have been identified. Conclusion In the genomes of several mammalian species there is a gene that encodes a novel, single domain ACE-like protein, ACE3. In mouse, rat, cow and dog ACE3, the catalytic Glu is replaced by Gln in the putative zinc binding motif, indicating that in these species ACE3 would lack catalytic activity as a zinc metalloprotease. In humans, no evidence was found that the ACE3 gene is expressed and the presence of deletions and insertions in the sequence indicate that ACE3 is a pseudogene. PMID:17597519

  19. Decreased expression level of BER genes in Alzheimer's disease patients is not derivative of their DNA methylation status.

    PubMed

    Sliwinska, Agnieszka; Sitarek, Przemysław; Toma, Monika; Czarny, Piotr; Synowiec, Ewelina; Krupa, Renata; Wigner, Paulina; Bialek, Katarzyna; Kwiatkowski, Dominik; Korycinska, Anna; Majsterek, Ireneusz; Szemraj, Janusz; Galecki, Piotr; Sliwinski, Tomasz

    2017-10-03

    Neurodegeneration in Alzheimer's disease can be caused by accumulation of oxidative DNA damage resulting from altered expression of genes involved in the base excision repair system (BER). Promoter methylation can affect the profile of BER genes expression. Decreased expression of BER genes was observed in the brains of AD patients. The aim of our study was to compare the expression and methylation profiles of six genes coding for proteins involved in BER, namely: hOGG1, APE1, MUTYH, NEIL1, PARP1 and XRCC1, in the peripheral blood cells of AD patients and healthy volunteers. The study consisted of 100 persons diagnosed with Alzheimer's disease according to DSM-IV criteria, and 110 healthy volunteers. DNA and total RNA were isolated from venous blood cells. Promoter methylation profiles were obtained by High Resolution Melting (HRM) analysis of bisulfide converted DNA samples. Real-time PCR with TaqMan probes was employed for gene expression analysis. APE1, hOGG1, MUTYH, PARP1 and NEIL1 were significantly (p<0.001) down-regulated in the lymphocytes of AD patients, as compared to healthy volunteers. Expression of XRCC1 didn't differ significantly between both groups. We did not find any differences in the methylation pattern of any of the investigated BER genes. The methylation status of promoters is not associated with downregulation of BER genes. Our results show that downregulation of BER genes detected in peripheral blood samples could reflect the changes occurring in the brain of patients with AD, and may be a useful biomarker of this disease. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Gene-gene interaction between COMT and MAOA potentially predicts the intelligence of attention-deficit hyperactivity disorder boys in China.

    PubMed

    Qian, Qiu-Jin; Yang, Li; Wang, Yu-Feng; Zhang, Hao-Bo; Guan, Li-Li; Chen, Yun; Ji, Ning; Liu, Lu; Faraone, S V

    2010-05-01

    The catechol-O-methyltransferase (COMT) gene contains a functional polymorphism (Val158Met) affecting the activity of the enzyme, and the monoamine oxidase A (MAOA) gene contains a VNTR polymorphism (MAOA-uVNTR) that affects the transcription of the gene. COMT and MAOA each contribute to the enzymatic degradation of dopamine and noradrenaline. Prefrontal cortical (PFC) function, which plays an important role in individual cognitive abilities, including intelligence, is modulated by dopamine. Since our previous association studies between attention deficit hyperactivity disorder (ADHD) and these two functional polymorphisms consistently showed the low activity alleles were preferentially transmitted to inattentive ADHD boys, the goal of the present study was to test the hypothesis that the interaction between COMT Val158Met and MAOA-uVNTR may affect the intelligence in a clinical sample of Chinese male ADHD subjects (n = 264). We found that the COMT x MAOA interaction significantly predicted full scale (FSIQ) and performance (PIQ) IQ scores (P = 0.039, 0.011); the MAOA-uVNTR significantly predicted FSIQ, PIQ and verbal IQ (VIQ) (P = 0.009, 0.019, 0.038); COMT Val158Met independently had no effect on any of the IQ scores. Only the COMT x MAOA interaction for PIQ remained significant after a Bonferroni correction. Among all combined genotypes, the valval-3R genotype predicted higher intelligence, (average 106.7 +/- 1.6, 95% C.I. 103.7-109.8 for FSIQ), and the valval-4R predicted lower intelligence (average 98.0 +/- 2.3, 95% C.I. 93.5-102.6 for FSIQ). These results suggest that there is an inverted U-shaped relationship between intelligence and dopaminergic activity in our sample. Our finding that gene-gene interaction between COMT and MAOA predicts the intelligence of ADHD boys in China is intriguing but requires replication in other samples.

  1. Prediction and Validation of Disease Genes Using HeteSim Scores.

    PubMed

    Zeng, Xiangxiang; Liao, Yuanlu; Liu, Yuansheng; Zou, Quan

    2017-01-01

    Deciphering the gene disease association is an important goal in biomedical research. In this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate disease genes. Two methods based on heterogeneous networks constructed using protein-protein interaction, gene-phenotype associations, and phenotype-phenotype similarity, are presented. In HeteSim_MultiPath (HSMP), HeteSim scores of different paths are combined with a constant that dampens the contributions of longer paths. In HeteSim_SVM (HSSVM), HeteSim scores are combined with a machine learning method. The 3-fold experiments show that our non-machine learning method HSMP performs better than the existing non-machine learning methods, our machine learning method HSSVM obtains similar accuracy with the best existing machine learning method CATAPULT. From the analysis of the top 10 predicted genes for different diseases, we found that HSSVM avoid the disadvantage of the existing machine learning based methods, which always predict similar genes for different diseases. The data sets and Matlab code for the two methods are freely available for download at http://lab.malab.cn/data/HeteSim/index.jsp.

  2. A four-gene signature predicts survival in clear-cell renal-cell carcinoma.

    PubMed

    Dai, Jun; Lu, Yuchao; Wang, Jinyu; Yang, Lili; Han, Yingyan; Wang, Ying; Yan, Dan; Ruan, Qiurong; Wang, Shaogang

    2016-12-13

    Clear-cell renal-cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma (RCC), accounting for about 80% of RCC. In order to find potential prognostic biomarkers in ccRCC, we presented a four-gene signature to evaluate the prognosis of ccRCC. SurvExpress and immunohistochemical (IHC) staining of tissue microarrays were used to analyze the association between the four genes and the prognosis of ccRCC. Data from TCGA dataset revealed a prognostic prompt function of the four genes (PTEN, PIK3C2A, ITPA and BCL3). Further discovery suggested that the four-gene signature predicted survival better than any of the four genes alone. Moreover, IHC staining demonstrated a consistent result with TCGA, indicating that the signature was an independent prognostic factor of survival in ccRCC. Univariate and multivariate Cox proportional hazard regression analysis were conducted to verify the association of clinicopathological variables and the four genes' expression levels with survival. The results further testified that the risk (four-gene signature) was an independent prognostic factors of both Overall Survival (OS) and Disease-free Survival (DFS) (P<0.05). In conclusion, the four-gene signature was correlated with the survival of ccRCC, and therefore, may help to provide significant clinical implications for predicting the prognosis of patients.

  3. Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus.

    PubMed

    Lu, Yao; Deng, Jingyuan; Rhodes, Judith C; Lu, Hui; Lu, Long Jason

    2014-06-01

    Aspergillus fumigatus (Af) is a ubiquitous and opportunistic pathogen capable of causing acute, invasive pulmonary disease in susceptible hosts. Despite current therapeutic options, mortality associated with invasive Af infections remains unacceptably high, increasing 357% since 1980. Therefore, there is an urgent need for the development of novel therapeutic strategies, including more efficacious drugs acting on new targets. Thus, as noted in a recent review, "the identification of essential genes in fungi represents a crucial step in the development of new antifungal drugs". Expanding the target space by rapidly identifying new essential genes has thus been described as "the most important task of genomics-based target validation". In previous research, we were the first to show that essential gene annotation can be reliably transferred between distantly related four Prokaryotic species. In this study, we extend our machine learning approach to the much more complex Eukaryotic fungal species. A compendium of essential genes is predicted in Af by transferring known essential gene annotations from another filamentous fungus Neurospora crassa. This approach predicts essential genes by integrating diverse types of intrinsic and context-dependent genomic features encoded in microbial genomes. The predicted essential datasets contained 1674 genes. We validated our results by comparing our predictions with known essential genes in Af, comparing our predictions with those predicted by homology mapping, and conducting conditional expressed alleles. We applied several layers of filters and selected a set of potential drug targets from the predicted essential genes. Finally, we have conducted wet lab knockout experiments to verify our predictions, which further validates the accuracy and wide applicability of the machine learning approach. The approach presented here significantly extended our ability to predict essential genes beyond orthologs and made it possible to

  4. Predicting features of breast cancer with gene expression patterns.

    PubMed

    Lu, Xuesong; Lu, Xin; Wang, Zhigang C; Iglehart, J Dirk; Zhang, Xuegong; Richardson, Andrea L

    2008-03-01

    Data from gene expression arrays hold an enormous amount of biological information. We sought to determine if global gene expression in primary breast cancers contained information about biologic, histologic, and anatomic features of the disease in individual patients. Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers [estrogen receptor (ER) and HER2], histologic features [grade and lymphatic-vascular invasion (LVI)], and stage parameters (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy was determined by cross-validation error rate; multidimensional scaling (MDS) allowed visualization of the predicted states under study. Models built from gene expression data accurately predict ER and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data is inaccurate at predicting tumor size, lymph node status or LVI. The best model for prediction of nodal status included tumor size, LVI status and pathologically defined tumor subtype (based on combinations of ER, HER2, and grade); the addition of microarray-based prediction to this model failed to improve the prediction accuracy. Global gene expression supports a binary division of ER, HER2, and grade, clearly separating tumors into two categories; intermediate values for these bio-indicators do not define intermediate tumor subsets. Results are consistent with a model of regional metastasis that depends on inherent biologic differences in metastatic propensity between breast cancer subtypes, upon which time and chance then operate.

  5. Gene and translation initiation site prediction in metagenomic sequences

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hyatt, Philip Douglas; LoCascio, Philip F; Hauser, Loren John

    2012-01-01

    Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translationmore » initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.« less

  6. Prediction of exercise-mediated changes in metabolic markers by gene polymorphism.

    PubMed

    Kahara, Toshio; Takamura, Toshinari; Hayakawa, Tetsuo; Nagai, Yukihiro; Yamaguchi, Hiromi; Katsuki, Tatsuo; Katsuki, Ken-ichi; Katsuki, Michio; Kobayashi, Ken-ichi

    2002-08-01

    The effects of regular physical exercise on obesity-associated metabolic abnormalities vary for each individual. In this study, we investigated whether genotypes of genes associated with obesity can predict the effects of exercise on changes in metabolic markers in healthy men. Healthy Japanese men (n=106) performed the exercise program at 50% of their maximal heart rate for 20-60 min a day, 2-3 days each week for 3 months. The levels of fasting plasma glucose (FPG) and serum leptin significantly decreased after the exercise program. Polymorphisms of the beta3-adrenergic receptor (beta3AR) and uncoupling protein-1 (UCP-1) genes were analyzed with RFLP methods. In the Trp/Trp genotype of the beta3AR gene, the levels of serum leptin, FPG and fructosamine (FrAm) decreased significantly after the exercise program, but not in the Arg/Arg genotype. In the AG heterozygote and the GG homozygote of the UCP-1 gene, FPG and FrAm levels were significantly reduced, respectively. In conclusion, gene polymorphism of the beta3AR and UCP-1 was found to be associated with the exercise-mediated improvement in glucose tolerance and leptin resistance in healthy Japanese men.

  7. MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes.

    PubMed

    Zhu, Huaiqiu; Hu, Gang-Qing; Yang, Yi-Fan; Wang, Jin; She, Zhen-Su

    2007-03-16

    Despite a remarkable success in the computational prediction of genes in Bacteria and Archaea, a lack of comprehensive understanding of prokaryotic gene structures prevents from further elucidation of differences among genomes. It continues to be interesting to develop new ab initio algorithms which not only accurately predict genes, but also facilitate comparative studies of prokaryotic genomes. This paper describes a new prokaryotic genefinding algorithm based on a comprehensive statistical model of protein coding Open Reading Frames (ORFs) and Translation Initiation Sites (TISs). The former is based on a linguistic "Entropy Density Profile" (EDP) model of coding DNA sequence and the latter comprises several relevant features related to the translation initiation. They are combined to form a so-called Multivariate Entropy Distance (MED) algorithm, MED 2.0, that incorporates several strategies in the iterative program. The iterations enable us to develop a non-supervised learning process and to obtain a set of genome-specific parameters for the gene structure, before making the prediction of genes. Results of extensive tests show that MED 2.0 achieves a competitive high performance in the gene prediction for both 5' and 3' end matches, compared to the current best prokaryotic gene finders. The advantage of the MED 2.0 is particularly evident for GC-rich genomes and archaeal genomes. Furthermore, the genome-specific parameters given by MED 2.0 match with the current understanding of prokaryotic genomes and may serve as tools for comparative genomic studies. In particular, MED 2.0 is shown to reveal divergent translation initiation mechanisms in archaeal genomes while making a more accurate prediction of TISs compared to the existing gene finders and the current GenBank annotation.

  8. A deep auto-encoder model for gene expression prediction.

    PubMed

    Xie, Rui; Wen, Jia; Quitadamo, Andrew; Cheng, Jianlin; Shi, Xinghua

    2017-11-17

    Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns. We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

  9. Prediction of gene expression with cis-SNPs using mixed models and regularization methods.

    PubMed

    Zeng, Ping; Zhou, Xiang; Huang, Shuiping

    2017-05-11

    It has been shown that gene expression in human tissues is heritable, thus predicting gene expression using only SNPs becomes possible. The prediction of gene expression can offer important implications on the genetic architecture of individual functional associated SNPs and further interpretations of the molecular basis underlying human diseases. We compared three types of methods for predicting gene expression using only cis-SNPs, including the polygenic model, i.e. linear mixed model (LMM), two sparse models, i.e. Lasso and elastic net (ENET), and the hybrid of LMM and sparse model, i.e. Bayesian sparse linear mixed model (BSLMM). The three kinds of prediction methods have very different assumptions of underlying genetic architectures. These methods were evaluated using simulations under various scenarios, and were applied to the Geuvadis gene expression data. The simulations showed that these four prediction methods (i.e. Lasso, ENET, LMM and BSLMM) behaved best when their respective modeling assumptions were satisfied, but BSLMM had a robust performance across a range of scenarios. According to R 2 of these models in the Geuvadis data, the four methods performed quite similarly. We did not observe any clustering or enrichment of predictive genes (defined as genes with R 2  ≥ 0.05) across the chromosomes, and also did not see there was any clear relationship between the proportion of the predictive genes and the proportion of genes in each chromosome. However, an interesting finding in the Geuvadis data was that highly predictive genes (e.g. R 2  ≥ 0.30) may have sparse genetic architectures since Lasso, ENET and BSLMM outperformed LMM for these genes; and this observation was validated in another gene expression data. We further showed that the predictive genes were enriched in approximately independent LD blocks. Gene expression can be predicted with only cis-SNPs using well-developed prediction models and these predictive genes were enriched in

  10. GeneMachine: gene prediction and sequence annotation.

    PubMed

    Makalowska, I; Ryan, J F; Baxevanis, A D

    2001-09-01

    A number of free-standing programs have been developed in order to help researchers find potential coding regions and deduce gene structure for long stretches of what is essentially 'anonymous DNA'. As these programs apply inherently different criteria to the question of what is and is not a coding region, multiple algorithms should be used in the course of positional cloning and positional candidate projects to assure that all potential coding regions within a previously-identified critical region are identified. We have developed a gene identification tool called GeneMachine which allows users to query multiple exon and gene prediction programs in an automated fashion. BLAST searches are also performed in order to see whether a previously-characterized coding region corresponds to a region in the query sequence. A suite of Perl programs and modules are used to run MZEF, GENSCAN, GRAIL 2, FGENES, RepeatMasker, Sputnik, and BLAST. The results of these runs are then parsed and written into ASN.1 format. Output files can be opened using NCBI Sequin, in essence using Sequin as both a workbench and as a graphical viewer. The main feature of GeneMachine is that the process is fully automated; the user is only required to launch GeneMachine and then open the resulting file with Sequin. Annotations can then be made to these results prior to submission to GenBank, thereby increasing the intrinsic value of these data. GeneMachine is freely-available for download at http://genome.nhgri.nih.gov/genemachine. A public Web interface to the GeneMachine server for academic and not-for-profit users is available at http://genemachine.nhgri.nih.gov. The Web supplement to this paper may be found at http://genome.nhgri.nih.gov/genemachine/supplement/.

  11. Combining heavy ion radiation and artificial microRNAs to target the homologous recombination repair gene efficiently kills human tumor cells.

    PubMed

    Zheng, Zhiming; Wang, Ping; Wang, Hongyan; Zhang, Xiangming; Wang, Minli; Cucinotta, Francis A; Wang, Ya

    2013-02-01

    Previously, we demonstrated that heavy ions kill more cells at the same dose than X-rays because DNA-clustered lesions produced by heavy ions affect nonhomologous end-joining (NHEJ) repair but not homologous recombination repair (HRR). We have also shown that our designed artificial microRNAs (amiRs) could efficiently target XRCC4 (an essential factor for NHEJ) or XRCC2 (an essential factor for HRR) and sensitize human tumor cells to X-rays. Based on these data, we were interested in testing the hypothesis that combining heavy ions and amiRs to target HRR but not NHEJ should more efficiently kill human tumor cells. Human tumor cell lines (U87MG, a brain tumor cell line, and A549, a lung cancer cell line) and their counterparts, overexpressed with amiR to target XRCC2, XRCC4 or both, were used in this study. Survival sensitivities were examined using a clonogenic assay after these cells were exposed to X-rays or heavy ions. In addition, these cell lines were subcutaneously injected into nude mice to form xenografts and the tumor size was compared after the tumor areas were exposed to X-rays or heavy ions. Although targeting either XRCC4 (NHEJ factor) or XRCC2 (HRR factor) sensitized the human tumor cells to X-rays, in vitro and the xenograft animal model, targeting only XRCC2 but not XRCC4 sensitized the human tumor cells to heavy ions in vitro and in the xenograft animal model. Combining heavy ions with targeting the HRR pathway, but not the NHEJ pathway, could significantly improve the efficiency of tumor cell death. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Pharmacogenomics of platinum-based chemotherapy response in NSCLC: a genotyping study and a pooled analysis

    PubMed Central

    Chen, Juan; Wang, Zhan; Zou, Ting; Cui, Jiajia; Yin, Jiye; Zheng, Wei; Jiang, Wuzhong; Zhou, Honghao; Liu, Zhaoqian

    2016-01-01

    Published data showed inconsistent results about associations of extensively studied polymorphisms with platinum-based chemotherapy response. Our study aimed to provide reliable conclusions of these associations by detecting genotypes of the SNPs in a larger sample size and summarizing a comprehensive pooled analysis. 13 SNPs in 8 genes were genotyped in 1024 NSCLC patients by SequenomMassARRAY. 39 published studies and our study were included in meta-analysis. Patients with GA or GG genotypes of XRCC1 G1196 had better response than AA genotype carriers (Genotyping study: OR = 0.72, 95%CI: 0.53-0.96, P = 0.028; Meta-analysis: OR = 0.74, 95%CI: 0.62-0.89, P = 0.001). Patients carrying CT or TT genotypes of XRCC1 C580T could be more sensitive to platinum-based chemotherapy compared to patients with CC genotype (OR = 0.54, 95%CI: 0.37-0.80, P = 0.002). CC genotype of XRCC3 C18067T carriers showed more resistance to platinum-based chemotherapy when compared to those with CT or TT genotypes (OR = 0.69, 95%CI: 0.52-0.91, P = 0.009). Our study indicated that XRCC1 G1196A/C580T and XRCC3 C18067T should be paid attention for personalized platinum-based chemotherapy in NSCLC patients. PMID:27248474

  13. Predicting Gene Structures from Multiple RT-PCR Tests

    NASA Astrophysics Data System (ADS)

    Kováč, Jakub; Vinař, Tomáš; Brejová, Broňa

    It has been demonstrated that the use of additional information such as ESTs and protein homology can significantly improve accuracy of gene prediction. However, many sources of external information are still being omitted from consideration. Here, we investigate the use of product lengths from RT-PCR experiments in gene finding. We present hardness results and practical algorithms for several variants of the problem and apply our methods to a real RT-PCR data set in the Drosophila genome. We conclude that the use of RT-PCR data can improve the sensitivity of gene prediction and locate novel splicing variants.

  14. CodingQuarry: highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts.

    PubMed

    Testa, Alison C; Hane, James K; Ellwood, Simon R; Oliver, Richard P

    2015-03-11

    The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against

  15. A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival.

    PubMed

    Botta, C; Di Martino, M T; Ciliberto, D; Cucè, M; Correale, P; Rossi, M; Tagliaferri, P; Tassone, P

    2016-12-16

    Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment.

  16. GeneSilico protein structure prediction meta-server.

    PubMed

    Kurowski, Michal A; Bujnicki, Janusz M

    2003-07-01

    Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

  17. ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

    PubMed Central

    Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

    2015-01-01

    In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. PMID:25977299

  18. Combining Heavy Ion Radiation and Artificial MicroRNAs to Target the Homologous Recombination Repair Gene Efficiently Kills Human Tumor Cells

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zheng Zhiming; Department of Radiation Oncology, School of Medicine, Winship Cancer Institute, Emory University, Atlanta, Georgia; Wang Ping

    2013-02-01

    Purpose: Previously, we demonstrated that heavy ions kill more cells at the same dose than X-rays because DNA-clustered lesions produced by heavy ions affect nonhomologous end-joining (NHEJ) repair but not homologous recombination repair (HRR). We have also shown that our designed artificial microRNAs (amiRs) could efficiently target XRCC4 (an essential factor for NHEJ) or XRCC2 (an essential factor for HRR) and sensitize human tumor cells to X-rays. Based on these data, we were interested in testing the hypothesis that combining heavy ions and amiRs to target HRR but not NHEJ should more efficiently kill human tumor cells. Methods and Materials:more » Human tumor cell lines (U87MG, a brain tumor cell line, and A549, a lung cancer cell line) and their counterparts, overexpressed with amiR to target XRCC2, XRCC4 or both, were used in this study. Survival sensitivities were examined using a clonogenic assay after these cells were exposed to X-rays or heavy ions. In addition, these cell lines were subcutaneously injected into nude mice to form xenografts and the tumor size was compared after the tumor areas were exposed to X-rays or heavy ions. Results: Although targeting either XRCC4 (NHEJ factor) or XRCC2 (HRR factor) sensitized the human tumor cells to X-rays, in vitro and the xenograft animal model, targeting only XRCC2 but not XRCC4 sensitized the human tumor cells to heavy ions in vitro and in the xenograft animal model. Conclusions: Combining heavy ions with targeting the HRR pathway, but not the NHEJ pathway, could significantly improve the efficiency of tumor cell death.« less

  19. Gene function prediction with gene interaction networks: a context graph kernel approach.

    PubMed

    Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu

    2010-01-01

    Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.

  20. Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways.

    PubMed

    Chen, Lei; Zhang, Yu-Hang; Wang, ShaoPeng; Zhang, YunHua; Huang, Tao; Cai, Yu-Dong

    2017-01-01

    Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.

  1. Suppression of p53-inducible gene 3 is significant for glioblastoma progression and predicts poor patient prognosis.

    PubMed

    Quan, Jishu; Li, Yong; Jin, Meihua; Chen, Dunfu; Yin, Xuezhe; Jin, Ming

    2017-03-01

    Glioblastoma is the most malignant and invasive brain tumor with extremely poor prognosis. p53-inducible gene 3, a downstream molecule of the tumor suppressor p53, has been found involved in apoptosis and oxidative stress response. However, the functions of p53-inducible gene 3(PIG3) in cancer are far from clear including glioblastoma. In this study, we found that p53-inducible gene 3 expression was suppressed in glioblastoma tissues compared with normal tissues. And the expression of p53-inducible gene 3 was significantly associated with the World Health Organization grade. Patients with high p53-inducible gene 3 expression have a significantly longer median survival time (15 months) than those with low p53-inducible gene 3 expression (8 months). According to Cox regression analysis, p53-inducible gene 3 was an independent prognostic factor with multivariate hazard ratio of 0.578 (95% confidence interval, 0.352-0.947; p = 0.030) for overall survival. Additionally, gain and loss of function experiments showed that knockdown of p53-inducible gene 3 significantly increased the proliferation and invasion ability of glioblastoma cells while overexpression of p53-inducible gene 3 inhibited the proliferation and invasion ability. The results of in vivo glioblastoma models further confirmed that p53-inducible gene 3 suppression promoted glioblastoma progression. Altogether, our data suggest that high expression of p53-inducible gene 3 is significant for glioblastoma inhibition and p53-inducible gene 3 independently indicates good prognosis in patients, which might be a novel prognostic biomarker or potential therapeutic target in glioblastoma.

  2. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning.

    PubMed

    He, Zhili; Zhang, Ping; Wu, Linwei; Rocha, Andrea M; Tu, Qichao; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D; Wu, Liyou; Yang, Yunfeng; Elias, Dwayne A; Watson, David B; Adams, Michael W W; Fields, Matthew W; Alm, Eric J; Hazen, Terry C; Adams, Paul D; Arkin, Adam P; Zhou, Jizhong

    2018-02-20

    Contamination from anthropogenic activities has significantly impacted Earth's biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly ( P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. IMPORTANCE Disentangling the relationships between biodiversity and ecosystem functioning is an important but poorly understood topic in ecology. Predicting ecosystem functioning on the basis of biodiversity is even more difficult, particularly with microbial biomarkers. As an exploratory effort, this study used key microbial functional genes as biomarkers to provide predictive understanding of environmental contamination and ecosystem functioning. The results indicated that the overall functional gene richness

  3. Sensitivity analysis of gene ranking methods in phenotype prediction.

    PubMed

    deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan L; Sonis, Stephen T

    2016-12-01

    It has become clear that noise generated during the assay and analytical processes has the ability to disrupt accurate interpretation of genomic studies. Not only does such noise impact the scientific validity and costs of studies, but when assessed in the context of clinically translatable indications such as phenotype prediction, it can lead to inaccurate conclusions that could ultimately impact patients. We applied a sequence of ranking methods to damp noise associated with microarray outputs, and then tested the utility of the approach in three disease indications using publically available datasets. This study was performed in three phases. We first theoretically analyzed the effect of noise in phenotype prediction problems showing that it can be expressed as a modeling error that partially falsifies the pathways. Secondly, via synthetic modeling, we performed the sensitivity analysis for the main gene ranking methods to different types of noise. Finally, we studied the predictive accuracy of the gene lists provided by these ranking methods in synthetic data and in three different datasets related to cancer, rare and neurodegenerative diseases to better understand the translational aspects of our findings. In the case of synthetic modeling, we showed that Fisher's Ratio (FR) was the most robust gene ranking method in terms of precision for all the types of noise at different levels. Significance Analysis of Microarrays (SAM) provided slightly lower performance and the rest of the methods (fold change, entropy and maximum percentile distance) were much less precise and accurate. The predictive accuracy of the smallest set of high discriminatory probes was similar for all the methods in the case of Gaussian and Log-Gaussian noise. In the case of class assignment noise, the predictive accuracy of SAM and FR is higher. Finally, for real datasets (Chronic Lymphocytic Leukemia, Inclusion Body Myositis and Amyotrophic Lateral Sclerosis) we found that FR and SAM

  4. Probability-based collaborative filtering model for predicting gene-disease associations.

    PubMed

    Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

    2017-12-28

    Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

  5. Cancer Risks Associated with Inherited Mutations in Ovarian Cancer Susceptibility Genes Beyond BRCA1 and BRCA2

    DTIC Science & Technology

    2016-05-01

    PALB2 (FANCO),MSH2, MLH1, MSH6, PMS2 , 9 other known breast cancer genes: ATM, CHEK2, FAM175A (abraxas), FAMCM, NBN, PTEN, RECQL, TP53 and XRCC2) and...patients were enrolled with a known mutation in a gene of interest including 1 each with a mutation in RAD51D, RAD51C, PALB2, BARD1, one with PMS2 ...BRCA2, PMS2 , BLM, RAD51C and 1 with mutations in MSH6 and RAD51D. Of the 48 patients with a second cancer, most had an invasive breast cancer, but

  6. GeneSilico protein structure prediction meta-server

    PubMed Central

    Kurowski, Michal A.; Bujnicki, Janusz M.

    2003-01-01

    Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

  7. An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

    PubMed

    Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

    2018-05-14

    A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

  8. Gene expression patterns in formalin-fixed, paraffin-embedded core biopsies predict docetaxel chemosensitivity in breast cancer patients.

    PubMed

    Chang, Jenny C; Makris, Andreas; Gutierrez, M Carolina; Hilsenbeck, Susan G; Hackett, James R; Jeong, Jennie; Liu, Mei-Lan; Baker, Joffre; Clark-Langone, Kim; Baehner, Frederick L; Sexton, Krsytal; Mohsin, Syed; Gray, Tara; Alvarez, Laura; Chamness, Gary C; Osborne, C Kent; Shak, Steven

    2008-03-01

    Previously, we had identified gene expression patterns that predicted response to neoadjuvant docetaxel. Other studies have validated that a high Recurrence Score (RS) by the 21-gene RT-PCR assay is predictive of worse prognosis but better response to chemotherapy. We investigated whether tumor expression of these 21 genes and other candidate genes can predict response to docetaxel. Core biopsies from 97 patients were obtained before treatment with neoadjuvant docetaxel (4 cycles, 100 mg/m2 q3 weeks). Three 10-microm FFPE sections were submitted for quantitative RT-PCR assays of 192 genes that were selected from our previous work and the literature. Of the 97 patients, 81 (84%) had sufficient invasive cancer, 80 (82%) had sufficient RNA for QRTPCR assay, and 72 (74%) had clinical response data. Mean age was 48.5 years, and the median tumor size was 6 cm. Clinical complete responses (CR) were observed in 12 (17%), partial responses in 41 (57%), stable disease in 17 (24%), and progressive disease in 2 patients (3%). A significant relationship (P<0.05) between gene expression and CR was observed for 14 genes, including CYBA. CR was associated with lower expression of the ER gene group and higher expression of the proliferation gene group from the 21 gene assay. Of note, CR was more likely with a high RS (P=0.008). We have established molecular profiles of sensitivity to docetaxel. RT-PCR technology provides a potential platform for a predictive test of docetaxel chemosensitivity using small amounts of routinely processed material.

  9. Predicting Gene Structure Changes Resulting from Genetic Variants via Exon Definition Features.

    PubMed

    Majoros, William H; Holt, Carson; Campbell, Michael S; Ware, Doreen; Yandell, Mark; Reddy, Timothy E

    2018-04-25

    Genetic variation that disrupts gene function by altering gene splicing between individuals can substantially influence traits and disease. In those cases, accurately predicting the effects of genetic variation on splicing can be highly valuable for investigating the mechanisms underlying those traits and diseases. While methods have been developed to generate high quality computational predictions of gene structures in reference genomes, the same methods perform poorly when used to predict the potentially deleterious effects of genetic changes that alter gene splicing between individuals. Underlying that discrepancy in predictive ability are the common assumptions by reference gene finding algorithms that genes are conserved, well-formed, and produce functional proteins. We describe a probabilistic approach for predicting recent changes to gene structure that may or may not conserve function. The model is applicable to both coding and noncoding genes, and can be trained on existing gene annotations without requiring curated examples of aberrant splicing. We apply this model to the problem of predicting altered splicing patterns in the genomes of individual humans, and we demonstrate that performing gene-structure prediction without relying on conserved coding features is feasible. The model predicts an unexpected abundance of variants that create de novo splice sites, an observation supported by both simulations and empirical data from RNA-seq experiments. While these de novo splice variants are commonly misinterpreted by other tools as coding or noncoding variants of little or no effect, we find that in some cases they can have large effects on splicing activity and protein products, and we propose that they may commonly act as cryptic factors in disease. The software is available from geneprediction.org/SGRF. bmajoros@duke.edu. Supplementary information is available at Bioinformatics online.

  10. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    PubMed

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  11. Identification of HMX1 target genes: A predictive promoter model approach

    PubMed Central

    Boulling, Arnaud; Wicht, Linda

    2013-01-01

    Purpose A homozygous mutation in the H6 family homeobox 1 (HMX1) gene is responsible for a new oculoauricular defect leading to eye and auricular developmental abnormalities as well as early retinal degeneration (MIM 612109). However, the HMX1 pathway remains poorly understood, and in the first approach to better understand the pathway’s function, we sought to identify the target genes. Methods We developed a predictive promoter model (PPM) approach using a comparative transcriptomic analysis in the retina at P15 of a mouse model lacking functional Hmx1 (dmbo mouse) and its respective wild-type. This PPM was based on the hypothesis that HMX1 binding site (HMX1-BS) clusters should be more represented in promoters of HMX1 target genes. The most differentially expressed genes in the microarray experiment that contained HMX1-BS clusters were used to generate the PPM, which was then statistically validated. Finally, we developed two genome-wide target prediction methods: one that focused on conserving PPM features in human and mouse and one that was based on the co-occurrence of HMX1-BS pairs fitting the PPM, in human or in mouse, independently. Results The PPM construction revealed that sarcoglycan, gamma (35kDa dystrophin-associated glycoprotein) (Sgcg), teashirt zinc finger homeobox 2 (Tshz2), and solute carrier family 6 (neurotransmitter transporter, glycine) (Slc6a9) genes represented Hmx1 targets in the mouse retina at P15. Moreover, the genome-wide target prediction revealed that mouse genes belonging to the retinal axon guidance pathway were targeted by Hmx1. Expression of these three genes was experimentally validated using a quantitative reverse transcription PCR approach. The inhibitory activity of Hmx1 on Sgcg, as well as protein tyrosine phosphatase, receptor type, O (Ptpro) and Sema3f, two targets identified by the PPM, were validated with luciferase assay. Conclusions Gene expression analysis between wild-type and dmbo mice allowed us to develop a PPM

  12. ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

    PubMed

    Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

    2015-07-01

    In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    PubMed

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  14. Are SNP-Smoking Association Studies Needed in Controls? DNA Repair Gene Polymorphisms and Smoking Intensity

    PubMed Central

    Verde, Zoraida; Reinoso, Luis; Chicharro, Luis Miguel; Resano, Pilar; Sánchez-Hernández, Ignacio; Rodríguez González-Moro, Jose Miguel; Bandrés, Fernando

    2015-01-01

    Variations in tobacco-related cancers, incidence and prevalence reflect differences in tobacco consumption in addition to genetic factors. Besides, genes related to lung cancer risk could be related to smoking behavior. Polymorphisms altering DNA repair capacity may lead to synergistic effects with tobacco carcinogen-induced lung cancer risk. Common problems in genetic association studies, such as presence of gene-by-environment (G x E) correlation in the population, may reduce the validity of these designs. The main purpose of this study was to evaluate the independence assumption for selected SNPs and smoking behaviour in a cohort of 320 healthy Spanish smokers. We found an association between the wild type alleles of XRCC3 Thr241Met or KLC3 Lys751Gln and greater smoking intensity (OR = 12.98, 95% CI = 2.86–58.82 and OR=16.90, 95% CI=2.09-142.8; respectively). Although preliminary, the results of our study provide evidence that genetic variations in DNA-repair genes may influence both smoking habits and the development of lung cancer. Population-specific G x E studies should be carried out when genetic and environmental factors interact to cause the disease. PMID:26017978

  15. Lifespan and Stress Resistance in Drosophila with Overexpressed DNA Repair Genes

    PubMed Central

    Shaposhnikov, Mikhail; Proshkina, Ekaterina; Shilova, Lyubov; Zhavoronkov, Alex; Moskalev, Alexey

    2015-01-01

    DNA repair declines with age and correlates with longevity in many animal species. In this study, we investigated the effects of GAL4-induced overexpression of genes implicated in DNA repair on lifespan and resistance to stress factors in Drosophila melanogaster. Stress factors included hyperthermia, oxidative stress, and starvation. Overexpression was either constitutive or conditional and either ubiquitous or tissue-specific (nervous system). Overexpressed genes included those involved in recognition of DNA damage (homologs of HUS1, CHK2), nucleotide and base excision repair (homologs of XPF, XPC and AP-endonuclease-1), and repair of double-stranded DNA breaks (homologs of BRCA2, XRCC3, KU80 and WRNexo). The overexpression of different DNA repair genes led to both positive and negative effects on lifespan and stress resistance. Effects were dependent on GAL4 driver, stage of induction, sex, and role of the gene in the DNA repair process. While the constitutive/neuron-specific and conditional/ubiquitous overexpression of DNA repair genes negatively impacted lifespan and stress resistance, the constitutive/ubiquitous and conditional/neuron-specific overexpression of Hus1, mnk, mei-9, mus210, and WRNexo had beneficial effects. This study demonstrates for the first time the effects of overexpression of these DNA repair genes on both lifespan and stress resistance in D. melanogaster. PMID:26477511

  16. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    EPA Science Inventory

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  17. Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes.

    PubMed

    Lomsadze, Alexandre; Gemayel, Karl; Tang, Shiyuyun; Borodovsky, Mark

    2018-05-17

    In a conventional view of the prokaryotic genome organization, promoters precede operons and ribosome binding sites (RBSs) with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of precomputed "heuristic" models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as noncanonical RBS patterns. To assess the accuracy of GeneMarkS-2, we used genes validated by COG (Clusters of Orthologous Groups) annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of ∼5000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts. © 2018 Lomsadze et al.; Published by Cold Spring Harbor Laboratory Press.

  18. Repair of radiation-induced heat-labile sites is independent of DNA-PKcs, XRCC1 or PARP

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Stenerlöw, Bo; Karlsson, Karin H.; Radulescu, Irina

    2008-04-29

    Ionizing radiation induces a variety of different DNA lesions: in addition to the most critical DNA damage, the DSB, numerous base alterations, SSBs and other modifications of the DNA double-helix are formed. When several non-DSB lesions are clustered within a short distance along DNA, or close to a DSB, they may interfere with the repair of DSBs and affect the measurement of DSB induction and repair. We have previously shown that a substantial fraction of DSBs measured by pulsed-field gel electrophoresis (PFGE) are in fact due to heat-labile sites (HLS) within clustered lesions, thus reflecting an artifact of preparation ofmore » genomic DNA at elevated temperature. To further characterize the influence of HLS on DSB induction and repair, four human cell lines (GM5758, GM7166, M059K, U-1810) with apparently normal DSB rejoining were tested for bi-phasic rejoining after gamma irradiation. When heat-released DSBs were excluded from the measurements the fraction of fast rejoining decreased to less than 50% of the total. However, neither the half-times of the fast (t{sub 1/2} = 7-8 min) or slow (t{sub 1/2} = 2.5 h) DSB rejoining were changed significantly. At t=0 the heat-released DSBs accounted for almost 40% of the DSBs, corresponding to 10 extra DSB/cell/Gy in the initial DSB yield. These heat-released DSBs were repaired within 60-90 min in all tested cells, including M059K cells treated with wortmannin or DNA-PKcs defect M059J cells. Furthermore, cells lacking XRCC1 or Poly(ADP-ribose) polymerase-1 (PARP-1) rejoined both total DSBs and heat-released DSBs similar to normal cells. In summary, the presence of heat-labile sites have a substantial impact on DSB induction yields and DSB rejoining rates measured by pulsed-field gel electrophoresis, and HLS repair is independent of DNA-PKcs, XRCC1 and PARP.« less

  19. Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

    PubMed

    Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

    2009-02-01

    Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

  20. The role of gene-gene interaction in the prediction of criminal behavior.

    PubMed

    Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

    2014-04-01

    A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

    PubMed Central

    Peña-Castillo, Lourdes; Tasan, Murat; Myers, Chad L; Lee, Hyunju; Joshi, Trupti; Zhang, Chao; Guan, Yuanfang; Leone, Michele; Pagnani, Andrea; Kim, Wan Kyu; Krumpelman, Chase; Tian, Weidong; Obozinski, Guillaume; Qi, Yanjun; Mostafavi, Sara; Lin, Guan Ning; Berriz, Gabriel F; Gibbons, Francis D; Lanckriet, Gert; Qiu, Jian; Grant, Charles; Barutcuoglu, Zafer; Hill, David P; Warde-Farley, David; Grouios, Chris; Ray, Debajyoti; Blake, Judith A; Deng, Minghua; Jordan, Michael I; Noble, William S; Morris, Quaid; Klein-Seetharaman, Judith; Bar-Joseph, Ziv; Chen, Ting; Sun, Fengzhu; Troyanskaya, Olga G; Marcotte, Edward M; Xu, Dong; Hughes, Timothy R; Roth, Frederick P

    2008-01-01

    Background: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated. Results: In this study, a standardized collection of mouse functional genomic data was assembled; nine bioinformatics teams used this data set to independently train classifiers and generate predictions of function, as defined by Gene Ontology (GO) terms, for 21,603 mouse genes; and the best performing submissions were combined in a single set of predictions. We identified strengths and weaknesses of current functional genomic data sets and compared the performance of function prediction algorithms. This analysis inferred functions for 76% of mouse genes, including 5,000 currently uncharacterized genes. At a recall rate of 20%, a unified set of predictions averaged 41% precision, with 26% of GO terms achieving a precision better than 90%. Conclusion: We performed a systematic evaluation of diverse, independently developed computational approaches for predicting gene function from heterogeneous data sources in mammals. The results show that currently available data for mammals allows predictions with both breadth and accuracy. Importantly, many highly novel predictions emerge for the 38% of mouse genes that remain uncharacterized. PMID:18613946

  2. Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

    PubMed

    You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

    2014-01-01

    Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

  3. Prediction of gene expression in embryonic structures of Drosophila melanogaster.

    PubMed

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-07-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms.

  4. Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster

    PubMed Central

    Samsonova, Anastasia A; Niranjan, Mahesan; Russell, Steven; Brazma, Alvis

    2007-01-01

    Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms. PMID:17658945

  5. Experimental validation of predicted cancer genes using FRET

    NASA Astrophysics Data System (ADS)

    Guala, Dimitri; Bernhem, Kristoffer; Ait Blal, Hammou; Jans, Daniel; Lundberg, Emma; Brismar, Hjalmar; Sonnhammer, Erik L. L.

    2018-07-01

    Huge amounts of data are generated in genome wide experiments, designed to investigate diseases with complex genetic causes. Follow up of all potential leads produced by such experiments is currently cost prohibitive and time consuming. Gene prioritization tools alleviate these constraints by directing further experimental efforts towards the most promising candidate targets. Recently a gene prioritization tool called MaxLink was shown to outperform other widely used state-of-the-art prioritization tools in a large scale in silico benchmark. An experimental validation of predictions made by MaxLink has however been lacking. In this study we used Fluorescence Resonance Energy Transfer, an established experimental technique for detection of protein-protein interactions, to validate potential cancer genes predicted by MaxLink. Our results provide confidence in the use of MaxLink for selection of new targets in the battle with polygenic diseases.

  6. Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

    PubMed

    Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

    2017-10-03

    Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

  7. Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes

    PubMed Central

    Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

    2017-01-01

    Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274

  8. Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

    PubMed

    Zhou, Hang; Yang, Yang; Shen, Hong-Bin

    2017-03-15

    Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  9. First Generation Gene Expression Signature for Early Prediction of Late Occurring Hematological Acute Radiation Syndrome in Baboons.

    PubMed

    Port, M; Herodin, F; Valente, M; Drouet, M; Lamkowski, A; Majewski, M; Abend, M

    2016-07-01

    We implemented a two-stage study to predict late occurring hematologic acute radiation syndrome (HARS) in a baboon model based on gene expression changes measured in peripheral blood within the first two days after irradiation. Eighteen baboons were irradiated to simulate different patterns of partial-body and total-body exposure, which corresponded to an equivalent dose of 2.5 or 5 Gy. According to changes in blood cell counts the surviving baboons (n = 17) exhibited mild (H1-2, n = 4) or more severe (H2-3, n = 13) HARS. Blood samples taken before irradiation served as unexposed control (H0, n = 17). For stage I of this study, a whole genome screen (mRNA microarrays) was performed using a portion of the samples (H0, n = 5; H1-2, n = 4; H2-3, n = 5). For stage II, using the remaining samples and the more sensitive methodology, qRT-PCR, validation was performed on candidate genes that were differentially up- or down-regulated during the first two days after irradiation. Differential gene expression was defined as significant (P < 0.05) and greater than or equal to a twofold difference above a H0 classification. From approximately 20,000 genes, on average 46% appeared to be expressed. On day 1 postirradiation for H2-3, approximately 2-3 times more genes appeared up-regulated (1,418 vs. 550) or down-regulated (1,603 vs. 735) compared to H1-2. This pattern became more pronounced at day 2 while the number of differentially expressed genes decreased. The specific genes showed an enrichment of biological processes coding for immune system processes, natural killer cell activation and immune response (P = 1 × E-06 up to 9 × E-14). Based on the P values, magnitude and sustained differential gene expression over time, we selected 89 candidate genes for validation using qRT-PCR. Ultimately, 22 genes were confirmed for identification of H1-3 classifications and seven genes for identification of H2-3 classifications using qRT-PCR. For H1-3 classifications, most genes were

  10. Prediction of epigenetically regulated genes in breast cancer cell lines

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen

    the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.« less

  11. Prediction of epigenetically regulated genes in breast cancer cell lines.

    PubMed

    Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria E H; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

    2010-06-04

    panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.

  12. A network approach to predict pathogenic genes for Fusarium graminearum.

    PubMed

    Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

    2010-10-04

    Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which

  13. Experimental verification of a predicted novel microRNA located in human PIK3CA gene with a potential oncogenic function in colorectal cancer.

    PubMed

    Saleh, Ali Jason; Soltani, Bahram M; Dokanehiifard, Sadat; Medlej, Abdallah; Tavalaei, Mahmoud; Mowla, Seyed Javad

    2016-10-01

    PI3K/AKT signaling is involved in cell survival, proliferation, and migration. In this pathway, PI3Kα enzyme is composed of a regulatory protein encoded by p85 gene and a catalytic protein encoded by PIK3CA gene. Human PIK3CA locus is amplified in several cancers including lung and colorectal cancer (CRC). Therefore, microRNAs (miRNAs) that are encoded within the PIK3CA gene might have a role in cancer development. Here, we report a novel microRNA named PIK3CA-miR1 (EBI accession no. LN626315), which is located within PIK3CA gene. A DNA segment corresponding to PIK3CA-premir1 sequence was transfected in human cell lines that resulted in generation of mature exogenous PIK3CA-miR1. Following the overexpression of PIK3CA-miR1, its predicted target genes (APPL1 and TrkC) were significantly downregulated in the CRC-originated HCT116 and SW480 cell lines, detected by qRT-PCR. Then, dual luciferase assay supported the interaction of PIK3CA-miR1 with APPL1 and TrkC transcripts. Endogenous PIK3CA-miR1 expression was also detected in several cell lines (highly in HCT116 and SW480) and highly in CRC specimens. Consistently, overexpression of PIK3CA-premir1 in HCT116 and SW480 cells resulted in significant reduction of the sub-G1 cell distribution and apoptotic cell rate, as detected by flowcytometry, and resulted in increased cell proliferation, as detected by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. PIK3CA-miR1 overexpression also resulted in Wnt signaling upregulation detected by Top/Fop assay. Overall, accumulative evidences indicated the presence of a bona fide novel onco-miRNA encoded within the PIK3CA oncogene, which is highly expressed in colorectal cancer and has a survival effect in CRC-originated cells.

  14. A Third Approach to Gene Prediction Suggests Thousands of Additional Human Transcribed Regions

    PubMed Central

    Glusman, Gustavo; Qin, Shizhen; El-Gewely, M. Raafat; Siegel, Andrew F; Roach, Jared C; Hood, Leroy; Smit, Arian F. A

    2006-01-01

    The identification and characterization of the complete ensemble of genes is a main goal of deciphering the digital information stored in the human genome. Many algorithms for computational gene prediction have been described, ultimately derived from two basic concepts: (1) modeling gene structure and (2) recognizing sequence similarity. Successful hybrid methods combining these two concepts have also been developed. We present a third orthogonal approach to gene prediction, based on detecting the genomic signatures of transcription, accumulated over evolutionary time. We discuss four algorithms based on this third concept: Greens and CHOWDER, which quantify mutational strand biases caused by transcription-coupled DNA repair, and ROAST and PASTA, which are based on strand-specific selection against polyadenylation signals. We combined these algorithms into an integrated method called FEAST, which we used to predict the location and orientation of thousands of putative transcription units not overlapping known genes. Many of the newly predicted transcriptional units do not appear to code for proteins. The new algorithms are particularly apt at detecting genes with long introns and lacking sequence conservation. They therefore complement existing gene prediction methods and will help identify functional transcripts within many apparent “genomic deserts.” PMID:16543943

  15. Pharmacogenetic Study in Rectal Cancer Patients Treated With Preoperative Chemoradiotherapy: Polymorphisms in Thymidylate Synthase, Epidermal Growth Factor Receptor, GSTP1, and DNA Repair Genes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Paez, David, E-mail: dpaez@santpau.cat; Salazar, Juliana; Pare, Laia

    Purpose: Several studies have been performed to evaluate the usefulness of neoadjuvant treatment using oxaliplatin and fluoropyrimidines for locally advanced rectal cancer. However, preoperative biomarkers of outcome are lacking. We studied the polymorphisms in thymidylate synthase, epidermal growth factor receptor, glutathione S-transferase pi 1 (GSTP1), and several DNA repair genes to evaluate their usefulness as pharmacogenetic markers in a cohort of 128 rectal cancer patients treated with preoperative chemoradiotherapy. Methods and Materials: Blood samples were obtained from 128 patients with Stage II-III rectal cancer. DNA was extracted from the peripheral blood nucleated cells, and the genotypes were analyzed by polymerasemore » chain reaction amplification and automated sequencing techniques or using a 48.48 dynamic array on the BioMark system. The germline polymorphisms studied were thymidylate synthase, (VNTR/5 Prime UTR, 2R G>C single nucleotide polymorphism [SNP], 3R G>C SNP), epidermal growth factor receptor (Arg497Lys), GSTP1 (Ile105val), excision repair cross-complementing 1 (Asn118Asn, 8092C>A, 19716G>C), X-ray repair cross-complementing group 1 (XRCC1) (Arg194Trp, Arg280His, Arg399Gln), and xeroderma pigmentosum group D (Lys751Gln). The pathologic response, pathologic regression, progression-free survival, and overall survival were evaluated according to each genotype. Results: The Asterisk-Operator 3/ Asterisk-Operator 3 thymidylate synthase genotype was associated with a greater response rate (pathologic complete remission and microfoci residual tumor, 59% in Asterisk-Operator 3/ Asterisk-Operator 3 vs. 35% in Asterisk-Operator 2/ Asterisk-Operator 2 and Asterisk-Operator 2/ Asterisk-Operator 3; p = .013). For the thymidylate synthase genotype, the median progression-free survival was 103 months for the Asterisk-Operator 3/ Asterisk-Operator 3 patients and 84 months for the Asterisk-Operator 2/ Asterisk-Operator 2 and Asterisk-Operator 2

  16. Influence of Morinda citrifolia (Noni) on Expression of DNA Repair Genes in Cervical Cancer Cells.

    PubMed

    Gupta, Rakesh Kumar; Bajpai, Deepti; Singh, Neeta

    2015-01-01

    Previous studies have suggested that Morinda citrifolia (Noni) has potential to reduce cancer risk. The purpose of this study was to investigate the effect of Noni, cisplatin, and their combination on DNA repair genes in the SiHa cervical cancer cell line. SiHa cells were cultured and treated with 10% Noni, 10 μg/dl cisplatin or their combination for 24 hours. Post culturing, the cells were pelleted, RNA extracted, and processed for investigating DNA repair genes by real time PCR. The expression of nucleotide excision repair genes ERCC1, ERCC2, and ERCC4 and base excision repair gene XRCC1 was increased 4 fold, 8.9 fold, 4 fold, and 5.5 fold, respectively, on treatment with Noni as compared to untreated controls (p<0.05). In contrast, expression was found to be decreased 22 fold, 13 fold, 16 fold, and 23 fold on treatment with cisplatin (p<0.05). However, the combination of Noni and cisplatin led to an increase of 2 fold, 1.6 fold, 3 fold, 1.2 fold, respectively (p<0.05). Noni enhanced the expression of DNA repair genes by itself and in combination with cisplatin. However, high expression of DNA repair genes at mRNA level only signifies efficient DNA transcription of the above mentioned genes; further investigations are needed to evaluate the DNA repair protein expression.

  17. Prediction of gene-phenotype associations in humans, mice, and plants using phenologs.

    PubMed

    Woods, John O; Singh-Blom, Ulf Martin; Laurent, Jon M; McGary, Kriston L; Marcotte, Edward M

    2013-06-21

    Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes. In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data--from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans--establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene-phenotype associations, as for the Arabidopsis response to vernalization phenotype. We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.

  18. Gene function prediction based on the Gene Ontology hierarchical structure.

    PubMed

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  19. SGP-1: Prediction and Validation of Homologous Genes Based on Sequence Alignments

    PubMed Central

    Wiehe, Thomas; Gebauer-Jung, Steffi; Mitchell-Olds, Thomas; Guigó, Roderic

    2001-01-01

    Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors. PMID:11544202

  20. miRWalk--database: prediction of possible miRNA binding sites by "walking" the genes of three genomes.

    PubMed

    Dweep, Harsh; Sticht, Carsten; Pandey, Priyanka; Gretz, Norbert

    2011-10-01

    MicroRNAs are small, non-coding RNA molecules that can complementarily bind to the mRNA 3'-UTR region to regulate the gene expression by transcriptional repression or induction of mRNA degradation. Increasing evidence suggests a new mechanism by which miRNAs may regulate target gene expression by binding in promoter and amino acid coding regions. Most of the existing databases on miRNAs are restricted to mRNA 3'-UTR region. To address this issue, we present miRWalk, a comprehensive database on miRNAs, which hosts predicted as well as validated miRNA binding sites, information on all known genes of human, mouse and rat. All mRNAs, mitochondrial genes and 10 kb upstream flanking regions of all known genes of human, mouse and rat were analyzed by using a newly developed algorithm named 'miRWalk' as well as with eight already established programs for putative miRNA binding sites. An automated and extensive text-mining search was performed on PubMed database to extract validated information on miRNAs. Combined information was put into a MySQL database. miRWalk presents predicted and validated information on miRNA-target interaction. Such a resource enables researchers to validate new targets of miRNA not only on 3'-UTR, but also on the other regions of all known genes. The 'Validated Target module' is updated every month and the 'Predicted Target module' is updated every 6 months. miRWalk is freely available at http://mirwalk.uni-hd.de/. Copyright © 2011 Elsevier Inc. All rights reserved.

  1. A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

    PubMed

    Damasco, Christian; Lembo, Antonio; Somma, Maria Patrizia; Gatti, Maurizio; Di Cunto, Ferdinando; Provero, Paolo

    2011-02-28

    The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

  2. Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

    PubMed

    Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

    2013-01-02

    Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.

  3. Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

    PubMed

    Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

    2013-09-26

    Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function

  4. Gene expression analysis predicts insect venom anaphylaxis in indolent systemic mastocytosis.

    PubMed

    Niedoszytko, M; Bruinenberg, M; van Doormaal, J J; de Monchy, J G R; Nedoszytko, B; Koppelman, G H; Nawijn, M C; Wijmenga, C; Jassem, E; Elberink, J N G Oude

    2011-05-01

    Anaphylaxis to insect venom (Hymenoptera) is most severe in patients with mastocytosis and may even lead to death. However, not all patients with mastocytosis suffer from anaphylaxis. The aim of the study was to analyze differences in gene expression between patients with indolent systemic mastocytosis (ISM) and a history of insect venom anaphylaxis (IVA) compared to those patients without a history of anaphylaxis, and to determine the predictive use of gene expression profiling. Whole-genome gene expression analysis was performed in peripheral blood cells. Twenty-two adults with ISM were included: 12 with a history of IVA and 10 without a history of anaphylaxis of any kind. Significant differences in single gene expression corrected for multiple testing were found for 104 transcripts (P < 0.05). Gene ontology analysis revealed that the differentially expressed genes were involved in pathways responsible for the development of cancer and focal and cell adhesion suggesting that the expression of genes related to the differentiation state of cells is higher in patients with a history of anaphylaxis. Based on the gene expression profiles, a naïve Bayes prediction model was built identifying patients with IVA. In ISM, gene expression profiles are different between patients with a history of IVA and those without. These findings might reflect a more pronounced mast cells dysfunction in patients without a history of anaphylaxis. Gene expression profiling might be a useful tool to predict the risk of anaphylaxis on insect venom in patients with ISM. Prospective studies are needed to substantiate any conclusions. © 2010 John Wiley & Sons A/S.

  5. Genomic analysis of primordial dwarfism reveals novel disease genes.

    PubMed

    Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S

    2014-02-01

    Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis.

  6. Genomic analysis of primordial dwarfism reveals novel disease genes

    PubMed Central

    Shaheen, Ranad; Faqeih, Eissa; Ansari, Shinu; Abdel-Salam, Ghada; Al-Hassnan, Zuhair N.; Al-Shidi, Tarfa; Alomar, Rana; Sogaty, Sameera; Alkuraya, Fowzan S.

    2014-01-01

    Primordial dwarfism (PD) is a disease in which severely impaired fetal growth persists throughout postnatal development and results in stunted adult size. The condition is highly heterogeneous clinically, but the use of certain phenotypic aspects such as head circumference and facial appearance has proven helpful in defining clinical subgroups. In this study, we present the results of clinical and genomic characterization of 16 new patients in whom a broad definition of PD was used (e.g., 3M syndrome was included). We report a novel PD syndrome with distinct facies in two unrelated patients, each with a different homozygous truncating mutation in CRIPT. Our analysis also reveals, in addition to mutations in known PD disease genes, the first instance of biallelic truncating BRCA2 mutation causing PD with normal bone marrow analysis. In addition, we have identified a novel locus for Seckel syndrome based on a consanguineous multiplex family and identified a homozygous truncating mutation in DNA2 as the likely cause. An additional novel PD disease candidate gene XRCC4 was identified by autozygome/exome analysis, and the knockout mouse phenotype is highly compatible with PD. Thus, we add a number of novel genes to the growing list of PD-linked genes, including one which we show to be linked to a novel PD syndrome with a distinct facial appearance. PD is extremely heterogeneous genetically and clinically, and genomic tools are often required to reach a molecular diagnosis. PMID:24389050

  7. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    PubMed

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  8. Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

    PubMed

    van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

    2014-03-01

    For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

  9. Observed parenting behaviors interact with a polymorphism of the brain-derived neurotrophic factor gene to predict the emergence of oppositional defiant and callous-unemotional behaviors at age 3 years.

    PubMed

    Willoughby, Michael T; Mills-Koonce, Roger; Propper, Cathi B; Waschbusch, Daniel A

    2013-11-01

    Using the Durham Child Health and Development Study, this study (N = 171) tested whether observed parenting behaviors in infancy (6 and 12 months) and toddlerhood/preschool (24 and 36 months) interacted with a child polymorphism of the brain-derived neurotrophic factor gene to predict oppositional defiant disorder (ODD) and callous-unemotional (CU) behaviors at age 3 years. Child genotype interacted with observed harsh and intrusive (but not sensitive) parenting to predict ODD and CU behaviors. Harsh-intrusive parenting was more strongly associated with ODD and CU for children with a methionine allele of the brain-derived neurotrophic factor gene. CU behaviors were uniquely predicted by harsh-intrusive parenting in infancy, whereas ODD behaviors were predicted by harsh-intrusive parenting in both infancy and toddlerhood/preschool. The results are discussed from the perspective of the contributions of caregiving behaviors as contributing to distinct aspects of early onset disruptive behavior.

  10. Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

    NASA Astrophysics Data System (ADS)

    Basyuni, M.; Wati, R.

    2018-03-01

    The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

  11. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds

  12. Co-acting gene networks predict TRAIL responsiveness of tumour cells with high accuracy.

    PubMed

    O'Reilly, Paul; Ortutay, Csaba; Gernon, Grainne; O'Connell, Enda; Seoighe, Cathal; Boyce, Susan; Serrano, Luis; Szegezdi, Eva

    2014-12-19

    importance of functional interactions in predicting the biological response. The advantage of co-acting gene clusters is that this analysis does not depend on differential expression and is able to incorporate direct- and indirect gene interactions as well as tissue- and cell-specific characteristics. This approach (1) identified a descriptor of TRAIL sensitivity which performs significantly better as a predictor of TRAIL sensitivity than any previously reported gene signatures, (2) identified potential novel regulators of TRAIL-responsiveness and (3) provided a systematic view highlighting fundamental differences between the molecular wiring of sensitive and resistant cell types.

  13. The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity

    PubMed Central

    Wang, Quanli; Halvorsen, Matt; Han, Yujun; Weir, William H.; Allen, Andrew S.; Goldstein, David B.

    2015-01-01

    Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene’s proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene’s regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen’s Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance

  14. Biological interpretation of genome-wide association studies using predicted gene functions.

    PubMed

    Pers, Tune H; Karjalainen, Juha M; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R; Yang, Jian; Lui, Julian C; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S N; Hirschhorn, Joel N; Franke, Lude

    2015-01-19

    The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

  15. Traditional Chinese Medicine Curcumin Sensitizes Human Colon Cancer to Radiation by Altering the Expression of DNA Repair-related Genes.

    PubMed

    Yang, Guangen; Qiu, Jianming; Wang, Dong; Tao, Yong; Song, Yihuan; Wang, Hongtao; Tang, Juping; Wang, Xing; Sun, Y U; Yang, Zhijian; Hoffman, Robert M

    2018-01-01

    The aim of the present study was to investigate the radio-sensitizing efficacy of curcumin, a traditional Chinese medicine (TCM) on colon cancer cells in vitro and in vivo. Human colon cancer HT-29 cells were treated with curcumin (2.5 μM), irradiation (10 Gy) and the combination of irradiation and curcumin. Cell proliferation was assessed using the MTT assay. Apoptotic cells were detected by Annexin V-PE/7-AAD analysis. PCR was performed to determine differential-expression profiling of 95 DNA-repair genes in irradiated cells and cells treated with both irradiation and curcumin. Differentially-expressed genes were confirmed by Western blotting. In vivo radio-sensitizing efficacy of curcumin was assessed in a xenograft mouse model of HT-29 colon cancer. Curcumin was administrated daily by intraperitoneal injection at 20 mg/kg/dose. Mice received irradiation (10 Gy) twice weekly. Apoptosis of the cancer cells following treatment was determined by TUNEL staining. Irradiation induced proliferation inhibition and apoptosis of HT-29 cells in vitro. Concurrent curcumin treatment sensitized the HT-29 tumor to irradiation (p<0.01). DNA repair-related genes CCNH and XRCC5 were upregulated and LIG4 and PNKP downregulated by the combination of curcumin and irradiation compared with irradiation alone (p<0.05). Combined treatment of curcumin and irradiation resulted in a significantly greater tumor-growth inhibition and apoptosis compared to irradiation treatment alone (p<0.01). Curcumin sensitizes human colon cancer in vitro and in vivo to radiation. Downregulation of LIG4 and PNKP and upregulation of XRCC5 and CCNH DNA-repair-related genes were involved in the radio-sensitizing efficacy of curcumin in colon cancer. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  16. EGFR Gene Amplification and KRAS Mutation Predict Response to Combination Targeted Therapy in Metastatic Colorectal Cancer.

    PubMed

    Khan, Sajid A; Zeng, Zhaoshi; Shia, Jinru; Paty, Philip B

    2017-07-01

    Genetic variability in KRAS and EGFR predicts response to cetuximab in irinotecan refractory colorectal cancer. Whether these markers or others remain predictive in combination biologic therapies including bevacizumab is unknown. We identified predictive biomarkers from patients with irinotecan refractory metastatic colorectal cancer treated with cetuximab plus bevacizumab. Patients who received cetuximab plus bevacizumab for irinotecan refractory colorectal cancer in either of two Phase II trials conducted were identified. Tumor tissue was available for 33 patients. Genomic DNA was extracted and used for mutational analysis of KRAS, BRAF, and p53 genes. Fluorescence in situ hybridization was performed to assess EGFR copy number. The status of single genes and various combinations were tested for association with response. Seven of 33 patients responded to treatment. KRAS mutations were found in 14/33 cases, and 0 responded to treatment (p = 0.01). EGFR gene amplification was seen in 3/33 of tumors and in every case was associated with response to treatment (p < 0.001). TP53 and BRAF mutations were found in 18/33 and 0/33 tumors, respectively, and there were no associations with response to either gene. EGFR gene amplification and KRAS mutations are predictive markers for patients receiving combination biologic therapy of cetuximab plus bevacizumab for metastatic colorectal cancer. One marker or the other is present in the tumor of half of all patients allowing treatment response to be predicted with a high degree of certainty. The role for molecular markers in combination biologic therapy seems promising.

  17. Biological interpretation of genome-wide association studies using predicted gene functions

    PubMed Central

    Pers, Tune H.; Karjalainen, Juha M.; Chan, Yingleong; Westra, Harm-Jan; Wood, Andrew R.; Yang, Jian; Lui, Julian C.; Vedantam, Sailaja; Gustafsson, Stefan; Esko, Tonu; Frayling, Tim; Speliotes, Elizabeth K.; Boehnke, Michael; Raychaudhuri, Soumya; Fehrmann, Rudolf S.N.; Hirschhorn, Joel N.; Franke, Lude

    2015-01-01

    The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes. PMID:25597830

  18. Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

    PubMed

    Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

    2017-09-25

    The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

  19. Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

    PubMed

    Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

    2013-12-01

    To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Gene-Specific DNA Methylation Changes Predict Remission in Patients with ANCA-Associated Vasculitis

    PubMed Central

    Jones, Britta E.; Yang, Jiajin; Muthigi, Akhil; Hogan, Susan L.; Hu, Yichun; Starmer, Joshua; Henderson, Candace D.; Poulton, Caroline J.; Brant, Elizabeth J.; Pendergraft, William F.; Jennette, J. Charles; Falk, Ronald J.

    2017-01-01

    ANCA-associated vasculitis is an autoimmune condition characterized by vascular inflammation and organ damage. Pharmacologically induced remission of this condition is complicated by relapses. Potential triggers of relapse are immunologic challenges and environmental insults, both of which associate with changes in epigenetic silencing modifications. Altered histone modifications implicated in gene silencing associate with aberrant autoantigen expression. To establish a link between DNA methylation, a model epigenetic gene silencing modification, and autoantigen gene expression and disease status in ANCA-associated vasculitis, we measured gene-specific DNA methylation of the autoantigen genes myeloperoxidase (MPO) and proteinase 3 (PRTN3) in leukocytes of patients with ANCA-associated vasculitis observed longitudinally (n=82) and of healthy controls (n=32). Patients with active disease demonstrated hypomethylation of MPO and PRTN3 and increased expression of the autoantigens; in remission, DNA methylation generally increased. Longitudinal analysis revealed that patients with ANCA-associated vasculitis could be divided into two groups, on the basis of whether DNA methylation increased or decreased from active disease to remission. In patients with increased DNA methylation, MPO and PRTN3 expression correlated with DNA methylation. Kaplan–Meier estimate of relapse revealed patients with increased DNA methylation at the PRTN3 promoter had a significantly greater probability of a relapse-free period (P<0.001), independent of ANCA serotype. Patients with decreased DNA methylation at the PRTN3 promoter had a greater risk of relapse (hazard ratio, 4.55; 95% confidence interval, 2.09 to 9.91). Thus, changes in the DNA methylation status of the PRTN3 promoter may predict the likelihood of stable remission and explain autoantigen gene regulation. PMID:27821628

  1. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    He, Zhili; Zhang, Ping; Wu, Linwei

    Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

  2. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

    PubMed Central

    Zhang, Ping; Wu, Linwei; Rocha, Andrea M.; Shi, Zhou; Wu, Bo; Qin, Yujia; Wang, Jianjun; Yan, Qingyun; Curtis, Daniel; Ning, Daliang; Van Nostrand, Joy D.; Wu, Liyou; Watson, David B.; Adams, Michael W. W.; Alm, Eric J.; Adams, Paul D.; Arkin, Adam P.

    2018-01-01

    ABSTRACT Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminants would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. This study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning. PMID:29463661

  3. Microbial Functional Gene Diversity Predicts Groundwater Contamination and Ecosystem Functioning

    DOE PAGES

    He, Zhili; Zhang, Ping; Wu, Linwei; ...

    2018-02-20

    Contamination from anthropogenic activities has significantly impacted Earth’s biosphere. However, knowledge about how environmental contamination affects the biodiversity of groundwater microbiomes and ecosystem functioning remains very limited. Here, we used a comprehensive functional gene array to analyze groundwater microbiomes from 69 wells at the Oak Ridge Field Research Center (Oak Ridge, TN), representing a wide pH range and uranium, nitrate, and other contaminants. We hypothesized that the functional diversity of groundwater microbiomes would decrease as environmental contamination (e.g., uranium or nitrate) increased or at low or high pH, while some specific populations capable of utilizing or resistant to those contaminantsmore » would increase, and thus, such key microbial functional genes and/or populations could be used to predict groundwater contamination and ecosystem functioning. Our results indicated that functional richness/diversity decreased as uranium (but not nitrate) increased in groundwater. In addition, about 5.9% of specific key functional populations targeted by a comprehensive functional gene array (GeoChip 5) increased significantly (P < 0.05) as uranium or nitrate increased, and their changes could be used to successfully predict uranium and nitrate contamination and ecosystem functioning. Here, this study indicates great potential for using microbial functional genes to predict environmental contamination and ecosystem functioning.« less

  4. Phylogenomic detection and functional prediction of genes potentially important for plant meiosis.

    PubMed

    Zhang, Luoyan; Kong, Hongzhi; Ma, Hong; Yang, Ji

    2018-02-15

    Meiosis is a specialized type of cell division necessary for sexual reproduction in eukaryotes. A better understanding of the cytological procedures of meiosis has been achieved by comprehensive cytogenetic studies in plants, while the genetic mechanisms regulating meiotic progression remain incompletely understood. The increasing accumulation of complete genome sequences and large-scale gene expression datasets has provided a powerful resource for phylogenomic inference and unsupervised identification of genes involved in plant meiosis. By integrating sequence homology and expression data, 164, 131, 124 and 162 genes potentially important for meiosis were identified in the genomes of Arabidopsis thaliana, Oryza sativa, Selaginella moellendorffii and Pogonatum aloides, respectively. The predicted genes were assigned to 45 meiotic GO terms, and their functions were related to different processes occurring during meiosis in various organisms. Most of the predicted meiotic genes underwent lineage-specific duplication events during plant evolution, with about 30% of the predicted genes retaining only a single copy in higher plant genomes. The results of this study provided clues to design experiments for better functional characterization of meiotic genes in plants, promoting the phylogenomic approach to the evolutionary dynamics of the plant meiotic machineries. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

    PubMed

    Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

    Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

  6. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

    PubMed Central

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

    2016-01-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

  7. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

    PubMed

    Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

    2017-11-24

    Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

  8. Clustering gene expression data based on predicted differential effects of GV interaction.

    PubMed

    Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

    2005-02-01

    Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

  9. Well-characterized sequence features of eukaryote genomes and implications for ab initio gene prediction.

    PubMed

    Huang, Ying; Chen, Shi-Yi; Deng, Feilong

    2016-01-01

    In silico analysis of DNA sequences is an important area of computational biology in the post-genomic era. Over the past two decades, computational approaches for ab initio prediction of gene structure from genome sequence alone have largely facilitated our understanding on a variety of biological questions. Although the computational prediction of protein-coding genes has already been well-established, we are also facing challenges to robustly find the non-coding RNA genes, such as miRNA and lncRNA. Two main aspects of ab initio gene prediction include the computed values for describing sequence features and used algorithm for training the discriminant function, and by which different combinations are employed into various bioinformatic tools. Herein, we briefly review these well-characterized sequence features in eukaryote genomes and applications to ab initio gene prediction. The main purpose of this article is to provide an overview to beginners who aim to develop the related bioinformatic tools.

  10. Cell-specific prediction and application of drug-induced gene expression profiles.

    PubMed

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

    2018-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

  11. Cell-specific prediction and application of drug-induced gene expression profiles

    PubMed Central

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

    2017-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

  12. Mutations in a novel gene with transmembrane domains underlie Usher syndrome type 3.

    PubMed

    Joensuu, T; Hämäläinen, R; Yuan, B; Johnson, C; Tegelberg, S; Gasparini, P; Zelante, L; Pirvola, U; Pakarinen, L; Lehesjoki, A E; de la Chapelle, A; Sankila, E M

    2001-10-01

    Usher syndrome type 3 (USH3) is an autosomal recessive disorder characterized by progressive hearing loss, severe retinal degeneration, and variably present vestibular dysfunction, assigned to 3q21-q25. Here, we report on the positional cloning of the USH3 gene. By haplotype and linkage-disequilibrium analyses in Finnish carriers of a putative founder mutation, the critical region was narrowed to 250 kb, of which we sequenced, assembled, and annotated 207 kb. Two novel genes-NOPAR and UCRP-and one previously identified gene-H963-were excluded as USH3, on the basis of mutational analysis. USH3, the candidate gene that we identified, encodes a 120-amino-acid protein. Fifty-two Finnish patients were homozygous for a termination mutation, Y100X; patients in two Finnish families were compound heterozygous for Y100X and for a missense mutation, M44K, whereas patients in an Italian family were homozygous for a 3-bp deletion leading to an amino acid deletion and substitution. USH3 has two predicted transmembrane domains, and it shows no homology to known genes. As revealed by northern blotting and reverse-transcriptase PCR, it is expressed in many tissues, including the retina.

  13. Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

    PubMed

    Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

    2014-11-01

    COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  14. Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

    PubMed Central

    Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

    2007-01-01

    Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (<4 kgs weight loss). We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box) approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%±8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier) improved prediction accuracy to 80.9%±2.2%. Conclusion Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

  15. Four-gene Pan-African Blood Signature Predicts Progression to Tuberculosis.

    PubMed

    Suliman, Sara; Thompson, Ethan; Sutherland, Jayne; Weiner Rd, January; Ota, Martin O C; Shankar, Smitha; Penn-Nicholson, Adam; Thiel, Bonnie; Erasmus, Mzwandile; Maertzdorf, Jeroen; Duffy, Fergal J; Hill, Philip C; Hughes, E Jane; Stanley, Kim; Downing, Katrina; Fisher, Michelle L; Valvo, Joe; Parida, Shreemanta K; van der Spuy, Gian; Tromp, Gerard; Adetifa, Ifedayo M O; Donkor, Simon; Howe, Rawleigh; Mayanja-Kizza, Harriet; Boom, W Henry; Dockrell, Hazel; Ottenhoff, Tom H M; Hatherill, Mark; Aderem, Alan; Hanekom, Willem A; Scriba, Thomas J; Kaufmann, Stefan He; Zak, Daniel E; Walzl, Gerhard

    2018-04-06

    Contacts of tuberculosis (TB) patients constitute an important target population for preventative measures as they are at high risk of infection with Mycobacterium tuberculosis and progression to disease. We investigated biosignatures with predictive ability for incident tuberculosis. In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, polymerase chain reaction (PCR) and the Pair Ratio algorithm in a training/test set approach. Overall, 79 progressors, who developed tuberculosis between 3 and 24 months following exposure, and 328 matched non-progressors, who remained healthy during 24 months of follow-up, were investigated. A four-transcript signature (RISK4), derived from samples in a South African and Gambian training set, predicted progression up to two years before onset of disease in blinded test set samples from South Africa, The Gambia and Ethiopia with little population-associated variability and also validated on an external cohort of South African adolescents with latent Mycobacterium tuberculosis infection. By contrast, published diagnostic or prognostic tuberculosis signatures predicted on samples from some but not all 3 countries, indicating site-specific variability. Post-hoc meta-analysis identified a single gene pair, C1QC/TRAV27, that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events. Collectively, we developed a simple whole blood-based PCR test to predict tuberculosis in household contacts from diverse African populations, with potential for implementation in national TB contact investigation programs.

  16. Predicting nuclear gene coalescence from mitochondrial data: the three-times rule.

    PubMed

    Palumbi, S R; Cipriano, F; Hare, M P

    2001-05-01

    Coalescence theory predicts when genetic drift at nuclear loci will result in fixation of sequence differences to produce monophyletic gene trees. However, the theory is difficult to apply to particular taxa because it hinges on genetically effective population size, which is generally unknown. Neutral theory also predicts that evolution of monophyly will be four times slower in nuclear than in mitochondrial genes primarily because genetic drift is slower at nuclear loci. Variation in mitochondrial DNA (mtDNA) within and between species has been studied extensively, but can these mtDNA data be used to predict coalescence in nuclear loci? Comparison of neutral theories of coalescence of mitochondrial and nuclear loci suggests a simple rule of thumb. The "three-times rule" states that, on average, most nuclear loci will be monophyletic when the branch length leading to the mtDNA sequences of a species is three times longer than the average mtDNA sequence diversity observed within that species. A test using mitochondrial and nuclear intron data from seven species of whales and dolphins suggests general agreement with predictions of the three-times rule. We define the coalescence ratio as the mitochondrial branch length for a species divided by intraspecific mtDNA diversity. We show that species with high coalescence ratios show nuclear monophyly, whereas species with low ratios have polyphyletic nuclear gene trees. As expected, species with intermediate coalescence ratios show a variety of patterns. Especially at very high or low coalescence ratios, the three-times rule predicts nuclear gene patterns that can help detect the action of selection. The three-times rule may be useful as an empirical benchmark for evaluating evolutionary processes occurring at multiple loci.

  17. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

    PubMed

    Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

    2010-06-30

    Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

  18. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

    PubMed Central

    2010-01-01

    Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast

  19. PreCisIon: PREdiction of CIS-regulatory elements improved by gene's positION.

    PubMed

    Elati, Mohamed; Nicolle, Rémy; Junier, Ivan; Fernández, David; Fekih, Rim; Font, Julio; Képès, François

    2013-02-01

    Conventional approaches to predict transcriptional regulatory interactions usually rely on the definition of a shared motif sequence on the target genes of a transcription factor (TF). These efforts have been frustrated by the limited availability and accuracy of TF binding site motifs, usually represented as position-specific scoring matrices, which may match large numbers of sites and produce an unreliable list of target genes. To improve the prediction of binding sites, we propose to additionally use the unrelated knowledge of the genome layout. Indeed, it has been shown that co-regulated genes tend to be either neighbors or periodically spaced along the whole chromosome. This study demonstrates that respective gene positioning carries significant information. This novel type of information is combined with traditional sequence information by a machine learning algorithm called PreCisIon. To optimize this combination, PreCisIon builds a strong gene target classifier by adaptively combining weak classifiers based on either local binding sequence or global gene position. This strategy generically paves the way to the optimized incorporation of any future advances in gene target prediction based on local sequence, genome layout or on novel criteria. With the current state of the art, PreCisIon consistently improves methods based on sequence information only. This is shown by implementing a cross-validation analysis of the 20 major TFs from two phylogenetically remote model organisms. For Bacillus subtilis and Escherichia coli, respectively, PreCisIon achieves on average an area under the receiver operating characteristic curve of 70 and 60%, a sensitivity of 80 and 70% and a specificity of 60 and 56%. The newly predicted gene targets are demonstrated to be functionally consistent with previously known targets, as assessed by analysis of Gene Ontology enrichment or of the relevant literature and databases.

  20. Prediction of protein subcellular localization by weighted gene ontology terms.

    PubMed

    Chi, Sang-Mun

    2010-08-27

    We develop a new weighting approach of gene ontology (GO) terms for predicting protein subcellular localization. The weights of individual GO terms, corresponding to their contribution to the prediction algorithm, are determined by the term-weighting methods used in text categorization. We evaluate several term-weighting methods, which are based on inverse document frequency, information gain, gain ratio, odds ratio, and chi-square and its variants. Additionally, we propose a new term-weighting method based on the logarithmic transformation of chi-square. The proposed term-weighting method performs better than other term-weighting methods, and also outperforms state-of-the-art subcellular prediction methods. Our proposed method achieves 98.1%, 99.3%, 98.1%, 98.1%, and 95.9% overall accuracies for the animal BaCelLo independent dataset (IDS), fungal BaCelLo IDS, animal Höglund IDS, fungal Höglund IDS, and PLOC dataset, respectively. Furthermore, the close correlation between high-weighted GO terms and subcellular localizations suggests that our proposed method appropriately weights GO terms according to their relevance to the localizations. Copyright 2010 Elsevier Inc. All rights reserved.

  1. Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.

    PubMed

    Bartsch, Georg; Mitra, Anirban P; Mitra, Sheetal A; Almal, Arpit A; Steven, Kenneth E; Skinner, Donald G; Fry, David W; Lenehan, Peter F; Worzel, William P; Cote, Richard J

    2016-02-01

    Due to the high recurrence risk of nonmuscle invasive urothelial carcinoma it is crucial to distinguish patients at high risk from those with indolent disease. In this study we used a machine learning algorithm to identify the genes in patients with nonmuscle invasive urothelial carcinoma at initial presentation that were most predictive of recurrence. We used the genes in a molecular signature to predict recurrence risk within 5 years after transurethral resection of bladder tumor. Whole genome profiling was performed on 112 frozen nonmuscle invasive urothelial carcinoma specimens obtained at first presentation on Human WG-6 BeadChips (Illumina®). A genetic programming algorithm was applied to evolve classifier mathematical models for outcome prediction. Cross-validation based resampling and gene use frequencies were used to identify the most prognostic genes, which were combined into rules used in a voting algorithm to predict the sample target class. Key genes were validated by quantitative polymerase chain reaction. The classifier set included 21 genes that predicted recurrence. Quantitative polymerase chain reaction was done for these genes in a subset of 100 patients. A 5-gene combined rule incorporating a voting algorithm yielded 77% sensitivity and 85% specificity to predict recurrence in the training set, and 69% and 62%, respectively, in the test set. A singular 3-gene rule was constructed that predicted recurrence with 80% sensitivity and 90% specificity in the training set, and 71% and 67%, respectively, in the test set. Using primary nonmuscle invasive urothelial carcinoma from initial occurrences genetic programming identified transcripts in reproducible fashion, which were predictive of recurrence. These findings could potentially impact nonmuscle invasive urothelial carcinoma management. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  2. Prediction of target genes for miR-140-5p in pulmonary arterial hypertension using bioinformatics methods.

    PubMed

    Li, Fangwei; Shi, Wenhua; Wan, Yixin; Wang, Qingting; Feng, Wei; Yan, Xin; Wang, Jian; Chai, Limin; Zhang, Qianqian; Li, Manxiang

    2017-12-01

    The expression of microRNA (miR)-140-5p is known to be reduced in both pulmonary arterial hypertension (PAH) patients and monocrotaline-induced PAH models in rat. Identification of target genes for miR-140-5p with bioinformatics analysis may reveal new pathways and connections in PAH. This study aimed to explore downstream target genes and relevant signaling pathways regulated by miR-140-5p to provide theoretical evidences for further researches on role of miR-140-5p in PAH. Multiple downstream target genes and upstream transcription factors (TFs) of miR-140-5p were predicted in the analysis. Gene ontology (GO) enrichment analysis indicated that downstream target genes of miR-140-5p were enriched in many biological processes, such as biological regulation, signal transduction, response to chemical stimulus, stem cell proliferation, cell surface receptor signaling pathways. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis found that downstream target genes were mainly located in Notch, TGF-beta, PI3K/Akt, and Hippo signaling pathway. According to TF-miRNA-mRNA network, the important downstream target genes of miR-140-5p were PPI, TGF-betaR1, smad4, JAG1, ADAM10, FGF9, PDGFRA, VEGFA, LAMC1, TLR4, and CREB. After thoroughly reviewing published literature, we found that 23 target genes and seven signaling pathways were truly inhibited by miR-140-5p in various tissues or cells; most of these verified targets were in accordance with our present prediction. Other predicted targets still need further verification in vivo and in vitro .

  3. Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

    PubMed Central

    2013-01-01

    Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

  4. Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

    PubMed

    Patel, Nihir; Wang, Jason T L

    2015-10-01

    Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

  5. Ion channel gene expression predicts survival in glioma patients

    PubMed Central

    Wang, Rong; Gurguis, Christopher I.; Gu, Wanjun; Ko, Eun A; Lim, Inja; Bang, Hyoweon; Zhou, Tong; Ko, Jae-Hong

    2015-01-01

    Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients. PMID:26235283

  6. GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

    PubMed

    Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

    2018-04-24

    Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

  7. The role of ITPA and ribavirin transporter genes polymorphisms in prediction of ribavirin-induced anaemia in chronic hepatitis C Egyptian patients.

    PubMed

    El Desoky, Ehab S; Abdelhafez, Alaa T; Cusato, Jessica; Kamel, Sherif I; Hussein, Abeer Mr; De Nicolo, Amedeo; Di Perri, Giovanni; D'Avolio, Antonio

    2017-09-01

    Few data are available concerning the roles of polymorphisms of inosine triphosphatase (ITPA) gene and ribavirin (RBV) transporter genes in the prediction of RBV-induced anaemia among Egyptians with chronic hepatitis C (CHC). Genotyping of three ITPA gene variants and two variants of RBV transporter genes has been performed in 123 patients under pegylated interferon-α/ribavirin treatment. The baseline haemoglobin and ITPA rs1127354 CA/AA have been found as predictors of anaemia at 4, 8 and 12 weeks of RBV therapy. In addition, ITPA rs7270101 AC/CC and age predicted anaemia after 12 weeks of therapy. In conclusion, the ITPA variant rs1127354C>A significantly predict RBV-induced anaemia during the first 3 months of treatment and it is recommended to be assessed before RBV administration. © 2017 John Wiley & Sons Australia, Ltd.

  8. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

    PubMed

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

    2016-05-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

  9. Effective gene prediction by high resolution frequency estimator based on least-norm solution technique

    PubMed Central

    2014-01-01

    Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method. PMID:24386895

  10. Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

    PubMed Central

    Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

    2009-01-01

    Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

  11. An Intrinsically Disordered APLF Links Ku, DNA-PKcs, and XRCC4-DNA Ligase IV in an Extended Flexible Non-homologous End Joining Complex

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hammel, Michal; Yu, Yaping; Radhakrishnan, Sarvan K.

    DNA double-strand break (DSB) repair by non-homologous end joining (NHEJ) in human cells is initiated by Ku heterodimer binding to a DSB, followed by recruitment of core NHEJ factors including DNA-dependent protein kinase catalytic subunit (DNA-PKcs), XRCC4-like factor (XLF), and XRCC4 (X4)-DNA ligase IV (L4). Ku also interacts with accessory factors such as aprataxin and polynucleotide kinase/phosphatase-like factor (APLF). But, how these factors interact to tether, process, and ligate DSB ends while allowing regulation and chromatin interactions remains enigmatic. Here, small angle X-ray scattering (SAXS) and mutational analyses show APLF is largely an intrinsically disordered protein that binds Ku, Ku/DNA-PKcsmore » (DNA-PK), and X4L4 within an extended flexible NHEJ core complex. X4L4 assembles with Ku heterodimers linked to DNA-PKcs via flexible Ku80 C-terminal regions (Ku80CTR) in a complex stabilized through APLF interactions with Ku, DNA-PK, and X4L4. Our collective results unveil the solution architecture of the six-protein complex and suggest cooperative assembly of an extended flexible NHEJ core complex that supports APLF accessibility while possibly providing flexible attachment of the core complex to chromatin. The resulting dynamic tethering furthermore, provides geometric access of L4 catalytic domains to the DNA ends during ligation and of DNA-PKcs for targeted phosphorylation of other NHEJ proteins as well as trans-phosphorylation of DNA-PKcs on the opposing DSB without disrupting the core ligation complex. Overall the results shed light on evolutionary conservation of Ku, X4, and L4 activities, while explaining the observation that Ku80CTR and DNA-PKcs only occur in a subset of higher eukaryotes.« less

  12. An Intrinsically Disordered APLF Links Ku, DNA-PKcs, and XRCC4-DNA Ligase IV in an Extended Flexible Non-homologous End Joining Complex

    DOE PAGES

    Hammel, Michal; Yu, Yaping; Radhakrishnan, Sarvan K.; ...

    2016-11-14

    DNA double-strand break (DSB) repair by non-homologous end joining (NHEJ) in human cells is initiated by Ku heterodimer binding to a DSB, followed by recruitment of core NHEJ factors including DNA-dependent protein kinase catalytic subunit (DNA-PKcs), XRCC4-like factor (XLF), and XRCC4 (X4)-DNA ligase IV (L4). Ku also interacts with accessory factors such as aprataxin and polynucleotide kinase/phosphatase-like factor (APLF). But, how these factors interact to tether, process, and ligate DSB ends while allowing regulation and chromatin interactions remains enigmatic. Here, small angle X-ray scattering (SAXS) and mutational analyses show APLF is largely an intrinsically disordered protein that binds Ku, Ku/DNA-PKcsmore » (DNA-PK), and X4L4 within an extended flexible NHEJ core complex. X4L4 assembles with Ku heterodimers linked to DNA-PKcs via flexible Ku80 C-terminal regions (Ku80CTR) in a complex stabilized through APLF interactions with Ku, DNA-PK, and X4L4. Our collective results unveil the solution architecture of the six-protein complex and suggest cooperative assembly of an extended flexible NHEJ core complex that supports APLF accessibility while possibly providing flexible attachment of the core complex to chromatin. The resulting dynamic tethering furthermore, provides geometric access of L4 catalytic domains to the DNA ends during ligation and of DNA-PKcs for targeted phosphorylation of other NHEJ proteins as well as trans-phosphorylation of DNA-PKcs on the opposing DSB without disrupting the core ligation complex. Overall the results shed light on evolutionary conservation of Ku, X4, and L4 activities, while explaining the observation that Ku80CTR and DNA-PKcs only occur in a subset of higher eukaryotes.« less

  13. Identification and Characterization of Switchgrass Histone H3 and CENH3 Genes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Miao, Jiamin; Frazier, Taylor; Huang, Linkai

    Switchgrass is one of the most promising energy crops and only recently has been employed for biofuel production. The draft genome of switchgrass was recently released; however, relatively few switchgrass genes have been functionally characterized. CENH3, the major histone protein found in centromeres, along with canonical H3 and other histones, plays an important role in maintaining genome stability and integrity. Despite their importance, the histone H3 genes of switchgrass have remained largely uninvestigated. In this study, we identified 17 putative switchgrass histone H3 genes in silico. Of these genes, 15 showed strong homology to histone H3 genes including six H3.1more » genes, three H3.3 genes, four H3.3-like genes and two H3.1-like genes. The remaining two genes were found to be homologous to CENH3. RNA-seq data derived from lowland cultivar Alamo and upland cultivar Dacotah allowed us to identify SNPs in the histone H3 genes and compare their differential gene expression. Interestingly, we also found that overexpression of switchgrass histone H3 and CENH3 genes in N. benthamiana could trigger cell death of the transformed plant cells. Localization and deletion analyses of the histone H3 and CENH3 genes revealed that nuclear localization of the N-terminal tail is essential and sufficient for triggering the cell death phenotype. Lastly, our results deliver insight into the mechanisms underlying the histone-triggered cell death phenotype and provide a foundation for further studying the variations of the histone H3 and CENH3 genes in switchgrass.« less

  14. Identification and Characterization of Switchgrass Histone H3 and CENH3 Genes

    DOE PAGES

    Miao, Jiamin; Frazier, Taylor; Huang, Linkai; ...

    2016-07-12

    Switchgrass is one of the most promising energy crops and only recently has been employed for biofuel production. The draft genome of switchgrass was recently released; however, relatively few switchgrass genes have been functionally characterized. CENH3, the major histone protein found in centromeres, along with canonical H3 and other histones, plays an important role in maintaining genome stability and integrity. Despite their importance, the histone H3 genes of switchgrass have remained largely uninvestigated. In this study, we identified 17 putative switchgrass histone H3 genes in silico. Of these genes, 15 showed strong homology to histone H3 genes including six H3.1more » genes, three H3.3 genes, four H3.3-like genes and two H3.1-like genes. The remaining two genes were found to be homologous to CENH3. RNA-seq data derived from lowland cultivar Alamo and upland cultivar Dacotah allowed us to identify SNPs in the histone H3 genes and compare their differential gene expression. Interestingly, we also found that overexpression of switchgrass histone H3 and CENH3 genes in N. benthamiana could trigger cell death of the transformed plant cells. Localization and deletion analyses of the histone H3 and CENH3 genes revealed that nuclear localization of the N-terminal tail is essential and sufficient for triggering the cell death phenotype. Lastly, our results deliver insight into the mechanisms underlying the histone-triggered cell death phenotype and provide a foundation for further studying the variations of the histone H3 and CENH3 genes in switchgrass.« less

  15. Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

    PubMed

    Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

    2016-02-19

    Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

  16. Predicting Hydrologic Function With Aquatic Gene Fragments

    NASA Astrophysics Data System (ADS)

    Good, S. P.; URycki, D. R.; Crump, B. C.

    2018-03-01

    Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

  17. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling.

    PubMed

    Klein, Eric A; Cooperberg, Matthew R; Magi-Galluzzi, Cristina; Simko, Jeffry P; Falzarano, Sara M; Maddala, Tara; Chan, June M; Li, Jianbo; Cowan, Janet E; Tsiatis, Athanasios C; Cherbavaz, Diana B; Pelham, Robert J; Tenggara-Hunter, Imelda; Baehner, Frederick L; Knezevic, Dejan; Febbo, Phillip G; Shak, Steven; Kattan, Michael W; Lee, Mark; Carroll, Peter R

    2014-09-01

    Prostate tumor heterogeneity and biopsy undersampling pose challenges to accurate, individualized risk assessment for men with localized disease. To identify and validate a biopsy-based gene expression signature that predicts clinical recurrence, prostate cancer (PCa) death, and adverse pathology. Gene expression was quantified by reverse transcription-polymerase chain reaction for three studies-a discovery prostatectomy study (n=441), a biopsy study (n=167), and a prospectively designed, independent clinical validation study (n=395)-testing retrospectively collected needle biopsies from contemporary (1997-2011) patients with low to intermediate clinical risk who were candidates for active surveillance (AS). The main outcome measures defining aggressive PCa were clinical recurrence, PCa death, and adverse pathology at prostatectomy. Cox proportional hazards regression models were used to evaluate the association between gene expression and time to event end points. Results from the prostatectomy and biopsy studies were used to develop and lock a multigene-expression-based signature, called the Genomic Prostate Score (GPS); in the validation study, logistic regression was used to test the association between the GPS and pathologic stage and grade at prostatectomy. Decision-curve analysis and risk profiles were used together with clinical and pathologic characteristics to evaluate clinical utility. Of the 732 candidate genes analyzed, 288 (39%) were found to predict clinical recurrence despite heterogeneity and multifocality, and 198 (27%) were predictive of aggressive disease after adjustment for prostate-specific antigen, Gleason score, and clinical stage. Further analysis identified 17 genes representing multiple biological pathways that were combined into the GPS algorithm. In the validation study, GPS predicted high-grade (odds ratio [OR] per 20 GPS units: 2.3; 95% confidence interval [CI], 1.5-3.7; p<0.001) and high-stage (OR per 20 GPS units: 1.9; 95% CI, 1.3-3

  18. Pretreatment Dynamic Susceptibility Contrast MRI Perfusion in Glioblastoma: Prediction of EGFR Gene Amplification.

    PubMed

    Gupta, A; Young, R J; Shah, A D; Schweitzer, A D; Graber, J J; Shi, W; Zhang, Z; Huse, J; Omuro, A M P

    2015-06-01

    Molecular and genetic testing is becoming increasingly relevant in GBM. We sought to determine whether dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) perfusion imaging could predict EGFR-defined subtypes of GBM. We retrospectively identified 106 consecutive glioblastoma (GBM) patients with known EGFR gene amplification, and a subset of 65 patients who also had known EGFRvIII gene mutation status. All patients underwent T2* DSC MRI perfusion. DSC perfusion maps and T2* signal intensity time curves were evaluated, and the following measures of tumor perfusion were recorded: (1) maximum relative cerebral blood volume (rCBV), (2) relative peak height (rPH), and (3) percent signal recovery (PSR). The imaging metrics were correlated to EGFR gene amplification and EGFRvIII mutation status using univariate analyses. EGFR amplification was present in 44 (41.5 %) subjects and absent in 62 (58.5 %). Among the 65 subjects who had undergone EGFRvIII mutation transcript analysis, 18 subjects (27.7 %) tested positive for the EGFRvIII mutation, whereas 47 (72.3 %) did not. Higher median rCBV (3.31 versus 2.62, p = 0.01) and lower PSR (0.70 versus 0.78, p = 0.03) were associated with high levels of EGFR amplification. Higher median rPH (3.68 versus 2.76, p = 0.03) was associated with EGFRvIII mutation. DSC MRI perfusion may have a role in identifying patients with EGFR gene amplification and EGFRvIII gene mutation status, potential targets for individualized treatment protocols. Our results raise the need for further investigation for imaging biomarkers of genetically unique GBM subtypes.

  19. Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.

    PubMed

    Guilloux, Jean-Philippe; Bassi, Sabrina; Ding, Ying; Walsh, Chris; Turecki, Gustavo; Tseng, George; Cyranowski, Jill M; Sibille, Etienne

    2015-02-01

    Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

  20. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    EPA Science Inventory

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

  1. In silico study of breast cancer associated gene 3 using LION Target Engine and other tools.

    PubMed

    León, Darryl A; Cànaves, Jaume M

    2003-12-01

    Sequence analysis of individual targets is an important step in annotation and validation. As a test case, we investigated human breast cancer associated gene 3 (BCA3) with LION Target Engine and with other bioinformatics tools. LION Target Engine confirmed that the BCA3 gene is located on 11p15.4 and that the two most likely splice variants (lacking exon 3 and exons 3 and 5, respectively) exist. Based on our manual curation of sequence data, it is proposed that an additional variant (missing only exon 5) published in a public sequence repository, is a prediction artifact. A significant number of new orthologs were also identified, and these were the basis for a high-quality protein secondary structure prediction. Moreover, our research confirmed several distinct functional domains as described in earlier reports. Sequence conservation from multiple sequence alignments, splice variant identification, secondary structure predictions, and predicted phosphorylation sites suggest that the removal of interaction sites through alternative splicing might play a modulatory role in BCA3. This in silico approach shows the depth and relevance of an analysis that can be accomplished by including a variety of publicly available tools with an integrated and customizable life science informatics platform.

  2. PNPLA3 gene in liver diseases.

    PubMed

    Trépo, Eric; Romeo, Stefano; Zucman-Rossi, Jessica; Nahon, Pierre

    2016-08-01

    Genome-wide association studies (GWAS) in the field of liver diseases have revealed previously unknown pathogenic loci and generated new biological hypotheses. In 2008, a GWAS performed in a population-based sample study, where hepatic liver fat content was measured by magnetic spectroscopy, showed a strong association between a variant (rs738409 C>G p.I148M) in the patatin-like phospholipase domain containing 3 (PNPLA3) gene and nonalcoholic fatty liver disease. Further replication studies have shown robust associations between PNPLA3 and steatosis, fibrosis/cirrhosis, and hepatocellular carcinoma on a background of metabolic, alcoholic, and viral insults. The PNPLA3 protein has lipase activity towards triglycerides in hepatocytes and retinyl esters in hepatic stellate cells. The I148M substitution leads to a loss of function promoting triglyceride accumulation in hepatocytes. Although PNPLA3 function has been extensively studied, the molecular mechanisms leading to hepatic fibrosis and carcinogenesis remain unclear. This unsuspected association has highlighted the fact that liver fat metabolism may have a major impact on the pathophysiology of liver diseases. Conversely, alone, this locus may have limited predictive value with regard to liver disease outcomes in clinical practice. Additional studies at the genome-wide level will be required to identify new variants associated with liver damage and cancer to explain a greater proportion of the heritability of these phenotypes. Thus, incorporating PNPLA3 and other genetic variants in combination with clinical data will allow for the development of tailored predictive models. This attractive approach should be evaluated in prospective cohorts. Copyright © 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  3. Validation of predictive models for germline mutations in DNA mismatch repair genes in colorectal cancer.

    PubMed

    Monzon, Jose G; Cremin, Carol; Armstrong, Linlea; Nuk, Jennifer; Young, Sean; Horsman, Doug E; Garbutt, Kristy; Bajdik, Chris D; Gill, Sharlene

    2010-02-15

    Lynch syndrome is defined by the presence of germline mutations in mismatch repair (MMR) genes. Several models have been recently devised that predict mutation carrier status (Myriad Genetics, Wijnen, Barnetson, PREMM and MMRpro models). Families at moderate-high risk for harboring a Lynch-associated mutation, referred to the BC Cancer Agency (BCCA) Hereditary Cancer Program (HCP), underwent mutation analysis, immunohistochemistry and/or microsatellite testing. Seventy-two tested cases were included. Twenty-five patients were mutation positive (34.7%) and 47 were mutation negative (65.3%). Nineteen of 43 patients who were both microsatellite stable and normal on immunohistochemistry for MLH1 and MSH2 were also genotyped for mutations in these genes; all 19 were negative for MMR gene mutations. Model-derived probabilities of harboring a MMR gene mutation in the proband were calculated and compared to observed results. The area under the ROC curves were 0.75 (95%CI; 0.63-0.87), 0.86 (0.7-0.96), 0.89 (0.82-0.97), 0.89 (0.81-0.98) and 0.93 (0.86-0.99) for the Myriad, Barnetson, Wijnen, MMRpro and PREMM models, respectively. The Amsterdam II criteria had a sensitivity and specificity of 0.76 and 0.74, respectively, in this cohort. The PREMM model demonstrated the best performance for predicting carrier status based on the positive likelihood ratios at the >10%, >20% and >30% probability thresholds. In this referred cohort, the PREMM model had the most favorable concordance index and predictive performance for carrier status based on the positive LR. These prediction models (PREMM, MMRPro and Wijnen) may soon replace the Amsterdam II and revised Bethesda criteria as a prescreening tool for Lynch mutations.

  4. FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences.

    PubMed

    Schiex, Thomas; Gouzy, Jérôme; Moisan, Annick; de Oliveira, Yannick

    2003-07-01

    We describe FrameD, a program that predicts coding regions in prokaryotic and matured eukaryotic sequences. Initially targeted at gene prediction in bacterial GC rich genomes, the gene model used in FrameD also allows to predict genes in the presence of frameshifts and partially undetermined sequences which makes it also very suitable for gene prediction and frameshift correction in unfinished sequences such as EST and EST cluster sequences. Like recent eukaryotic gene prediction programs, FrameD also includes the ability to take into account protein similarity information both in its prediction and its graphical output. Its performances are evaluated on different bacterial genomes. The web site (http://genopole.toulouse.inra.fr/bioinfo/FrameD/FD) allows direct prediction, sequence correction and translation and the ability to learn new models for new organisms.

  5. XLS (c9orf142) is a new component of mammalian DNA double-stranded break repair.

    PubMed

    Craxton, A; Somers, J; Munnur, D; Jukes-Jones, R; Cain, K; Malewicz, M

    2015-06-01

    Repair of double-stranded DNA breaks (DSBs) in mammalian cells primarily occurs by the non-homologous end-joining (NHEJ) pathway, which requires seven core proteins (Ku70/Ku86, DNA-PKcs (DNA-dependent protein kinase catalytic subunit), Artemis, XRCC4-like factor (XLF), XRCC4 and DNA ligase IV). Here we show using combined affinity purification and mass spectrometry that DNA-PKcs co-purifies with all known core NHEJ factors. Furthermore, we have identified a novel evolutionary conserved protein associated with DNA-PKcs-c9orf142. Computer-based modelling of c9orf142 predicted a structure very similar to XRCC4, hence we have named c9orf142-XLS (XRCC4-like small protein). Depletion of c9orf142/XLS in cells impaired DSB repair consistent with a defect in NHEJ. Furthermore, c9orf142/XLS interacted with other core NHEJ factors. These results demonstrate the existence of a new component of the NHEJ DNA repair pathway in mammalian cells.

  6. Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

    PubMed Central

    Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

    2014-01-01

    Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

  7. Matrix factorization-based data fusion for gene function prediction in baker's yeast and slime mold.

    PubMed

    Zitnik, Marinka; Zupan, Blaž

    2014-01-01

    The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker's yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps.

  8. Genomic Prediction of Gene Bank Wheat Landraces.

    PubMed

    Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J; Wenzl, Peter; Singh, Sukhwinder

    2016-07-07

    This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, "diversity" and "prediction", including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15-20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials

  9. Identification of a novel CLRN1 gene mutation in Usher syndrome type 3: two case reports.

    PubMed

    Yoshimura, Hidekane; Oshikawa, Chie; Nakayama, Jun; Moteki, Hideaki; Usami, Shin-Ichi

    2015-05-01

    This study examines the CLRN1 gene mutation analysis in Japanese patients who were diagnosed with Usher syndrome type 3 (USH3) on the basis of clinical findings. Genetic analysis using massively parallel DNA sequencing (MPS) was conducted to search for 9 causative USH genes in 2 USH3 patients. We identified the novel pathogenic mutation in the CLRN1 gene in 2 patients. The missense mutation was confirmed by functional prediction software and segregation analysis. Both patients were diagnosed as having USH3 caused by the CLRN1 gene mutation. This is the first report of USH3 with a CLRN1 gene mutation in Asian populations. Validating the presence of clinical findings is imperative for properly differentiating among USH subtypes. In addition, mutation screening using MPS enables the identification of causative mutations in USH. The clinical diagnosis of this phenotypically variable disease can then be confirmed. © The Author(s) 2015.

  10. Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

    PubMed

    Held, Elizabeth; Cape, Joshua; Tintle, Nathan

    2016-01-01

    Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

  11. Spaceflight modulates gene expression in the whole blood of astronauts.

    PubMed

    Barrila, Jennifer; Ott, C Mark; LeBlanc, Carly; Mehta, Satish K; Crabbé, Aurélie; Stafford, Phillip; Pierson, Duane L; Nickerson, Cheryl A

    2016-01-01

    Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1 , HSP27 , GPX1 , XRCC1 , BAG-1 , HHR23A , FAP48 , and C-FOS . No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.

  12. Spaceflight modulates gene expression in the whole blood of astronauts

    PubMed Central

    Barrila, Jennifer; Ott, C Mark; LeBlanc, Carly; Mehta, Satish K; Crabbé, Aurélie; Stafford, Phillip; Pierson, Duane L; Nickerson, Cheryl A

    2016-01-01

    Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1, HSP27, GPX1, XRCC1, BAG-1, HHR23A, FAP48, and C-FOS. No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight. PMID:28725744

  13. NF-κB gene signature predicts prostate cancer progression

    PubMed Central

    Jin, Renjie; Yi, Yajun; Yull, Fiona E.; Blackwell, Timothy S.; Clark, Peter E.; Koyama, Tatsuki; Smith, Joseph A.; Matusik, Robert J.

    2014-01-01

    In many prostate cancer (PCa) patients, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage PCa would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with PCa progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse PCa model when compared to Hi-Myc alone. Using the non-malignant NF-κB activated androgen depleted mouse prostate, a NF-κB Activated Recurrence Predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with PCa. This transgenic mouse model derived gene signature provides a useful and unique molecular profile for human PCa prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery. PMID:24686169

  14. Dinucleotide controlled null models for comparative RNA gene prediction.

    PubMed

    Gesell, Tanja; Washietl, Stefan

    2008-05-27

    Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

  15. Rapidly Evolving Toll-3/4 Genes Encode Male-Specific Toll-Like Receptors in Drosophila.

    PubMed

    Levin, Tera C; Malik, Harmit S

    2017-09-01

    Animal Toll-like receptors (TLRs) have evolved through a pattern of duplication and divergence. Whereas mammalian TLRs directly recognize microbial ligands, Drosophila Tolls bind endogenous ligands downstream of both developmental and immune signaling cascades. Here, we find that most Toll genes in Drosophila evolve slowly with little gene turnover (gains/losses), consistent with their important roles in development and indirect roles in microbial recognition. In contrast, we find that the Toll-3/4 genes have experienced an unusually rapid rate of gene gains and losses, resulting in lineage-specific Toll-3/4s and vastly different gene repertoires among Drosophila species, from zero copies (e.g., D. mojavensis) to nineteen copies (e.g., D. willistoni). In D. willistoni, we find strong evidence for positive selection in Toll-3/4 genes, localized specifically to an extracellular region predicted to overlap with the binding site of Spätzle, the only known ligand of insect Tolls. However, because Spätzle genes are not experiencing similar selective pressures, we hypothesize that Toll-3/4s may be rapidly evolving because they bind to a different ligand, akin to TLRs outside of insects. We further find that most Drosophila Toll-3/4 genes are either weakly expressed or expressed exclusively in males, specifically in the germline. Unlike other Toll genes in D. melanogaster, Toll-3, and Toll-4 have apparently escaped from essential developmental roles, as knockdowns have no substantial effects on viability or male fertility. Based on these findings, we propose that the Toll-3/4 genes represent an exceptionally rapidly evolving lineage of Drosophila Toll genes, which play an unusual, as-yet-undiscovered role in the male germline. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  16. Rapidly Evolving Toll-3/4 Genes Encode Male-Specific Toll-Like Receptors in Drosophila

    PubMed Central

    Levin, Tera C.; Malik, Harmit S.

    2017-01-01

    Abstract Animal Toll-like receptors (TLRs) have evolved through a pattern of duplication and divergence. Whereas mammalian TLRs directly recognize microbial ligands, Drosophila Tolls bind endogenous ligands downstream of both developmental and immune signaling cascades. Here, we find that most Toll genes in Drosophila evolve slowly with little gene turnover (gains/losses), consistent with their important roles in development and indirect roles in microbial recognition. In contrast, we find that the Toll-3/4 genes have experienced an unusually rapid rate of gene gains and losses, resulting in lineage-specific Toll-3/4s and vastly different gene repertoires among Drosophila species, from zero copies (e.g., D. mojavensis) to nineteen copies (e.g., D. willistoni). In D. willistoni, we find strong evidence for positive selection in Toll-3/4 genes, localized specifically to an extracellular region predicted to overlap with the binding site of Spätzle, the only known ligand of insect Tolls. However, because Spätzle genes are not experiencing similar selective pressures, we hypothesize that Toll-3/4s may be rapidly evolving because they bind to a different ligand, akin to TLRs outside of insects. We further find that most Drosophila Toll-3/4 genes are either weakly expressed or expressed exclusively in males, specifically in the germline. Unlike other Toll genes in D. melanogaster, Toll-3, and Toll-4 have apparently escaped from essential developmental roles, as knockdowns have no substantial effects on viability or male fertility. Based on these findings, we propose that the Toll-3/4 genes represent an exceptionally rapidly evolving lineage of Drosophila Toll genes, which play an unusual, as-yet-undiscovered role in the male germline. PMID:28541576

  17. Gene signature based on degradome-related genes can predict distal metastasis in cervical cancer patients.

    PubMed

    Fernandez-Retana, Jorge; Zamudio-Meza, Horacio; Rodriguez-Morales, Miguel; Pedroza-Torres, Abraham; Isla-Ortiz, David; Herrera, Luis; Jacobo-Herrera, Nadia; Peralta-Zaragoza, Oscar; López-Camarillo, César; Morales-Gonzalez, Fermin; Cantu de Leon, David; Pérez-Plasencia, Carlos

    2017-06-01

    Cervical cancer is one of the leading causes of death in women worldwide, which mainly affects developing countries. The patients who suffer a recurrence and/or progression disease have a higher risk of developing distal metastases. Proteases comprising the degradome given its ability to promote cell growth, migration, and invasion of tissues play an important role during tumor development and progression. In this study, we used high-density microarrays and quantitative reverse transcriptase polymerase chain reaction to evaluate the degradome profile and their inhibitors in 112 samples of patients diagnosed with locally advanced cervical cancer. Clinical follow-up was done during a period of 3 years. Using a correlation analysis between the response to treatment and the development of metastasis, we established a molecular signature comprising eight degradome-related genes (FAM111B, FAM111A, CFB, PSMB8, PSMB9, CASP7, PRSS16, and CD74) with the ability to discriminate patients at risk of distal metastases. In conclusion, present results show that molecular signature obtained from degradome genes can predict the possibility of metastasis in patients with locally advanced cervical cancer.

  18. Genomic Prediction of Gene Bank Wheat Landraces

    PubMed Central

    Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J.; Wenzl, Peter; Singh, Sukhwinder

    2016-01-01

    This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite

  19. The Choice between MapMan and Gene Ontology for Automated Gene Function Prediction in Plant Science

    PubMed Central

    Klie, Sebastian; Nikoloski, Zoran

    2012-01-01

    Since the introduction of the Gene Ontology (GO), the analysis of high-throughput data has become tightly coupled with the use of ontologies to establish associations between knowledge and data in an automated fashion. Ontologies provide a systematic description of knowledge by a controlled vocabulary of defined structure in which ontological concepts are connected by pre-defined relationships. In plant science, MapMan and GO offer two alternatives for ontology-driven analyses. Unlike GO, initially developed to characterize microbial systems, MapMan was specifically designed to cover plant-specific pathways and processes. While the dependencies between concepts in MapMan are modeled as a tree, in GO these are captured in a directed acyclic graph. Therefore, the difference in ontologies may cause discrepancies in data reduction, visualization, and hypothesis generation. Here provide the first systematic comparative analysis of GO and MapMan for the case of the model plant species Arabidopsis thaliana (Arabidopsis) with respect to their structural properties and difference in distributions of information content. In addition, we investigate the effect of the two ontologies on the specificity and sensitivity of automated gene function prediction via the coupling of co-expression networks and the guilt-by-association principle. Automated gene function prediction is particularly needed for the model plant Arabidopsis in which only half of genes have been functionally annotated based on sequence similarity to known genes. The results highlight the need for structured representation of species-specific biological knowledge, and warrants caution in the design principles employed in future ontologies. PMID:22754563

  20. PRISM 3: expanded prediction of natural product chemical structures from microbial genomes

    PubMed Central

    Skinnider, Michael A.; Merwin, Nishanth J.; Johnston, Chad W.

    2017-01-01

    Abstract Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. PMID:28460067

  1. Phylogenetic analysis of the cytochrome P450 3 (CYP3) gene family.

    PubMed

    McArthur, Andrew G; Hegelund, Tove; Cox, Rachel L; Stegeman, John J; Liljenberg, Mette; Olsson, Urban; Sundberg, Per; Celander, Malin C

    2003-08-01

    Cytochrome P450 genes (CYP) constitute a superfamily with members known from the Bacteria, Archaea, and Eukarya. The CYP3 gene family includes the CYP3A and CYP3B subfamilies. Members of the CYP3A subfamily represent the dominant CYP forms expressed in the digestive and respiratory tracts of vertebrates. The CYP3A enzymes metabolize a wide variety of chemically diverse lipophilic organic compounds. To understand vertebrate CYP3 diversity better, we determined the killifish (Fundulus heteroclitus) CYP3A30 and CYP3A56 and the ball python (Python regius) CYP3A42 sequences. We performed phylogenetic analyses of 45 vertebrate CYP3 amino acid sequences using a Bayesian approach. Our analyses indicate that teleost, diapsid, and mammalian CYP3A genes have undergone independent diversification and that the ancestral vertebrate genome contained a single CYP3A gene. Most CYP3A diversity is the product of recent gene duplication events. There is strong support for placement of the guinea pig CYP3A genes within the rodent CYP3A diversification. The rat, mouse, and hamster CYP3A genes are mixed among several rodent CYP3A subclades, indicative of a complex history involving speciation and gene duplication.

  2. Factors affecting interactome-based prediction of human genes associated with clinical signs.

    PubMed

    González-Pérez, Sara; Pazos, Florencio; Chagoyen, Mónica

    2017-07-17

    Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome. Our analysis reveals that these approaches can locate genes associated with clinical signs with variable performance that depends on the sign and associated disease. We analyzed several clinical and biological factors that explain these variable results, including number of genes involved (mono- vs. oligogenic diseases), mode of inheritance, type of clinical sign and gene product function. Our results indicate that the characteristics of the clinical signs and their related diseases should be considered for interpreting the results of network-prediction methods, such as those aimed at discovering disease-related genes and variants. These results are important due the increasing use of clinical signs as an alternative to diseases for studying the molecular basis of human pathologies.

  3. SNPs of GSTM1, T1, P1, epoxide hydrolase and DNA repair enzyme XRCC1 and risk of urinary transitional cell carcinoma in southwestern Taiwan

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hsu, L.-I; Chiu, Allen W.; Huan, Steven K.

    A hospital-based case-control study was conducted near a former black-foot disease (BFD)-endemic area in southwestern Taiwan to examine the possible risk factors and genetic susceptibility for urinary transitional cell carcinoma (TCC). A total of 221 patients with pathologically confirmed TCC and 223 age-sex-matched control subjects from urology outpatient clinics were recruited between 1998 and 2002. The results showed that residency in the BFD area and consumption of well water for more than 10 years was a strong factor on urinary cancer risk (odds ratio [OR],8.16, 95% confidence interval [CI],3.34-19.90, p < 0.0001). Dose response relationship between average arsenic concentration inmore » well water and TCC risk was also observed. Cigarette smoking played a relatively minor role in urinary carcinogenesis in this study. The GSTP1 Ile105Val A {yields} G polymorphism was significantly associated with cancer risk (A/G + G/G: OR = 0.60, 95%CI = 0.39-0.94, p = 0.02), and the effect of Val105 allele was largely confined to the subjects diagnosed earlier than 55 years old (A/G + G/G: OR,0.29; 95% CI, 0.09-0.87, p = 0.03). The results suggest that GSTP1 is a candidate for susceptibility locus and Ile105 allele may predispose individuals to early-onset urinary TCC. The GSTM1 null genotype was associated with tumors of high-invasiveness (OR,2.21; 95% CI, 1.34-4.73) as well as with early-onset TCC risk (OR,2.53; 95% CI, 0.97-6.59). Our preliminary results showed the XRCC1 Arg194Trp were associated with arsenic-related urinary TCC and the interaction between the genotype and the exposure was statistically significant. The modulating effect of the GSTM1, GSTT1, GSTP1 Ile105Val, EPHX Tyr113His and XRCC1 Arg280His on arsenic-related TCC risk was also suggestive. These observations implied that impaired metabolism of carcinogenic exposure as well as impaired DNA repair function play an important role in arsenic-related urinary transitional cell carcinogenesis.« less

  4. Prediction of missing common genes for disease pairs using network based module separation on incomplete human interactome.

    PubMed

    Akram, Pakeeza; Liao, Li

    2017-12-06

    Identification of common genes associated with comorbid diseases can be critical in understanding their pathobiological mechanism. This work presents a novel method to predict missing common genes associated with a disease pair. Searching for missing common genes is formulated as an optimization problem to minimize network based module separation from two subgraphs produced by mapping genes associated with disease onto the interactome. Using cross validation on more than 600 disease pairs, our method achieves significantly higher average receiver operating characteristic ROC Score of 0.95 compared to a baseline ROC score 0.60 using randomized data. Missing common genes prediction is aimed to complete gene set associated with comorbid disease for better understanding of biological intervention. It will also be useful for gene targeted therapeutics related to comorbid diseases. This method can be further considered for prediction of missing edges to complete the subgraph associated with disease pair.

  5. Dimethylarsinic acid in drinking water changed the morphology of urinary bladder but not the expression of DNA repair genes of bladder transitional epithelium in F344 rats.

    PubMed

    Wang, Amy; Wolf, Douglas C; Sen, Banalata; Knapp, Geremy W; Holladay, Steven D; Huckle, William R; Caceci, Thomas; Robertson, John L

    2009-06-01

    Inorganic arsenic increases urinary bladder transitional cell carcinoma in humans. In F344 rats, dimethylarsinic acid (DMA[V]) increases transitional cell carcinoma. Arsenic-induced inhibition of DNA repair has been reported in cultured cell lines and in lymphocytes of arsenic-exposed humans, but it has not been studied in urinary bladder. Should inhibition of DNA damage repair in transitional epithelium occur, it may contribute to carcinogenesis or cocarcinogenesis. We investigated morphology and expression of DNA repair genes in F344 rat transitional cells following up to 100 ppm DMA(V) in drinking water for four weeks. Mitochondria were very sensitive to DMA(V), and swollen mitochondria appeared to be the main source of vacuoles in the transitional epithelium. Real-time reverse transcriptase polymerase chain reaction (Real-Time RT PCR) showed the mRNA levels of tested DNA repair genes, ataxia telangectasia mutant (ATM), X-ray repair cross-complementing group 1 (XRCC1), excision repair cross-complementing group 3/xeroderma pigmentosum B (ERCC3/XPB), and DNA polymerase beta (Polbeta), were not altered by DMA(V). These data suggested that either DMA(V) does not affect DNA repair in the bladder or DMA(V) affects DNA repair without affecting baseline mRNA levels of repair genes. The possibility remains that DMA(V) may lower damage-induced increases in repair gene expression or cause post-translational modification of repair enzymes.

  6. Prediction of cardioembolic, arterial and lacunar causes of cryptogenic stroke by gene expression and infarct location

    PubMed Central

    Jickling, Glen C; Stamova, Boryana; Ander, Bradley P; Zhan, Xinhua; Liu, Dazhi; Sison, Shara-Mae; Verro, Piero; Sharp, Frank R

    2012-01-01

    Background and Purpose The cause of ischemic stroke remains unclear, or cryptogenic, in as many as 35% of stroke patients. Not knowing the cause of stroke restricts optimal implementation of prevention therapy and limits stroke research. We demonstrate how gene expression profiles in blood can be used in conjunction with a measure of infarct location on neuroimaging to predict a probable cause in cryptogenic stroke. Methods The cause of cryptogenic stroke was predicted using previously described profiles of differentially expressed genes characteristic of patients with cardioembolic, arterial and lacunar stroke. RNA was isolated from peripheral blood of 131 cryptogenic strokes and compared to profiles derived from 149 strokes of known cause. Each sample was run on Affymetrix U133 Plus2.0 microarrays. Cause of cryptogenic stroke was predicted using gene expression in blood and infarct location. Results Cryptogenic strokes were predicted to be 58% cardioembolic, 18% arterial, 12% lacunar and 12% unclear etiology. Cryptogenic stroke of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA2DS2-VASc scores compared to stroke of predicted arterial etiology. Predicted lacunar strokes had higher systolic and diastolic blood pressures and lower NIHSS compared to predicted arterial and cardioembolic strokes. Cryptogenic strokes of unclear predicted etiology were less likely to have a prior TIA or ischemic stroke. Conclusions Gene expression in conjunction with a measure of infarct location can predict a probable cause in cryptogenic strokes. Predicted groups require further evaluation to determine whether relevant clinical, imaging, or therapeutic differences exist for each group. PMID:22627989

  7. The histone H3 variant H3.3 regulates gene body DNA methylation in Arabidopsis thaliana.

    PubMed

    Wollmann, Heike; Stroud, Hume; Yelagandula, Ramesh; Tarutani, Yoshiaki; Jiang, Danhua; Jing, Li; Jamge, Bhagyshree; Takeuchi, Hidenori; Holec, Sarah; Nie, Xin; Kakutani, Tetsuji; Jacobsen, Steven E; Berger, Frédéric

    2017-05-18

    Gene bodies of vertebrates and flowering plants are occupied by the histone variant H3.3 and DNA methylation. The origin and significance of these profiles remain largely unknown. DNA methylation and H3.3 enrichment profiles over gene bodies are correlated and both have a similar dependence on gene transcription levels. This suggests a mechanistic link between H3.3 and gene body methylation. We engineered an H3.3 knockdown in Arabidopsis thaliana and observed transcription reduction that predominantly affects genes responsive to environmental cues. When H3.3 levels are reduced, gene bodies show a loss of DNA methylation correlated with transcription levels. To study the origin of changes in DNA methylation profiles when H3.3 levels are reduced, we examined genome-wide distributions of several histone H3 marks, H2A.Z, and linker histone H1. We report that in the absence of H3.3, H1 distribution increases in gene bodies in a transcription-dependent manner. We propose that H3.3 prevents recruitment of H1, inhibiting H1's promotion of chromatin folding that restricts access to DNA methyltransferases responsible for gene body methylation. Thus, gene body methylation is likely shaped by H3.3 dynamics in conjunction with transcriptional activity.

  8. Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

    PubMed Central

    Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

    2014-01-01

    The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

  9. Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

    PubMed

    Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

    2018-02-02

    Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

  10. Genome sequence analysis of predicted polyprenol reductase gene from mangrove plant kandelia obovata

    NASA Astrophysics Data System (ADS)

    Basyuni, M.; Sagami, H.; Baba, S.; Oku, H.

    2018-03-01

    It has been previously reported that dolichols but not polyprenols were predominated in mangrove leaves and roots. Therefore, the occurrence of larger amounts of dolichol in leaves of mangrove plants implies that polyprenol reductase is responsible for the conversion of polyprenol to dolichol may be active in mangrove leaves. Here we report the early assessment of probably polyprenol reductase gene from genome sequence of mangrove plant Kandelia obovata. The functional assignment of the gene was based on a homology search of the sequences against the non-redundant (nr) peptide database of NCBI using Blastx. The degree of sequence identity between DNA sequence and known polyprenol reductase was confirmed using the Blastx probability E-value, total score, and identity. The genome sequence data resulted in three partial sequences, termed c23157 (700 bp), c23901 (960 bp), and c24171 (531 bp). The c23157 gene showed the highest similarity (61%) to predicted polyprenol reductase 2- like from Gossypium raimondii with E-value 2e-100. The second gene was c23901 to exhibit high similarity (78%) to the steroid 5-alpha-reductase Det2 from J. curcas with E-value 2e-140. Furthermore, the c24171 gene depicted highest similarity (79%) to the polyprenol reductase 2 isoform X1 from Jatropha curcas with E- value 7e-21.The present study suggested that the c23157, c23901, and c24171, genes may encode predicted polyprenol reductase. The c23157, c23901, c24171 are therefore the new type of predicted polyprenol reductase from K. obovata.

  11. Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

    PubMed Central

    Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

    2012-01-01

    Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

  12. Mutations in BRCA1, BRCA2 and other breast and ovarian cancer susceptibility genes in Central and South American populations.

    PubMed

    Jara, Lilian; Morales, Sebastian; de Mayo, Tomas; Gonzalez-Hormazabal, Patricio; Carrasco, Valentina; Godoy, Raul

    2017-10-06

    Breast cancer (BC) is the most common malignancy among women worldwide. A major advance in the understanding of the genetic etiology of BC was the discovery of BRCA1 and BRCA2 (BRCA1/2) genes, which are considered high-penetrance BC genes. In non-carriers of BRCA1/2 mutations, disease susceptibility may be explained of a small number of mutations in BRCA1/2 and a much higher proportion of mutations in ethnicity-specific moderate- and/or low-penetrance genes. In Central and South American populations, studied have focused on analyzing the distribution and prevalence of BRCA1/2 mutations and other susceptibility genes that are scarce in Latin America as compared to North America, Europe, Australia, and Israel. Thus, the aim of this review is to present the current state of knowledge regarding pathogenic BRCA variants and other BC susceptibility genes. We conducted a comprehensive review of 47 studies from 12 countries in Central and South America published between 2002 and 2017 reporting the prevalence and/or spectrum of mutations and pathogenic variants in BRCA1/2 and other BC susceptibility genes. The studies on BRCA1/2 mutations screened a total of 5956 individuals, and studies on susceptibility genes analyzed a combined sample size of 11,578 individuals. To date, a total of 190 different BRCA1/2 pathogenic mutations in Central and South American populations have been reported in the literature. Pathogenic mutations or variants that increase BC risk have been reported in the following genes or genomic regions: ATM, BARD1, CHECK2, FGFR2, GSTM1, MAP3K1, MTHFR, PALB2, RAD51, TOX3, TP53, XRCC1, and 2q35.

  13. A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

    DOE PAGES

    Wang, Pin; Wang, Yunshan; Hang, Bo; ...

    2016-07-11

    Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

  14. A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Pin; Wang, Yunshan; Hang, Bo

    Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

  15. Predictive biomarkers of sensitivity to the phosphatidylinositol 3' kinase inhibitor GDC-0941 in breast cancer preclinical models.

    PubMed

    O'Brien, Carol; Wallin, Jeffrey J; Sampath, Deepak; GuhaThakurta, Debraj; Savage, Heidi; Punnoose, Elizabeth A; Guan, Jane; Berry, Leanne; Prior, Wei Wei; Amler, Lukas C; Belvin, Marcia; Friedman, Lori S; Lackner, Mark R

    2010-07-15

    The class I phosphatidylinositol 3' kinase (PI3K) plays a major role in proliferation and survival in a wide variety of human cancers. A key factor in successful development of drugs targeting this pathway is likely to be the identification of responsive patient populations with predictive diagnostic biomarkers. This study sought to identify candidate biomarkers of response to the selective PI3K inhibitor GDC-0941. We used a large panel of breast cancer cell lines and in vivo xenograft models to identify candidate predictive biomarkers for a selective inhibitor of class I PI3K that is currently in clinical development. The approach involved pharmacogenomic profiling as well as analysis of gene expression data sets from cells profiled at baseline or after GDC-0941 treatment. We found that models harboring mutations in PIK3CA, amplification of human epidermal growth factor receptor 2, or dual alterations in two pathway components were exquisitely sensitive to the antitumor effects of GDC-0941. We found that several models that do not harbor these alterations also showed sensitivity, suggesting a need for additional diagnostic markers. Gene expression studies identified a collection of genes whose expression was associated with in vitro sensitivity to GDC-0941, and expression of a subset of these genes was found to be intimately linked to signaling through the pathway. Pathway focused biomarkers and the gene expression signature described in this study may have utility in the identification of patients likely to benefit from therapy with a selective PI3K inhibitor. Copyright 2010 AACR.

  16. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

    PubMed

    Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

    2013-09-22

    High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

  17. CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

    PubMed Central

    Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

    2015-01-01

    Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

  18. CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

    PubMed

    Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

    2015-10-13

    Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

  19. SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

    PubMed Central

    2014-01-01

    Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

  20. In silico prediction of novel therapeutic targets using gene-disease association data.

    PubMed

    Ferrero, Enrico; Dunham, Ian; Sanseau, Philippe

    2017-08-29

    Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is sufficient to predict therapeutic targets that are actively being pursued by pharmaceutical companies or are already on the market. To test our hypothesis, we train four different classifiers (a random forest, a support vector machine, a neural network and a gradient boosting machine) on partially labelled data and evaluate their performance using nested cross-validation and testing on an independent set. We then select the best performing model and use it to make predictions on more than 15,000 genes. Finally, we validate our predictions by mining the scientific literature for proposed therapeutic targets. We observe that the data types with the best predictive power are animal models showing a disease-relevant phenotype, differential expression in diseased tissue and genetic association with the disease under investigation. On a test set, the neural network classifier achieves over 71% accuracy with an AUC of 0.76 when predicting therapeutic targets in a semi-supervised learning setting. We use this model to gain insights into current and failed programmes and to predict 1431 novel targets, of which a highly significant proportion has been independently proposed in the literature. Our in silico approach shows that data linking genes and diseases is sufficient to predict novel therapeutic targets effectively and confirms that this type of evidence is essential for formulating or strengthening hypotheses in the target discovery process. Ultimately, more rapid and automated target

  1. The Transcription Factors Islet and Lim3 Combinatorially Regulate Ion Channel Gene Expression

    PubMed Central

    Wolfram, Verena; Southall, Tony D.; Günay, Cengiz; Prinz, Astrid A.; Brand, Andrea H.

    2014-01-01

    Expression of appropriate ion channels is essential to allow developing neurons to form functional networks. Our previous studies have identified LIM-homeodomain (HD) transcription factors (TFs), expressed by developing neurons, that are specifically able to regulate ion channel gene expression. In this study, we use the technique of DNA adenine methyltransferase identification (DamID) to identify putative gene targets of four such TFs that are differentially expressed in Drosophila motoneurons. Analysis of targets for Islet (Isl), Lim3, Hb9, and Even-skipped (Eve) identifies both ion channel genes and genes predicted to regulate aspects of dendritic and axonal morphology. Significantly, some ion channel genes are bound by more than one TF, consistent with the possibility of combinatorial regulation. One such gene is Shaker (Sh), which encodes a voltage-dependent fast K+ channel (Kv1.1). DamID reveals that Sh is bound by both Isl and Lim3. We used body wall muscle as a test tissue because in conditions of low Ca2+, the fast K+ current is carried solely by Sh channels (unlike neurons in which a second fast K+ current, Shal, also contributes). Ectopic expression of isl, but not Lim3, is sufficient to reduce both Sh transcript and Sh current level. By contrast, coexpression of both TFs is additive, resulting in a significantly greater reduction in both Sh transcript and current compared with isl expression alone. These observations provide evidence for combinatorial activity of Isl and Lim3 in regulating ion channel gene expression. PMID:24523544

  2. DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation

    PubMed Central

    Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

    2017-01-01

    Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo. The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer. PMID:28123849

  3. DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation.

    PubMed

    Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

    2017-01-01

    Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo . The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer.

  4. Prediction of Bacillus weihenstephanensis acid resistance: the use of gene expression patterns to select potential biomarkers.

    PubMed

    Desriac, N; Postollec, F; Coroller, L; Sohier, D; Abee, T; den Besten, H M W

    2013-10-01

    Exposure to mild stress conditions can activate stress adaptation mechanisms and provide cross-resistance towards otherwise lethal stresses. In this study, an approach was followed to select molecular biomarkers (quantitative gene expressions) to predict induced acid resistance after exposure to various mild stresses, i.e. exposure to sublethal concentrations of salt, acid and hydrogen peroxide during 5 min to 60 min. Gene expression patterns of unstressed and mildly stressed cells of Bacillus weihenstephanensis were correlated to their acid resistance (3D value) which was estimated after exposure to lethal acid conditions. Among the twenty-nine candidate biomarkers, 12 genes showed expression patterns that were correlated either linearly or non-linearly to acid resistance, while for the 17 other genes the correlation remains to be determined. The selected genes represented two types of biomarkers, (i) four direct biomarker genes (lexA, spxA, narL, bkdR) for which expression patterns upon mild stress treatment were linearly correlated to induced acid resistance; and (ii) nine long-acting biomarker genes (spxA, BcerKBAB4_0325, katA, trxB, codY, lacI, BcerKBAB4_1716, BcerKBAB4_2108, relA) which were transiently up-regulated during mild stress exposure and correlated to increased acid resistance over time. Our results highlight that mild stress induced transcripts can be linearly or non-linearly correlated to induced acid resistance and both approaches can be used to find relevant biomarkers. This quantitative and systematic approach opens avenues to select cellular biomarkers that could be incremented in mathematical models to predict microbial behaviour. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

    PubMed

    Skinnider, Michael A; Merwin, Nishanth J; Johnston, Chad W; Magarvey, Nathan A

    2017-07-03

    Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

    PubMed

    Lewis, Tony E; Sillitoe, Ian; Andreeva, Antonina; Blundell, Tom L; Buchan, Daniel W A; Chothia, Cyrus; Cuff, Alison; Dana, Jose M; Filippis, Ioannis; Gough, Julian; Hunter, Sarah; Jones, David T; Kelley, Lawrence A; Kleywegt, Gerard J; Minneci, Federico; Mitchell, Alex; Murzin, Alexey G; Ochoa-Montaño, Bernardo; Rackham, Owen J L; Smith, James; Sternberg, Michael J E; Velankar, Sameer; Yeats, Corin; Orengo, Christine

    2013-01-01

    Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

  7. XLS (c9orf142) is a new component of mammalian DNA double-stranded break repair

    PubMed Central

    Craxton, A; Somers, J; Munnur, D; Jukes-Jones, R; Cain, K; Malewicz, M

    2015-01-01

    Repair of double-stranded DNA breaks (DSBs) in mammalian cells primarily occurs by the non-homologous end-joining (NHEJ) pathway, which requires seven core proteins (Ku70/Ku86, DNA-PKcs (DNA-dependent protein kinase catalytic subunit), Artemis, XRCC4-like factor (XLF), XRCC4 and DNA ligase IV). Here we show using combined affinity purification and mass spectrometry that DNA-PKcs co-purifies with all known core NHEJ factors. Furthermore, we have identified a novel evolutionary conserved protein associated with DNA-PKcs—c9orf142. Computer-based modelling of c9orf142 predicted a structure very similar to XRCC4, hence we have named c9orf142—XLS (XRCC4-like small protein). Depletion of c9orf142/XLS in cells impaired DSB repair consistent with a defect in NHEJ. Furthermore, c9orf142/XLS interacted with other core NHEJ factors. These results demonstrate the existence of a new component of the NHEJ DNA repair pathway in mammalian cells. PMID:25941166

  8. Prevalence of pfhrp2 and pfhrp3 gene deletions in Puerto Lempira, Honduras.

    PubMed

    Abdallah, Joseph F; Okoth, Sheila Akinyi; Fontecha, Gustavo A; Torres, Rosa Elena Mejia; Banegas, Engels I; Matute, María Luisa; Bucheli, Sandra Tamara Mancero; Goldman, Ira F; de Oliveira, Alexandre Macedo; Barnwell, John W; Udhayakumar, Venkatachalam

    2015-01-21

    Recent studies have demonstrated the deletion of the histidine-rich protein 2 (PfHRP2) gene (pfhrp2) in field isolates of Plasmodium falciparum, which could result in false negative test results when PfHRP2-based rapid diagnostic tests (RDTs) are used for malaria diagnosis. Although primary diagnosis of malaria in Honduras is determined based on microscopy, RDTs may be useful in remote areas. In this study, it was investigated whether there are deletions of the pfhrp2, pfhrp3 and their respective flanking genes in 68 P. falciparum parasite isolates collected from the city of Puerto Lempira, Honduras. In addition, further investigation considered the possible correlation between parasite population structure and the distribution of these gene deletions by genotyping seven neutral microsatellites. Sixty-eight samples used in this study, which were obtained from a previous chloroquine efficacy study, were utilized in the analysis. All samples were genotyped for pfhrp2, pfhrp3 and flanking genes by PCR. The samples were then genotyped for seven neutral microsatellites in order to determine the parasite population structure in Puerto Lempira at the time of sample collection. It was found that all samples were positive for pfhrp2 and its flanking genes on chromosome 8. However, only 50% of the samples were positive for pfhrp3 and its neighboring genes while the rest were either pfhrp3-negative only or had deleted a combination of pfhrp3 and its neighbouring genes on chromosome 13. Population structure analysis predicted that there are at least two distinct parasite population clusters in this sample population. It was also determined that a greater proportion of parasites with pfhrp3-(and flanking gene) deletions belonged to one cluster compared to the other. The findings indicate that the P. falciparum parasite population in the municipality of Puerto Lempira maintains the pfhrp2 gene and that PfHRP2-based RDTs could be considered for use in this region; however

  9. Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

    PubMed Central

    Tian, Weidong; Zhang, Lan V; Taşan, Murat; Gibbons, Francis D; King, Oliver D; Park, Julie; Wunderlich, Zeba; Cherry, J Michael; Roth, Frederick P

    2008-01-01

    Background: Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. Results: We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships. Conclusion: Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions. PMID:18613951

  10. MATRIX FACTORIZATION-BASED DATA FUSION FOR GENE FUNCTION PREDICTION IN BAKER’S YEAST AND SLIME MOLD

    PubMed Central

    ŽITNIK, MARINKA; ZUPAN, BLAŽ

    2014-01-01

    The development of effective methods for the characterization of gene functions that are able to combine diverse data sources in a sound and easily-extendible way is an important goal in computational biology. We have previously developed a general matrix factorization-based data fusion approach for gene function prediction. In this manuscript, we show that this data fusion approach can be applied to gene function prediction and that it can fuse various heterogeneous data sources, such as gene expression profiles, known protein annotations, interaction and literature data. The fusion is achieved by simultaneous matrix tri-factorization that shares matrix factors between sources. We demonstrate the effectiveness of the approach by evaluating its performance on predicting ontological annotations in slime mold D. discoideum and on recognizing proteins of baker’s yeast S. cerevisiae that participate in the ribosome or are located in the cell membrane. Our approach achieves predictive performance comparable to that of the state-of-the-art kernel-based data fusion, but requires fewer data preprocessing steps. PMID:24297565

  11. Biological networks for predicting chemical hepatocarcinogenicity using gene expression data from treated mice and relevance across human and rat species.

    PubMed

    Thomas, Reuben; Thomas, Russell S; Auerbach, Scott S; Portier, Christopher J

    2013-01-01

    Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species.

  12. Predicting Gene Expression Level from Relative Codon Usage Bias: An Application to Escherichia coli Genome

    PubMed Central

    Roymondal, Uttam; Das, Shibsankar; Sahoo, Satyabrata

    2009-01-01

    We present an expression measure of a gene, devised to predict the level of gene expression from relative codon bias (RCB). There are a number of measures currently in use that quantify codon usage in genes. Based on the hypothesis that gene expressivity and codon composition is strongly correlated, RCB has been defined to provide an intuitively meaningful measure of an extent of the codon preference in a gene. We outline a simple approach to assess the strength of RCB (RCBS) in genes as a guide to their likely expression levels and illustrate this with an analysis of Escherichia coli (E. coli) genome. Our efforts to quantitatively predict gene expression levels in E. coli met with a high level of success. Surprisingly, we observe a strong correlation between RCBS and protein length indicating natural selection in favour of the shorter genes to be expressed at higher level. The agreement of our result with high protein abundances, microarray data and radioactive data demonstrates that the genomic expression profile available in our method can be applied in a meaningful way to the study of cell physiology and also for more detailed studies of particular genes of interest. PMID:19131380

  13. Reduce Manual Curation by Combining Gene Predictions from Multiple Annotation Engines, a Case Study of Start Codon Prediction

    PubMed Central

    Ederveen, Thomas H. A.; Overmars, Lex; van Hijum, Sacha A. F. T.

    2013-01-01

    Nowadays, prokaryotic genomes are sequenced faster than the capacity to manually curate gene annotations. Automated genome annotation engines provide users a straight-forward and complete solution for predicting ORF coordinates and function. For many labs, the use of AGEs is therefore essential to decrease the time necessary for annotating a given prokaryotic genome. However, it is not uncommon for AGEs to provide different and sometimes conflicting predictions. Combining multiple AGEs might allow for more accurate predictions. Here we analyzed the ab initio open reading frame (ORF) calling performance of different AGEs based on curated genome annotations of eight strains from different bacterial species with GC% ranging from 35–52%. We present a case study which demonstrates a novel way of comparative genome annotation, using combinations of AGEs in a pre-defined order (or path) to predict ORF start codons. The order of AGE combinations is from high to low specificity, where the specificity is based on the eight genome annotations. For each AGE combination we are able to derive a so-called projected confidence value, which is the average specificity of ORF start codon prediction based on the eight genomes. The projected confidence enables estimating likeliness of a correct prediction for a particular ORF start codon by a particular AGE combination, pinpointing ORFs notoriously difficult to predict start codons. We correctly predict start codons for 90.5±4.8% of the genes in a genome (based on the eight genomes) with an accuracy of 81.1±7.6%. Our consensus-path methodology allows a marked improvement over majority voting (9.7±4.4%) and with an optimal path ORF start prediction sensitivity is gained while maintaining a high specificity. PMID:23675487

  14. Amplification of Genomic DNA for Decoy Receptor 3 Predicts Post-Resection Disease Recurrence in Breast Cancer Patients.

    PubMed

    Kanbayashi, Chizuko; Koyama, Yu; Ichikawa, Hiroshi; Sakata, Eiko; Hasegawa, Miki; Toshikawa, Chie; Manba, Naoko; Ikarashi, Mayuko; Kobayashi, Takashi; Minagawa, Masahiro; Kosugi, Shin-Ichi; Wakai, Toshifumi

    2014-02-01

    Decoy receptor 3 (DcR3), a member of the tumor necrosis factor receptor (TNFR) superfamily, shows inhibitory effects on Fas-mediated apoptosis. Currently, data are lacking on the correlation between DcR3 and the recurrence of breast cancer. The authors examined DcR3 mRNA expression and genomic amplification in breast cancer, and investigated the effect of DcR3 gene amplification on prognosis of patients. A total of 95 patients formed the basis of the current retrospective study. DcR3 mRNA expression in breast cancer tissues was examined by RNase protection assay and in situ hybridization. DcR3 gene amplification was examined by quantitative polymerase chain reaction. The correlation between DcR3 gene amplification status and clinicopathological factors was examined and also the relationship between DcR3-Amp and relapse and survival. The relative copy numbers of DcR3 genomic DNA correlated significantly with the levels of DcR3 mRNA expression (ρ = 0.755, P = 0.0067). In addition, lymphatic invasion correlated significantly with DcR3 gene amplification (P = 0.012). However, there was no correlation between the remaining clinicopathological factors and DcR3 gene amplification. In the univariate analysis, the recurrence-free survival (RFS) rate of patients who were positive for DcR3 gene amplification was significantly lower than that of patients who were negative for DcR3 gene amplification (P = 0.0271). Multivariate analysis showed that DcR3 gene amplification (P = 0.028) and disease stage (P < 0.001) remained significant independent predictors of RFS. DcR3 gene amplification was significantly correlated with lymphatic invasion, and also DcR3 gene amplification predicts recurrence after resection, which may be an important prognostic factor in breast cancer patients.

  15. Prediction of functionally significant single nucleotide polymorphisms in PTEN tumor suppressor gene: An in silico approach.

    PubMed

    Khan, Imran; Ansari, Irfan A; Singh, Pratichi; Dass J, Febin Prabhu

    2017-09-01

    The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

  16. Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

    PubMed Central

    Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

    2008-01-01

    Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

  17. Live cell imaging combined with high-energy single-ion microbeam

    NASA Astrophysics Data System (ADS)

    Guo, Na; Du, Guanghua; Liu, Wenjing; Guo, Jinlong; Wu, Ruqun; Chen, Hao; Wei, Junzhe

    2016-03-01

    DNA strand breaks can lead to cell carcinogenesis or cell death if not repaired rapidly and efficiently. An online live cell imaging system was established at the high energy microbeam facility at the Institute of Modern Physics to study early and fast cellular response to DNA damage after high linear energy transfer ion radiation. The HT1080 cells expressing XRCC1-RFP were irradiated with single high energy nickel ions, and time-lapse images of the irradiated cells were obtained online. The live cell imaging analysis shows that strand-break repair protein XRCC1 was recruited to the ion hit position within 20 s in the cells and formed bright foci in the cell nucleus. The fast recruitment of XRCC1 at the ion hits reached a maximum at about 200 s post-irradiation and then was followed by a slower release into the nucleoplasm. The measured dual-exponential kinetics of XRCC1 protein are consistent with the proposed consecutive reaction model, and the measurements obtained that the reaction rate constant of the XRCC1 recruitment to DNA strand break is 1.2 × 10-3 s-1 and the reaction rate constant of the XRCC1 release from the break-XRCC1 complex is 1.2 × 10-2 s-1.

  18. Establishment of a 12-gene expression signature to predict colon cancer prognosis

    PubMed Central

    Zhao, Guangxi; Dong, Pingping; Wu, Bingrui

    2018-01-01

    A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with

  19. Signal-3L: A 3-layer approach for predicting signal peptides.

    PubMed

    Shen, Hong-Bin; Chou, Kuo-Chen

    2007-11-16

    Functioning as an "address tag" that directs nascent proteins to their proper cellular and extracellular locations, signal peptides have become a crucial tool in finding new drugs or reprogramming cells for gene therapy. To effectively and timely use such a tool, however, the first important thing is to develop an automated method for rapidly and accurately identifying the signal peptide for a given nascent protein. With the avalanche of new protein sequences generated in the post-genomic era, the challenge has become even more urgent and critical. In this paper, we have developed a novel method for predicting signal peptide sequences and their cleavage sites in human, plant, animal, eukaryotic, Gram-positive, and Gram-negative protein sequences, respectively. The new predictor is called Signal-3L that consists of three prediction engines working, respectively, for the following three progressively deepening layers: (1) identifying a query protein as secretory or non-secretory by an ensemble classifier formed by fusing many individual OET-KNN (optimized evidence-theoretic K nearest neighbor) classifiers operated in various dimensions of PseAA (pseudo amino acid) composition spaces; (2) selecting a set of candidates for the possible signal peptide cleavage sites of a query secretory protein by a subsite-coupled discrimination algorithm; (3) determining the final cleavage site by fusing the global sequence alignment outcome for each of the aforementioned candidates through a voting system. Signal-3L is featured by high success prediction rates with short computational time, and hence is particularly useful for the analysis of large-scale datasets. Signal-3L is freely available as a web-server at http://chou.med.harvard.edu/bioinf/Signal-3L/ or http://202.120.37.186/bioinf/Signal-3L, where, to further support the demand of the related areas, the signal peptides identified by Signal-3L for all the protein entries in Swiss-Prot databank that do not have signal peptide

  20. Variables Predicting Prospective Biology Teachers' Acceptance Perceptions Regarding Gene Technology

    ERIC Educational Resources Information Center

    Yilmaz, Mirac; Demirhan, Haydar

    2014-01-01

    The different opinions on products and applications of gene technology (GT) draw attention to the training and education activities related to GT. The purpose of this study is to review some variables predicting the acceptance perception regarding GT, and to investigate their changes at levels. The prospective teachers' subjective knowledge and…

  1. Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn

    PubMed Central

    Maron, Jill L.; Hwang, Jooyeon S.; Pathak, Subash; Ruthazer, Robin; Russell, Ruby L.; Alterovitz, Gil

    2014-01-01

    Objective To combine mathematical modeling of salivary gene expression microarray data and systems biology annotation with RT-qPCR amplification to identify (phase I) and validate (phase II) salivary biomarker analysis for the prediction of oral feeding readiness in preterm infants. Study design Comparative whole transcriptome microarray analysis from 12 preterm newborns pre- and post-oral feeding success was used for computational modeling and systems biology analysis to identify potential salivary transcripts associated with oral feeding success (phase I). Selected gene expression biomarkers (15 from computational modeling; 6 evidence-based; and 3 reference) were evaluated by RT-qPCR amplification on 400 salivary samples from successful (n=200) and unsuccessful (n=200) oral feeders (phase II). Genes, alone and in combination, were evaluated by a multivariate analysis controlling for sex and post-conceptional age (PCA) to determine the probability that newborns achieved successful oral feeding. Results Advancing post-conceptional age (p < 0.001) and female sex (p = 0.05) positively predicted an infant’s ability to feed orally. A combination of five genes, NPY2R (hunger signaling), AMPK (energy homeostasis), PLXNA1 (olfactory neurogenesis), NPHP4 (visual behavior) and WNT3 (facial development), in addition to PCA and sex, demonstrated good accuracy for determining feeding success (AUROC = 0.78). Conclusions We have identified objective and biologically relevant salivary biomarkers that noninvasively assess a newborn’s developing brain, sensory and facial development as they relate to oral feeding success. Understanding the mechanisms that underlie the development of oral feeding readiness through translational and computational methods may improve clinical decision making while decreasing morbidities and health care costs. PMID:25620512

  2. The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

    PubMed

    Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

    2017-01-01

    Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

  3. Diagnostic and predictive value of urine PCA3 gene expression for the clinical management of patients with altered prostatic specific antigen.

    PubMed

    Rodón, N; Trías, I; Verdú, M; Román, R; Domínguez, A; Calvo, M; Banus, J M; Ballesta, A M; Maestro, M L; Puig, X

    2014-04-01

    Analyze the impact of the introduction of the study of PCA3 gene in post-prostatic massage urine in the clinical management of patients with PSA altered, evaluating its diagnostic ability and predictive value of tumor aggressiveness. Observational, prospective, multicenter study of patients with suspected prostate cancer (PC) candidates for biopsy. We present a series of 670 consecutive samples of urine collected post-prostatic massage for three years in which we determined the "PCA3 score" (s-PCA3). Biopsy was only indicated in cases with s-positive PCA3. The s-PCA3 was positive in 43.7% of samples. In the 124 biopsies performed, the incidence of PC or atypical small acinar proliferation was 54%, reaching 68,6% in s-PCA3≥100. Statistically significant relationship between the s-PCA3 and tumor grade was demonstrated. In cases with s-PCA3 between 35 and 50 only 23% of PC were high grade (Gleason≥7), compared to 76.7% in cases with s-PCA3 over 50. There was a statistically significant correlation between s-PCA3 and cylinders affected. Both relationships were confirmed by applying a log-linear model. The incorporation of PCA3 can avoid the need for biopsies in 54% of patients. s-PCA3 positivity increases the likelihood of a positive biopsy, especially in higher s-PCA3 100 (68.6%). s-PCA3 is also an indicator of tumor aggressiveness and provides essential information in making treatment decisions. Copyright © 2013 AEU. Published by Elsevier Espana. All rights reserved.

  4. A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

    DTIC Science & Technology

    2015-10-01

    1 Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors 5a. CONTRACT NUMBER W81XWH...BRCAlike, i.e. not HR deficient and are resistant to PARPis but are sensitive to platinum . These tumors exhibit alterations in another DNA repair

  5. Applicability of a gene expression based prediction method to SD and Wistar rats: an example of CARCINOscreen®.

    PubMed

    Matsumoto, Hiroshi; Saito, Fumiyo; Takeyoshi, Masahiro

    2015-12-01

    Recently, the development of several gene expression-based prediction methods has been attempted in the fields of toxicology. CARCINOscreen® is a gene expression-based screening method to predict carcinogenicity of chemicals which target the liver with high accuracy. In this study, we investigated the applicability of the gene expression-based screening method to SD and Wistar rats by using CARCINOscreen®, originally developed with F344 rats, with two carcinogens, 2,4-diaminotoluen and thioacetamide, and two non-carcinogens, 2,6-diaminotoluen and sodium benzoate. After the 28-day repeated dose test was conducted with each chemical in SD and Wistar rats, microarray analysis was performed using total RNA extracted from each liver. Obtained gene expression data were applied to CARCINOscreen®. Predictive scores obtained by the CARCINOscreen® for known carcinogens were > 2 in all strains of rats, while non-carcinogens gave prediction scores below 0.5. These results suggested that the gene expression based screening method, CARCINOscreen®, can be applied to SD and Wistar rats, widely used strains in toxicological studies, by setting of an appropriate boundary line of prediction score to classify the chemicals into carcinogens and non-carcinogens.

  6. Aberrant gene methylation in non-neoplastic mucosa as a predictive marker of ulcerative colitis-associated CRC.

    PubMed

    Scarpa, Marco; Scarpa, Melania; Castagliuolo, Ignazio; Erroi, Francesca; Kotsafti, Andromachi; Basato, Silvia; Brun, Paola; D'Incà, Renata; Rugge, Massimo; Angriman, Imerio; Castoro, Carlo

    2016-03-01

    BACKGROUND PROMOTER: hypermethylation plays a major role in cancer through transcriptional silencing of critical genes. The aim of our study is to evaluate the methylation status of these genes in the colonic mucosa without dysplasia or adenocarcinoma at the different steps of sporadic and UC-related carcinogenesis and to investigate the possible role of genomic methylation as a marker of CRC. The expression of Dnmts 1 and 3A was significantly increased in UC-related carcinogenesis compared to non inflammatory colorectal carcinogenesis. In non-neoplastic colonic mucosa, the number of methylated genes resulted significantly higher in patients with CRC and in those with UC-related CRC compared to the HC and UC patients and patients with dysplastic lesion of the colon. The number of methylated genes in non-neoplastic colonic mucosa predicted the presence of CRC with good accuracy either in non inflammatory and inflammatory related CRC. Colonic mucosal samples were collected from healthy subjects (HC) (n = 30) and from patients with ulcerative colitis (UC) (n = 29), UC and dysplasia (n = 14), UC and cancer (n = 10), dysplastic adenoma (n = 14), and colon adenocarcinoma (n = 10). DNA methyltransferases-1, -3a, -3b, mRNA expression were quantified by real time qRT-PCR. The methylation status of CDH13, APC, MLH1, MGMT1 and RUNX3 gene promoters was assessed by methylation-specific PCR. Methylation status of APC, CDH13, MGMT, MLH1 and RUNX3 in the non-neoplastic mucosa may be used as a marker of CRC: these preliminary results could allow for the adjustment of a patient's surveillance interval and to select UC patients who should undergo intensive surveillance.

  7. Predicting gene expression levels from codon biases in alpha-proteobacterial genomes.

    PubMed

    Karlin, Samuel; Barnett, Melanie J; Campbell, Allan M; Fisher, Robert F; Mrazek, Jan

    2003-06-10

    Predicted highly expressed (PHX) genes in five currently available high G+C complete alpha-proteobacterial genomes are analyzed. These include: the nitrogen-fixing plant symbionts Sinorhizobium meliloti (SINME) and Mesorhizobium loti (MESLO), the nonpathogenic aquatic bacterium Caulobacter crescentus (CAUCR), the plant pathogen Agrobacterium tumefaciens (AGRTU), and the mammalian pathogen Brucella melitensis (BRUME). Three of these genomes, SINME, AGRTU, and BRUME, contain multiple chromosomes or megaplasmids (>1 Mb length). PHX genes in these genomes are concentrated mainly in the major (largest) chromosome with few PHX genes found in the secondary chromosomes and megaplasmids. Tricarboxylic acid cycle and aerobic respiration genes are strongly PHX in all five genomes, whereas anaerobic pathways of glycolysis and fermentation are mostly not PHX. Only in MESLO (but not SINME) and BRUME are most glycolysis genes PHX. Many flagellar genes are PHX in MESLO and CAUCR, but mostly are not PHX in SINME and AGRTU. The nonmotile BRUME also carries many flagellar genes but these are generally not PHX and all but one are located in the second chromosome. CAUCR stands out among available prokaryotic genomes with 25 PHX TonB-dependent receptors. These are putatively involved in uptake of iron ions and other nonsoluble compounds.

  8. Biological Networks for Predicting Chemical Hepatocarcinogenicity Using Gene Expression Data from Treated Mice and Relevance across Human and Rat Species

    PubMed Central

    Thomas, Reuben; Thomas, Russell S.; Auerbach, Scott S.; Portier, Christopher J.

    2013-01-01

    Background Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. Objectives To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. Methods Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. Results Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. Conclusions Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species. PMID:23737943

  9. Nucleotide sequence and expression of a novel pectate lyase gene (pel-3) and a closely linked endopolygalacturonase gene (peh-1) of Erwinia carotovora subsp. carotovora 71.

    PubMed Central

    Liu, Y; Chatterjee, A; Chatterjee, A K

    1994-01-01

    Our previous genetic analysis (J. W. Willis, J. K. Engwall, and A. K. Chatterjee, Phytopathology 77:1199-1205, 1987) had revealed a tight linkage between pel-3 (pel, pectate lyase gene) and peh-1 (peh, polygalacturonase gene) within the chromosome of Erwinia carotovora subsp. carotovora 71. Nucleotide sequencing, transcript assays, and expression of enzymatic activities in Escherichia coli have now confirmed that a 3,500-bp segment contains the open reading frames (ORFs) for Pel-3 and Peh-1. The 1,041-bp pel-3 ORF and the 1,206-bp peh-1 ORF are separated by a 579-bp sequence. The genes are transcribed divergently from their own promoters. In E. coli and E. carotovora subsp. carotovora 71, peh-1 is better expressed than pel-3. However, plant signals activate the expression of both the genes in E. carotovora subsp. carotovora. A consensus integration host factor (IHF)-binding sequence upstream of pel-3 appears physiologically significant, since pel-3 promoter activity is higher in an E. coli IHF+ strain than in an IHF- strain. While peh-1 has extensive homology with plant and bacterial peh genes, pel-3 appears not to have significant homology with the pel genes belonging to the pelBC, pelADE, or periplasmic pel families. Pel-3 also is unusual in that it is predicted to contain an ATP- and GTP-binding site motif A (P-loop) not found in the other Pels. Images PMID:8074530

  10. [The value of 5-HTT gene polymorphism for the assessment and prediction of male adolescence violence].

    PubMed

    Yu, Yue; Liu, Xiang; Yang, Zhen-xing; Qiu, Chang-jian; Ma, Xiao-hong

    2012-08-01

    To establish an adolescent violence crime prediction model, and to assess the value of serotonin transporter (5-HTT) gene polymorphism for the assessment and prediction of violent crime. Investigative tools were used to analyze the difference in personality dimensions, social support, coping styles, aggressiveness, impulsivity, and family condition scale between 223 adolescents with violence behavior and 148 adolescents without violence behavior. The distribution of 5-HTT gene polymorphisms (5-HTTLPR and 5-HTTVNTR) was compared between the two groups. The role of 5-HTT gene polymorphism on adolescent personality, impulsion and aggression scale also was also analyzed. Stepwise logistic regression was used to establish a predictive model for adolescent violent crime. Significant difference was found between the violence group and the control group on multiple dimensions of psychology and environment scales. However, no statistical difference was found with regard to the 5-HTT genotypes and alleles between adolescents with violent behaviors and normal controls. The rate of prediction accuracy was not significantly improved when 5-HTT gene polymorphism was taken into the model. The violent crime of adolescents was closely related with social and environmental factors. No association was found between 5-HTT polymorphisms and adolescent violence criminal behavior.

  11. Polymorphisms in metabolism and repair genes affects DNA damage caused by open-cast coal mining exposure.

    PubMed

    Espitia-Pérez, Lyda; Sosa, Milton Quintana; Salcedo-Arteaga, Shirley; León-Mejía, Grethel; Hoyos-Giraldo, Luz Stella; Brango, Hugo; Kvitko, Katia; da Silva, Juliana; Henriques, João A P

    2016-09-15

    Increasing evidence suggest that occupational exposure to open-cast coal mining residues like dust particles, heavy metals and Polycyclic Aromatic Hydrocarbons (PAHs) may cause a wide range of DNA damage and genomic instability that could be associated to initial steps in cancer development and other work-related diseases. The aim of our study was to evaluate if key polymorphisms in metabolism genes CYP1A1Msp1, GSTM1Null, GSTT1Null and DNA repair genes XRCC1Arg194Trp and hOGG1Ser326Cys could modify individual susceptibility to adverse coal exposure effects, considering the DNA damage (Comet assay) and micronucleus formation in lymphocytes (CBMN) and buccal mucosa cells (BMNCyt) as endpoints for genotoxicity. The study population is comprised of 200 healthy male subjects, 100 open-cast coal-mining workers from "El Cerrejón" (world's largest open-cast coal mine located in Guajira - Colombia) and 100 non-exposed referents from general population. The data revealed a significant increase of CBMN frequency in peripheral lymphocytes of occupationally exposed workers carrying the wild-type variant of GSTT1 (+) gene. Exposed subjects carrying GSTT1null polymorphism showed a lower micronucleus frequency compared with their positive counterparts (FR: 0.83; P=0.04), while BMNCyt, frequency and Comet assay parameters in lymphocytes: Damage Index (DI) and percentage of DNA in the tail (Tail % DNA) were significantly higher in exposed workers with the GSTM1Null polymorphism. Other exfoliated buccal mucosa abnormalities related to cell death (Karyorrhexis and Karyolysis) were increased in GSTT/M1Null carriers. Nuclear buds were significantly higher in workers carrying the CYP1A1Msp1 (m1/m2, m2/m2) allele. Moreover, BMNCyt frequency and Comet assay parameters were significantly lower in exposed carriers of XRCC1Arg194Trp (Arg/Trp, Trp/Trp) and hOGG1Ser326Cys (Ser/Cys, Cys/Cys), thereby providing new data to the increasing evidence about the protective role of these polymorphisms

  12. Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

    PubMed

    Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

    2015-05-13

    Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico

  13. Sequence diversity within the reovirus S2 gene: reovirus genes reassort in nature, and their termini are predicted to form a panhandle motif.

    PubMed Central

    Chapell, J D; Goral, M I; Rodgers, S E; dePamphilis, C W; Dermody, T S

    1994-01-01

    To better understand genetic diversity within mammalian reoviruses, we determined S2 nucleotide and deduced sigma 2 amino acid sequences of nine reovirus strains and compared these sequences with those of prototype strains of the three reovirus serotypes. The S2 gene and sigma 2 protein are highly conserved among the four type 1, one type 2, and seven type 3 strains studied. Phylogenetic analyses based on S2 nucleotide sequences of the 12 reovirus strains indicate that diversity within the S2 gene is independent of viral serotype. Additionally, we found marked topological differences between phylogenetic trees generated from S1 and S2 gene nucleotide sequences of the seven type 3 strains. These results demonstrate that reovirus S1 and S2 genes have distinct evolutionary histories, thus providing phylogenetic evidence for lateral transfer of reovirus genes in nature. When variability among the 12 sigma 2-encoding S2 nucleotide sequences was analyzed at synonymous positions, we found that approximately 60 nucleotides at the 5' terminus and 30 nucleotides at the 3' terminus were markedly conserved in comparison with other sigma 2-encoding regions of S2. Predictions of RNA secondary structures indicate that the more conserved S2 sequences participate in the formation of an extended region of duplex RNA interrupted by a pair of stem-loops. Among the 12 deduced sigma 2 amino acid sequences examined, substitutions were observed at only 11% of amino acid positions. This finding suggests that constraints on the structure or function of sigma 2, perhaps in part because of its location in the virion core, have limited sequence diversity within this protein. PMID:8289378

  14. Identification of cancer cytotoxic modulators of PDE3A by predictive chemogenomics

    PubMed Central

    de Waal, Luc; Lewis, Timothy A.; Rees, Matthew G.; Tsherniak, Aviad; Wu, Xiaoyun; Choi, Peter S.; Gechijian, Lara; Hartigan, Christina; Faloon, Patrick W.; Hickey, Mark J.; Tolliday, Nicola; Carr, Steven A.; Clemons, Paul A.; Munoz, Benito; Wagner, Bridget K.; Shamji, Alykhan F.; Koehler, Angela N.; Schenone, Monica; Burgin, Alex B.; Schreiber, Stuart L.; Greulich, Heidi; Meyerson, Matthew

    2015-01-01

    High cancer death rates indicate the need for new anti-cancer therapeutic agents. Approaches to discover new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds by phenotypic compound library screening and target deconvolution by predictive chemogenomics. We found that sensitivity to 6-(4-(diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one, or DNMDP, across 766 cancer cell lines correlates with expression of the phosphodiesterase 3A gene, PDE3A. Like DNMDP, a subset of known PDE3A inhibitors kill selected cancer cells while others do not. Furthermore, PDE3A depletion leads to DNMDP resistance. We demonstrated that DNMDP binding to PDE3A promotes an interaction between PDE3A and Schlafen 12 (SLFN12), suggesting a neomorphic activity. Co-expression of SLFN12 with PDE3A correlates with DNMDP sensitivity, while depletion of SLFN12 results in decreased DNMDP sensitivity. Our results implicate PDE3A modulators as candidate cancer therapeutic agents and demonstrate the power of predictive chemogenomics in small-molecule discovery. PMID:26656089

  15. A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis.

    PubMed

    Yin, Xia; Wang, Xiaojie; Shen, Boqiang; Jing, Ying; Li, Qing; Cai, Mei-Chun; Gu, Zhuowei; Yang, Qi; Zhang, Zhenfeng; Liu, Jin; Li, Hongxia; Di, Wen; Zhuang, Guanglei

    2016-08-08

    We have previously reported surrogate biomarkers of VEGF pathway activities with the potential to provide predictive information for anti-VEGF therapies. The aim of this study was to systematically evaluate a new VEGF-dependent gene signature (VDGs) in relation to molecular subtypes of ovarian cancer and patient prognosis. Using microarray profiling and cross-species analysis, we identified 140-gene mouse VDGs and corresponding 139-gene human VDGs, which displayed enrichment of vasculature and basement membrane genes. In patients who received bevacizumab therapy and showed partial response, the expressions of VDGs (summarized to yield VDGs scores) were markedly decreased in post-treatment biopsies compared with pre-treatment baselines. In contrast, VDGs scores were not significantly altered following bevacizumab treatment in patients with stable or progressive disease. Analysis of VDGs in ovarian cancer showed that VDGs as a prognostic signature was able to predict patient outcome. Correlation estimation of VDGs scores and molecular features revealed that VDGs was overrepresented in mesenchymal subtype and BRCA mutation carriers. These findings highlighted the prognostic role of VEGF-mediated angiogenesis in ovarian cancer, and proposed a VEGF-dependent gene signature as a molecular basis for developing novel diagnostic strategies to aid patient selection for VEGF-targeted agents.

  16. Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

    PubMed Central

    Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

    2011-01-01

    Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

  17. Gene expression analysis in zebrafish embryos: a potential approach to predict effect concentrations in the fish early life stage test.

    PubMed

    Weil, Mirco; Scholz, Stefan; Zimmer, Michaela; Sacher, Frank; Duis, Karen

    2009-09-01

    Based on the hypothesis that analysis of gene expression could be used to predict chronic fish toxicity, the zebrafish (Danio rerio) embryo test (DarT), developed as a replacement method for the acute fish test, was expanded to a gene expression D. rerio embryo test (Gene-DarT). The effects of 14 substances on lethal and sublethal endpoints of the DarT and on expression of potential marker genes were investigated: the aryl hydrocarbon receptor 2, cytochrome P450 1A (cypla), heat shock protein 70, fizzy-related protein 1, the transcription factors v-maf musculoaponeurotic fibrosarcoma oncogene family protein g (avian) 1 and NF-E2-p45-related factor, and heme oxygenase 1 (hmox1). After exposure of zebrafish embryos for 48 h, differential gene expression was evaluated using reverse transcriptase-polymerase chain reaction, gel electrophoresis, and densitometric analysis of the gels. All tested compounds significantly affected the expression of at least one potential marker gene, with cyp1a and hmox1 being most sensitive. Lowest-observed-effect concentrations (LOECs) for gene expression were below concentrations resulting in 10% lethal effects in the DarT. For 10 (3,4- and 3,5-dichloroaniline, 1,4-dichlorobenzene, 2,4-dinitrophenol, atrazine, parathion-ethyl, chlorotoluron, genistein, 4-nitroquinoline-1-oxide, and cadmium) out of the 14 tested substances, LOEC values derived with the Gene-DarT differ by a factor of less than 10 from LOEC values of fish early life stage tests with zebrafish. For pentachloroaniline and pentachlorobenzene, the Gene-DarT showed a 23- and 153-fold higher sensitivity, respectively, while for lindane, it showed a 13-fold lower sensitivity. For ivermectin, the Gene-DarT was by a factor of more than 1,000 less sensitive than the acute fish test. The results of the present study indicate that gene expression analysis in zebrafish embryos could principally be used to predict effect concentrations in the fish early life stage test.

  18. Live cell imaging combined with high-energy single-ion microbeam

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Guo, Na; Du, Guanghua, E-mail: gh-du@impcas.ac.cn; Liu, Wenjing

    DNA strand breaks can lead to cell carcinogenesis or cell death if not repaired rapidly and efficiently. An online live cell imaging system was established at the high energy microbeam facility at the Institute of Modern Physics to study early and fast cellular response to DNA damage after high linear energy transfer ion radiation. The HT1080 cells expressing XRCC1-RFP were irradiated with single high energy nickel ions, and time-lapse images of the irradiated cells were obtained online. The live cell imaging analysis shows that strand-break repair protein XRCC1 was recruited to the ion hit position within 20 s in themore » cells and formed bright foci in the cell nucleus. The fast recruitment of XRCC1 at the ion hits reached a maximum at about 200 s post-irradiation and then was followed by a slower release into the nucleoplasm. The measured dual-exponential kinetics of XRCC1 protein are consistent with the proposed consecutive reaction model, and the measurements obtained that the reaction rate constant of the XRCC1 recruitment to DNA strand break is 1.2 × 10{sup −3} s{sup −1} and the reaction rate constant of the XRCC1 release from the break-XRCC1 complex is 1.2 × 10{sup −2} s{sup −1}.« less

  19. Entropy-based gene ranking without selection bias for the predictive classification of microarray data.

    PubMed

    Furlanello, Cesare; Serafini, Maria; Merler, Stefano; Jurman, Giuseppe

    2003-11-06

    We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process). With E-RFE, we speed up the recursive feature elimination (RFE) with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

  20. Prediction of essential proteins based on gene expression programming.

    PubMed

    Zhong, Jiancheng; Wang, Jianxin; Peng, Wei; Zhang, Zhen; Pan, Yi

    2013-01-01

    Essential proteins are indispensable for cell survive. Identifying essential proteins is very important for improving our understanding the way of a cell working. There are various types of features related to the essentiality of proteins. Many methods have been proposed to combine some of them to predict essential proteins. However, it is still a big challenge for designing an effective method to predict them by integrating different features, and explaining how these selected features decide the essentiality of protein. Gene expression programming (GEP) is a learning algorithm and what it learns specifically is about relationships between variables in sets of data and then builds models to explain these relationships. In this work, we propose a GEP-based method to predict essential protein by combing some biological features and topological features. We carry out experiments on S. cerevisiae data. The experimental results show that the our method achieves better prediction performance than those methods using individual features. Moreover, our method outperforms some machine learning methods and performs as well as a method which is obtained by combining the outputs of eight machine learning methods. The accuracy of predicting essential proteins can been improved by using GEP method to combine some topological features and biological features.

  1. CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.

    PubMed

    Nikulova, Anna A; Favorov, Alexander V; Sutormin, Roman A; Makeev, Vsevolod J; Mironov, Andrey A

    2012-07-01

    Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

  2. High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity.

    PubMed

    De Wolf, Hans; Cougnaud, Laure; Van Hoorde, Kirsten; De Bondt, An; Wegner, Joerg K; Ceulemans, Hugo; Göhlmann, Hinrich

    2018-04-01

    By adding biological information, beyond the chemical properties and desired effect of a compound, uncharted compound areas and connections can be explored. In this study, we add transcriptional information for 31K compounds of Janssen's primary screening deck, using the HT L1000 platform and assess (a) the transcriptional connection score for generating compound similarities, (b) machine learning algorithms for generating target activity predictions, and (c) the scaffold hopping potential of the resulting hits. We demonstrate that the transcriptional connection score is best computed from the significant genes only and should be interpreted within its confidence interval for which we provide the stats. These guidelines help to reduce noise, increase reproducibility, and enable the separation of specific and promiscuous compounds. The added value of machine learning is demonstrated for the NR3C1 and HSP90 targets. Support Vector Machine models yielded balanced accuracy values ≥80% when the expression values from DDIT4 & SERPINE1 and TMEM97 & SPR were used to predict the NR3C1 and HSP90 activity, respectively. Combining both models resulted in 22 new and confirmed HSP90-independent NR3C1 inhibitors, providing two scaffolds (i.e., pyrimidine and pyrazolo-pyrimidine), which could potentially be of interest in the treatment of depression (i.e., inhibiting the glucocorticoid receptor (i.e., NR3C1), while leaving its chaperone, HSP90, unaffected). As such, the initial hit rate increased by a factor 300, as less, but more specific chemistry could be screened, based on the upfront computed activity predictions.

  3. A yeast functional screen predicts new candidate ALS disease genes

    PubMed Central

    Couthouis, Julien; Hart, Michael P.; Shorter, James; DeJesus-Hernandez, Mariely; Erion, Renske; Oristano, Rachel; Liu, Annie X.; Ramos, Daniel; Jethava, Niti; Hosangadi, Divya; Epstein, James; Chiang, Ashley; Diaz, Zamia; Nakaya, Tadashi; Ibrahim, Fadia; Kim, Hyung-Jun; Solski, Jennifer A.; Williams, Kelly L.; Mojsilovic-Petrovic, Jelena; Ingre, Caroline; Boylan, Kevin; Graff-Radford, Neill R.; Dickson, Dennis W.; Clay-Falcone, Dana; Elman, Lauren; McCluskey, Leo; Greene, Robert; Kalb, Robert G.; Lee, Virginia M.-Y.; Trojanowski, John Q.; Ludolph, Albert; Robberecht, Wim; Andersen, Peter M.; Nicholson, Garth A.; Blair, Ian P.; King, Oliver D.; Bonini, Nancy M.; Van Deerlin, Vivianna; Rademakers, Rosa; Mourelatos, Zissimos; Gitler, Aaron D.

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating and universally fatal neurodegenerative disease. Mutations in two related RNA-binding proteins, TDP-43 and FUS, that harbor prion-like domains, cause some forms of ALS. There are at least 213 human proteins harboring RNA recognition motifs, including FUS and TDP-43, raising the possibility that additional RNA-binding proteins might contribute to ALS pathogenesis. We performed a systematic survey of these proteins to find additional candidates similar to TDP-43 and FUS, followed by bioinformatics to predict prion-like domains in a subset of them. We sequenced one of these genes, TAF15, in patients with ALS and identified missense variants, which were absent in a large number of healthy controls. These disease-associated variants of TAF15 caused formation of cytoplasmic foci when expressed in primary cultures of spinal cord neurons. Very similar to TDP-43 and FUS, TAF15 aggregated in vitro and conferred neurodegeneration in Drosophila, with the ALS-linked variants having a more severe effect than wild type. Immunohistochemistry of postmortem spinal cord tissue revealed mislocalization of TAF15 in motor neurons of patients with ALS. We propose that aggregation-prone RNA-binding proteins might contribute very broadly to ALS pathogenesis and the genes identified in our yeast functional screen, coupled with prion-like domain prediction analysis, now provide a powerful resource to facilitate ALS disease gene discovery. PMID:22065782

  4. Predicting chemical bioavailability using microarray gene expression data and regression modeling: A tale of three explosive compounds.

    PubMed

    Gong, Ping; Nan, Xiaofei; Barker, Natalie D; Boyd, Robert E; Chen, Yixin; Wilkins, Dawn E; Johnson, David R; Suedel, Burton C; Perkins, Edward J

    2016-03-08

    Chemical bioavailability is an important dose metric in environmental risk assessment. Although many approaches have been used to evaluate bioavailability, not a single approach is free from limitations. Previously, we developed a new genomics-based approach that integrated microarray technology and regression modeling for predicting bioavailability (tissue residue) of explosives compounds in exposed earthworms. In the present study, we further compared 18 different regression models and performed variable selection simultaneously with parameter estimation. This refined approach was applied to both previously collected and newly acquired earthworm microarray gene expression datasets for three explosive compounds. Our results demonstrate that a prediction accuracy of R(2) = 0.71-0.82 was achievable at a relatively low model complexity with as few as 3-10 predictor genes per model. These results are much more encouraging than our previous ones. This study has demonstrated that our approach is promising for bioavailability measurement, which warrants further studies of mixed contamination scenarios in field settings.

  5. Effect of fenofibrate on oxidative DNA damage and on gene expression related to cell proliferation and apoptosis in rats.

    PubMed

    Nishimura, Jihei; Dewa, Yasuaki; Muguruma, Masako; Kuroiwa, Yuichi; Yasuno, Hiroaki; Shima, Tomomi; Jin, Mailan; Takahashi, Miwa; Umemura, Takashi; Mitsumori, Kunitoshi

    2007-05-01

    To investigate the relationship between fenofibrate (FF) and oxidative stress, enzymatic, histopathological, and molecular biological analyses were performed in the liver of male F344 rats fed 2 doses of FF (Experiment 1; 0 and 6000 ppm) for 3 weeks and 3 doses (Experiment 2; 0, 3000, and 6000 ppm) for 9 weeks. FF treatment increased the activity of enzymes such as carnitine acetyltransferase, carnitine palmitoyltransferase, fatty acyl-CoA oxidizing system, and catalase in the liver. However, it decreased those of superoxide dismutase in the liver in both experiments. Increased 8-hydroxy-2'-deoxyguanosine levels in liver DNA and lipofuscin accumulation were observed in the treated rats of Experiment 2. In vitro measurement of reactive oxygen species (ROS) in rat liver microsomes revealed a dose-dependent increase due to FF treatment. Microarray (only Experiment 1) or real-time reverse transcription-polymerase chain reaction analyses revealed that the expression levels of metabolism and DNA repair-related genes such as Aco, Cyp4a1, Cat, Yc2, Gpx2, Apex1, Xrcc5, Mgmt, Mlh1, Gadd45a, and Nbn were increased in FF-treated rats. These results provide evidence of a direct or indirect relationship between oxidative stress and FF treatment. In addition, increases in the expression levels of cell cycle-related genes such as Chek1, Cdc25a, and Ccdn1; increases in the expression levels of cell proliferation-related genes such as Hdgfrp3 and Vegfb; and fluctuations in the expression levels of apoptosis-related genes such as Casp11 and Trp53inp1 were observed in these rats. This suggests that cell proliferation induction, apoptosis suppression, and DNA damage due to oxidative stresses are probably involved in the mechanism of hepatocarcinogenesis due to FF in rats.

  6. A Novel Method to Predict Highly Expressed Genes Based on Radius Clustering and Relative Synonymous Codon Usage.

    PubMed

    Tran, Tuan-Anh; Vo, Nam Tri; Nguyen, Hoang Duc; Pham, Bao The

    2015-12-01

    Recombinant proteins play an important role in many aspects of life and have generated a huge income, notably in the industrial enzyme business. A gene is introduced into a vector and expressed in a host organism-for example, E. coli-to obtain a high productivity of target protein. However, transferred genes from particular organisms are not usually compatible with the host's expression system because of various reasons, for example, codon usage bias, GC content, repetitive sequences, and secondary structure. The solution is developing programs to optimize for designing a nucleotide sequence whose origin is from peptide sequences using properties of highly expressed genes (HEGs) of the host organism. Existing data of HEGs determined by practical and computer-based methods do not satisfy for qualifying and quantifying. Therefore, the demand for developing a new HEG prediction method is critical. We proposed a new method for predicting HEGs and criteria to evaluate gene optimization. Codon usage bias was weighted by amplifying the difference between HEGs and non-highly expressed genes (non-HEGs). The number of predicted HEGs is 5% of the genome. In comparison with Puigbò's method, the result is twice as good as Puigbò's one, in kernel ratio and kernel sensitivity. Concerning transcription/translation factor proteins (TF), the proposed method gives low TF sensitivity, while Puigbò's method gives moderate one. In summary, the results indicated that the proposed method can be a good optional applying method to predict optimized genes for particular organisms, and we generated an HEG database for further researches in gene design.

  7. Analysis of the aac(3)-VIa gene encoding a novel 3-N-acetyltransferase.

    PubMed Central

    Rather, P N; Mann, P A; Mierzwa, R; Hare, R S; Miller, G H; Shaw, K J

    1993-01-01

    Biochemical analysis (G. A. Papanicolaou, R. S. Hare, R. Mierzwa, and G. H. Miller, abstr. 152, Program Abstr. 29th Intersci. Conf. Antimicrob. Agents Chemother., 1989) demonstrated the presence of a novel 3-N-acetyltransferase in Enterobacter cloacae 88020217. This organism was resistant to gentamicin, and the MIC of 2'-N-ethylnetilmicin for it was fourfold lower than that of 6'-N-ethylnetilmicin, a resistance pattern which suggested 2'-acetylating activity. However, high-pressure liquid chromatography analysis demonstrated that the enzyme acetylated sisomicin in the 3 position. We have cloned the structural gene for this enzyme from a large (> 70-kb) conjugative plasmid present in E. cloacae. Subcloning experiments have localized the aac(3)-VIa gene to a 2.1-kb Sau3A fragment. The deduced AAC(3)-VIa protein showed 48% amino acid identity to the AAC(3)-IIa protein and 39% identity to the AAC(3)-VII protein. Examination of the 5'-flanking sequences demonstrated that the aac(3)-VIa gene was located 167 bp downstream of the aadA1 gene and was present in an integron. In addition, the aac(3)-VIa gene is also downstream of a 59-base element often seen in an integron environment. Primer extension analysis has identified a promoter for the aac(3)-VIa gene downstream of both the aadA1 gene and a 59-base element. Images PMID:8257126

  8. Computational Prediction of miRNA Genes from Small RNA Sequencing Data

    PubMed Central

    Kang, Wenjing; Friedländer, Marc R.

    2015-01-01

    Next-generation sequencing now for the first time allows researchers to gage the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. microRNAs (miRNAs) are 22 nucleotide small RNAs (sRNAs) that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq), which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here, we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field. PMID:25674563

  9. Highly Predictive Reprogramming of tRNA Modifications Is Linked to Selective Expression of Codon-Biased Genes

    PubMed Central

    2016-01-01

    Cells respond to stress by controlling gene expression at several levels, with little known about the role of translation. Here, we demonstrate a coordinated translational stress response system involving stress-specific reprogramming of tRNA wobble modifications that leads to selective translation of codon-biased mRNAs representing different classes of critical response proteins. In budding yeast exposed to four oxidants and five alkylating agents, tRNA modification patterns accurately distinguished among chemically similar stressors, with 14 modified ribonucleosides forming the basis for a data-driven model that predicts toxicant chemistry with >80% sensitivity and specificity. tRNA modification subpatterns also distinguish SN1 from SN2 alkylating agents, with SN2-induced increases in m3C in tRNA mechanistically linked to selective translation of threonine-rich membrane proteins from genes enriched with ACC and ACT degenerate codons for threonine. These results establish tRNA modifications as predictive biomarkers of exposure and illustrate a novel regulatory mechanism for translational control of cell stress response. PMID:25772370

  10. A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

    PubMed Central

    Kohonen, Pekka; Parkkinen, Juuso A.; Willighagen, Egon L.; Ceder, Rebecca; Wennerberg, Krister; Kaski, Samuel; Grafström, Roland C.

    2017-01-01

    Predicting unanticipated harmful effects of chemicals and drug molecules is a difficult and costly task. Here we utilize a ‘big data compacting and data fusion’—concept to capture diverse adverse outcomes on cellular and organismal levels. The approach generates from transcriptomics data set a ‘predictive toxicogenomics space’ (PTGS) tool composed of 1,331 genes distributed over 14 overlapping cytotoxicity-related gene space components. Involving ∼2.5 × 108 data points and 1,300 compounds to construct and validate the PTGS, the tool serves to: explain dose-dependent cytotoxicity effects, provide a virtual cytotoxicity probability estimate intrinsic to omics data, predict chemically-induced pathological states in liver resulting from repeated dosing of rats, and furthermore, predict human drug-induced liver injury (DILI) from hepatocyte experiments. Analysing 68 DILI-annotated drugs, the PTGS tool outperforms and complements existing tests, leading to a hereto-unseen level of DILI prediction accuracy. PMID:28671182

  11. Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

    PubMed Central

    Lamb, John R.; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Hao, Ke; Chudin, Eugene; Fraser, Hunter B.; Millstein, Joshua; Ferguson, Mark; Suver, Christine; Ivanovska, Irena; Scott, Martin; Philippar, Ulrike; Bansal, Dimple; Zhang, Zhan; Burchard, Julja; Smith, Ryan; Greenawalt, Danielle; Cleary, Michele; Derry, Jonathan; Loboda, Andrey; Watters, James; Poon, Ronnie T. P.; Fan, Sheung T.; Yeung, Chun; Lee, Nikki P. Y.; Guinney, Justin; Molony, Cliona; Emilsson, Valur; Buser-Doepner, Carolyn; Zhu, Jun; Friend, Stephen; Mao, Mao; Shaw, Peter M.; Dai, Hongyue; Luk, John M.; Schadt, Eric E.

    2011-01-01

    Background In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. Methodology/Principal Findings Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ∼250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. Conclusions/Significance This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types. PMID:21750698

  12. Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

    PubMed Central

    Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

    2012-01-01

    About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

  13. A germline mutation in the BRCA1 3'UTR predicts Stage IV breast cancer.

    PubMed

    Dorairaj, Jemima J; Salzman, David W; Wall, Deirdre; Rounds, Tiffany; Preskill, Carina; Sullivan, Catherine A W; Lindner, Robert; Curran, Catherine; Lezon-Geyda, Kim; McVeigh, Terri; Harris, Lyndsay; Newell, John; Kerin, Michael J; Wood, Marie; Miller, Nicola; Weidhaas, Joanne B

    2014-06-10

    A germline, variant in the BRCA1 3'UTR (rs8176318) was previously shown to predict breast and ovarian cancer risk in women from high-risk families, as well as increased risk of triple negative breast cancer. Here, we tested the hypothesis that this variant predicts tumor biology, like other 3'UTR mutations in cancer. The impact of the BRCA1-3'UTR-variant on BRCA1 gene expression, and altered response to external stimuli was tested in vitro using a luciferase reporter assay. Gene expression was further tested in vivo by immunoflourescence staining on breast tumor tissue, comparing triple negative patient samples with the variant (TG or TT) or non-variant (GG) BRCA1 3'UTR. To determine the significance of the variant on clinically relevant endpoints, a comprehensive collection of West-Irish breast cancer patients were tested for the variant. Finally, an association of the variant with breast screening clinical phenotypes was evaluated using a cohort of women from the High Risk Breast Program at the University of Vermont. Luciferase reporters with the BRCA1-3'UTR-variant (T allele) displayed significantly lower gene expression, as well as altered response to external hormonal stimuli, compared to the non-variant 3'UTR (G allele) in breast cancer cell lines. This was confirmed clinically by the finding of reduced BRCA1 gene expression in triple negative samples from patients carrying the homozygous TT variant, compared to non-variant patients. The BRCA1-3'UTR-variant (TG or TT) also associated with a modest increased risk for developing breast cancer in the West-Irish cohort (OR=1.4, 95% CI 1.1-1.8, p=0.033). More importantly, patients with the BRCA1-3'UTR-variant had a 4-fold increased risk of presenting with Stage IV disease (p=0.018, OR=3.37, 95% CI 1.3-11.0). Supporting that this finding is due to tumor biology, and not difficulty screening, obese women with the BRCA1-3'UTR-variant had significantly less dense breasts (p=0.0398) in the Vermont cohort. A variant in

  14. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

    PubMed Central

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

    2017-01-01

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

  15. Genomic profiling is predictive of response to cisplatin treatment but not to PI3K inhibition in bladder cancer patient-derived xenografts

    PubMed Central

    Ramakrishnan, Swathi; Elbanna, May; Wang, Jianmin; Hu, Qiang; Glenn, Sean T.; Murakami, Mitsuko; Liu, Lu; Gomez, Eduardo Cortes; Sun, Yuchen; Conroy, Jacob; Miles, Kiersten Marie; Malathi, Kullappan; Ramaiah, Sudha; Anbarasu, Anand; Woloszynska-Read, Anna; Johnson, Candace S.; Conroy, Jeffrey; Liu, Song; Morrison, Carl D.; Pili, Roberto

    2016-01-01

    Purpose Effective systemic therapeutic options are limited for bladder cancer. In this preclinical study we tested whether bladder cancer gene alterations may be predictive of treatment response. Experimental design We performed genomic profiling of two bladder cancer patient derived tumor xenografts (PDX). We optimized the exome sequence analysis method to overcome the mouse genome interference. Results We identified a number of somatic mutations, mostly shared by the primary tumors and PDX. In particular, BLCAb001, which is less responsive to cisplatin than BLCAb002, carried non-sense mutations in several genes associated with cisplatin resistance, including MLH1, BRCA2, and CASP8. Furthermore, RNA-Seq analysis revealed the overexpression of cisplatin resistance associated genes such as SLC7A11, TLE4, and IL1A in BLCAb001. Two different PIK3CA mutations, E542K and E545K, were identified in BLCAb001 and BLCAb002, respectively. Thus, we tested whether the genomic profiling was predictive of response to a dual PI3K/mTOR targeting agent, LY3023414. Despite harboring similar PIK3CA mutations, BLCAb001 and BLCAb002 exhibited differential response, both in vitro and in vivo. Sustained target modulation was observed in the sensitive model BLCAb002 but not in BLCAb001, as well as decreased autophagy. Interestingly, computational modelling of mutant structures and affinity binding to PI3K revealed that E542K mutation was associated with weaker drug binding than E545K. Conclusions Our results suggest that the presence of activating PIK3CA mutations may not necessarily predict in vivo treatment response to PI3K targeted therapies, while specific gene alterations may be predictive for cisplatin response in bladder cancer models and, potentially, in patients as well. PMID:27823983

  16. Comparative and evolutionary analysis of the 14-3-3 family genes in eleven fishes.

    PubMed

    Cao, Jun; Tan, Xiaona

    2018-07-01

    14-3-3 proteins are a type of highly conserved acidic proteins, which are distributed over a wide variety of organisms and are involved in multiple cellular processes. While the comparative and evolutionary analysis of this gene family is unavailable in various fish species. In this study, we identified 101 putative 14-3-3 genes in 11 fish species and divided them into 5 groups via phylogenetic analysis. Synteny analysis implied conserved and dynamic evolution characteristics near the 14-3-3 gene loci in some vertebrates. We also found that some recombination events have accelerated the evolution of this gene family. Moreover, a positive selection site was also identified, and mutation of this site could reduce the 14-3-3 stability. Divergent expression profiles of the zebrafish 14-3-3 genes were further investigated under organophosphorus stress, suggesting that they may be involved in the different osmoregulation and immune response. The results will serve as a foundation for the further functional investigation into the 14-3-3 genes in fishes. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. Breast cancer risk associated with genotypic polymorphism of the nonhomologous end-joining genes: a multigenic study on cancer susceptibility.

    PubMed

    Fu, Yi-Ping; Yu, Jyh-Cherng; Cheng, Ting-Chih; Lou, M Ann; Hsu, Giu-Cheng; Wu, Chia-Yun; Chen, Sou-Tong; Wu, Hurng-Sheng; Wu, Pei-Ei; Shen, Chen-Yang

    2003-05-15

    The role of the familial breast cancer susceptibility genes, BRCA1 and BRCA2, in the homologous recombination pathway for DNA double-strand break (DSB) repair suggests that the mechanisms involved in DNA DSB repair are of particular etiological importance during breast tumorigenesis. However, there is currently no evidence for an association between breast cancer and the other DSB repair pathway, the nonhomologous end-joining (NHEJ) pathway. It is possible that, because this DNA repair pathway is so crucial for mammalian cells to maintain genomic stability, any severe defects in it would result in serious outcomes, such as genomic instability and cell death, and block subsequent cell outgrowth and tumor formation. Thus, only subtle defects arising from low-penetrance alleles would escape lethality accumulating essential genetic changes and be associated with cancer formation, and the tumorigenic contribution of these alleles would become more obvious if individual putative high-risk genotypes of each NHEJ gene act jointly. Furthermore, this joint effect might be modified by specific environmental factors, and we hypothesized that estrogen exposure might be one such factor because estrogen is suggested to cause DNA DSBs, triggering breast tumorigenesis. Because single nucleotide polymorphisms (SNPs) are the most subtle genetic variation in the genome, to examine these hypotheses, we have genotyped 30 SNPs in all five NHEJ genes (Ku70, Ku80, DNA-PKcs, Ligase IV, and XRCC4) in 254 primary breast cancer patients and 379 healthy controls. Support for these hypotheses came from the observations that (a) two SNPs in Ku70 and XRCC4 were associated with breast cancer risk (P < 0.05); (b) a trend toward increased risk of developing breast cancer was found in women harboring a greater number of putative high-risk genotypes of NHEJ genes (an adjusted odds ratio of 1.46 for having one additional putative high-risk genotype; 95% confidence interval, 1.19-1.80); (c) this

  18. Finding approximate gene clusters with Gecko 3.

    PubMed

    Winter, Sascha; Jahn, Katharina; Wehner, Stefanie; Kuchenbecker, Leon; Marz, Manja; Stoye, Jens; Böcker, Sebastian

    2016-11-16

    Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in <40 min. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children.

    PubMed

    Verhagen, Lilly M; Zomer, Aldert; Maes, Mailis; Villalba, Julian A; Del Nogal, Berenice; Eleveld, Marc; van Hijum, Sacha Aft; de Waard, Jacobus H; Hermans, Peter Wm

    2013-02-01

    Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Our data justify the further exploration of our signature set as biomarkers

  20. A predictive signature gene set for discriminating active from latent tuberculosis in Warao Amerindian children

    PubMed Central

    2013-01-01

    Background Tuberculosis (TB) continues to cause a high toll of disease and death among children worldwide. The diagnosis of childhood TB is challenged by the paucibacillary nature of the disease and the difficulties in obtaining specimens. Whereas scientific and clinical research efforts to develop novel diagnostic tools have focused on TB in adults, childhood TB has been relatively neglected. Blood transcriptional profiling has improved our understanding of disease pathogenesis of adult TB and may offer future leads for diagnosis and treatment. No studies applying gene expression profiling of children with TB have been published so far. Results We identified a 116-gene signature set that showed an average prediction error of 11% for TB vs. latent TB infection (LTBI) and for TB vs. LTBI vs. healthy controls (HC) in our dataset. A minimal gene set of only 9 genes showed the same prediction error of 11% for TB vs. LTBI in our dataset. Furthermore, this minimal set showed a significant discriminatory value for TB vs. LTBI for all previously published adult studies using whole blood gene expression, with average prediction errors between 17% and 23%. In order to identify a robust representative gene set that would perform well in populations of different genetic backgrounds, we selected ten genes that were highly discriminative between TB, LTBI and HC in all literature datasets as well as in our dataset. Functional annotation of these genes highlights a possible role for genes involved in calcium signaling and calcium metabolism as biomarkers for active TB. These ten genes were validated by quantitative real-time polymerase chain reaction in an additional cohort of 54 Warao Amerindian children with LTBI, HC and non-TB pneumonia. Decision tree analysis indicated that five of the ten genes were sufficient to classify 78% of the TB cases correctly with no LTBI subjects wrongly classified as TB (100% specificity). Conclusions Our data justify the further exploration of our

  1. Single-Nucleotide Polymorphisms Within the Thrombomodulin Gene (THBD) Predict Mortality in Patients With Graft-Versus-Host Disease.

    PubMed

    Rachakonda, Sivaramakrishna P; Penack, Olaf; Dietrich, Sascha; Blau, Olga; Blau, Igor Wolfgang; Radujkovic, Aleksandar; Isermann, Berend; Ho, Anthony D; Uharek, Lutz; Dreger, Peter; Kumar, Rajiv; Luft, Thomas

    2014-10-20

    Steroid-refractory graft-versus-host disease (GVHD) is a major and often fatal complication after allogeneic stem-cell transplantation (alloSCT). Although the pathophysiology of steroid refractoriness is not fully understood, evidence is accumulating that endothelial cell stress is involved, and endothelial thrombomodulin (THBD) plays a role in this process. Here we assess whether single-nucleotide polymorphisms (SNPs) within the THBD gene predict outcome after alloSCT. Seven SNPs within the THBD gene were studied (rs1962, rs1042579, rs1042580, rs3176123, rs3176124, rs3176126, and rs3176134) in a training cohort of 306 patients. The relevant genotypes were then validated in an independent cohort (n = 321). In the training cohort, an increased risk of nonrelapse mortality (NRM) was associated with three of seven SNPs tested: rs1962, rs1042579 (in linkage disequilibrium with rs3176123), and rs1042580. When patients were divided into risk groups (one v no high-risk SNP), a strong correlation with NRM was observed (hazard ratio [HR], 2.31; 95% CI, 1.36 to 3.95; P = .002). More specifically, NRM was predicted by THBD SNPs in patients who later developed GVHD (HR, 3.03; 95% CI, 1.61 to 5.68; P < .001) but not in patients without GVHD. In contrast, THBD SNPs did not predict incidence of acute GVHD. Multivariable analyses adjusting for clinical variables confirmed the independent effect of THBD SNPs on NRM. All findings could be reproduced in the validation cohort. THBD SNPs predict mortality of manifest GVHD but not the risk of acquiring GVHD, supporting the hypothesis that endothelial vulnerability contributes to GVHD refractoriness. © 2014 by American Society of Clinical Oncology.

  2. Two novel mutations in NOTCH3 gene causes cerebral autosomal dominant arteriopathy with subcritical infarct and leucoencephalopathy in two Chinese families.

    PubMed

    Zhu, Yuyou; Wang, Juan; Wu, Yuanbo; Wang, Guoping; Hu, Bai

    2015-01-01

    To investigate the genetic pathogenic causes of cerebral autosomal dominant arteriopathy with subcritical infarct and leucoencephalopathy (CADASIL) in two Chinese families, to provide the molecular basis for genetic counseling and antenatal diagnosis. The genetic mutation of gene NOTCH3 of propositus and family members was analyzed in these two CADASIL families by polymerase chain reaction and DNA sequencing technology directly. At the same time, the NOTCH3 gene mutation point of 100 healthy collators was detected, to explicit the pathogenic mutation by function prediction with Polyphen-2 and SIFT. Both propositus of the two families and patients with symptom were all accorded with the clinical features of CADASIL. It was shown by DNA sequencing that the 19(th) exon [c. 3043 T > A (p.Cys1015Ser)] in gene NOTCH3 of propositus, 2 patients (II3, III7), and a presymptomatic patient (IV1) in Family I all had heterozygosity missense mutation; and the 3(rd) exon [c.316T > G, p. (Cys106Gly)] in gene NOTCH3 of the propositus, a patient (IV3) and two presymptomatic patients (IV5, 6) in Family II all had heterozygosity missense mutation; and no mutations were detected in the 100 healthy collators. It was indicated by analyzing the function prediction that the mutation of [c. 3043 T > A (p.Cys1015Ser)] and [c.316T > G, p. (Cys106Gly)] may both influence encoding protein in NOTCH3. By analysis of the conservatism of mutation point in each species, these two basic groups were highly conserved. The heterozygosity missense mutation of 19(th) exon [c. 3043 T > A (p.Cys1015Ser)] and the 3(rd) exon [c.316T > G, p. (Cys106Gly)] in NOTCH3 gene are the new pathogenic mutations of CADASIL, and enriches the mutation spectrum of NOTCH3 gene.

  3. Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).

    PubMed

    Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

    2017-08-01

    A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table. All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. The average performance of all algorithm increases due of the decreasing of dimensionality of the unique values of these elements (2697 platforms, 537 organisms, 454 labels, 9 molecules, and 5 types). Our work suggests that experimental metadata such as present in GEO can be accurately predicted using rule mining algorithms. Our work has implications for both prospective and retrospective augmentation of metadata quality, which are geared towards making data easier to find and reuse. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  4. [NOTCH3 gene mutations in two Chinese families featuring cerebral autosomal dominant arteriopathy with subcortical infarct and leucoencephalopathy].

    PubMed

    Sun, Qiying; Li, Wenwen; Zhou, Yafang; Yi, Fang; Wang, Jianfeng; Hu, Yacen; Yao, Lingyan; Zhou, Lin; Xu, Hongwei

    2017-12-10

    To analyze potential mutations of the NOTCH3 gene in two Chinese families featuring cerebral autosomal dominant arteriopathy with subcortical infarct and leucoencephalopathy (CADASIL). The two probands and related family members and 100 healthy controls were recruited. Potential mutations of the NOTCH3 gene were screened by PCR and direct sequencing. PolyPhen-2 and SIFT software were used to predict the protein function. The conditions of both probands were adult-onset, with main clinical features including recurrent transient ischemic attacks and/or strokes, cognitive impairment. MRI findings suggested multiple cerebral infarcts and severe leukoencephalopathy. A heterozygous mutation c.328C>T (p.Arg110Cys), which was located in exon 3 of the NOTCH3 gene and known as a causative mutation, was identified in proband 1. A novel heterozygous mutation c.1013 G>C (p.Cys338Ser) located in exon 6 of the NOTCH3 gene was identified in the proband 2, which was not reported previously. The same mutations were not detected among the 100 unrelated healthy controls. Function analysis suggested that heterozygous mutation c.1013G>C can severely affect the functions of NOTCH3 protein. Two heterozygous missense mutations in the NOTCH3 gene have been identified in two families affected with CADASIL. The novel heterozygous Cys338Ser mutation in exon 6 of the NOTCH3 gene probably underlies the CADASIL.

  5. Phase 1/2 study of valproic acid and short-course radiotherapy plus capecitabine as preoperative treatment in low-moderate risk rectal cancer-V-shoRT-R3 (Valproic acid--short Radiotherapy--rectum 3rd trial).

    PubMed

    Avallone, Antonio; Piccirillo, Maria Carmela; Delrio, Paolo; Pecori, Biagio; Di Gennaro, Elena; Aloj, Luigi; Tatangelo, Fabiana; D'Angelo, Valentina; Granata, Cinzia; Cavalcanti, Ernesta; Maurea, Nicola; Maiolino, Piera; Bianco, Franco; Montano, Massimo; Silvestro, Lucrezia; Terranova Barberio, Manuela; Roca, Maria Serena; Di Maio, Massimo; Marone, Pietro; Botti, Gerardo; Petrillo, Antonella; Daniele, Gennaro; Lastoria, Secondo; Iaffaioli, Vincenzo R; Romano, Giovanni; Caracò, Corradina; Muto, Paolo; Gallo, Ciro; Perrone, Francesco; Budillon, Alfredo

    2014-11-24

    Locally advanced rectal cancer (LARC) is a heterogeneous group of tumors where a risk-adapted therapeutic strategy is needed. Short-course radiotherapy (SCRT) is a more convenient option for LARC patients than preoperative long-course RT plus capecitabine. Histone-deacetylase inhibitors (HDACi) have shown activity in combination with RT and chemotherapy in the treatment of solid tumors. Valproic acid (VPA) is an anti-epileptic drug with HDACi and anticancer activity. In preclinical studies, our group showed that the addition of HDACi, including VPA, to capecitabine produces synergistic antitumour effects by up-regulating thymidine phosphorylase (TP), the key enzyme converting capecitabine to 5-FU, and by downregulating thymidylate synthase (TS), the 5-FU target. Two parallel phase-1 studies will assess the safety of preoperative SCRT (5 fractions each of 5 Gy, on days 1 to 5) combined with (a) capecitabine alone (increasing dose levels: 500-825 mg/m2/bid), on days 1-21, or (b) capecitabine as above plus VPA (oral daily day -14 to 21, with an intra-patient titration for a target serum level of 50-100 microg/ml) followed by surgery 8 weeks after the end of SCRT, in low-moderate risk RC patients. Also, a randomized phase-2 study will be performed to explore whether the addition of VPA and/or capecitabine to preoperative SCRT might increase pathologic complete tumor regression (TRG1) rate. A sample size of 86 patients (21-22/arm) was calculated under the hypothesis that the addition of capecitabine or VPA to SCRT can improve the TRG1 rate from 5% to 20%, with one-sided alpha = 0.10 and 80% power.Several biomarkers will be evaluated comparing normal mucosa with tumor (TP, TS, VEGF, RAD51, XRCC1, Histones/proteins acetylation, HDAC isoforms) and on blood samples (polymorphisms of DPD, TS, XRCC1, GSTP1, RAD51 and XRCC3, circulating endothelial and progenitors cells; PBMCs-Histones/proteins acetylation). Tumor metabolism will be measured by 18FDG-PET at baseline and 15

  6. Domain mapping of the Rad51 paralog protein complexes

    PubMed Central

    Miller, Kristi A.; Sawicka, Dorota; Barsky, Daniel; Albala, Joanna S.

    2004-01-01

    The five human Rad51 paralogs are suggested to play an important role in the maintenance of genome stability through their function in DNA double-strand break repair. These proteins have been found to form two distinct complexes in vivo, Rad51B–Rad51C–Rad51D–Xrcc2 (BCDX2) and Rad51C–Xrcc3 (CX3). Based on the recent Pyrococcus furiosus Rad51 structure, we have used homology modeling to design deletion mutants of the Rad51 paralogs. The models of the human Rad51B, Rad51C, Xrcc3 and murine Rad51D (mRad51D) proteins reveal distinct N-terminal and C-terminal domains connected by a linker region. Using yeast two-hybrid and co-immunoprecipitation techniques, we have demonstrated that a fragment of Rad51B containing amino acid residues 1–75 interacts with the C-terminus and linker of Rad51C, residues 79–376, and this region of Rad51C also interacts with mRad51D and Xrcc3. We have also determined that the N-terminal domain of mRad51D, residues 4–77, binds to Xrcc2 while the C-terminal domain of mRad51D, residues 77–328, binds Rad51C. By this, we have identified the binding domains of the BCDX2 and CX3 complexes to further characterize the interaction of these proteins and propose a scheme for the three-dimensional architecture of the BCDX2 and CX3 paralog complexes. PMID:14704354

  7. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

    PubMed Central

    Ni, Ying; Aghamirzaie, Delasa; Elmarakeby, Haitham; Collakova, Eva; Li, Song; Grene, Ruth; Heath, Lenwood S.

    2016-01-01

    Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git. PMID:28066488

  8. Gene expression models for prediction of longitudinal dispersion coefficient in streams

    NASA Astrophysics Data System (ADS)

    Sattar, Ahmed M. A.; Gharabaghi, Bahram

    2015-05-01

    Longitudinal dispersion is the key hydrologic process that governs transport of pollutants in natural streams. It is critical for spill action centers to be able to predict the pollutant travel time and break-through curves accurately following accidental spills in urban streams. This study presents a novel gene expression model for longitudinal dispersion developed using 150 published data sets of geometric and hydraulic parameters in natural streams in the United States, Canada, Europe, and New Zealand. The training and testing of the model were accomplished using randomly-selected 67% (100 data sets) and 33% (50 data sets) of the data sets, respectively. Gene expression programming (GEP) is used to develop empirical relations between the longitudinal dispersion coefficient and various control variables, including the Froude number which reflects the effect of reach slope, aspect ratio, and the bed material roughness on the dispersion coefficient. Two GEP models have been developed, and the prediction uncertainties of the developed GEP models are quantified and compared with those of existing models, showing improved prediction accuracy in favor of GEP models. Finally, a parametric analysis is performed for further verification of the developed GEP models. The main reason for the higher accuracy of the GEP models compared to the existing regression models is that exponents of the key variables (aspect ratio and bed material roughness) are not constants but a function of the Froude number. The proposed relations are both simple and accurate and can be effectively used to predict the longitudinal dispersion coefficients in natural streams.

  9. The R148.3 Gene Modulates Caenorhabditis elegans Lifespan and Fat Metabolism

    PubMed Central

    Roy-Bellavance, Catherine; Grants, Jennifer M.; Miard, Stéphanie; Lee, Kayoung; Rondeau, Évelyne; Guillemette, Chantal; Simard, Martin J.; Taubert, Stefan; Picard, Frédéric

    2017-01-01

    Despite many advances, the molecular links between energy metabolism and longevity are not well understood. Here, we have used the nematode model Caenorhabditis elegans to study the role of the yet-uncharacterized gene R148.3 in fat accumulation and lifespan. In wild-type worms, a R148.3p::GFP reporter showed enhanced expression throughout life in the pharynx, in neurons, and in muscles. Functionally, a protein fusing a predicted 22 amino acid N-terminal signal sequence (SS) of R148.3 to mCherry displayed robust accumulation in coelomyocytes, indicating that R148.3 is a secreted protein. Systematic depletion of R148.3 by RNA interference (RNAi) at L1 but not at young-adult stage enhanced triglyceride accumulation, which was associated with increased food uptake and lower expression of genes involved in lipid oxidation. However, RNAi of R148.3 at both L1 and young-adult stages robustly diminished mean and maximal lifespan of wild-type worms, and also abolished the long-lived phenotypes of eat-2 and daf-2/InsR mutants. Based on these data, we propose that R148.3 is an SS that modulates fat mass and longevity in an independent manner. PMID:28620088

  10. STAT3 Target Genes Relevant to Human Cancers

    PubMed Central

    Carpenter, Richard L.; Lo, Hui-Wen

    2014-01-01

    Since its discovery, the STAT3 transcription factor has been extensively studied for its function as a transcriptional regulator and its role as a mediator of development, normal physiology, and pathology of many diseases, including cancers. These efforts have uncovered an array of genes that can be positively and negatively regulated by STAT3, alone and in cooperation with other transcription factors. Through regulating gene expression, STAT3 has been demonstrated to play a pivotal role in many cellular processes including oncogenesis, tumor growth and progression, and stemness. Interestingly, recent studies suggest that STAT3 may behave as a tumor suppressor by activating expression of genes known to inhibit tumorigenesis. Additional evidence suggested that STAT3 may elicit opposing effects depending on cellular context and tumor types. These mixed results signify the need for a deeper understanding of STAT3, including its upstream regulators, parallel transcription co-regulators, and downstream target genes. To help facilitate fulfilling this unmet need, this review will be primarily focused on STAT3 downstream target genes that have been validated to associate with tumorigenesis and/or malignant biology of human cancers. PMID:24743777

  11. A transversal approach to predict gene product networks from ontology-based similarity

    PubMed Central

    Chabalier, Julie; Mosser, Jean; Burgun, Anita

    2007-01-01

    Background Interpretation of transcriptomic data is usually made through a "standard" approach which consists in clustering the genes according to their expression patterns and exploiting Gene Ontology (GO) annotations within each expression cluster. This approach makes it difficult to underline functional relationships between gene products that belong to different expression clusters. To address this issue, we propose a transversal analysis that aims to predict functional networks based on a combination of GO processes and data expression. Results The transversal approach presented in this paper consists in computing the semantic similarity between gene products in a Vector Space Model. Through a weighting scheme over the annotations, we take into account the representativity of the terms that annotate a gene product. Comparing annotation vectors results in a matrix of gene product similarities. Combined with expression data, the matrix is displayed as a set of functional gene networks. The transversal approach was applied to 186 genes related to the enterocyte differentiation stages. This approach resulted in 18 functional networks proved to be biologically relevant. These results were compared with those obtained through a standard approach and with an approach based on information content similarity. Conclusion Complementary to the standard approach, the transversal approach offers new insight into the cellular mechanisms and reveals new research hypotheses by combining gene product networks based on semantic similarity, and data expression. PMID:17605807

  12. Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

    PubMed

    Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

    2017-01-09

    The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. A lung cancer risk classifier comprising genome maintenance genes measured in normal bronchial epithelial cells.

    PubMed

    Yeo, Jiyoun; Crawford, Erin L; Zhang, Xiaolu; Khuder, Sadik; Chen, Tian; Levin, Albert; Blomquist, Thomas M; Willey, James C

    2017-05-02

    Annual low dose CT (LDCT) screening of individuals at high demographic risk reduces lung cancer mortality by more than 20%. However, subjects selected for screening based on demographic criteria typically have less than a 10% lifetime risk for lung cancer. Thus, there is need for a biomarker that better stratifies subjects for LDCT screening. Toward this goal, we previously reported a lung cancer risk test (LCRT) biomarker comprising 14 genome-maintenance (GM) pathway genes measured in normal bronchial epithelial cells (NBEC) that accurately classified cancer (CA) from non-cancer (NC) subjects. The primary goal of the studies reported here was to optimize the LCRT biomarker for high specificity and ease of clinical implementation. Targeted competitive multiplex PCR amplicon libraries were prepared for next generation sequencing (NGS) analysis of transcript abundance at 68 sites among 33 GM target genes in NBEC specimens collected from a retrospective cohort of 120 subjects, including 61 CA cases and 59 NC controls. Genes were selected for analysis based on contribution to the previously reported LCRT biomarker and/or prior evidence for association with lung cancer risk. Linear discriminant analysis was used to identify the most accurate classifier suitable to stratify subjects for screening. After cross-validation, a model comprising expression values from 12 genes (CDKN1A, E2F1, ERCC1, ERCC4, ERCC5, GPX1, GSTP1, KEAP1, RB1, TP53, TP63, and XRCC1) and demographic factors age, gender, and pack-years smoking, had Receiver Operator Characteristic area under the curve (ROC AUC) of 0.975 (95% CI: 0.96-0.99). The overall classification accuracy was 93% (95% CI 88%-98%) with sensitivity 93.1%, specificity 92.9%, positive predictive value 93.1% and negative predictive value 93%. The ROC AUC for this classifier was significantly better (p < 0.0001) than the best model comprising demographic features alone. The LCRT biomarker reported here displayed high accuracy and ease

  14. Expression of the filaggrin gene in umbilical cord blood predicts eczema risk in infancy: A birth cohort study.

    PubMed

    Ziyab, A H; Ewart, S; Lockett, G A; Zhang, H; Arshad, H; Holloway, J W; Karmaus, W

    2017-09-01

    Filaggrin gene (FLG) expression, particularly in the skin, has been linked to the development of the skin barrier and is associated with eczema risk. However, knowledge as to whether FLG expression in umbilical cord blood (UCB) is associated with eczema development and prediction is lacking. This study sought to assess whether FLG expression in UCB associates with and predicts the development of eczema in infancy. Infants enrolled in a birth cohort study (n=94) were assessed for eczema at ages 3, 6, and 12 months. Five probes measuring FLG transcripts expression in UCB were available from genomewide gene expression profiling. FLG genetic variants R501X, 2282del4, and S3247X were genotyped. Associations were assessed using Poisson regression with robust variance estimation. Area under the curve (AUC), describing the discriminatory/predictive performance of fitted models, was estimated from logistic regression. Increased level of FLG expression measured by probe A_24_P51322 was associated with reduced risk of eczema during the first year of life (RR=0.60, 95% CI: 0.38-0.95). In contrast, increased level of FLG antisense transcripts measured by probe A_21_P0014075 was associated with increased risk of eczema (RR=2.02, 95% CI: 1.10-3.72). In prediction models including FLG expression, FLG genetic variants, and sex, discrimination between children who will and will not develop eczema at 3 months of age was high (AUC: 0.91, 95% CI: 0.84-0.98). This study demonstrated, for the first time, that FLG expression in UCB is associated with eczema development in infancy. Moreover, our analysis provided prediction models that were capable of discriminating, to a great extent, between those who will and will not develop eczema in infancy. Therefore, early identification of infants at increased risk of developing eczema is possible and such high-risk newborns may benefit from early stratification and intervention. © 2017 John Wiley & Sons Ltd.

  15. EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

    PubMed

    Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

    2014-07-01

    The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. The primary structures of two yeast enolase genes. Homology between the 5' noncoding flanking regions of yeast enolase and glyceraldehyde-3-phosphate dehydrogenase genes.

    PubMed

    Holland, M J; Holland, J P; Thill, G P; Jackson, K A

    1981-02-10

    Segments of yeast genomic DNA containing two enolase structural genes have been isolated by subculture cloning procedures using a cDNA hybridization probe synthesized from purified yeast enolase mRNA. Based on restriction endonuclease and transcriptional maps of these two segments of yeast DNA, each hybrid plasmid contains a region of extensive nucleotide sequence homology which forms hybrids with the cDNA probe. The DNA sequences which flank this homologous region in the two hybrid plasmids are nonhomologous indicating that these sequences are nontandemly repeated in the yeast genome. The complete nucleotide sequence of the coding as well as the flanking noncoding regions of these genes has been determined. The amino acid sequence predicted from one reading frame of both structural genes is extremely similar to that determined for yeast enolase (Chin, C. C. Q., Brewer, J. M., Eckard, E., and Wold, F. (1981) J. Biol. Chem. 256, 1370-1376), confirming that these isolated structural genes encode yeast enolase. The nucleotide sequences of the coding regions of the genes are approximately 95% homologous, and neither gene contains an intervening sequence. Codon utilization in the enolase genes follows the same biased pattern previously described for two yeast glyceraldehyde-3-phosphate dehydrogenase structural genes (Holland, J. P., and Holland, M. J. (1980) J. Biol. Chem. 255, 2596-2605). DNA blotting analysis confirmed that the isolated segments of yeast DNA are colinear with yeast genomic DNA and that there are two nontandemly repeated enolase genes per haploid yeast genome. The noncoding portions of the two enolase genes adjacent to the initiation and termination codons are approximately 70% homologous and contain sequences thought to be involved in the synthesis and processing messenger RNA. Finally there are regions of extensive homology between the two enolase structural genes and two yeast glyceraldehyde-3-phosphate dehydrogenase structural genes within the 5

  17. Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions.

    PubMed

    Zhou, Weichen; Ma, Yanyun; Zhang, Jun; Hu, Jingyi; Zhang, Menghan; Wang, Yi; Li, Yi; Wu, Lijun; Pan, Yida; Zhang, Yitong; Zhang, Xiaonan; Zhang, Xinxin; Zhang, Zhanqing; Zhang, Jiming; Li, Hai; Lu, Lungen; Jin, Li; Wang, Jiucun; Yuan, Zhenghong; Liu, Jie

    2017-11-01

    Liver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus-infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)-infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV-DNA) in large-scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions. We analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine-learning methods including Random Forest, K-nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model. Significant genes related to clinical parameters were found enriching in the immune system, interferon-stimulated, regulation of cytokine production, anti-apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77-0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65-0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible. This is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. A germline mutation in the BRCA1 3’UTR predicts Stage IV breast cancer

    PubMed Central

    2014-01-01

    Background A germline, variant in the BRCA1 3’UTR (rs8176318) was previously shown to predict breast and ovarian cancer risk in women from high-risk families, as well as increased risk of triple negative breast cancer. Here, we tested the hypothesis that this variant predicts tumor biology, like other 3’UTR mutations in cancer. Methods The impact of the BRCA1-3’UTR-variant on BRCA1 gene expression, and altered response to external stimuli was tested in vitro using a luciferase reporter assay. Gene expression was further tested in vivo by immunoflourescence staining on breast tumor tissue, comparing triple negative patient samples with the variant (TG or TT) or non-variant (GG) BRCA1 3’UTR. To determine the significance of the variant on clinically relevant endpoints, a comprehensive collection of West-Irish breast cancer patients were tested for the variant. Finally, an association of the variant with breast screening clinical phenotypes was evaluated using a cohort of women from the High Risk Breast Program at the University of Vermont. Results Luciferase reporters with the BRCA1-3’UTR-variant (T allele) displayed significantly lower gene expression, as well as altered response to external hormonal stimuli, compared to the non-variant 3’UTR (G allele) in breast cancer cell lines. This was confirmed clinically by the finding of reduced BRCA1 gene expression in triple negative samples from patients carrying the homozygous TT variant, compared to non-variant patients. The BRCA1-3’UTR-variant (TG or TT) also associated with a modest increased risk for developing breast cancer in the West-Irish cohort (OR = 1.4, 95% CI 1.1-1.8, p = 0.033). More importantly, patients with the BRCA1-3’UTR-variant had a 4-fold increased risk of presenting with Stage IV disease (p = 0.018, OR = 3.37, 95% CI 1.3-11.0). Supporting that this finding is due to tumor biology, and not difficulty screening, obese women with the BRCA1-3’UTR-variant had

  19. Molecular Phylogeny and Predicted 3D Structure of Plant beta-D-N-Acetylhexosaminidase

    PubMed Central

    Hossain, Md. Anowar

    2014-01-01

    beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom. PMID:25165734

  20. Comparative genomic analysis of the Lipase3 gene family in five plant species reveals distinct evolutionary origins.

    PubMed

    Wang, Dan; Zhang, Lin; Hu, JunFeng; Gao, Dianshuai; Liu, Xin; Sha, Yan

    2018-04-01

    Lipases are physiologically important and ubiquitous enzymes that share a conserved domain and are classified into eight different families based on their amino acid sequences and fundamental biological properties. The Lipase3 family of lipases was reported to possess a canonical fold typical of α/β hydrolases and a typical catalytic triad, suggesting a distinct evolutionary origin for this family. Genes in the Lipase3 family do not have the same functions, but maintain the conserved Lipase3 domain. There have been extensive studies of Lipase3 structures and functions, but little is known about their evolutionary histories. In this study, all lipases within five plant species were identified, and their phylogenetic relationships and genetic properties were analyzed and used to group them into distinct evolutionary families. Each identified lipase family contained at least one dicot and monocot Lipase3 protein, indicating that the gene family was established before the split of dicots and monocots. Similar intron/exon numbers and predicted protein sequence lengths were found within individual groups. Twenty-four tandem Lipase3 gene duplications were identified, implying that the distinctive function of Lipase3 genes appears to be a consequence of translocation and neofunctionalization after gene duplication. The functional genes EDS1, PAD4, and SAG101 that are reportedly involved in pathogen response were all located in the same group. The nucleotide diversity (Dxy) and the ratio of nonsynonymous to synonymous nucleotide substitutions rates (Ka/Ks) of the three genes were significantly greater than the average across the genomes. We further observed evidence for selection maintaining diversity on three genes in the Toll-Interleukin-1 receptor type of nucleotide binding/leucine-rich repeat immune receptor (TIR-NBS LRR) immunity-response signaling pathway, indicating that they could be vulnerable to pathogen effectors.

  1. Identification of the 14-3-3 gene family in Rafflesia cantleyi

    NASA Astrophysics Data System (ADS)

    Rosli, Khadijah; Wan, Kiew-Lian

    2018-04-01

    Rafflesia is known to be the largest flower in the world. Due to its size and appearance, it is considered to be very unique. Little is known about the molecular biology of this rare parasitic flowering plant as it is very difficult to locate and has a short life-span as a flower. Physiological activities in plants are regulated by signalling regulators such as the members of the 14-3-3 gene family. The number of members of this gene family varies in plants and there are thirteen known members in Arabidopsis thaliana. Their role is to bind to phosphorylated targets to complete signal transduction processes. Sequence comparison using BLAST of transcriptome data from three different Rafflesia cantleyi floral bud stages against the Swissprot database revealed 27 transcripts annotated as members of this gene family. All of the transcripts were expressed during floral bud stage 1 (S1) while 14 and four transcripts were expressed during floral bud stages 2 (S2) and 3 (S3), respectively. Significant downregulation was recorded for six and nine transcripts at S1 vs. S2 and S2 vs. S3 respectively. This gene family may play a critical role as signalling regulators during the development of Rafflesia floral bud.

  2. Construction of a novel multi-gene assay (42-gene classifier) for prediction of late recurrence in ER-positive breast cancer patients.

    PubMed

    Tsunashima, Ryo; Naoi, Yasuto; Shimazu, Kenzo; Kagara, Naofumi; Shimoda, Masashi; Tanei, Tomonori; Miyake, Tomohiro; Kim, Seung Jin; Noguchi, Shinzaburo

    2018-05-04

    Prediction models for late (> 5 years) recurrence in ER-positive breast cancer need to be developed for the accurate selection of patients for extended hormonal therapy. We attempted to develop such a prediction model focusing on the differences in gene expression between breast cancers with early and late recurrence. For the training set, 779 ER-positive breast cancers treated with tamoxifen alone for 5 years were selected from the databases (GSE6532, GSE12093, GSE17705, and GSE26971). For the validation set, 221 ER-positive breast cancers treated with adjuvant hormonal therapy for 5 years with or without chemotherapy at our hospital were included. Gene expression was assayed by DNA microarray analysis (Affymetrix U133 plus 2.0). With the 42 genes differentially expressed in early and late recurrence breast cancers in the training set, a prediction model (42GC) for late recurrence was constructed. The patients classified by 42GC into the late recurrence-like group showed a significantly (P = 0.006) higher late recurrence rate as expected but a significantly (P = 1.62 × E-13) lower rate for early recurrence than non-late recurrence-like group. These observations were confirmed for the validation set, i.e., P = 0.020 for late recurrence and P = 5.70 × E-5 for early recurrence. We developed a unique prediction model (42GC) for late recurrence by focusing on the biological differences between breast cancers with early and late recurrence. Interestingly, patients in the late recurrence-like group by 42GC were at low risk for early recurrence.

  3. Genomic Features That Predict Allelic Imbalance in Humans Suggest Patterns of Constraint on Gene Expression Variation

    PubMed Central

    Fédrigo, Olivier; Haygood, Ralph; Mukherjee, Sayan; Wray, Gregory A.

    2009-01-01

    Variation in gene expression is an important contributor to phenotypic diversity within and between species. Although this variation often has a genetic component, identification of the genetic variants driving this relationship remains challenging. In particular, measurements of gene expression usually do not reveal whether the genetic basis for any observed variation lies in cis or in trans to the gene, a distinction that has direct relevance to the physical location of the underlying genetic variant, and which may also impact its evolutionary trajectory. Allelic imbalance measurements identify cis-acting genetic effects by assaying the relative contribution of the two alleles of a cis-regulatory region to gene expression within individuals. Identification of patterns that predict commonly imbalanced genes could therefore serve as a useful tool and also shed light on the evolution of cis-regulatory variation itself. Here, we show that sequence motifs, polymorphism levels, and divergence levels around a gene can be used to predict commonly imbalanced genes in a human data set. Reduction of this feature set to four factors revealed that only one factor significantly differentiated between commonly imbalanced and nonimbalanced genes. We demonstrate that these results are consistent between the original data set and a second published data set in humans obtained using different technical and statistical methods. Finally, we show that variation in the single allelic imbalance-associated factor is partially explained by the density of genes in the region of a target gene (allelic imbalance is less probable for genes in gene-dense regions), and, to a lesser extent, the evenness of expression of the gene across tissues and the magnitude of negative selection on putative regulatory regions of the gene. These results suggest that the genomic distribution of functional cis-regulatory variants in the human genome is nonrandom, perhaps due to local differences in evolutionary

  4. Genomic organization and expression of the human MSH3 gene

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Watanabe, Atsushi; Ikejima, Miyoko; Suzuki, Noriko

    1996-02-01

    We have studied the expression and genomic organization of the human MSH3 gene, which encodes a human homologue of the bacterial DNA mismatch repair protein MutS. This gene is located upstream of the dihydrofolate reductase (DHFR) gene. Northern analysis has demonstrated that the hMSH3 gene is expressed in a variety of human tissues at low levels, like the DHFR gene. Characterization of cosmid clones has shown that the hMSH3 gene consists of 24 exons spanning at least 160 kb. All exon-intron junction sequences match the classical GT/AG rule, except that intron 6 has AT and AA at the ends. Twomore » major transcripts of 5.0 and 3.8 kb have been shown to be derived from the differential use of two polyadenylation sites. Elucidation of the complete genomic organization and the nucleotide sequences of the introns of the hMSH3 gene should be useful for studying the function of this gene and the possible involvement of specific mutations of the hMSH3 gene in some diseases. 34 refs., 5 figs., 1 tab.« less

  5. Genetic variants of cell cycle pathway genes predict disease-free survival of hepatocellular carcinoma.

    PubMed

    Liu, Shun; Yang, Tian-Bo; Nan, Yue-Li; Li, An-Hua; Pan, Dong-Xiang; Xu, Yang; Li, Shu; Li, Ting; Zeng, Xiao-Yun; Qiu, Xiao-Qiang

    2017-07-01

    Disruption of the cell cycle pathway has previously been related to development of human cancers. However, associations between genetic variants of cell cycle pathway genes and prognosis of hepatocellular carcinoma (HCC) remain largely unknown. In this study, we evaluated the associations between 24 potential functional single nucleotide polymorphisms (SNPs) of 16 main cell cycle pathway genes and disease-free survival (DFS) of 271 HCC patients who had undergone radical surgery resection. We identified two SNPs, i.e., SMAD3 rs11556090 A>G and RBL2 rs3929G>C, that were independently predictive of DFS in an additive genetic model with false-positive report probability (FPRP) <0.2. The SMAD3 rs11556090G allele was associated with a poorer DFS, compared with the A allele [hazard ratio (HR) = 1.46, 95% confidential interval (95% CI) = 1.13-1.89, P = 0.004]; while the RBL2 rs3929 C allele was associated with a superior DFS, compared with the G allele (HR = 0.74, 95% CI = 0.57-0.96, P = 0.023). Additionally, patients with an increasing number of unfavorable genotypes (NUGs) of these loci had a significant shorter DFS (P trend  = 0.0001). Further analysis using receiver operating characteristic (ROC) curves showed that the model including the NUGs and known prognostic clinical variables demonstrated a significant improvement in predicting the 1-year DFS (P = 0.011). Moreover, the RBL2 rs3929 C allele was significantly associated with increased mRNA expression levels of RBL2 in liver tissue (P = 1.8 × 10 -7 ) and the whole blood (P = 3.9 × 10 -14 ). Our data demonstrated an independent or a joint effect of SMAD3 rs11556090 and RBL2 rs3929 in the cell cycle pathway on DFS of HCC, which need to be validated by large cohort and biological studies. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  6. Identification of Biomarker Genes To Predict Biodegradation of 1,4-Dioxane

    PubMed Central

    Gedalanga, Phillip B.; Pornwongthong, Peerapong; Mora, Rebecca; Chiang, Sheau-Yun Dora; Baldwin, Brett; Ogles, Dora

    2014-01-01

    Bacterial multicomponent monooxygenase gene targets in Pseudonocardia dioxanivorans CB1190 were evaluated for their use as biomarkers to identify the potential for 1,4-dioxane biodegradation in pure cultures and environmental samples. Our studies using laboratory pure cultures and industrial activated sludge samples suggest that the presence of genes associated with dioxane monooxygenase, propane monooxygenase, alcohol dehydrogenase, and aldehyde dehydrogenase are promising indicators of 1,4-dioxane biotransformation; however, gene abundance was insufficient to predict actual biodegradation. A time course gene expression analysis of dioxane and propane monooxygenases in Pseudonocardia dioxanivorans CB1190 and mixed communities in wastewater samples revealed important associations with the rates of 1,4-dioxane removal. In addition, transcripts of alcohol dehydrogenase and aldehyde dehydrogenase genes were upregulated during biodegradation, although only the aldehyde dehydrogenase was significantly correlated with 1,4-dioxane concentrations. Expression of the propane monooxygenase demonstrated a time-dependent relationship with 1,4-dioxane biodegradation in P. dioxanivorans CB1190, with increased expression occurring after over 50% of the 1,4-dioxane had been removed. While the fraction of P. dioxanivorans CB1190-like bacteria among the total bacterial population significantly increased with decrease in 1,4-dioxane concentrations in wastewater treatment samples undergoing active biodegradation, the abundance and expression of monooxygenase-based biomarkers were better predictors of 1,4-dioxane degradation than taxonomic 16S rRNA genes. This study illustrates that specific bacterial monooxygenase and dehydrogenase gene targets together can serve as effective biomarkers for 1,4-dioxane biodegradation in the environment. PMID:24632253

  7. A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

    NASA Astrophysics Data System (ADS)

    Feng, Shou; Fu, Ping; Zheng, Wenbin

    2018-03-01

    Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

  8. Single-Nucleotide Polymorphisms of Genes Involved in Repair of Oxidative DNA Damage and the Risk of Recurrent Depressive Disorder.

    PubMed

    Czarny, Piotr; Kwiatkowski, Dominik; Toma, Monika; Gałecki, Piotr; Orzechowska, Agata; Bobińska, Kinga; Bielecka-Kowalska, Anna; Szemraj, Janusz; Berk, Michael; Anderson, George; Śliwiński, Tomasz

    2016-11-20

    BACKGROUND Depressive disorder, including recurrent type (rDD), is accompanied by increased oxidative stress and activation of inflammatory pathways, which may induce DNA damage. This thesis is supported by the presence of increased levels of DNA damage in depressed patients. Such DNA damage is repaired by the base excision repair (BER) pathway. BER efficiency may be influenced by polymorphisms in BER-related genes. Therefore, we genotyped nine single-nucleotide polymorphisms (SNPs) in six genes encoding BER proteins. MATERIAL AND METHODS Using TaqMan, we selected and genotyped the following SNPs: c.-441G>A (rs174538) of FEN1, c.2285T>C (rs1136410) of PARP1, c.580C>T (rs1799782) and c.1196A>G (rs25487) of XRCC1, c.*83A>C (rs4796030) and c.*50C>T (rs1052536) of LIG3, c.-7C>T (rs20579) of LIG1, and c.-468T>G (rs1760944) and c.444T>G (rs1130409) of APEX1 in 599 samples (288 rDD patients and 311 controls). RESULTS We found a strong correlation between rDD and both SNPs of LIG3, their haplotypes, as well as a weaker association with the c.-468T>G of APEXI which diminished after Nyholt correction. Polymorphisms of LIG3 were also associated with early onset versus late onset depression, whereas the c.-468T>G polymorphism showed the opposite association. CONCLUSIONS The SNPs of genes involved in the repair of oxidative DNA damage may modulate rDD risk. Since this is an exploratory study, the results should to be treated with caution and further work needs to be done to elucidate the exact involvement of DNA damage and repair mechanisms in the development of this disease.

  9. Single-Nucleotide Polymorphisms of Genes Involved in Repair of Oxidative DNA Damage and the Risk of Recurrent Depressive Disorder

    PubMed Central

    Czarny, Piotr; Kwiatkowski, Dominik; Toma, Monika; Gałecki, Piotr; Orzechowska, Agata; Bobińska, Kinga; Bielecka-Kowalska, Anna; Szemraj, Janusz; Berk, Michael; Anderson, George; Śliwiński, Tomasz

    2016-01-01

    Background Depressive disorder, including recurrent type (rDD), is accompanied by increased oxidative stress and activation of inflammatory pathways, which may induce DNA damage. This thesis is supported by the presence of increased levels of DNA damage in depressed patients. Such DNA damage is repaired by the base excision repair (BER) pathway. BER efficiency may be influenced by polymorphisms in BER-related genes. Therefore, we genotyped nine single-nucleotide polymorphisms (SNPs) in six genes encoding BER proteins. Material/Methods Using TaqMan, we selected and genotyped the following SNPs: c.-441G>A (rs174538) of FEN1, c.2285T>C (rs1136410) of PARP1, c.580C>T (rs1799782) and c.1196A>G (rs25487) of XRCC1, c.*83A>C (rs4796030) and c.*50C>T (rs1052536) of LIG3, c.-7C>T (rs20579) of LIG1, and c.-468T>G (rs1760944) and c.444T>G (rs1130409) of APEX1 in 599 samples (288 rDD patients and 311 controls). Results We found a strong correlation between rDD and both SNPs of LIG3, their haplotypes, as well as a weaker association with the c.-468T>G of APEXI which diminished after Nyholt correction. Polymorphisms of LIG3 were also associated with early onset versus late onset depression, whereas the c.-468T>G polymorphism showed the opposite association. Conclusions The SNPs of genes involved in the repair of oxidative DNA damage may modulate rDD risk. Since this is an exploratory study, the results should to be treated with caution and further work needs to be done to elucidate the exact involvement of DNA damage and repair mechanisms in the development of this disease. PMID:27866211

  10. Differential Responses to Wnt and PCP Disruption Predict Expression and Developmental Function of Conserved and Novel Genes in a Cnidarian

    PubMed Central

    Lapébie, Pascal; Ruggiero, Antonella; Barreau, Carine; Chevalier, Sandra; Chang, Patrick; Dru, Philippe; Houliston, Evelyn; Momose, Tsuyoshi

    2014-01-01

    We have used Digital Gene Expression analysis to identify, without bilaterian bias, regulators of cnidarian embryonic patterning. Transcriptome comparison between un-manipulated Clytia early gastrula embryos and ones in which the key polarity regulator Wnt3 was inhibited using morpholino antisense oligonucleotides (Wnt3-MO) identified a set of significantly over and under-expressed transcripts. These code for candidate Wnt signaling modulators, orthologs of other transcription factors, secreted and transmembrane proteins known as developmental regulators in bilaterian models or previously uncharacterized, and also many cnidarian-restricted proteins. Comparisons between embryos injected with morpholinos targeting Wnt3 and its receptor Fz1 defined four transcript classes showing remarkable correlation with spatiotemporal expression profiles. Class 1 and 3 transcripts tended to show sustained expression at “oral” and “aboral” poles respectively of the developing planula larva, class 2 transcripts in cells ingressing into the endodermal region during gastrulation, while class 4 gene expression was repressed at the early gastrula stage. The preferential effect of Fz1-MO on expression of class 2 and 4 transcripts can be attributed to Planar Cell Polarity (PCP) disruption, since it was closely matched by morpholino knockdown of the specific PCP protein Strabismus. We conclude that endoderm and post gastrula-specific gene expression is particularly sensitive to PCP disruption while Wnt-/β-catenin signaling dominates gene regulation along the oral-aboral axis. Phenotype analysis using morpholinos targeting a subset of transcripts indicated developmental roles consistent with expression profiles for both conserved and cnidarian-restricted genes. Overall our unbiased screen allowed systematic identification of regionally expressed genes and provided functional support for a shared eumetazoan developmental regulatory gene set with both predicted and previously

  11. Differential responses to Wnt and PCP disruption predict expression and developmental function of conserved and novel genes in a cnidarian.

    PubMed

    Lapébie, Pascal; Ruggiero, Antonella; Barreau, Carine; Chevalier, Sandra; Chang, Patrick; Dru, Philippe; Houliston, Evelyn; Momose, Tsuyoshi

    2014-09-01

    We have used Digital Gene Expression analysis to identify, without bilaterian bias, regulators of cnidarian embryonic patterning. Transcriptome comparison between un-manipulated Clytia early gastrula embryos and ones in which the key polarity regulator Wnt3 was inhibited using morpholino antisense oligonucleotides (Wnt3-MO) identified a set of significantly over and under-expressed transcripts. These code for candidate Wnt signaling modulators, orthologs of other transcription factors, secreted and transmembrane proteins known as developmental regulators in bilaterian models or previously uncharacterized, and also many cnidarian-restricted proteins. Comparisons between embryos injected with morpholinos targeting Wnt3 and its receptor Fz1 defined four transcript classes showing remarkable correlation with spatiotemporal expression profiles. Class 1 and 3 transcripts tended to show sustained expression at "oral" and "aboral" poles respectively of the developing planula larva, class 2 transcripts in cells ingressing into the endodermal region during gastrulation, while class 4 gene expression was repressed at the early gastrula stage. The preferential effect of Fz1-MO on expression of class 2 and 4 transcripts can be attributed to Planar Cell Polarity (PCP) disruption, since it was closely matched by morpholino knockdown of the specific PCP protein Strabismus. We conclude that endoderm and post gastrula-specific gene expression is particularly sensitive to PCP disruption while Wnt-/β-catenin signaling dominates gene regulation along the oral-aboral axis. Phenotype analysis using morpholinos targeting a subset of transcripts indicated developmental roles consistent with expression profiles for both conserved and cnidarian-restricted genes. Overall our unbiased screen allowed systematic identification of regionally expressed genes and provided functional support for a shared eumetazoan developmental regulatory gene set with both predicted and previously unexplored

  12. A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

    PubMed Central

    Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

    2012-01-01

    The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

  13. Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter.

    PubMed

    Su, Zhao-Zhong; Sarkar, Devanand; Emdad, Luni; Duigou, Gregory J; Young, Charles S H; Ware, Joy; Randolph, Aaron; Valerie, Kristoffer; Fisher, Paul B

    2005-01-25

    One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies.

  14. Effective oligonucleotide-mediated gene disruption in ES cells lacking the mismatch repair protein MSH3.

    PubMed

    Dekker, M; Brouwers, C; Aarts, M; van der Torre, J; de Vries, S; van de Vrugt, H; te Riele, H

    2006-04-01

    We have previously demonstrated that site-specific insertion, deletion or substitution of one or two nucleotides in mouse embryonic stem cells (ES cells) by single-stranded deoxyribo-oligonucleotides is several hundred-fold suppressed by DNA mismatch repair (MMR) activity. Here, we have investigated whether compound mismatches and larger insertions escape detection by the MMR machinery and can be effectively introduced in MMR-proficient cells. We identified several compound mismatches that escaped detection by the MMR machinery to some extent, but could not define general rules predicting the efficacy of complex base-pair substitutions. In contrast, we found that four-nucleotide insertions were largely subject to suppression by the MSH2/MSH3 branch of MMR and could be effectively introduced in Msh3-deficient cells. As these cells have no overt mutator phenotype and Msh3-deficient mice do not develop cancer, Msh3-deficient ES cells can be used for oligonucleotide-mediated gene disruption. As an example, we present disruption of the Fanconi anemia gene Fancf.

  15. Base excision repair genes and risk of lung cancer among San Francisco Bay Area Latinos and African-Americans

    PubMed Central

    Chang, Jeffrey S.; Wrensch, Margaret R.; Hansen, Helen M.; Sison, Jennette D.; Aldrich, Melinda C.; Quesenberry, Charles P.; Seldin, Michael F.; Kelsey, Karl T.; Wiencke, John K.

    2009-01-01

    Base excision repair (BER) is the primary DNA damage repair mechanism for repairing small base lesions resulting from oxidation and alkylation damage. This study examines the association between 24 single-nucleotide polymorphisms (SNPs) belonging to five BER genes (XRCC1, APEX1, PARP1, MUTYH and OGG1) and lung cancer among Latinos (113 cases and 299 controls) and African-Americans (255 cases and 280 controls). The goal was to evaluate the differences in genetic contribution to lung cancer risk by ethnic groups. Analyses of individual SNPs and haplotypes were performed using unconditional logistic regressions adjusted for age, sex and genetic ancestry. Four SNPs among Latinos and one SNP among African-Americans were significantly (P < 0.05) associated with either risk of all lung cancer or non-small cell lung cancer (NSCLC). However, only the association between XRCC1 Arg399Gln (rs25487) and NSCLC among Latinos (odds ratio associated with every copy of Gln = 1.52; 95% confidence interval: 1.01–2.28) had a false-positive report probability of <0.5. Arg399Gln is a SNP with some functional evidence and has been shown previously to be an important SNP associated with lung cancer, mostly for Asians. Since the analyses were adjusted for genetic ancestry, the observed association between Arg399Gln and NSCLC among Latinos is unlikely to be confounded by population stratification; however, this result needs to be confirmed by additional studies among the Latino population. This study suggests that there are genetic differences in the association between BER pathway and lung cancer between Latinos and African-Americans. PMID:19029194

  16. The Prediction of Drug-Disease Correlation Based on Gene Expression Data.

    PubMed

    Cui, Hui; Zhang, Menghuan; Yang, Qingmin; Li, Xiangyi; Liebman, Michael; Yu, Ying; Xie, Lu

    2018-01-01

    The explosive growth of high-throughput experimental methods and resulting data yields both opportunity and challenge for selecting the correct drug to treat both a specific patient and their individual disease. Ideally, it would be useful and efficient if computational approaches could be applied to help achieve optimal drug-patient-disease matching but current efforts have met with limited success. Current approaches have primarily utilized the measureable effect of a specific drug on target tissue or cell lines to identify the potential biological effect of such treatment. While these efforts have met with some level of success, there exists much opportunity for improvement. This specifically follows the observation that, for many diseases in light of actual patient response, there is increasing need for treatment with combinations of drugs rather than single drug therapies. Only a few previous studies have yielded computational approaches for predicting the synergy of drug combinations by analyzing high-throughput molecular datasets. However, these computational approaches focused on the characteristics of the drug itself, without fully accounting for disease factors. Here, we propose an algorithm to specifically predict synergistic effects of drug combinations on various diseases, by integrating the data characteristics of disease-related gene expression profiles with drug-treated gene expression profiles. We have demonstrated utility through its application to transcriptome data, including microarray and RNASeq data, and the drug-disease prediction results were validated using existing publications and drug databases. It is also applicable to other quantitative profiling data such as proteomics data. We also provide an interactive web interface to allow our Prediction of Drug-Disease method to be readily applied to user data. While our studies represent a preliminary exploration of this critical problem, we believe that the algorithm can provide the basis for

  17. Coregulation of Terpenoid Pathway Genes and Prediction of Isoprene Production in Bacillus subtilis Using Transcriptomics.

    PubMed

    Hess, Becky M; Xue, Junfeng; Markillie, Lye Meng; Taylor, Ronald C; Wiley, H Steven; Ahring, Birgitte K; Linggi, Bryan

    2013-01-01

    The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes, as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding system level regulation and control of the pathway. To address these limitations, we examined Bacillus subtilis grown under multiple conditions and determined the relationship between altered isoprene production and gene expression patterns. We found that with respect to the amount of isoprene produced, terpenoid genes fall into two distinct subsets with opposing correlations. The group whose expression levels positively correlated with isoprene production included dxs, which is responsible for the commitment step in the pathway, ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome-wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. These analyses showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model that accurately predicts production of this secondary metabolite across many simulated environmental conditions.

  18. Coregulation of Terpenoid Pathway Genes and Prediction of Isoprene Production in Bacillus subtilis Using Transcriptomics

    PubMed Central

    Hess, Becky M.; Xue, Junfeng; Markillie, Lye Meng; Taylor, Ronald C.; Wiley, H. Steven; Ahring, Birgitte K.; Linggi, Bryan

    2013-01-01

    The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes, as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding system level regulation and control of the pathway. To address these limitations, we examined Bacillus subtilis grown under multiple conditions and determined the relationship between altered isoprene production and gene expression patterns. We found that with respect to the amount of isoprene produced, terpenoid genes fall into two distinct subsets with opposing correlations. The group whose expression levels positively correlated with isoprene production included dxs, which is responsible for the commitment step in the pathway, ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome-wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. These analyses showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model that accurately predicts production of this secondary metabolite across many simulated environmental conditions. PMID:23840410

  19. Coregulation of terpenoid pathway genes and prediction of isoprene production in Bacillus subtilis using transcriptomics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hess, Becky M.; Xue, Junfeng; Markillie, Lye Meng

    2013-06-19

    The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding the system level regulation and control of the pathway. To address this limitation, we examined Bacillus subtilis grown under multiple conditions and then determined the relationship between altered isoprene production and the pattern of gene expression. Wemore » found that terpenoid genes appeared to fall into two distinct subsets with opposing correlations with respect to the amount of isoprene produced. The group whose expression levels positively correlated with isoprene production included dxs, the gene responsible for the commitment step in the pathway, as well as ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. This analysis showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model which accurately predicts production of this secondary metabolite across many simulated environmental conditions.« less

  20. Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

    ERIC Educational Resources Information Center

    Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

    2010-01-01

    Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

  1. Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

    PubMed Central

    2014-01-01

    Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved

  2. A machine-learning approach reveals that alignment properties alone can accurately predict inference of lateral gene transfer from discordant phylogenies.

    PubMed

    Roettger, Mayo; Martin, William; Dagan, Tal

    2009-09-01

    Among the methods currently used in phylogenomic practice to detect the presence of lateral gene transfer (LGT), one of the most frequently employed is the comparison of gene tree topologies for different genes. In cases where the phylogenies for different genes are incompatible, or discordant, for well-supported branches there are three simple interpretations for the result: 1) gene duplications (paralogy) followed by many independent gene losses have occurred, 2) LGT has occurred, or 3) the phylogeny is well supported but for reasons unknown is nonetheless incorrect. Here, we focus on the third possibility by examining the properties of 22,437 published multiple sequence alignments, the Bayesian maximum likelihood trees for which either do or do not suggest the occurrence of LGT by the criterion of discordant branches. The alignments that produce discordant phylogenies differ significantly in several salient alignment properties from those that do not. Using a support vector machine, we were able to predict the inference of discordant tree topologies with up to 80% accuracy from alignment properties alone.

  3. Genome-wide identification, functional prediction, and evolutionary analysis of the R2R3-MYB superfamily in Brassica napus.

    PubMed

    Hajiebrahimi, Ali; Owji, Hajar; Hemmati, Shiva

    2017-10-01

    R2R3-MYB transcription factors (TFs) have been shown to play important roles in plants, including in development and in various stress conditions. Phylogenetic analysis showed the presence of 249 R2R3-MYB TFs in Brassica napus, called BnaR2R3-MYB TFs, clustered into 38 clades. BnaR2R3-MYB TFs were distributed on 19 chromosomes of B. napus. Sixteen gene clusters were identified. BnaR2R3-MYB TFs were characterized by motif prediction, gene structure analysis, and gene ontology. Evolutionary analysis revealed that BnaR2R3-MYB TFs are mainly formed as a result of whole-genome duplication. Orthologs and paralogs of BnaR2R3-MYB TFs were identified in B. napus, B. rapa, B. oleracea, and Arabidopsis thaliana using synteny-based methods. Purifying selection was pervasive within R2R3-MYB TFs. K n /K s values lower than 0.3 indicated that BnaR2R3-MYB TFs are being functionally converged. The role of gene conversion in the formation of BnaR2R3-MYB TFs was significant. Cis-regulatory elements in the upstream regions of BnaR2R3-MYB genes, miRNA targeting BnaR2R3MYB TFs, and post translational modifications were identified. Digital expression data revealed that BnaR2R3-MYB genes were highly expressed in the roots and under high salinity treatment after 24 h. BnaMYB21, BnaMYB141, and BnaMYB148 have been suggested for improving salt-tolerant B. napus. BnaR2R3-MYB genes were mostly up regulated on the 14th day post inoculation with Leptosphaeria biglobosa and L. maculan. BnaMYB150 is a candidate for increased tolerance to Leptospheria in B. napus.

  4. Novel Mutation in the ATP-Binding Cassette Transporter A3 (ABCA3) Encoding Gene Causes Respiratory Distress Syndrome in A Term Newborn in Southwest Iran

    PubMed Central

    Rezaei, Farideh; Shafiei, Mohammad; Shariati, Gholamreza; Dehdashtian, Ali; Mohebbi, Maryam; Galehdari, Hamid

    2016-01-01

    Introduction ABCA3 glycoprotein belongs to the ATP-binding cassette (ABC) superfamily of transporters, which utilize the energy derived from hydrolysis of ATP for the translocation of a wide variety of substrates across the plasma membrane. Mutations in the ABCA3 gene are knowingly causative for fatal surfactant deficiency, particularly respiratory distress syndrome (RDS) in term babies. Case Presentation In this study, Sanger sequencing of the whole ABCA3 gene (NCBI NM_001089) was performed in a neonatal boy with severe RDS. A homozygous mutation has been identified in the patient. Parents were heterozygous for the same missense mutation GGA > AGA at position 202 in exon 6 of the ABCA3 gene (c.604G > A; p.G202R). Furthermore, 70 normal individuals have been analyzed for the mentioned change with negative results. Conclusions Regarding Human Genome Mutation Database (HGMD) and other literature recherche, the detected change is a novel mutation and has not been reported before. Bioinformatics mutation predicting tools prefer it as pathogenic. PMID:27437095

  5. Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer.

    PubMed

    Wang, Haiying; Molina, Julian; Jiang, John; Ferber, Matthew; Pruthi, Sandhya; Jatkoe, Timothy; Derecho, Carlo; Rajpurohit, Yashoda; Zheng, Jian; Wang, Yixin

    2013-11-01

    Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and

  6. Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

    PubMed

    Weber, Kristina L; Welly, Bryan T; Van Eenennaam, Alison L; Young, Amy E; Porto-Neto, Laercio R; Reverter, Antonio; Rincon, Gonzalo

    2016-01-01

    Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

  7. Transformation of NIH3T3 Cells with Synthetic c‐Ha‐ras Genes

    PubMed Central

    Kamiya, Hiroyuki; Miura, Kazunobu; Ohtomo, Noriko; Koda, Toshiaki; Kakinuma, Mitsuaki; Nishimura, Susumu

    1989-01-01

    Synthetic human c‐Ha‐ras genes in which amino acid codons were altered to those which are frequently used in highly expressed Escherichia coli genes were ligated to the 3′‐end of Rous sarcoma virus long terminal repeat. When NIH3T3 cells were transfected with the plasmids having those genes with valine at codon 12, leucine at codon 61 or arginine at codon 61, transformants were efficiently produced. These results indicated that the synthetic c‐Ha‐ras genes are expressed in a mammalian system even though their codon usage is altered to correspond with that of E. colt. This expression vector system should he useful for studies on the structure‐function relationships of c‐Ha‐ras, since the synthetic gene can be easily modified to have multiple base alterations, and can also be used simultaneously for the production of large amounts of p21 in E. coli for biochemical and biophysical studies. PMID:2542206

  8. MiR-339 and especially miR-766 reactivate the expression of tumor suppressor genes in colorectal cancer cell lines through DNA methyltransferase 3B gene inhibition.

    PubMed

    Afgar, Ali; Fard-Esfahani, Pezhman; Mehrtash, Amirhosein; Azadmanesh, Kayhan; Khodarahmi, Farnaz; Ghadir, Mahdis; Teimoori-Toolabi, Ladan

    2016-11-01

    It is observed that upregulation of DNMT3B enzyme in some cancers, including colon cancer, could lead to silencing of tumor suppressor genes. MiR-339 and miR-766 have been predicted to target 3'UTR of DNMT3B gene. Luciferase reporter assay validated that individual and co-transfection of miR-766 and miR-339 into the HEK293T cell reduced luciferase activity to 26% ± 0.41%, 43% ± 0.42 and 64% ± 0.52%, respectively, compared to the control (P < 0.05). Furthermore, transduction of miR-339 and miR-766 expressing viruses into colon cancer cell lines (SW480 and HCT116) decreased DNMT3B expression (1.5, 3-fold) and (3, 4-fold), respectively. In addition, DNA methylation of some tumor suppressor genes decreased. Expression of these genes such as SFRP1 (2 and 1.6-fold), SFRP2 (0.07 and 4-fold), WIF1 (0.05 and 4-fold), and DKK2 (2 and 4-fold) increased in SW-339 and SW-766 cell lines; besides, expression increments for these genes in HCT-339 and HCT-766 cell lines were (2.8, 4-fold), (0.005, 1.5-fold), (1.7 and 3-fold) and (0.04, 1.7-fold), respectively. Also, while in SW-766, cell proliferation reduced to 2.8% and 21.7% after 24 and 48 hours, respectively, SW-339 showed no reduced proliferation. Meanwhile, HCT-766 and HCT-339 showed (3.5%, 12.8%) and (18.8%, 33.9%) reduced proliferation after 24 and 48 hours, respectively. Finally, targeting DNMT3B by these miRs, decreased methylation of tumor suppressor genes such as SFRP1, SFRP2, WIF1 and DKK2 in the mentioned cell lines, and returned the expression of these tumor suppressor genes which can contribute to lethal effect on colon cancer cells and reducing tumorigenicity of these cells.

  9. Prediction of C. elegans Longevity Genes by Human and Worm Longevity Networks

    PubMed Central

    de Magalhães, João Pedro; Ruvkun, Gary; Fraifeld, Vadim E.; Curran, Sean P.

    2012-01-01

    Intricate and interconnected pathways modulate longevity, but screens to identify the components of these pathways have not been saturating. Because biological processes are often executed by protein complexes and fine-tuned by regulatory factors, the first-order protein-protein interactors of known longevity genes are likely to participate in the regulation of longevity. Data-rich maps of protein interactions have been established for many cardinal organisms such as yeast, worms, and humans. We propose that these interaction maps could be mined for the identification of new putative regulators of longevity. For this purpose, we have constructed longevity networks in both humans and worms. We reasoned that the essential first-order interactors of known longevity-associated genes in these networks are more likely to have longevity phenotypes than randomly chosen genes. We have used C. elegans to determine whether post-developmental inactivation of these essential genes modulates lifespan. Our results suggest that the worm and human longevity networks are functionally relevant and possess a high predictive power for identifying new longevity regulators. PMID:23144747

  10. A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants.

    PubMed

    Pilkington, Sarah M; Crowhurst, Ross; Hilario, Elena; Nardozza, Simona; Fraser, Lena; Peng, Yongyan; Gunaseelan, Kularajathevan; Simpson, Robert; Tahir, Jibran; Deroles, Simon C; Templeton, Kerry; Luo, Zhiwei; Davy, Marcus; Cheng, Canhong; McNeilage, Mark; Scaglione, Davide; Liu, Yifei; Zhang, Qiong; Datson, Paul; De Silva, Nihal; Gardiner, Susan E; Bassett, Heather; Chagné, David; McCallum, John; Dzierzon, Helge; Deng, Cecilia; Wang, Yen-Yi; Barron, Lorna; Manako, Kelvina; Bowen, Judith; Foster, Toshi M; Erridge, Zoe A; Tiffin, Heather; Waite, Chethi N; Davies, Kevin M; Grierson, Ella P; Laing, William A; Kirk, Rebecca; Chen, Xiuyin; Wood, Marion; Montefiori, Mirco; Brummell, David A; Schwinn, Kathy E; Catanach, Andrew; Fullerton, Christina; Li, Dawei; Meiyalaghan, Sathiyamoorthy; Nieuwenhuizen, Niels; Read, Nicola; Prakash, Roneel; Hunter, Don; Zhang, Huaibi; McKenzie, Marian; Knäbel, Mareike; Harris, Alastair; Allan, Andrew C; Gleave, Andrew; Chen, Angela; Janssen, Bart J; Plunkett, Blue; Ampomah-Dwamena, Charles; Voogd, Charlotte; Leif, Davin; Lafferty, Declan; Souleyre, Edwige J F; Varkonyi-Gasic, Erika; Gambi, Francesco; Hanley, Jenny; Yao, Jia-Long; Cheung, Joey; David, Karine M; Warren, Ben; Marsh, Ken; Snowden, Kimberley C; Lin-Wang, Kui; Brian, Lara; Martinez-Sanchez, Marcela; Wang, Mindy; Ileperuma, Nadeesha; Macnee, Nikolai; Campin, Robert; McAtee, Peter; Drummond, Revel S M; Espley, Richard V; Ireland, Hilary S; Wu, Rongmei; Atkinson, Ross G; Karunairetnam, Sakuntala; Bulley, Sean; Chunkath, Shayhan; Hanley, Zac; Storey, Roy; Thrimawithana, Amali H; Thomson, Susan; David, Charles; Testolin, Raffaele; Huang, Hongwen; Hellens, Roger P; Schaffer, Robert J

    2018-04-16

    Most published genome sequences are drafts, and most are dominated by computational gene prediction. Draft genomes typically incorporate considerable sequence data that are not assigned to chromosomes, and predicted genes without quality confidence measures. The current Actinidia chinensis (kiwifruit) 'Hongyang' draft genome has 164 Mb of sequences unassigned to pseudo-chromosomes, and omissions have been identified in the gene models. A second genome of an A. chinensis (genotype Red5) was fully sequenced. This new sequence resulted in a 554.0 Mb assembly with all but 6 Mb assigned to pseudo-chromosomes. Pseudo-chromosomal comparisons showed a considerable number of translocation events have occurred following a whole genome duplication (WGD) event some consistent with centromeric Robertsonian-like translocations. RNA sequencing data from 12 tissues and ab initio analysis informed a genome-wide manual annotation, using the WebApollo tool. In total, 33,044 gene loci represented by 33,123 isoforms were identified, named and tagged for quality of evidential support. Of these 3114 (9.4%) were identical to a protein within 'Hongyang' The Kiwifruit Information Resource (KIR v2). Some proportion of the differences will be varietal polymorphisms. However, as most computationally predicted Red5 models required manual re-annotation this proportion is expected to be small. The quality of the new gene models was tested by fully sequencing 550 cloned 'Hort16A' cDNAs and comparing with the predicted protein models for Red5 and both the original 'Hongyang' assembly and the revised annotation from KIR v2. Only 48.9% and 63.5% of the cDNAs had a match with 90% identity or better to the original and revised 'Hongyang' annotation, respectively, compared with 90.9% to the Red5 models. Our study highlights the need to take a cautious approach to draft genomes and computationally predicted genes. Our use of the manual annotation tool WebApollo facilitated manual checking and

  11. Genome-Wide Identification of R2R3-MYB Genes and Expression Analyses During Abiotic Stress in Gossypium raimondii

    PubMed Central

    He, Qiuling; Jones, Don C.; Li, Wei; Xie, Fuliang; Ma, Jun; Sun, Runrun; Wang, Qinglian; Zhu, Shuijin; Zhang, Baohong

    2016-01-01

    The R2R3-MYB is one of the largest families of transcription factors, which have been implicated in multiple biological processes. There is great diversity in the number of R2R3-MYB genes in different plants. However, there is no report on genome-wide characterization of this gene family in cotton. In the present study, a total of 205 putative R2R3-MYB genes were identified in cotton D genome (Gossypium raimondii), that are much larger than that found in other cash crops with fully sequenced genomes. These GrMYBs were classified into 13 groups with the R2R3-MYB genes from Arabidopsis and rice. The amino acid motifs and phylogenetic tree were predicted and analyzed. The sequences of GrMYBs were distributed across 13 chromosomes at various densities. The results showed that the expansion of the G. Raimondii R2R3-MYB family was mainly attributable to whole genome duplication and segmental duplication. Moreover, the expression pattern of 52 selected GrMYBs and 46 GaMYBs were tested in roots and leaves under different abiotic stress conditions. The results revealed that the MYB genes in cotton were differentially expressed under salt and drought stress treatment. Our results will be useful for determining the precise role of the MYB genes during stress responses with crop improvement. PMID:27009386

  12. A new compound heterozygous frameshift mutation in the type II 3{beta}-hydroxysteroid dehydrogenase 3{beta}-HSD gene causes salt-wasting 3{beta}-HSD deficiency congenital adrenal hyperplasia

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, L.; Sakkal-Alkaddour, S.; Chang, Ying T.

    1996-01-01

    We report a new compound heterozygous frameshift mutation in the type II 3{Beta}-hydroxysteroid dehydrogenase (3{beta}-HSD) gene in a Pakistanian female child with the salt-wasting form of 3{Beta}-HSD deficiency congenital adrenal hyperplasia. The etiology for her congenital adrenal hyperplasia was not defined. Although the family history suggested possible 3{beta}-HSd deficiency disorder, suppressed adrenal function caused by excess glucocorticoid therapy in this child at 7 yr of age did not allow hormonal diagnosis. To confirm 3{beta}-HSD deficiency, we sequenced the type II 3{beta}-HSD gene in the patient, her family, and the parents of her deceased paternal cousins. The type II 3{beta}-HSD genemore » region of a putative promotor, exons I, II, III, and IV, and exon-intron boundaries were amplified by PCR and sequenced in all subjects. The DNA sequence of the child revealed a single nucleotide deletion at codon 318 [ACA(Thr){r_arrow}AA] in exon IV in one allele, and two nucleotide deletions at codon 273 [AAA(Lys){r_arrow}A] in exon IV in the other allele. The remaining gene sequences were normal. The codon 318 mutation was found in one allele from the father, brother, and parents of the deceased paternal cousins. The codon 273 mutation was found in one allele of the mother and a sister. These findings confirmed inherited 3{beta}-HSD deficiency in the child caused by the compound heterozygous type II 3{beta}-HSD gene mutation. Both codons at codons 279 and 367, respectively, are predicted to result in an altered and truncated type II 3{beta}-HSD protein, thereby causing salt-wasting 3{beta}-HSD deficiency in the patient. 21 refs., 2 figs., 1 tab.« less

  13. Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.

    PubMed

    Suo, Chen; Hrydziuszko, Olga; Lee, Donghwan; Pramana, Setia; Saputra, Dhany; Joshi, Himanshu; Calza, Stefano; Pawitan, Yudi

    2015-08-15

    Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores (P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/. yudi.pawitan@ki.se Supplementary data are

  14. Genes that characterize T3-predominant Graves' thyroid tissues.

    PubMed

    Matsumoto, Chisa; Ito, Mitsuru; Yamada, Hiroya; Yamakawa, Noriko; Yoshida, Hiroshi; Date, Arisa; Watanabe, Mikio; Hidaka, Yoh; Iwatani, Yoshinori; Miyauchi, Akira; Takano, Toru

    2013-02-01

    3,5,3'-Triiodothyronine (T(3))-predominant Graves' disease is characterized by the increasing volume of thyroid goiter resulting in poor prognosis. Although type 1 and type 2 iodothyronine deiodinases (DIO1 and DIO2 respectively) are known to be overexpressed in the thyroid tissues of T(3)-predominant Graves' disease, the pathogenesis of this disease is still unclear. The aim of our study is to identify genes that characterize T(3)-predominant Graves' disease tissue in order to clarify the molecular mechanism of this disease. mRNAs from two thyroid tissues of both typical T(3)-predominant and common-type Graves' disease were analyzed with DNA microarrays with probes for 28 869 genes. Genes identified to be differentially expressed between the two groups were further analyzed in the second and third screenings using 70 Graves' thyroid tissues by real-time quantitative RT-PCR. Twenty-three candidate genes were selected as being differentially expressed in the first screening with microarrays. Among these, seven genes, leucine-rich repeat neuronal 1 (LRRN1), bone morphogenetic protein 8a (BMP8A), N-cadherin (CDH2), phosphodiesterase 1A (PDE1A), creatine kinase mitochondrial 2 (CKMT2), integrin beta-3 (ITGB3), and protein tyrosine phosphatase non-receptor type 4 (PTPN4), were confirmed to be differentially expressed in DIO1 or DIO2 over- and underexpressing Graves' tissues. These genes are related to the characteristics of T(3)-predominant Graves' disease, such as high titer level of serum anti-TSH receptor antibody, high free T(3) to free thyroxine ratio, and a large goiter size. They might play a role in the pathogenesis of T(3)-predominant Graves' disease.

  15. Usher Syndrome Type III: Revised Genomic Structure of the USH3 Gene and Identification of Novel Mutations

    PubMed Central

    Fields, Randall R.; Zhou, Guimei; Huang, Dali; Davis, Jack R.; Möller, Claes; Jacobson, Samuel G.; Kimberling, William J.; Sumegi, Janos

    2002-01-01

    Usher syndrome type III is an autosomal recessive disorder characterized by progressive sensorineural hearing loss, vestibular dysfunction, and retinitis pigmentosa. The disease gene was localized to 3q25 and recently was identified by positional cloning. In the present study, we have revised the structure of the USH3 gene, including a new translation start site, 5′ untranslated region, and a transcript encoding a 232–amino acid protein. The mature form of the protein is predicted to contain three transmembrane domains and 204 residues. We have found four new disease-causing mutations, including one that appears to be relatively common in the Ashkenazi Jewish population. We have also identified mouse (chromosome 3) and rat (chromosome 2) orthologues, as well as two human paralogues on chromosomes 4 and 10. PMID:12145752

  16. Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients

    PubMed Central

    Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G.; Hoffman, Eric P.

    2016-01-01

    Abstract Objective. To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. Methods. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Results. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19 + B cells and CD68 + macrophages in responders. Conclusion. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. PMID:27215813

  17. Anopheles gambiae genome reannotation through synthesis of ab initio and comparative gene prediction algorithms

    PubMed Central

    Li, Jun; Riehle, Michelle M; Zhang, Yan; Xu, Jiannong; Oduol, Frederick; Gomez, Shawn M; Eiglmeier, Karin; Ueberheide, Beatrix M; Shabanowitz, Jeffrey; Hunt, Donald F; Ribeiro, José MC; Vernick, Kenneth D

    2006-01-01

    Background Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. Results We reannotate the A. gambiae genome by synthesizing comparative and ab initio sets of predicted coding sequences (CDSs) into a single set using an exon-gene-union algorithm followed by an open-reading-frame-selection algorithm. The reannotation predicts 20,970 CDSs supported by at least two lines of evidence, and it lowers the proportion of CDSs lacking start and/or stop codons to only approximately 4%. The reannotated CDS set includes a set of 4,681 novel CDSs not represented in the Ensembl annotation but with EST support, and another set of 4,031 Ensembl-supported genes that undergo major structural and, therefore, probably functional changes in the reannotated set. The quality and accuracy of the reannotation was assessed by comparison with end sequences from 20,249 full-length cDNA clones, and evaluation of mass spectrometry peptide hit rates from an A. gambiae shotgun proteomic dataset confirms that the reannotated CDSs offer a high quality protein database for proteomics. We provide a functional proteomics annotation, ReAnoXcel, obtained by analysis of the new CDSs through the AnoXcel pipeline, which allows functional comparisons of the CDS sets within the same bioinformatic platform. CDS data are available for download. Conclusion Comprehensive A. gambiae genome reannotation is achieved through a combination of comparative and ab initio gene prediction algorithms. PMID:16569258

  18. X-ray cross-complementing groups 1 rs1799782 C>T polymorphisms and colorectal cancer susceptibility: A meta-analysis based on Chinese Han population.

    PubMed

    Wang, Liming; Qian, Junfeng; Ying, Chunxiao; Zhuang, Yongwei; Shang, Xingjie; Xu, Fang

    2016-12-01

    X-ray cross-complementing groups 1 (XRCC1) rs1799782 C>T polymorphisms and colorectal cancer susceptibility were not clear. The purpose of this study was to evaluate the association between XRCC1 rs1799782 C>T polymorphisms and colorectal cancer susceptibility by meta-analysis. Related databases of Medline, CNKI, and Wanfang were systematic searched for the studies related to XRCC1 rs1799782 C>T polymorphisms and colorectal cancer risk in Chinese Han population. The genotype distribution of CC, CT and TT were extracted from each included studies in the colorectal cancer patients and healthy control subjects. The odds ratio (OR) and its 95% confidence interval (95% CI) was used to assess the correlation between genetype and colorectal cancer risk. The publications for this study was evaluated by Begg's funnel plot and Egger's line regression test. The median frequency of CC, CT, and TT genotype in cancer group were 48%, 41% and 11%; For control group, they were 51%, 40% and 8%; the pooled results showed that OR = 1.32 (95% CI: 1.041-1.67, P < 0.05). The pooled results indicated that XRCC1 rs1799782 C>T polymorphisms was associated with colorectal cancer susceptibility in recessive genetic model OR = 1.32 (95% CI: 1.041-1.67, P < 0.05), dominant genetic model OR = 1.21 (95% CI: 1.00-1.46, P < 0.05) and homozygous genetic model OR = 1.43 (95% CI: 1.07-1.91, P < 0.05). The funnel plot was significant asymmetric at the bottom and the Egger's test also indicated significant publication bias (t = 2.43, P = 0.04) for recessive genetic model. But, no publication bias was found in dominant and homozygous model (P > 0.05). Chinese Han people with rs1799782 TT/CT genotype of XRCC1 gene may have increased risk of developing colorectal.

  19. Why does parental language input style predict child language development? A twin study of gene-environment correlation.

    PubMed

    Dale, Philip S; Tosto, Maria Grazia; Hayiou-Thomas, Marianna E; Plomin, Robert

    2015-01-01

    There are well-established correlations between parental input style and child language development, which have typically been interpreted as evidence that the input style causes, or influences the rate of, changes in child language. We present evidence from a large twin study (TEDS; 8395 pairs for this report) that there are also likely to be both child-to-parent effects and shared genetic effects on parent and child. Self-reported parental language style at child age 3 and age 4 was aggregated into an 'informal language stimulation' factor and a 'corrective feedback' factor at each age; the former was positively correlated with child language concurrently and longitudinally at 3, 4, and 4.5 years, whereas the latter was weakly and negatively correlated. Both parental input factors were moderately heritable, as was child language. Longitudinal bivariate analysis showed that the correlation between the language stimulation factor and child language was significantly and moderately due to shared genes. There is some suggestive evidence from longitudinal phenotypic analysis that the prediction from parental language stimulation to child language includes both evocative and passive gene-environment correlation, with the latter playing a larger role. The reader will understand why correlations between parental language and rate of child language are by themselves ambiguous, and how twin studies can clarify the relationship. The reader will also understand that, based on the present study, at least two aspects of parental language style - informal language stimulation and corrective feedback - have substantial genetic influence, and that for informal language stimulation, a substantial portion of the prediction to child language represents the effect of shared genes on both parent and child. It will also be appreciated that these basic research findings do not imply that parental language input style is unimportant or that interventions cannot be effective. Copyright

  20. The tumorigenic FGFR3-TACC3 gene fusion escapes miR-99a regulation in glioblastoma.

    PubMed

    Parker, Brittany C; Annala, Matti J; Cogdell, David E; Granberg, Kirsi J; Sun, Yan; Ji, Ping; Li, Xia; Gumin, Joy; Zheng, Hong; Hu, Limei; Yli-Harja, Olli; Haapasalo, Hannu; Visakorpi, Tapio; Liu, Xiuping; Liu, Chang-Gong; Sawaya, Raymond; Fuller, Gregory N; Chen, Kexin; Lang, Frederick F; Nykter, Matti; Zhang, Wei

    2013-02-01

    Fusion genes are chromosomal aberrations that are found in many cancers and can be used as prognostic markers and drug targets in clinical practice. Fusions can lead to production of oncogenic fusion proteins or to enhanced expression of oncogenes. Several recent studies have reported that some fusion genes can escape microRNA regulation via 3'-untranslated region (3'-UTR) deletion. We performed whole transcriptome sequencing to identify fusion genes in glioma and discovered FGFR3-TACC3 fusions in 4 of 48 glioblastoma samples from patients both of mixed European and of Asian descent, but not in any of 43 low-grade glioma samples tested. The fusion, caused by tandem duplication on 4p16.3, led to the loss of the 3'-UTR of FGFR3, blocking gene regulation of miR-99a and enhancing expression of the fusion gene. The fusion gene was mutually exclusive with EGFR, PDGFR, or MET amplification. Using cultured glioblastoma cells and a mouse xenograft model, we found that fusion protein expression promoted cell proliferation and tumor progression, while WT FGFR3 protein was not tumorigenic, even under forced overexpression. These results demonstrated that the FGFR3-TACC3 gene fusion is expressed in human cancer and generates an oncogenic protein that promotes tumorigenesis in glioblastoma.

  1. ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

    PubMed Central

    Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

    2015-01-01

    Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

  2. A distinct adipose tissue gene expression response to caloric restriction predicts 6-mo weight maintenance in obese subjects.

    PubMed

    Mutch, David M; Pers, Tune H; Temanni, M Ramzi; Pelloux, Veronique; Marquez-Quiñones, Adriana; Holst, Claus; Martinez, J Alfredo; Babalis, Dimitris; van Baak, Marleen A; Handjieva-Darlenska, Teodora; Walker, Celia G; Astrup, Arne; Saris, Wim H M; Langin, Dominique; Viguerie, Nathalie; Zucker, Jean-Daniel; Clément, Karine

    2011-12-01

    Weight loss has been shown to reduce risk factors associated with cardiovascular disease and diabetes; however, successful maintenance of weight loss continues to pose a challenge. The present study was designed to assess whether changes in subcutaneous adipose tissue (scAT) gene expression during a low-calorie diet (LCD) could be used to differentiate and predict subjects who experience successful short-term weight maintenance from subjects who experience weight regain. Forty white women followed a dietary protocol consisting of an 8-wk LCD phase followed by a 6-mo weight-maintenance phase. Participants were classified as weight maintainers (WMs; 0-10% weight regain) and weight regainers (WRs; 50-100% weight regain) by considering changes in body weight during the 2 phases. Anthropometric measurements, bioclinical variables, and scAT gene expression were studied in all individuals before and after the LCD. Energy intake was estimated by using 3-d dietary records. No differences in body weight and fasting insulin were observed between WMs and WRs at baseline or after the LCD period. The LCD resulted in significant decreases in body weight and in several plasma variables in both groups. WMs experienced a significant reduction in insulin secretion in response to an oral-glucose-tolerance test after the LCD; in contrast, no changes in insulin secretion were observed in WRs after the LCD. An ANOVA of scAT gene expression showed that genes regulating fatty acid metabolism, citric acid cycle, oxidative phosphorylation, and apoptosis were regulated differently by the LCD in WM and WR subjects. This study suggests that LCD-induced changes in insulin secretion and scAT gene expression may have the potential to predict successful short-term weight maintenance. This trial was registered at clinicaltrials.gov as NCT00390637.

  3. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    PubMed

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http

  4. MicroRNA-124-3p expression and its prospective functional pathways in hepatocellular carcinoma: A quantitative polymerase chain reaction, gene expression omnibus and bioinformatics study.

    PubMed

    He, Rong-Quan; Yang, Xia; Liang, Liang; Chen, Gang; Ma, Jie

    2018-04-01

    The present study aimed to explore the potential clinical significance of microRNA (miR)-124-3p expression in the hepatocarcinogenesis and development of hepatocellular carcinoma (HCC), as well as the potential target genes of functional HCC pathways. Reverse transcription-quantitative polymerase chain reaction was performed to evaluate the expression of miR-124-3p in 101 HCC and adjacent non-cancerous tissue samples. Additionally, the association between miR-124-3p expression and clinical parameters was also analyzed. Differentially expressed genes identified following miR-124-3p transfection, the prospective target genes predicted in silico and the key genes of HCC obtained from Natural Language Processing (NLP) were integrated to obtain potential target genes of miR-124-3p in HCC. Relevant signaling pathways were assessed with protein-protein interaction (PPI) networks, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein Annotation Through Evolutionary Relationships (PANTHER) pathway enrichment analysis. miR-124-3p expression was significantly reduced in HCC tissues compared with expression in adjacent non-cancerous liver tissues. In HCC, miR-124-3p was demonstrated to be associated with clinical stage. The mean survival time of the low miR-124-3p expression group was reduced compared with that of the high expression group. A total of 132 genes overlapped from differentially expressed genes, miR-124-3p predicted target genes and NLP identified genes. PPI network construction revealed a total of 109 nodes and 386 edges, and 20 key genes were identified. The major enriched terms of three GO categories included regulation of cell proliferation, positive regulation of cellular biosynthetic processes, cell leading edge, cytosol and cell projection, protein kinase activity, transcription activator activity and enzyme binding. KEGG analysis revealed pancreatic cancer, prostate cancer and non-small cell lung cancer as the

  5. Genes encoding p-coumarate 3-hydroxylase (C3H) and methods of use

    DOEpatents

    Chapple, Clinton C. S.; Franke, Rochus; Ruegger, Max O.

    2006-07-04

    The present invention is directed to a method for altering secondary metabolism in plants, specifically phenylpropanoid metabolism. The present invention is further directed to a mutant p-coumarate 3-hydroxylase gene, referred to herein as the ref8 gene, its protein product which can be used to prepare gene constructs and transgenic plants. The gene constructs and transgenic plants are further aspects of the present invention.

  6. RGAugury: a pipeline for genome-wide prediction of resistance gene analogs (RGAs) in plants.

    PubMed

    Li, Pingchuan; Quan, Xiande; Jia, Gaofeng; Xiao, Jin; Cloutier, Sylvie; You, Frank M

    2016-11-02

    Resistance gene analogs (RGAs), such as NBS-encoding proteins, receptor-like protein kinases (RLKs) and receptor-like proteins (RLPs), are potential R-genes that contain specific conserved domains and motifs. Thus, RGAs can be predicted based on their conserved structural features using bioinformatics tools. Computer programs have been developed for the identification of individual domains and motifs from the protein sequences of RGAs but none offer a systematic assessment of the different types of RGAs. A user-friendly and efficient pipeline is needed for large-scale genome-wide RGA predictions of the growing number of sequenced plant genomes. An integrative pipeline, named RGAugury, was developed to automate RGA prediction. The pipeline first identifies RGA-related protein domains and motifs, namely nucleotide binding site (NB-ARC), leucine rich repeat (LRR), transmembrane (TM), serine/threonine and tyrosine kinase (STTK), lysin motif (LysM), coiled-coil (CC) and Toll/Interleukin-1 receptor (TIR). RGA candidates are identified and classified into four major families based on the presence of combinations of these RGA domains and motifs: NBS-encoding, TM-CC, and membrane associated RLP and RLK. All time-consuming analyses of the pipeline are paralleled to improve performance. The pipeline was evaluated using the well-annotated Arabidopsis genome. A total of 98.5, 85.2, and 100 % of the reported NBS-encoding genes, membrane associated RLPs and RLKs were validated, respectively. The pipeline was also successfully applied to predict RGAs for 50 sequenced plant genomes. A user-friendly web interface was implemented to ease command line operations, facilitate visualization and simplify result management for multiple datasets. RGAugury is an efficiently integrative bioinformatics tool for large scale genome-wide identification of RGAs. It is freely available at Bitbucket: https://bitbucket.org/yaanlpc/rgaugury .

  7. An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

    PubMed

    Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

    2017-07-25

    Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

  8. Web application for automatic prediction of gene translation elongation efficiency.

    PubMed

    Sokolov, Vladimir; Zuraev, Bulat; Lashin, Sergei; Matushkin, Yury

    2015-09-03

    Expression efficiency is one of the major characteristics describing genes in various modern investigations. Expression efficiency of genes is regulated at various stages: transcription, translation, posttranslational protein modification and others. In this study, a special EloE (Elongation Efficiency) web application is described. The EloE sorts the organism's genes in a descend order on their theoretical rate of the elongation stage of translation based on the analysis of their nucleotide sequences. Obtained theoretical data have a significant correlation with available experimental data of gene expression in various organisms. In addition, the program identifies preferential codons in organism's genes and defines distribution of potential secondary structures energy in 5´ and 3´ regions of mRNA. The EloE can be useful in preliminary estimation of translation elongation efficiency for genes for which experimental data are not available yet. Some results can be used, for instance, in other programs modeling artificial genetic structures in genetically engineered experiments.

  9. Safety and immunogenicity of MAGE-A3 cancer immunotherapeutic with dacarbazine in patients with MAGE-A3-positive metastatic cutaneous melanoma: an open phase I/II study with a first assessment of a predictive gene signature

    PubMed Central

    Grob, Jean-Jacques; Mortier, Laurent; D’Hondt, Lionel; Grange, Florent; Baurain, Jean Francois; Dréno, Brigitte; Lebbe, Céleste; Robert, Caroline; Dompmartin, Anne; Neyns, Bart; Gillet, Marc; Louahed, Jamila; Jarnjak, Silvija; Lehmann, Frédéric F

    2017-01-01

    Background We assessed safety, immunogenicity and clinical activity of recombinant MAGE-A3 antigen combined with AS15 immunostimulant (MAGE-A3 immunotherapeutic) in association with dacarbazine in patients with metastatic melanoma. Methods In this open-label, phase I/II, uncontrolled multicentre trial conducted in Belgium and France, patients with MAGE-A3-positive melanoma received up to 24 doses of MAGE-A3 immunotherapeutic (four cycles) coadministered with eight doses of dacarbazine. Adverse events (AE) were recorded until 31 days postvaccination, and serious AEs (SAE), until 30 days following the last dose. MAGE-A3-specific antibodies were measured by ELISA. Clinical activity of MAGE-A3 immunotherapeutic was assessed in patients positive/negative for previously identified gene signature (GS) associated with clinical outcome. Results Forty-eight patients were enrolled and treated (32 GS+, 15 GS−, 1 unknown GS status); two patients completed the study. All patients reported AEs, the most common were ‘general disorders and administration site conditions’ (94%). Treatment-related AEs were reported by 85% of patients; the most common was pain at injection site (38%). Sixteen SAEs were reported by 21% of patients; two were considered as treatment related (neutropenia and thrombocytopenia; grade 4). Postdose 4, all patients were seropositive for MAGE-A3-specific antibodies, with a geometric mean titre of 2778.7 ELISA units (EU)/mL (95% CI 1638.3 to 4712.8). One complete and three partial responses were reported (only in GS+ patients). Median overall survival was 11.4 months for GS+ and 5.3 months for GS− patients. Conclusion Although this trial shows poor results compared with the new results with checkpoint inhibitors, it gives an interesting insight in rapidly developing fields like combinations of immunotherapy and chemotherapy, new generation vaccines and the use of gene profile as a predictive marker. Trial registration number NCT00849875. PMID:29177094

  10. Safety and immunogenicity of MAGE-A3 cancer immunotherapeutic with dacarbazine in patients with MAGE-A3-positive metastatic cutaneous melanoma: an open phase I/II study with a first assessment of a predictive gene signature.

    PubMed

    Grob, Jean-Jacques; Mortier, Laurent; D'Hondt, Lionel; Grange, Florent; Baurain, Jean Francois; Dréno, Brigitte; Lebbe, Céleste; Robert, Caroline; Dompmartin, Anne; Neyns, Bart; Gillet, Marc; Louahed, Jamila; Jarnjak, Silvija; Lehmann, Frédéric F

    2017-01-01

    We assessed safety, immunogenicity and clinical activity of recombinant MAGE-A3 antigen combined with AS15 immunostimulant (MAGE-A3 immunotherapeutic) in association with dacarbazine in patients with metastatic melanoma. In this open-label, phase I/II, uncontrolled multicentre trial conducted in Belgium and France, patients with MAGE-A3-positive melanoma received up to 24 doses of MAGE-A3 immunotherapeutic (four cycles) coadministered with eight doses of dacarbazine. Adverse events (AE) were recorded until 31 days postvaccination, and serious AEs (SAE), until 30 days following the last dose. MAGE-A3-specific antibodies were measured by ELISA. Clinical activity of MAGE-A3 immunotherapeutic was assessed in patients positive/negative for previously identified gene signature (GS) associated with clinical outcome. Forty-eight patients were enrolled and treated (32 GS+, 15 GS-, 1 unknown GS status); two patients completed the study. All patients reported AEs, the most common were 'general disorders and administration site conditions' (94%). Treatment-related AEs were reported by 85% of patients; the most common was pain at injection site (38%). Sixteen SAEs were reported by 21% of patients; two were considered as treatment related (neutropenia and thrombocytopenia; grade 4). Postdose 4, all patients were seropositive for MAGE-A3-specific antibodies, with a geometric mean titre of 2778.7 ELISA units (EU)/mL (95% CI 1638.3 to 4712.8). One complete and three partial responses were reported (only in GS+ patients). Median overall survival was 11.4 months for GS+ and 5.3 months for GS- patients. Although this trial shows poor results compared with the new results with checkpoint inhibitors, it gives an interesting insight in rapidly developing fields like combinations of immunotherapy and chemotherapy, new generation vaccines and the use of gene profile as a predictive marker. NCT00849875.

  11. Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review.

    PubMed

    Kim, Bum Jun; Kim, Jung Han; Kim, Hyeong Su; Zang, Dae Young

    2017-02-21

    The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: 'kidney or renal', 'carcinoma or cancer or neoplasm or malignancy', 'von Hippel-Lindau or VHL', 'alteration or mutation or methylation', and 'prognostic or predictive'. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC.

  12. The tumorigenic FGFR3-TACC3 gene fusion escapes miR-99a regulation in glioblastoma

    PubMed Central

    Parker, Brittany C.; Annala, Matti J.; Cogdell, David E.; Granberg, Kirsi J.; Sun, Yan; Ji, Ping; Li, Xia; Gumin, Joy; Zheng, Hong; Hu, Limei; Yli-Harja, Olli; Haapasalo, Hannu; Visakorpi, Tapio; Liu, Xiuping; Liu, Chang-gong; Sawaya, Raymond; Fuller, Gregory N.; Chen, Kexin; Lang, Frederick F.; Nykter, Matti; Zhang, Wei

    2013-01-01

    Fusion genes are chromosomal aberrations that are found in many cancers and can be used as prognostic markers and drug targets in clinical practice. Fusions can lead to production of oncogenic fusion proteins or to enhanced expression of oncogenes. Several recent studies have reported that some fusion genes can escape microRNA regulation via 3′–untranslated region (3′-UTR) deletion. We performed whole transcriptome sequencing to identify fusion genes in glioma and discovered FGFR3-TACC3 fusions in 4 of 48 glioblastoma samples from patients both of mixed European and of Asian descent, but not in any of 43 low-grade glioma samples tested. The fusion, caused by tandem duplication on 4p16.3, led to the loss of the 3′-UTR of FGFR3, blocking gene regulation of miR-99a and enhancing expression of the fusion gene. The fusion gene was mutually exclusive with EGFR, PDGFR, or MET amplification. Using cultured glioblastoma cells and a mouse xenograft model, we found that fusion protein expression promoted cell proliferation and tumor progression, while WT FGFR3 protein was not tumorigenic, even under forced overexpression. These results demonstrated that the FGFR3-TACC3 gene fusion is expressed in human cancer and generates an oncogenic protein that promotes tumorigenesis in glioblastoma. PMID:23298836

  13. Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

    PubMed Central

    Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

    2012-01-01

    Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

  14. Caffeine inhibits homology-directed repair of I-SceI-induced DNA double-strand breaks.

    PubMed

    Wang, Huichen; Boecker, Wilfried; Wang, Hongyan; Wang, Xiang; Guan, Jun; Thompson, Larry H; Nickoloff, Jac A; Iliakis, George

    2004-01-22

    We recently reported that two Chinese hamster mutants deficient in the RAD51 paralogs XRCC2 and XRCC3 show reduced radiosensitization after treatment with caffeine, thus implicating homology-directed repair (HDR) of DNA double-strand breaks (DSBs) in the mechanism of caffeine radiosensitization. Here, we investigate directly the effect of caffeine on HDR initiated by DSBs induced by a rare cutting endonuclease (I-SceI) into one of two direct DNA repeats. The results demonstrate a strong inhibition by caffeine of HDR in wild-type cells, and a substantial reduction of this effect in HDR-deficient XRCC3 mutant cells. Inhibition of HDR and cell radiosensitization to killing shows similar dependence on caffeine concentration suggesting a cause-effect relationship between these effects. UCN-01, a kinase inhibitor that effectively abrogates checkpoint activation in irradiated cells, has only a small effect on HDR, indicating that similar to radiosensitization, inhibition of checkpoint signaling is not sufficient for HDR inhibition. Recombination events occurring during treatment with caffeine are characterized by rearrangements reminiscent to those previously reported for the XRCC3 mutant, and immunofluorescence microscopy demonstrates significantly reduced formation of IR-specific RAD51 foci after caffeine treatment. In summary, our results identify inhibition of HDR as a significant contributor to caffeine radiosensitization.

  15. KLF15 promotes transcription of KLF3 gene in bovine adipocytes.

    PubMed

    Guo, Hongfang; Khan, Rajwali; Raza, Sayed Haidar Abbas; Ning, Yue; Wei, Dawei; Wu, Sen; Hosseini, Seyed Mahdi; Ullah, Irfan; Garcia, Matthew D; Zan, Linsen

    2018-06-15

    The Krüppel-like factors (KLF) family plays an important role in adipogenesis, which is subject to internal hierarchical regulation. KLF3 is a member of KLF family, mainly responsible for adipocyte differentiation and fat deposition. However, the transcriptional regulation of bovine KLF3 gene and its relationship with KLF15 gene remains unclear during bovine adipogenesis. Here, we report that the expression pattern of KLF3 and KLF15 genes during bovine adipogenesis, when KLF15 gene was overexpressed through adenoviral vector (Ad-KLF15) in bovine adipocytes the expression level of KLF3 gene was increased, similarly when KLF15 was down regulated through siRNA the expression level of KLF3 was also reduced. To explore the transcriptional regulation of bovine KLF3 gene and its relationship with KLF15, serial deletion constructs of the 5'flanking region of bovine KLF3gene revealed through dual-luciferase reporter assay that the core promoter is located in -264 to -76 regions. The most proximal GGGG element in the promoter of the bovine KLF3 gene (located in -264 to -76 regions) is required for promotion by KLF15. Electrophoretic mobility shift (EMSA) and chromatin immunoprecipitation (ChIP) assays further confirmed that KLF15 gene binds to the KLF3 gene core promoter region in bovine adipocytes. These findings conclude that KLF15 promotes the transcriptional activity of KLF3 in bovine adipocytes. This mechanism to provides a new direction for further study of adipogenesis by internal regulation of members within KLF family. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer

    PubMed Central

    WANG, HAIYING; MOLINA, JULIAN; JIANG, JOHN; FERBER, MATTHEW; PRUTHI, SANDHYA; JATKOE, TIMOTHY; DERECHO, CARLO; RAJPUROHIT, YASHODA; ZHENG, JIAN; WANG, YIXIN

    2013-01-01

    Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and

  17. Altered Gene Expressions and Cytogenetic Repair Efficiency in Cells with Suppressed Expression of XPA after Proton Exposure

    NASA Technical Reports Server (NTRS)

    Zhang, Ye; Rohde, Larry H.; Gridley, Daila S.; Mehta, Satish K.; Pierson, Duane L.; Wu, Honglu

    2009-01-01

    Cellular responses to damages from ionizing radiation (IR) exposure are influenced not only by the genes involved in DNA double strand break (DSB) repair, but also by non- DSB repair genes. We demonstrated previously that suppressed expression of several non-DSB repair genes, such as XPA, elevated IR-induced cytogenetic damages. In the present study, we exposed human fibroblasts that were treated with control or XPA targeting siRNA to 250 MeV protons (0 to 4 Gy), and analyzed chromosome aberrations and expressions of genes involved in DNA repair. As expected, after proton irradiation, cells with suppressed expression of XPA showed a significantly elevated frequency of chromosome aberrations compared with control siRNA treated (CS) cells. Protons caused more severe DNA damages in XPA knock-down cells, as 36% cells contained multiple aberrations compared to 25% in CS cells after 4Gy proton irradiation. Comparison of gene expressions using the real-time PCR array technique revealed that expressions of p53 and its regulated genes in irradiated XPA suppressed cells were altered similarly as in CS cells, suggesting that the impairment of IR induced DNA repair in XPA suppressed cells is p53-independent. Except for XPA, which was more than 2 fold down regulated in XPA suppressed cells, several other DNA damage sensing and repair genes (GTSE1, RBBP8, RAD51, UNG and XRCC2) were shown a more than 1.5 fold difference between XPA knock-down cells and CS cells after proton exposure. The possible involvement of these genes in the impairment of DNA repair in XPA suppressed cells will be further investigated.

  18. Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

    PubMed Central

    Dinalankara, Wikum; Bravo, Héctor Corrada

    2015-01-01

    Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

  19. B29 Gene Silencing in Pituitary Cells is Regulated by Its 3′ Enhancer

    PubMed Central

    Malone, Cindy S.; Kuraishy, Ali I.; Fike, Francesca M.; Loya, Ruchika G.; Mikkili, Minil R.; Teitell, Michael A.; Wall, Randolph

    2007-01-01

    Summary B cell-specific B29 (Igβ, CD79b) genes in rat, mouse, and human are situated between the 5′ growth hormone (GH) locus control region (LCR) and the 3′ GH gene cluster. The entire GH genomic region is DNase1 hypersensitive in GH-expressing pituitary cells, which predicts an “open” chromatin configuration, and yet B29 is not expressed. The B29 promoter and enhancers exhibit histone deacetylation in pituitary cells, but histone deacetylase inhibition failed to activate B29 expression. The B29 promoter and a 3′ enhancer showed local dense DNA methylation in both pituitary and non-lymphoid cells consistent with gene silencing. However, DNA methyltransferase inhibition did not activate B29 expression either. B29 promoter constructs were minimally activated in transfected pituitary cells. Co-transfection of the B cell-specific octamer transcriptional co-activator Bob1 with the B29 promoter construct resulted in high level promoter activity in pituitary cells comparable to B29 promoter activity in transfected B cells. Unexpectedly, inclusion of the B29 3′ enhancer in B29 promoter constructs strongly inhibited B29 transcriptional activity even when pituitary cells were co-transfected with Bob1. Both Oct-1 and Pit-1 bind the B29 3′ enhancer in in vitro EMSA and in in vivo chromatin immunoprecipitation analyses. These data indicate that the GH locus-embedded, tissue-specific B29 gene is silenced in GH-expressing pituitary cells by epigenetic mechanisms, the lack of a B cell-specific transcription factor, and likely by the B29 3′ enhancer acting as a powerful silencer in a context and tissue-specific manner. PMID:16920149

  20. Resistance of hypoxic cells to ionizing radiation is influenced by homologous recombination status

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sprong, Debbie; Janssen, Hilde L.; Vens, Conchita

    2006-02-01

    Purpose: To determine the role of DNA repair in hypoxic radioresistance. Methods and Materials: Chinese hamster cell lines with mutations in homologous recombination (XRCC2, XRCC3, BRAC2, RAD51C) or nonhomologous end-joining (DNA-PKcs) genes were irradiated under normoxic (20% oxygen) and hypoxic (<0.1% oxygen) conditions, and the oxygen enhancement ratio (OER) was calculated. In addition, Fanconi anemia fibroblasts (complementation groups C and G) were compared with fibroblasts from nonsyndrome patients. RAD51 foci were studied using immunofluorescence. Results: All hamster cell lines deficient in homologous recombination showed a decrease in OER (1.5-2.0 vs. 2.6-3.0 for wild-types). In contrast, the OER for the DNA-PKcs-deficientmore » line was comparable to wild-type controls. The two Fanconi anemia cell strains also showed a significant reduction in OER. The OER for RAD51 foci formation at late times after irradiation was considerably lower than that for survival in wild-type cells. Conclusion: Homologous recombination plays an important role in determining hypoxic cell radiosensitivity. Lower OERs have also been reported in cells deficient in XPF and ERCC1, which, similar to homologous recombination genes, are known to play a role in cross-link repair. Because Fanconi anemia cells are also sensitive to cross-linking agents, this strengthens the notion that the capacity to repair cross-links determines hypoxic radiosensitivity.« less

  1. The association of folate pathway and DNA repair polymorphisms with susceptibility to childhood acute lymphoblastic leukemia.

    PubMed

    Goričar, Katja; Erčulj, Nina; Faganel Kotnik, Barbara; Debeljak, Maruša; Hovnik, Tinka; Jazbec, Janez; Dolžan, Vita

    2015-05-15

    Genetic factors may play an important role in susceptibility to childhood acute lymphoblastic leukemia (ALL). The aim of our study was to evaluate the associations of genetic polymorphisms in folate pathway and DNA repair genes with susceptibility to ALL. In total, 121 children with ALL and 184 unrelated healthy controls of Slovenian origin were genotyped for 14 polymorphisms in seven genes of folate pathway, base excision repair and homologous recombination repair (TYMS, MTHFR, OGG1, XRCC1, NBN, RAD51, and XRCC3). In addition, the exon 6 of NBN was screened for the presence of mutations using denaturing high performance liquid chromatography. Twelve polymorphisms were in Hardy-Weinberg equilibrium in controls and their genotype frequencies were in agreement with those reported in other Caucasian populations. Among the investigated polymorphisms and mutations, NBN Glu185Gln significantly decreased susceptibility to B-cell ALL (p=0.037), while TYMS 3R allele decreased susceptibility to T-cell ALL (p=0.011). Moreover, significantly decreased susceptibility to ALL was observed for MTHFR TA (p=0.030) and RAD51 GTT haplotypes (p=0.016). Susceptibility to ALL increased with the increasing number of risk alleles (ptrend=0.007). We also observed significant influence of hOGG-RAD51 and NBN-RAD51 interactions on susceptibility to ALL. Our results suggest that combination of several polymorphisms in DNA repair and folate pathways may significantly affect susceptibility to childhood ALL. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Accelerated Evolution of PAK3- and PIM1-like Kinase Gene Families in the Zebra Finch, Taeniopygia guttata

    PubMed Central

    Kong, Lesheng; Lovell, Peter V.; Heger, Andreas; Mello, Claudio V.; Ponting, Chris P.

    2010-01-01

    Genes encoding protein kinases tend to evolve slowly over evolutionary time, and only rarely do they appear as recent duplications in sequenced vertebrate genomes. Consequently, it was a surprise to find two families of kinase genes that have greatly and recently expanded in the zebra finch (Taeniopygia guttata) lineage. In contrast to other amniotic genomes (including chicken) that harbor only single copies of p21-activated serine/threonine kinase 3 (PAK3) and proviral integration site 1 (PIM1) genes, the zebra finch genome appeared at first to additionally contain 67 PAK3-like (PAK3L) and 51 PIM1-like (PIM1L) protein kinase genes. An exhaustive analysis of these gene models, however, revealed most to be incomplete, owing to the absence of terminal exons. After reprediction, 31 PAK3L genes and 10 PIM1L genes remain, and all but three are predicted, from the retention of functional sites and open reading frames, to be enzymatically active. PAK3L, but not PIM1L, gene sequences show evidence of recurrent episodes of positive selection, concentrated within structures spatially adjacent to N- and C-terminal protein regions that have been discarded from zebra finch PAK3L genes. At least seven zebra finch PAK3L genes were observed to be expressed in testis, whereas two sequences were found transcribed in the brain, one broadly including the song nuclei and the other in the ventricular zone and in cells resembling Bergmann's glia in the cerebellar Purkinje cell layer. Two PIM1L sequences were also observed to be expressed with broad distributions in the zebra finch brain, one in both the ventricular zone and the cerebellum and apparently associated with glial cells and the other showing neuronal cell expression and marked enrichment in midbrain/thalamic nuclei. These expression patterns do not correlate with zebra finch-specific features such as vocal learning. Nevertheless, our results show how ancient and conserved intracellular signaling molecules can be co

  3. RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.

    PubMed

    Hou, Qi; Bing, Zhi-Tong; Hu, Cheng; Li, Mao-Yin; Yang, Ke-Hu; Mo, Zu; Xie, Xiang-Wei; Liao, Ji-Lin; Lu, Yan; Horie, Shigeo; Lou, Ming-Wu

    2018-06-01

    Prostate cancer (PCa) is the most commonly diagnosed cancer in males in the Western world. Although prostate-specific antigen (PSA) has been widely used as a biomarker for PCa diagnosis, its results can be controversial. Therefore, new biomarkers are needed to enhance the clinical management of PCa. From publicly available microarray data, differentially expressed genes (DEGs) were identified by meta-analysis with RankProd. Genetic algorithm optimized artificial neural network (GA-ANN) was introduced to establish a diagnostic prediction model and to filter candidate genes. The diagnostic and prognostic capability of the prediction model and candidate genes were investigated in both GEO and TCGA datasets. Candidate genes were further validated by qPCR, Western Blot and Tissue microarray. By RankProd meta-analyses, 2306 significantly up- and 1311 down-regulated probes were found in 133 cases and 30 controls microarray data. The overall accuracy rate of the PCa diagnostic prediction model, consisting of a 15-gene signature, reached up to 100% in both the training and test dataset. The prediction model also showed good results for the diagnosis (AUC = 0.953) and prognosis (AUC of 5 years overall survival time = 0.808) of PCa in the TCGA database. The expression levels of three genes, FABP5, C1QTNF3 and LPHN3, were validated by qPCR. C1QTNF3 high expression was further validated in PCa tissue by Western Blot and Tissue microarray. In the GEO datasets, C1QTNF3 was a good predictor for the diagnosis of PCa (GSE6956: AUC = 0.791; GSE8218: AUC = 0.868; GSE26910: AUC = 0.972). In the TCGA database, C1QTNF3 was significantly associated with PCa patient recurrence free survival (P < .001, AUC = 0.57). In this study, we have developed a diagnostic and prognostic prediction model for PCa. C1QTNF3 was revealed as a promising biomarker for PCa. This approach can be applied to other high-throughput data from different platforms for the discovery of

  4. Characterization and anti-inflammation role of swine IFITM3 gene

    PubMed Central

    Li, He-Ping; Chen, Pei-Ge; Liu, Fu-Tao; Zhu, He-Shui; Jiao, Xian-Qin; Zhong, Kai; Guo, Yu-Jie; Zha, Guang-Ming; Han, Li-Qiang; Lu, Wei-Fei; Wang, Yue-Ying; Yang, Guo-Yu

    2017-01-01

    IFITM3 is involved in cell adhesion, apoptosis, immune, and antivirus activity. Furthermore, IFITM3 gene has been considered as a preferential marker for inflammatory diseases, and positive correlation to pathological grades. Therefore, we assumed that IFITM3 was regulated by different signal pathways. To better understand IFITM3 function in inflammatory response, we cloned swine IFITM3 gene, and detected IFITM3 distribution in tissues, as well as characterized this gene. Results indicated that the length of swine IFITM3 gene was 438 bp, encoding 145 amino acids. IFITM3 gene expression abundance was higher in spleen and lungs. Moreover, we next constructed the eukaryotic expression vector PBIFM3 and transfected into PK15 cells, finally obtained swine IFITM3 gene stable expression cell line. Meanwhile, we explored the effects of LPS on swine IFITM3 expression. Results showed that LPS increased IFITM3 mRNA abundance and exhibited time-dependent effect for LPS treatment. To further demonstrate the mechanism that IFITM3 regulated type I IFNs production, we also detected the important molecules expression of TLR4 signaling pathway. In transfected and non-transfected IFITM3 PK15 cells, LPS exacerbated the relative expression of TLR4-NFκB signaling molecules. However, the IFITM3 overexpression suppressed the inflammatory development of PK15 cells. In conclusion, these data indicated that the overexpression of swine IFITM3 could decrease the inflammatory response through TLR4 signaling pathway, and participate in type I interferon production. These findings may lead to an improved understanding of the biological function of IFITM3 in inflammation. PMID:29088728

  5. The Application of Gene Expression Profiling in Predictions of Occult Lymph Node Metastasis in Colorectal Cancer Patients

    PubMed Central

    Peyravian, Noshad; Larki, Pegah; Gharib, Ehsan; Nazemalhosseini-Mojarad, Ehsan; Anaraki, Fakhrosadate; Young, Chris; McClellan, James; Ashrafian Bonab, Maziar; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

    2018-01-01

    A key factor in determining the likely outcome for a patient with colorectal cancer is whether or not the tumour has metastasised to the lymph nodes—information which is also important in assessing any possibilities of lymph node resection so as to improve survival. In this review we perform a wide-range assessment of literature relating to recent developments in gene expression profiling (GEP) of the primary tumour, to determine their utility in assessing node status. A set of characteristic genes seems to be involved in the prediction of lymph node metastasis (LNM) in colorectal patients. Hence, GEP is applicable in personalised/individualised/tailored therapies and provides insights into developing novel therapeutic targets. Not only is GEP useful in prediction of LNM, but it also allows classification based on differences such as sample size, target gene expression, and examination method. PMID:29498671

  6. Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.

    PubMed

    Le, Duc-Hau; Verbeke, Lieven; Son, Le Hoang; Chu, Dinh-Toi; Pham, Van-Huy

    2017-11-14

    MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable

  7. H3K27me3 and H3K4me3 chromatin environment at super-induced dehydration stress memory genes of Arabidopsis thaliana.

    PubMed

    Liu, Ning; Fromm, Michael; Avramova, Zoya

    2014-03-01

    Pre-exposure to a stress may alter the plant's cellular, biochemical, and/or transcriptional responses during future encounters as a 'memory' from the previous stress. Genes increasing transcription in response to a first dehydration stress, but producing much higher transcript levels in a subsequent stress, represent the super-induced 'transcription memory' genes in Arabidopsis thaliana. The chromatin environment (histone H3 tri-methylations of Lys 4 and Lys 27, H3K4me3, and H3K27me3) studied at five dehydration stress memory genes revealed existence of distinct memory-response subclasses that responded differently to CLF deficiency and displayed different transcriptional activities during the watered recovery periods. Among the most important findings is the novel aspect of the H3K27me3 function observed at specific dehydration stress memory genes. In contrast to its well-known role as a chromatin repressive mechanism at developmentally regulated genes, H3K27me3 did not prevent transcription from the dehydration stress-responding genes. The high H3K27me3 levels present during transcriptionally inactive states did not interfere with the transition to active transcription and with H3K4me3 accumulation. H3K4me3 and H3K27me3 marks function independently and are not mutually exclusive at the dehydration stress-responding memory genes.

  8. Characterizing haploinsufficiency of SHELL gene to improve fruit form prediction in introgressive hybrids of oil palm.

    PubMed

    Teh, Chee-Keng; Muaz, Siti Dalila; Tangaya, Praveena; Fong, Po-Yee; Ong, Ai-Ling; Mayes, Sean; Chew, Fook-Tim; Kulaveerasingam, Harikrishna; Appleton, David

    2017-06-08

    The fundamental trait in selective breeding of oil palm (Eleais guineensis Jacq.) is the shell thickness surrounding the kernel. The monogenic shell thickness is inversely correlated to mesocarp thickness, where the crude palm oil accumulates. Commercial thin-shelled tenera derived from thick-shelled dura × shell-less pisifera generally contain 30% higher oil per bunch. Two mutations, sh MPOB (M1) and sh AVROS (M2) in the SHELL gene - a type II MADS-box transcription factor mainly present in AVROS and Nigerian origins, were reported to be responsible for different fruit forms. In this study, we have tested 1,339 samples maintained in Sime Darby Plantation using both mutations. Five genotype-phenotype discrepancies and eight controls were then re-tested with all five reported mutations (sh AVROS , sh MPOB , sh MPOB2 , sh MPOB3 and sh MPOB4 ) within the same gene. The integration of genotypic data, pedigree records and shell formation model further explained the haploinsufficiency effect on the SHELL gene with different number of functional copies. Some rare mutations were also identified, suggesting a need to further confirm the existence of cis-compound mutations in the gene. With this, the prediction accuracy of fruit forms can be further improved, especially in introgressive hybrids of oil palm. Understanding causative variant segregation is extremely important, even for monogenic traits such as shell thickness in oil palm.

  9. Prediction of atmospheric degradation data for POPs by gene expression programming.

    PubMed

    Luan, F; Si, H Z; Liu, H T; Wen, Y Y; Zhang, X Y

    2008-01-01

    Quantitative structure-activity relationship models for the prediction of the mean and the maximum atmospheric degradation half-life values of persistent organic pollutants were developed based on the linear heuristic method (HM) and non-linear gene expression programming (GEP). Molecular descriptors, calculated from the structures alone, were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. GEP yielded satisfactory prediction results: the square of the correlation coefficient r(2) was 0.80 and 0.81 for the mean and maximum half-life values of the test set, and the root mean square errors were 0.448 and 0.426, respectively. The results of this work indicate that the GEP is a very promising tool for non-linear approximations.

  10. PIK3CA gene mutations in Northwest Chinese esophageal squamous cell carcinoma

    PubMed Central

    Liu, Shi-Yuan; Chen, Wei; Chughtai, Ehtesham Annait; Qiao, Zhe; Jiang, Jian-Tao; Li, Shao-Min; Zhang, Wei; Zhang, Jin

    2017-01-01

    AIM To evaluate PIK3CA gene mutational status in Northwest Chinese esophageal squamous cell carcinoma (ESCC) patients, and examine the associations of PIK3CA gene mutations with clinicopathological characteristics and clinical outcome. METHODS A total of 210 patients with ESCC who underwent curative resection were enrolled in this study. Pyrosequencing was applied to investigate mutations in exons 9 and 20 of PIK3CA gene in 210 Northwest Chinese ESCCs. The associations of PIK3CA gene mutations with clinicopathological characteristics and clinical outcome were examined. RESULTS PIK3CA gene mutations in exon 9 were detected in 48 cases (22.9%) of a non-biased database of 210 curatively resected Northwest Chinese ESCCs. PIK3CA gene mutations were not associated with sex, tobacco use, alcohol use, tumor location, stage, or local recurrence. When compared with wild-type PIK3CA gene cases, patients with PIK3CA gene mutations in exons 9 experienced significantly better disease-free survival and overall survival rates. CONCLUSION The results of this study suggest that PIK3CA gene mutations could act as a prognostic biomarker in Northwest Chinese ESCC patients. PMID:28465643

  11. Predictive minimum description length principle approach to inferring gene regulatory networks.

    PubMed

    Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

    2011-01-01

    Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

  12. Gene Signature for Predicting Solid Tumors Patient Prognosis | NCI Technology Transfer Center | TTC

    Cancer.gov

    The National Cancer Institute’s Laboratory of Human Carcinogenesis seeks parties to license or co-develop a method of predicting the prognosis of a patient diagnosed with hepatocellular carcinoma (HCC) or breast cancer by detecting expression of one or more cancer-associated genes, and a method of identifying an agent for use in treating HCC.

  13. Meta4: a web application for sharing and annotating metagenomic gene predictions using web services.

    PubMed

    Richardson, Emily J; Escalettes, Franck; Fotheringham, Ian; Wallace, Robert J; Watson, Mick

    2013-01-01

    Whole-genome shotgun metagenomics experiments produce DNA sequence data from entire ecosystems, and provide a huge amount of novel information. Gene discovery projects require up-to-date information about sequence homology and domain structure for millions of predicted proteins to be presented in a simple, easy-to-use system. There is a lack of simple, open, flexible tools that allow the rapid sharing of metagenomics datasets with collaborators in a format they can easily interrogate. We present Meta4, a flexible and extensible web application that can be used to share and annotate metagenomic gene predictions. Proteins and predicted domains are stored in a simple relational database, with a dynamic front-end which displays the results in an internet browser. Web services are used to provide up-to-date information about the proteins from homology searches against public databases. Information about Meta4 can be found on the project website, code is available on Github, a cloud image is available, and an example implementation can be seen at.

  14. Improved methods and resources for paramecium genomics: transcription units, gene annotation and gene expression.

    PubMed

    Arnaiz, Olivier; Van Dijk, Erwin; Bétermier, Mireille; Lhuillier-Akakpo, Maoussi; de Vanssay, Augustin; Duharcourt, Sandra; Sallet, Erika; Gouzy, Jérôme; Sperling, Linda

    2017-06-26

    The 15 sibling species of the Paramecium aurelia cryptic species complex emerged after a whole genome duplication that occurred tens of millions of years ago. Given extensive knowledge of the genetics and epigenetics of Paramecium acquired over the last century, this species complex offers a uniquely powerful system to investigate the consequences of whole genome duplication in a unicellular eukaryote as well as the genetic and epigenetic mechanisms that drive speciation. High quality Paramecium gene models are important for research using this system. The major aim of the work reported here was to build an improved gene annotation pipeline for the Paramecium lineage. We generated oriented RNA-Seq transcriptome data across the sexual process of autogamy for the model species Paramecium tetraurelia. We determined, for the first time in a ciliate, candidate P. tetraurelia transcription start sites using an adapted Cap-Seq protocol. We developed TrUC, multi-threaded Perl software that in conjunction with TopHat mapping of RNA-Seq data to a reference genome, predicts transcription units for the annotation pipeline. We used EuGene software to combine annotation evidence. The high quality gene structural annotations obtained for P. tetraurelia were used as evidence to improve published annotations for 3 other Paramecium species. The RNA-Seq data were also used for differential gene expression analysis, providing a gene expression atlas that is more sensitive than the previously established microarray resource. We have developed a gene annotation pipeline tailored for the compact genomes and tiny introns of Paramecium species. A novel component of this pipeline, TrUC, predicts transcription units using Cap-Seq and oriented RNA-Seq data. TrUC could prove useful beyond Paramecium, especially in the case of high gene density. Accurate predictions of 3' and 5' UTR will be particularly valuable for studies of gene expression (e.g. nucleosome positioning, identification of cis

  15. Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

    PubMed

    Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

    2018-05-01

    Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients

  16. ZY3-02 Laser Altimeter Footprint Geolocation Prediction

    PubMed Central

    Xie, Junfeng; Tang, Xinming; Mo, Fan; Li, Guoyuan; Zhu, Guangbin; Wang, Zhenming; Fu, Xingke; Gao, Xiaoming; Dou, Xianhui

    2017-01-01

    Successfully launched on 30 May 2016, ZY3-02 is the first Chinese surveying and mapping satellite equipped with a lightweight laser altimeter. Calibration is necessary before the laser altimeter becomes operational. Laser footprint location prediction is the first step in calibration that is based on ground infrared detectors, and it is difficult because the sample frequency of the ZY3-02 laser altimeter is 2 Hz, and the distance between two adjacent laser footprints is about 3.5 km. In this paper, we build an on-orbit rigorous geometric prediction model referenced to the rigorous geometric model of optical remote sensing satellites. The model includes three kinds of data that must be predicted: pointing angle, orbit parameters, and attitude angles. The proposed method is verified by a ZY3-02 laser altimeter on-orbit geometric calibration test. Five laser footprint prediction experiments are conducted based on the model, and the laser footprint prediction accuracy is better than 150 m on the ground. The effectiveness and accuracy of the on-orbit rigorous geometric prediction model are confirmed by the test results. The geolocation is predicted precisely by the proposed method, and this will give a reference to the geolocation prediction of future land laser detectors in other laser altimeter calibration test. PMID:28934160

  17. ZY3-02 Laser Altimeter Footprint Geolocation Prediction.

    PubMed

    Xie, Junfeng; Tang, Xinming; Mo, Fan; Li, Guoyuan; Zhu, Guangbin; Wang, Zhenming; Fu, Xingke; Gao, Xiaoming; Dou, Xianhui

    2017-09-21

    Successfully launched on 30 May 2016, ZY3-02 is the first Chinese surveying and mapping satellite equipped with a lightweight laser altimeter. Calibration is necessary before the laser altimeter becomes operational. Laser footprint location prediction is the first step in calibration that is based on ground infrared detectors, and it is difficult because the sample frequency of the ZY3-02 laser altimeter is 2 Hz, and the distance between two adjacent laser footprints is about 3.5 km. In this paper, we build an on-orbit rigorous geometric prediction model referenced to the rigorous geometric model of optical remote sensing satellites. The model includes three kinds of data that must be predicted: pointing angle, orbit parameters, and attitude angles. The proposed method is verified by a ZY3-02 laser altimeter on-orbit geometric calibration test. Five laser footprint prediction experiments are conducted based on the model, and the laser footprint prediction accuracy is better than 150 m on the ground. The effectiveness and accuracy of the on-orbit rigorous geometric prediction model are confirmed by the test results. The geolocation is predicted precisely by the proposed method, and this will give a reference to the geolocation prediction of future land laser detectors in other laser altimeter calibration test.

  18. Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

    PubMed Central

    2013-01-01

    Background To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Methods Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Results Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration

  19. Large deletion at the CDC73 gene locus and search for predictive markers of the presence of a CDC73 genetic lesion.

    PubMed

    Muscarella, Lucia Anna; Turchetti, Daniela; Fontana, Andrea; Baorda, Filomena; Palumbo, Orazio; la Torre, Annamaria; de Martino, Danilo; Franco, Renato; Losito, Nunzia Simona; Repaci, Andrea; Pagotto, Uberto; Cinque, Luigia; Copetti, Massimiliano; Chiofalo, Maria Grazia; Pezzullo, Luciano; Graziano, Paolo; Scillitani, Alfredo; Guarnieri, Vito

    2018-04-17

    The Hyperparathyroidism with Jaw-Tumours syndrome is caused by mutations of the CDC73 gene: it has been suggested that early onset of the disease and high Ca 2+ levels may predict the presence of a CDC73 mutation. We searched for large deletions at the CDC73 locus in patients with: HPT-JT (nr 2), atypical adenoma (nr 7) or sporadic parathyroid carcinoma (nr 11) with a specific MLPA and qRT-PCR assays applied on DNA extracted from whole blood. A Medline search in database for all the papers reporting a CDC73 gene mutation, clinical/histological diagnosis, age at onset, Ca 2+ , PTH levels for familial/sporadic cases was conducted with the aim to possibly identify biochemical/clinical markers predictive, in first diagnosis, of the presence of a CDC73 gene mutation. A novel genomic deletion of the first 10 exons of the CDC73 gene was found in a 3-generation HPT-JT family, confirmed by SNP array analysis. A classification tree built on the published data, showed the highest probability of having a CDC73 mutation in subjects with age at the onset < 41.5 years (44/47 subjects, 93.6%, had the mutation). Whereas the lowest probability was found in subjects with age at the onset ≥ 41.5 years and Ca 2+ levels <13.96 mg/dL (7/20 subjects, 35.0%, had the mutation, odds ratio = 27.1, p < 0.001). We report a novel large genomic CDC73 gene deletion identified in an Italian HPT-JT family. Age at onset < 41.5 ys and Ca 2+ > 13.96 mg/dL are predictive for the presence of a CDC73 genetic lesion.

  20. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    NASA Astrophysics Data System (ADS)

    Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

    2015-12-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

  1. Phenome-driven disease genetics prediction toward drug discovery.

    PubMed

    Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

    2015-06-15

    Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

  2. Phenome-driven disease genetics prediction toward drug discovery

    PubMed Central

    Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

    2015-01-01

    Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp

  3. Sci—Thur AM: YIS - 02: Radiogenomic Modeling of Normal Tissue Toxicities in Prostate Cancer Patients Receiving Hypofractionated Radiotherapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Coates, J; Jeyaseelan, K; Ybarra, N

    2014-08-15

    Inter-patient radiation sensitivity variability has recently been shown to have a genetic component. This genetic component may play a key role in explaining the fluctuating rates of radiation-induced toxicities (RITs). Single nucleotide polymorphisms (SNPs) have thus far yielded inconsistent results in delineating RITs while copy number variations (CNVs) have not yet been investigated for such purposes. We explore a radiogenomic modeling approach to investigate the association of CNVs and SNPs, along with clinical and dosimetric variables, in radiation induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients treated with curative hypofractionated irradiation. A cohort of 62 prostatemore » cancer patients who underwent hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 to 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Late toxicity rates for RB grade 2 and 3 and grade 3 alone were 29.0% and 12.9%, respectively. ED toxicity was found to be 62.9%. Radiogenomic model performance was evaluated using receiver operating characteristic area under the curve (AUC) and resampling by cross-validation. Binary variables were evaluated using Chi-squared contingency table analysis and multivariate models by Spearman's rank correlation coefficient (rs). Ten patients were found to have three copies of xrcc1 CNV (RB: χ{sup 2}=14.6, p<0.001 and ED: χ{sup 2}=4.88, p=0.0272) and twelve had heterozygous rs25489 SNP (RB: χ{sup 2}=0.278, p=0.599 and ED: χ{sup 2}=0.112, p=0.732). Radiogenomic modeling yielded significant, cross-validated NTCP models for RB (AUC=0.665) and ED (AUC=0.754). These results indicate that CNVs may be potential predictive biomarkers of both late ED and RB.« less

  4. Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

    PubMed Central

    2009-01-01

    Background The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes. Results We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality. Conclusion We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality. PMID:19758426

  5. Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients.

    PubMed

    Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G; Hoffman, Eric P; Miller, Frederick W

    2016-09-01

    To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19(+) B cells and CD68(+) macrophages in responders. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. Published by Oxford University Press on behalf British Society for Rheumatology 2016. This work is written by US Government employees and is in the public domain in the US.

  6. An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data.

    PubMed

    Nidheesh, N; Abdul Nazeer, K A; Ameer, P M

    2017-12-01

    Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids. We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids. We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others. There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. A systems level predictive model for global gene regulation of methanogenesis in a hydrogenotrophic methanogen

    PubMed Central

    Yoon, Sung Ho; Turkarslan, Serdar; Reiss, David J.; Pan, Min; Burn, June A.; Costa, Kyle C.; Lie, Thomas J.; Slagel, Joseph; Moritz, Robert L.; Hackett, Murray; Leigh, John A.; Baliga, Nitin S.

    2013-01-01

    Methanogens catalyze the critical methane-producing step (called methanogenesis) in the anaerobic decomposition of organic matter. Here, we present the first predictive model of global gene regulation of methanogenesis in a hydrogenotrophic methanogen, Methanococcus maripaludis. We generated a comprehensive list of genes (protein-coding and noncoding) for M. maripaludis through integrated analysis of the transcriptome structure and a newly constructed Peptide Atlas. The environment and gene-regulatory influence network (EGRIN) model of the strain was constructed from a compendium of transcriptome data that was collected over 58 different steady-state and time-course experiments that were performed in chemostats or batch cultures under a spectrum of environmental perturbations that modulated methanogenesis. Analyses of the EGRIN model have revealed novel components of methanogenesis that included at least three additional protein-coding genes of previously unknown function as well as one noncoding RNA. We discovered that at least five regulatory mechanisms act in a combinatorial scheme to intercoordinate key steps of methanogenesis with different processes such as motility, ATP biosynthesis, and carbon assimilation. Through a combination of genetic and environmental perturbation experiments we have validated the EGRIN-predicted role of two novel transcription factors in the regulation of phosphate-dependent repression of formate dehydrogenase—a key enzyme in the methanogenesis pathway. The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions. PMID:24089473

  8. VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

    PubMed

    Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

    2007-07-01

    With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

  9. Study on predictive role of AR and EGFR family genes with response to neoadjuvant chemotherapy in locally advanced breast cancer in Indian women.

    PubMed

    Singh, L C; Chakraborty, Anurupa; Mishra, Ashwani K; Devi, Thoudam Regina; Sugandhi, Nidhi; Chintamani, Chintamani; Bhatnagar, Dinesh; Kapur, Sujala; Saxena, Sunita

    2012-06-01

    Locally advanced breast cancer (LABC) remains a clinical challenge as the majority of patients with this diagnosis develop distant metastases despite appropriate therapy. We analyzed expression of steroid and growth hormone receptor genes as well as gene associated with metabolism of chemotherapeutic drugs in locally advanced breast cancer before and after neoadjuvant chemotherapy (NACT) to study whether there is a change in gene expression induced by chemotherapy and whether such changes are associated with tumor response or non-response. Fifty patients were included with locally advanced breast cancer treated with cyclophosphamide, adriamycin, 5-fluorouracil (CAF)-based neoadjuvant chemotherapy before surgery. Total RNA was extracted from 50 match samples of pre- and post-NACT tumor tissues. RNA expression levels of epidermal growth factor receptor family genes including EGFR, ERBB2, ERBB3, androgen receptor (AR), and multidrug-resistance gene 1 (MDR1) were determined by quantitative real-time reverse transcriptase-polymerase chain reaction. Responders show significantly high levels of pre-NACT AR gene expression (P = 0.016), which reduces following NACT (P = 0.008), and hence can serve as a useful tool for the prediction of the success of neoadjuvant chemotherapy in individual cancer patients with locally advanced breast carcinoma. Moreover, a significant post-therapeutic increase in the expression levels of EGFR and MDR1 gene in responders (P = 0.026 and P < 0.001) as well as in non-responders (P = 0.055, P = 0.001) suggests that expression of these genes changes during therapy but they do not have any impact on tumor response, whereas a post-therapeutic reduction was observed in AR in responders. This indicates an independent predictive role of AR with response to NACT.

  10. The cure: design and evaluation of a crowdsourcing game for gene selection for breast cancer survival prediction.

    PubMed

    Good, Benjamin M; Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

    2014-07-29

    Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player's prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this

  11. The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction

    PubMed Central

    Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

    2014-01-01

    Background Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. Objective The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player’s prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. Methods We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Results Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive

  12. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    PubMed

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Comparative study of polymorphism frequencies of the CYP2D6, CYP3A5, CYP2C8 and IL-10 genes in Mexican and Spanish women with breast cancer.

    PubMed

    Alcazar-González, Gregorio Antonio; Calderón-Garcidueñas, Ana Laura; Garza-Rodríguez, María Lourdes; Rubio-Hernández, Gabriela; Escorza-Treviño, Sergio; Olano-Martin, Estibaliz; Cerda-Flores, Ricardo Martín; Castruita-Avila, Ana Lilia; González-Guerrero, Juan Francisco; le Brun, Stéphane; Simon-Buela, Laureano; Barrera-Saldaña, Hugo Alberto

    2013-10-01

    Pharmacogenetic studies in breast cancer (BC) may predict the efficacy of tamoxifen and the toxicity of paclitaxel and capecitabine. We determined the frequency of polymorphisms in the CYP2D6 gene associated with activation of tamoxifen, and those of the genes CYP2C8, CYP3A5 and DPYD associated with toxicity of paclitaxel and capecitabine. We also included a IL-10 gene polymorphism associated with advanced tumor stage at diagnosis. Genomic DNAs from 241 BC patients from northeast Mexico were genotyped using DNA microarray technology. For tamoxifen processing, CYP2D6 genotyping predicted that 90.8% of patients were normal metabolizers, 4.2% ultrarapid, 2.1% intermediate and 2.9% poor metabolizers. For paclitaxel and the CYP2C8 gene, 75.3% were normal, 23.4% intermediate and 1.3% poor metabolizers. Regarding the DPYD gene, only one patient was a poor metabolizer. For the IL-10 gene, 47.1% were poor metabolizers. These results contribute valuable information towards personalizing BC chemotherapy in Mexican women.

  14. Profiling of histone H3 lysine 9 trimethylation levels predicts transcription factor activity and survival in acute myeloid leukemia.

    PubMed

    Müller-Tidow, Carsten; Klein, Hans-Ulrich; Hascher, Antje; Isken, Fabienne; Tickenbrock, Lara; Thoennissen, Nils; Agrawal-Singh, Shuchi; Tschanter, Petra; Disselhoff, Christine; Wang, Yipeng; Becker, Anke; Thiede, Christian; Ehninger, Gerhard; zur Stadt, Udo; Koschmieder, Steffen; Seidl, Matthias; Müller, Frank U; Schmitz, Wilhelm; Schlenke, Peter; McClelland, Michael; Berdel, Wolfgang E; Dugas, Martin; Serve, Hubert

    2010-11-04

    Acute myeloid leukemia (AML) is commonly associated with alterations in transcription factors because of altered expression or gene mutations. These changes might induce leukemia-specific patterns of histone modifications. We used chromatin-immunoprecipitation on microarray to analyze histone 3 lysine 9 trimethylation (H3K9me3) patterns in primary AML (n = 108), acute lymphoid leukemia (n = 28), CD34(+) cells (n = 21) and white blood cells (n = 15) specimens. Hundreds of promoter regions in AML showed significant alterations in H3K9me3 levels. H3K9me3 deregulation in AML occurred preferentially as a decrease in H3K9me3 levels at core promoter regions. The altered genomic regions showed an overrepresentation of cis-binding sites for ETS and cyclic adenosine monophosphate response elements (CREs) for transcription factors of the CREB/CREM/ATF1 family. The decrease in H3K9me3 levels at CREs was associated with increased CRE-driven promoter activity in AML blasts in vivo. AML-specific H3K9me3 patterns were not associated with known cytogenetic abnormalities. But a signature derived from H3K9me3 patterns predicted event-free survival in AML patients. When the H3K9me3 signature was combined with established clinical prognostic markers, it outperformed prognosis prediction based on clinical parameters alone. These findings demonstrate widespread changes of H3K9me3 levels at gene promoters in AML. Signatures of histone modification patterns are associated with patient prognosis in AML.

  15. Profiling of histone H3 lysine 9 trimethylation levels predicts transcription factor activity and survival in acute myeloid leukemia

    PubMed Central

    Klein, Hans-Ulrich; Hascher, Antje; Isken, Fabienne; Tickenbrock, Lara; Thoennissen, Nils; Agrawal-Singh, Shuchi; Tschanter, Petra; Disselhoff, Christine; Wang, Yipeng; Becker, Anke; Thiede, Christian; Ehninger, Gerhard; zur Stadt, Udo; Koschmieder, Steffen; Seidl, Matthias; Müller, Frank U.; Schmitz, Wilhelm; Schlenke, Peter; McClelland, Michael; Berdel, Wolfgang E.; Dugas, Martin; Serve, Hubert

    2010-01-01

    Acute myeloid leukemia (AML) is commonly associated with alterations in transcription factors because of altered expression or gene mutations. These changes might induce leukemia-specific patterns of histone modifications. We used chromatin-immunoprecipitation on microarray to analyze histone 3 lysine 9 trimethylation (H3K9me3) patterns in primary AML (n = 108), acute lymphoid leukemia (n = 28), CD34+ cells (n = 21) and white blood cells (n = 15) specimens. Hundreds of promoter regions in AML showed significant alterations in H3K9me3 levels. H3K9me3 deregulation in AML occurred preferentially as a decrease in H3K9me3 levels at core promoter regions. The altered genomic regions showed an overrepresentation of cis-binding sites for ETS and cyclic adenosine monophosphate response elements (CREs) for transcription factors of the CREB/CREM/ATF1 family. The decrease in H3K9me3 levels at CREs was associated with increased CRE-driven promoter activity in AML blasts in vivo. AML-specific H3K9me3 patterns were not associated with known cytogenetic abnormalities. But a signature derived from H3K9me3 patterns predicted event-free survival in AML patients. When the H3K9me3 signature was combined with established clinical prognostic markers, it outperformed prognosis prediction based on clinical parameters alone. These findings demonstrate widespread changes of H3K9me3 levels at gene promoters in AML. Signatures of histone modification patterns are associated with patient prognosis in AML. PMID:20498303

  16. The 14-3-3σ gene promoter is methylated in both human melanocytes and melanoma

    PubMed Central

    2009-01-01

    Background Recent evidence demonstrates that 14-3-3σ acts as a tumor suppressor gene inactivated by methylation of its 5' CpG islands in epithelial tumor cells, while remaining un-methylated in normal human epithelia. The methylation analysis of 14-3-3σ has been largely overlooked in melanoma. Methods The methylation status of 14-3-3σ CpG island in melanocytes and melanoma cells was analyzed by methylation-specific sequencing (MSS) and quantitative methylation-specific PCR (Q-MSP). 14-3-3σ mRNA and protein expression in cell lines was detected by real-time RT-PCR and western blot. Melanoma cells were also treated by 5-aza-2'-deoxycytidine (DAC), a demethylating agent, and/or histone deacetylase inhibitor, Trichostatin A (TSA), to evaluate their effects on 14-3-3σ gene expression. Results 14-3-3σ is hypermethylated in both human melanocytes and most melanoma cells in a lineage-specific manner, resulting in the silencing of 14-3-3σ gene expression and the active induction of 14-3-3σ mRNA and protein expression following treatment with DAC. We also observed a synergistic effect upon gene expression when DAC was combined with TSA. The promoter methylation status of 14-3-3σ was analyzed utilizing Q-MSP in 20 melanoma tissue samples and 10 cell lines derived from these samples, showing that the majority of melanoma samples maintain their hypermethylation status of the 14-3-3σ gene. Conclusion 14-3-3σ is hypermethylated in human melanoma in a cell-linage specific manner. Spontaneous demethylation and re-expression of 14-3-3σ is a rare event in melanoma, indicating 14-3-3σ might have a tentative role in the pathogenesis of melanoma. PMID:19473536

  17. Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries.

    PubMed

    Monteiro Santos, Erika Maria; Valentin, Mev Dominguez; Carneiro, Felipe; de Oliveira, Ligia Petrolini; de Oliveira Ferreira, Fabio; Junior, Samuel Aguiar; Nakagawa, Wilson Toshihiko; Gomy, Israel; de Faria Ferraz, Victor Evangelista; da Silva Junior, Wilson Araujo; Carraro, Dirce Maria; Rossi, Benedito Mauro

    2012-02-09

    Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed. Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846), Barnetson (0.850), MMRpro (0.821) and Wijnen (0.807) models did not present significant statistical difference. The Myriad model presented lower AUC (0.704) than the four other models evaluated. Considering thresholds of ≥ 5%, the models sensitivity varied between 1 (Myriad) and 0.87 (Wijnen) and specificity ranged from 0 (Myriad) to 0.38 (Barnetson). The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.

  18. Towards Long-Range RNA Structure Prediction in Eukaryotic Genes.

    PubMed

    Pervouchine, Dmitri D

    2018-06-15

    The ability to form an intramolecular structure plays a fundamental role in eukaryotic RNA biogenesis. Proximate regions in the primary transcripts fold into a local secondary structure, which is then hierarchically assembled into a tertiary structure that is stabilized by RNA-binding proteins and long-range intramolecular base pairings. While the local RNA structure can be predicted reasonably well for short sequences, long-range structure at the scale of eukaryotic genes remains problematic from the computational standpoint. The aim of this review is to list functional examples of long-range RNA structures, to summarize current comparative methods of structure prediction, and to highlight their advances and limitations in the context of long-range RNA structures. Most comparative methods implement the “first-align-then-fold” principle, i.e., they operate on multiple sequence alignments, while functional RNA structures often reside in non-conserved parts of the primary transcripts. The opposite “first-fold-then-align” approach is currently explored to a much lesser extent. Developing novel methods in both directions will improve the performance of comparative RNA structure analysis and help discover novel long-range structures, their higher-order organization, and RNA⁻RNA interactions across the transcriptome.

  19. GenePRIMP: Improving Microbial Gene Prediction Quality

    ScienceCinema

    Pati, Amrita

    2018-01-24

    Amrita Pati of the DOE Joint Genome Institute's Genome Biology group talks about a computational pipeline that evaluates the accuracy of gene models in genomes and metagenomes at different stages of finishing at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.

  20. [Construction and function identification of luciferase reporter gene vectors containing SNPs in NFKBIA gene 3'UTR].

    PubMed

    Yang, Shuo; Li, Jia-li; Bi, Hui-chang; Zhou, Shou-ning; Liu, Xiao-man; Zeng, Hang; Hu, Bing-fang; Huang, Min

    2016-01-01

    This study aims to investigate the function of two SNPs (rs8904C > T and rs696G >A) in 3' untranslated region (3'UTR) of NFKBIA gene by constructing luciferase reporter gene. A patient's genomic DNA with rs8904 CC and rs696 GA genotype was used as the PCR template. Full-length 3'UTR of NFKBIA gene was amplified by different primers. After sequencing validation, these fragments were inserted to the luciferase reporter vector, pGL3-promoter to construct recombinant plasmids containing four kinds of haplotypes, pGL3-rs8904C/rs696G, pGL3-rs8904C/rs696A, pGL3-rs8904T/rs696G and pGL3-rs8904T/rs696A. Then these plasmids were transfected into LS174T cells and the luciferase activity was detected. Compared with pGL3-vector transfected cells (negative control), the luciferase activity of the four kinds of recombinant plasmids was significantly decreased (P < 0.001). For rs696G > A, the luciferase activity of the recombinant plasmids containing A allele (pGL3-rs8904C/rs696A and pGL3-rs8904T/rs696A) was about 45.1% (P < 0.05) and 56.1% (P < 0.001) lower than those containing G allele (pGL3-rs8904C/rs696G and pGL3-rs8904T/rs696G), respectively. For rs8904C > T, there were no significant differences in the luciferase activity between the recombinant plasmids containing T allele and those with C allele. Together, the luciferase reporter gene vectors containing SNPs in NFKBIA gene 3'UTR were constructed successfully and rs696G > A could decrease the luciferase activity while rs8904C >T didn't have much effect on the luciferase activity.