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Sample records for expression signatures predict

  1. An endometrial gene expression signature accurately predicts recurrent implantation failure after IVF

    PubMed Central

    Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.

    2016-01-01

    The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113

  2. mRNA Expression Signature of Gleason Grade Predicts Lethal Prostate Cancer

    PubMed Central

    Penney, Kathryn L.; Sinnott, Jennifer A.; Fall, Katja; Pawitan, Yudi; Hoshida, Yujin; Kraft, Peter; Stark, Jennifer R.; Fiorentino, Michelangelo; Perner, Sven; Finn, Stephen; Calza, Stefano; Flavin, Richard; Freedman, Matthew L.; Setlur, Sunita; Sesso, Howard D.; Andersson, Swen-Olof; Martin, Neil; Kantoff, Philip W.; Johansson, Jan-Erik; Adami, Hans-Olov; Rubin, Mark A.; Loda, Massimo; Golub, Todd R.; Andrén, Ove; Stampfer, Meir J.; Mucci, Lorelei A.

    2011-01-01

    Purpose Prostate-specific antigen screening has led to enormous overtreatment of prostate cancer because of the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and the most indeterminate in terms of prognosis. Patients and Methods Using the complementary DNA–mediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (n = 358) and Physicians' Health Study (PHS; n = 109). We developed an mRNA signature of Gleason grade comparing individuals with Gleason ≤ 6 to those with Gleason ≥ 8 tumors and applied the model among patients with Gleason 7 to discriminate lethal cases. Results We built a 157-gene signature using the Swedish data that predicted Gleason with low misclassification (area under the curve [AUC] = 0.91); when this signature was tested in the PHS, the discriminatory ability remained high (AUC = 0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4 + 3 or 3 + 4 (P = .006). Conclusion Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment. PMID:21537050

  3. 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

  4. Gene expression signatures and outcome prediction in mature B-cell malignancies.

    PubMed

    Dave, Sandeep S

    2006-07-01

    Non-Hodgkin's lymphomas comprise a diverse group of diseases that are subclassified by the state of differentiation of the malignant B cells, presence of specific cytogenetic abnormalities, and characteristic morphology. Gene expression profiling has revealed that within each category of non-Hodgkin's lymphoma, there exists a significant molecular heterogeneity that can be reflected in differences in tumor behavior and patient outcome. Appreciation of gene expression signatures that are associated with patient outcome will allow better prognostication of disease course and aid the application of molecularly selective patients to improve patient outcome. PMID:16916486

  5. An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia

    PubMed Central

    Metzeler, Klaus H.; Hummel, Manuela; Bloomfield, Clara D.; Spiekermann, Karsten; Braess, Jan; Sauerland, Maria-Cristina; Heinecke, Achim; Radmacher, Michael; Marcucci, Guido; Whitman, Susan P.; Maharry, Kati; Paschka, Peter; Larson, Richard A.; Berdel, Wolfgang E.; Büchner, Thomas; Wörmann, Bernhard; Mansmann, Ulrich; Hiddemann, Wolfgang

    2008-01-01

    Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene-expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes), which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P = .002), event-free survival (HR = 1.73; P = .001), and relapse-free survival (HR = 1.76; P = .025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD, and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR = 4.11; P < .001), event-free survival (HR = 2.90; P < .001), and relapse-free survival (HR = 3.14, P < .001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene-expression signature that offers additional prognostic information for patients with CN-AML. PMID:18716133

  6. Outcome Prediction of Children with Neuroblastoma using a Multigene Expression Signature, a Retrospective SIOPEN/COG/GPOH Study

    PubMed Central

    Vermeulen, Joëlle; De Preter, Katleen; Naranjo, Arlene; Vercruysse, Liesbeth; Roy, Nadine Van; Hellemans, Jan; Swerts, Katrien; Bravo, Sophie; Scaruffi, Paola; Tonini, Gian Paolo; Noguera, Rosa; Piqueras, Marta; Janoueix-Lerosey, Isabelle; Delattre, Olivier; Combaret, Valérie; Fischer, Matthias; Oberthuer, André; Ambros, Peter F.; Beiske, Klaus; Bénard, Jean; Marques, Barbara; Michon, Jean; Schleiermacher, Gudrun; Bernardi, Bruno De; Rubie, Hervé; Cañete, Adela; Castel, Victoria; Kohler, Janice; Pötschger, Ulrike; Ladenstein, Ruth; Hogarty, Michael D.; McGrady, Patrick; London, Wendy B.; Laureys, Geneviève; Speleman, Frank; Vandesompele, Jo

    2011-01-01

    BACKGROUND More accurate prognostic assessment of patients with neuroblastoma is required to improve the choice of risk-related therapy. The aim of this study is to develop and validate a gene expression signature for improved outcome prediction. METHODS Fifty-nine genes were carefully selected based on an innovative data-mining strategy and profiled in the largest neuroblastoma patient series (n=579) to date using RT-qPCR starting from only 20 ng of RNA. A multigene expression signature was built using 30 training samples, tested on 313 test samples and subsequently validated in a blind study on an independent set of 236 additional tumours. FINDINGS The signature accurately classifies patients with respect to overall and progression-free survival (p<0·0001). The signature has a performance, sensitivity, and specificity of 85·4% (95%CI: 77·7–93·2), 84·4% (95%CI: 66·5–94·1), and 86·5% (95%CI: 81·1–90·6), respectively to predict patient outcome. Multivariate analysis indicates that the signature is a significant independent predictor after controlling for currently used riskfactors. Patients with high molecular risk have a higher risk to die from disease and for relapse/progression than patients with low molecular risk (odds ratio of 19·32 (95%CI: 6·50–57·43) and 3·96 (95%CI: 1·97–7·97) for OS and PFS, respectively). Patients with increased risk for adverse outcome can also be identified within the current treatment groups demonstrating the potential of this signature for improved clinical management. These results were confirmed in the validation study in which the signature was also independently statistically significant in a model adjusted for MYCN status, age, INSS stage, ploidy, INPC grade of differentiation, and MKI. The high patient/gene ratio (579/59) underlies the observed statistical power and robustness. INTERPRETATION A 59-gene expression signature predicts outcome of neuroblastoma patients with high accuracy. The signature is

  7. A six gene expression signature defines aggressive subtypes and predicts outcome in childhood and adult acute lymphoblastic leukemia

    PubMed Central

    Wang, Jin; Mi, Jian-Qing; Debernardi, Alexandra; Vitte, Anne-Laure; Emadali, Anouk; Meyer, Julia A.; Charmpi, Konstantina; Ycart, Bernard; Callanan, Mary B.; Carroll, William L.; Khochbin, Saadi; Rousseaux, Sophie

    2015-01-01

    Abnormal gene expression in cancer represents an under-explored source of cancer markers and therapeutic targets. In order to identify gene expression signatures associated with survival in acute lymphoblastic leukemia (ALL), a strategy was designed to search for aberrant gene activity, which consists of applying several filters to transcriptomic datasets from two pediatric ALL studies. Six genes whose expression in leukemic blasts was associated with prognosis were identified:three genes predicting poor prognosis (AK022211, FASTKD1 and STARD4) and three genes associated with a favorable outcome (CAMSAP1, PCGF6 and SH3RF3). Combining the expression of these 6 genes could successfully predict prognosis not only in the two discovery pediatric ALL studies, but also in two independent validation cohorts of adult patients, one from a publicly available study and one consisting of 62 newly recruited Chinese patients. Moreover, our data demonstrate that our six gene based test is particularly efficient in stratifying MLL or BCR.ABL negative patients. Finally, common biological traits characterizing aggressive forms of ALL in both children and adults were found, including features of dormant hematopoietic stem cells, suggesting new therapeutic strategies. PMID:26001296

  8. A Five-Gene Expression Signature Predicts Clinical Outcome of Ovarian Serous Cystadenocarcinoma

    PubMed Central

    Guo, Wenna

    2016-01-01

    Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients' survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma. PMID:27478834

  9. Multisensors signature prediction workbench

    NASA Astrophysics Data System (ADS)

    Latger, Jean; Cathala, Thierry

    2015-10-01

    Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect then identify threats also using sensors. The sensors performance is very dependent on conditions e.g. time of day, atmospheric propagation, background ... Visible camera are very efficient for diurnal fine weather conditions, long wave infrared sensors for night vision, radar systems very efficient for seeing through atmosphere and/or foliage ... Besides, multi sensors systems, combining several collocated sensors with associated algorithms of fusion, provide better efficiency (typically for Enhanced Vision Systems). But these sophisticated systems are all the more difficult to conceive, assess and qualify. In that frame, multi sensors simulation is highly required. This paper focuses on multi sensors simulation tools. A first part makes a state of the Art of such simulation workbenches with a special focus on SE-Workbench. SEWorkbench is described with regards to infrared/EO sensors, millimeter waves sensors, active EO sensors and GNSS sensors. Then a general overview of simulation of targets and backgrounds signature objectives is presented, depending on the type of simulation required (parametric studies, open loop simulation, closed loop simulation, hybridization of SW simulation and HW ...). After the objective review, the paper presents some basic requirements for simulation implementation such as the deterministic behavior of simulation, mandatory to repeat it many times for parametric studies... Several technical topics are then discussed, such as the rendering technique (ray tracing vs. rasterization), the implementation (CPU vs. GP GPU) and the tradeoff between physical accuracy and performance of computation. Examples of results using SE-Workbench are showed and commented.

  10. Gene expression signature in organized and growth arrested mammaryacini predicts good outcome in breast cancer

    SciTech Connect

    Fournier, Marcia V.; Martin, Katherine J.; Kenny, Paraic A.; Xhaja, Kris; Bosch, Irene; Yaswen, Paul; Bissell, Mina J.

    2006-02-08

    To understand how non-malignant human mammary epithelial cells (HMEC) transit from a disorganized proliferating to an organized growth arrested state, and to relate this process to the changes that occur in breast cancer, we studied gene expression changes in non-malignant HMEC grown in three-dimensional cultures, and in a previously published panel of microarray data for 295 breast cancer samples. We hypothesized that the gene expression pattern of organized and growth arrested mammary acini would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in two HMEC cell lines, 184 (finite life span) and HMT3522 S1 (immortal non-malignant), on successive days post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines. We show that genes that are significantly lower in the organized, growth arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically.

  11. Gene Expression Signatures Predictive of Early Response and Outcome in High-Risk Childhood Acute Lymphoblastic Leukemia: A Children's Oncology Group Study

    PubMed Central

    Bhojwani, Deepa; Kang, Huining; Menezes, Renee X.; Yang, Wenjian; Sather, Harland; Moskowitz, Naomi P.; Min, Dong-Joon; Potter, Jeffrey W.; Harvey, Richard; Hunger, Stephen P.; Seibel, Nita; Raetz, Elizabeth A.; Pieters, Rob; Horstmann, Martin A.; Relling, Mary V.; den Boer, Monique L.; Willman, Cheryl L.; Carroll, William L.

    2008-01-01

    Purpose To identify children with acute lymphoblastic leukemia (ALL) at initial diagnosis who are at risk for inferior response to therapy by using molecular signatures. Patients and Methods Gene expression profiles were generated from bone marrow blasts at initial diagnosis from a cohort of 99 children with National Cancer Institute–defined high-risk ALL who were treated uniformly on the Children's Oncology Group (COG) 1961 study. For prediction of early response, genes that correlated to marrow status on day 7 were identified on a training set and were validated on a test set. An additional signature was correlated with long-term outcome, and the predictive models were validated on three large, independent patient cohorts. Results We identified a 24–probe set signature that was highly predictive of day 7 marrow status on the test set (P = .0061). Pathways were identified that may play a role in early blast regression. We have also identified a 47–probe set signature (which represents 41 unique genes) that was predictive of long-term outcome in our data set as well as three large independent data sets of patients with childhood ALL who were treated on different protocols. However, we did not find sufficient evidence for the added significance of these genes and the derived predictive models when other known prognostic features, such as age, WBC, and karyotype, were included in a multivariate analysis. Conclusion Genes and pathways that play a role in early blast regression may identify patients who may be at risk for inferior responses to treatment. A fully validated predictive gene expression signature was defined for high-risk ALL that provided insight into the biologic mechanisms of treatment failure. PMID:18802149

  12. High Expression of Three-Gene Signature Improves Prediction of Relapse-Free Survival in Estrogen Receptor-Positive and Node-Positive Breast Tumors.

    PubMed

    Thakkar, Arvind; Raj, Hemanth; Ravishankar; Muthuvelan, Bhaskaran; Balakrishnan, Arun; Padigaru, Muralidhara

    2015-01-01

    The objective of the present study was to validate prognostic gene signature for estrogen receptor alpha-positive (ER03B1+) and lymph node (+) breast cancer for improved selection of patients for adjuvant therapy. In our previous study, we identified a group of seven genes (GATA3, NTN4, SLC7A8, ENPP1, MLPH, LAMB2, and PLAT) that show elevated messenger RNA (mRNA) expression levels in ERα (+) breast cancer patient samples. The prognostic values of these genes were evaluated using gene expression data from three public data sets of breast cancer patients (n = 395). Analysis of ERα (+) breast cancer cohort (n = 195) showed high expression of GATA3, NTN4, and MLPH genes significantly associated with longer relapse-free survival (RFS). Next cohort of ERα (+) and node (+) samples (n = 109) revealed high mRNA expression of GATA3, SLC7A8, and MLPH significantly associated with longer RFS. Multivariate analysis of combined three-gene signature for ERα (+) cohort, and ERα (+) and node (+) cohorts showed better hazard ratio than individual genes. The validated three-gene signature sets for ERα (+) cohort, and ERα (+) and node (+) cohort may have potential clinical utility since they demonstrated predictive and prognostic ability in three independent public data sets. PMID:26648682

  13. High Expression of Three-Gene Signature Improves Prediction of Relapse-Free Survival in Estrogen Receptor-Positive and Node-Positive Breast Tumors

    PubMed Central

    Thakkar, Arvind; Raj, Hemanth; Ravishankar; Muthuvelan, Bhaskaran; Balakrishnan, Arun; Padigaru, Muralidhara

    2015-01-01

    The objective of the present study was to validate prognostic gene signature for estrogen receptor alpha-positive (ER03B1+) and lymph node (+) breast cancer for improved selection of patients for adjuvant therapy. In our previous study, we identified a group of seven genes (GATA3, NTN4, SLC7A8, ENPP1, MLPH, LAMB2, and PLAT) that show elevated messenger RNA (mRNA) expression levels in ERα (+) breast cancer patient samples. The prognostic values of these genes were evaluated using gene expression data from three public data sets of breast cancer patients (n = 395). Analysis of ERα (+) breast cancer cohort (n = 195) showed high expression of GATA3, NTN4, and MLPH genes significantly associated with longer relapse-free survival (RFS). Next cohort of ERα (+) and node (+) samples (n = 109) revealed high mRNA expression of GATA3, SLC7A8, and MLPH significantly associated with longer RFS. Multivariate analysis of combined three-gene signature for ERα (+) cohort, and ERα (+) and node (+) cohorts showed better hazard ratio than individual genes. The validated three-gene signature sets for ERα (+) cohort, and ERα (+) and node (+) cohort may have potential clinical utility since they demonstrated predictive and prognostic ability in three independent public data sets. PMID:26648682

  14. Gene expression signature-based chemical genomic prediction identifies a novel class of HSP90 pathway modulators.

    PubMed

    Hieronymus, Haley; Lamb, Justin; Ross, Kenneth N; Peng, Xiao P; Clement, Cristina; Rodina, Anna; Nieto, Maria; Du, Jinyan; Stegmaier, Kimberly; Raj, Srilakshmi M; Maloney, Katherine N; Clardy, Jon; Hahn, William C; Chiosis, Gabriela; Golub, Todd R

    2006-10-01

    Although androgen receptor (AR)-mediated signaling is central to prostate cancer, the ability to modulate AR signaling states is limited. Here we establish a chemical genomic approach for discovery and target prediction of modulators of cancer phenotypes, as exemplified by AR signaling. We first identify AR activation inhibitors, including a group of structurally related compounds comprising celastrol, gedunin, and derivatives. To develop an in silico approach for target pathway identification, we apply a gene expression-based analysis that classifies HSP90 inhibitors as having similar activity to celastrol and gedunin. Validating this prediction, we demonstrate that celastrol and gedunin inhibit HSP90 activity and HSP90 clients, including AR. Broadly, this work identifies new modes of HSP90 modulation through a gene expression-based strategy. PMID:17010675

  15. Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence

    PubMed Central

    Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

    2015-01-01

    Background: There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. Methods: All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. Results: The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. Conclusion: The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma. PMID:26131062

  16. Correlated miR-mRNA Expression Signatures of Mouse Hematopoietic Stem and Progenitor Cell Subsets Predict “Stemness” and “Myeloid” Interaction Networks

    PubMed Central

    Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I.

    2014-01-01

    Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a “stemness” signature in the most primitive hematopoietic stem cell (HSC) populations, as well as “myeloid” patterns associated with two branches of myeloid development. PMID:24747944

  17. An algorithm to discover gene signatures with predictive potential

    PubMed Central

    2010-01-01

    Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training. PMID:20813028

  18. 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

  19. Irma multisensor predictive signature model

    NASA Astrophysics Data System (ADS)

    Watson, John S.; Flynn, David S.; Wellfare, Michael R.; Richards, Mike; Prestwood, Lee

    1995-06-01

    The Irma synthetic signature model was one of the first high resolution synthetic infrared (IR) target and background signature models to be developed for tactical air-to-surface weapon scenarios. Originally developed in 1980 by the Armament Directorate of the Air Force Wright Laboratory (WL/MN), the Irma model was used exclusively to generate IR scenes for smart weapons research and development. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser channel. This two channel version, Irma 3.0, was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model which supported correlated frame-to-frame imagery. This and other improvements were released in Irma 2.2. Recently, Irma 3.2, a passive IR/millimeter wave (MMW) code, was completed. Currently, upgrades are underway to include an active MMW channel. Designated Irma 4.0, this code will serve as a cornerstone of sensor fusion research in the laboratory from 6.1 concept development to 6.3 technology demonstration programs for precision guided munitions. Several significant milestones have been reached in this development process and are demonstrated. The Irma 4.0 software design has been developed and interim results are available. Irma is being developed to facilitate multi-sensor smart weapons research and development. It is currently in distribution to over 80 agencies within the U.S. Air Force, U.S. Army, U.S. Navy, ARPA, NASA, Department of Transportation, academia, and industry.

  20. Digital gene expression signatures for maize development

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect determinacy of axillary meristems and thus alter branching patt...

  1. Melanoma microRNA signature predicts post-recurrence survival

    PubMed Central

    Segura, Miguel F.; Belitskaya-Lévy, Ilana; Rose, Amy E.; Zakrzewski, Jan; Gaziel, Avital; Hanniford, Douglas; Darvishian, Farbod; Berman, Russell; Shapiro, Richard; Pavlick, Anna; Osman, Iman; Hernando, Eva

    2015-01-01

    Purpose To identify a melanoma miRNA expression signature that is predictive of outcome and then evaluate its potential to improve risk stratification when added to the standard of care staging criteria. Experimental design Total RNA was extracted from 59 formalin-fixed paraffin embedded (FFPE) melanoma metastases and hybridized to miRNA arrays containing 911 probes. We then correlated miRNA expression with post-recurrence survival and other clinicopathological criteria. Results We identified a signature of 18 miRNAs whose overexpression was significantly correlated with longer survival, defined as more than 18 months post-recurrence survival. Subsequent cross-validation showed that a small subset of these miRNAs can predict post-recurrence survival in metastatic melanoma with an estimated accuracy of 80.2% [95% CI: 79.8%, 80.6%]. In contrast to standard of care staging criteria, this six-miRNA signature significantly stratified stage III patients into “better” and “worse” prognostic categories, and a multivariate Cox regression analysis revealed the signature to be an independent predictor of survival. Furthermore, we demonstrated that most miRNAs from the signature also showed differential expression between patients with “better” and “worse prognosis” in the corresponding paired primary melanoma. Conclusion MiRNA signatures have potential as clinically relevant biomarkers of prognosis in metastatic melanoma. Our data suggest that molecularly-based models of risk assessment can improve the standard staging criteria and support the incorporation of miRNAs into such models. PMID:20179230

  2. A metabolic signature predicts biological age in mice

    PubMed Central

    Tomás-Loba, Antonia; de Jesus, Bruno Bernardes; Mato, Jose M.; Blasco, Maria A.

    2012-01-01

    Our understanding of the mechanisms by which aging is produced is still very limited. Here, we have determined the sera metabolite profile of 117 wild-type mice of different genetic backgrounds ranging from 8-129 weeks of age. This has allowed us to define a robust metabolomic signature and a derived metabolomic score that reliably/accurately predicts the age of wild-type mice. In the case of telomerase-deficient mice, which have a shortened lifespan, their metabolomic score predicts older ages than expected. Conversely, in the case of mice that over-express telomerase, their metabolic score corresponded to younger ages than expected. Importantly, telomerase reactivation late in life by using a TERT based gene therapy recently described by us, significantly reverted the metabolic profile of old mice to that of younger mice, further confirming an anti-aging role for telomerase. Thus, the metabolomic signature associated to natural mouse aging accurately predicts aging produced by telomere shortening, suggesting that natural mouse aging is in part produced by presence of short telomeres. These results indicate that the metabolomic signature is associated to the biological age rather than to the chronological age. This constitutes one of the first aging-associated metabolomic signatures in a mammalian organism. PMID:23107558

  3. Hereditary family signature of facial expression

    PubMed Central

    Peleg, Gili; Katzir, Gadi; Peleg, Ofer; Kamara, Michal; Brodsky, Leonid; Hel-Or, Hagit; Keren, Daniel; Nevo, Eviatar

    2006-01-01

    Although facial expressions of emotion are universal, individual differences create a facial expression “signature” for each person; but, is there a unique family facial expression signature? Only a few family studies on the heredity of facial expressions have been performed, none of which compared the gestalt of movements in various emotional states; they compared only a few movements in one or two emotional states. No studies, to our knowledge, have compared movements of congenitally blind subjects with their relatives to our knowledge. Using two types of analyses, we show a correlation between movements of congenitally blind subjects with those of their relatives in think-concentrate, sadness, anger, disgust, joy, and surprise and provide evidence for a unique family facial expression signature. In the analysis “in-out family test,” a particular movement was compared each time across subjects. Results show that the frequency of occurrence of a movement of a congenitally blind subject in his family is significantly higher than that outside of his family in think-concentrate, sadness, and anger. In the analysis “the classification test,” in which congenitally blind subjects were classified to their families according to the gestalt of movements, results show 80% correct classification over the entire interview and 75% in anger. Analysis of the movements' frequencies in anger revealed a correlation between the movements' frequencies of congenitally blind individuals and those of their relatives. This study anticipates discovering genes that influence facial expressions, understanding their evolutionary significance, and elucidating repair mechanisms for syndromes lacking facial expression, such as autism. PMID:17043232

  4. A Molecular Signature Predictive of Indolent Prostate Cancer

    PubMed Central

    Irshad, Shazia; Bansal, Mukesh; Castillo-Martin, Mireia; Zheng, Tian; Aytes, Alvaro; Wenske, Sven; Le Magnen, Clémentine; Guarnieri, Paolo; Sumazin, Pavel; Benson, Mitchell C.; Shen, Michael M.; Califano, Andrea; Abate-Shen, Cory

    2014-01-01

    Many newly diagnosed prostate cancers present as low Gleason score tumors that require no treatment intervention. Distinguishing the many indolent tumors from the minority of lethal ones remains a major clinical challenge. We now show that low Gleason score prostate tumors can be distinguished as indolent and aggressive subgroups on the basis of their expression of genes associated with aging and senescence. Using gene set enrichment analysis, we identified a 19-gene signature enriched in indolent prostate tumors. We then further classified this signature with a decision tree learning model to identify three genes—FGFR1, PMP22, and CDKN1A—that together accurately predicted outcome of low Gleason score tumors. Validation of this three-gene panel on independent cohorts confirmed its independent prognostic value as well as its ability to improve prognosis with currently used clinical nomograms. Furthermore, protein expression of this three-gene panel in biopsy samples distinguished Gleason 6 patients who failed surveillance over a 10-year period. We propose that this signature may be incorporated into prognostic assays for monitoring patients on active surveillance to facilitate appropriate courses of treatment. PMID:24027026

  5. A prognostic gene expression signature in infratentorial ependymoma

    PubMed Central

    Wani, Khalida; Armstrong, Terri; Vera-Bolanos, Elizabeth; Raghunathan, Aditya; Ellison, David; Gilbertson, Richard; Vaillant, Brian; Goldman, Stewart; Packer, Roger J.; Fouladi, Maryam; Pollack, Ian; Mikkelsen, Tom; Prados, Michael; Omuro, Antonio; Soffietti, Riccardo; Ledoux, Alicia; Wilson, Charmaine; Long, Lihong; Gilbert, Mark; Aldape, Ken

    2013-01-01

    Patients with ependymoma exhibit a wide range of clinical outcomes that is currently unexplained by clinical or histological factors. Little is known regarding molecular biomarkers that could predict clinical behavior. Since recent data suggests that these tumors display biological characteristics according to their location (cerebral vs. infratentorial vs. spinal cord), rather than explore a broad spectrum of ependymoma, we focused on molecular alterations in ependymomas arising in the infratentorial compartment. Unsupervised clustering of available gene expression microarray data revealed two major subgroups of infratentorial ependymoma. Group 1 tumors over expressed genes that were associated with mesenchyme, Group 2 tumors showed no distinct gene ontologies. To assess the prognostic significance of these gene expression subgroups, real-time reverse-transcriptase polymerase chain reaction assays were performed on genes defining the subgroups in a training set. This resulted in a 10-gene prognostic signature. Multivariate analysis showed that the 10-gene signature was an independent predictor of recurrence-free survival after adjusting for clinical factors. Evaluation of an external dataset describing subgroups of infratentorial ependymomas showed concordance of subgroup definition, including validation of the mesenchymal subclass. Importantly, the 10-gene signature was validated as a predictor of recurrence-free survival in this dataset. Taken together, the results indicate a link between clinical outcome and biologically-identified subsets of infratentorial ependymoma and offer the potential for prognostic testing to estimate clinical aggressiveness in these tumors. PMID:22322993

  6. Why do Sequence Signatures Predict Enzyme Mechanism? Homology versus Chemistry

    PubMed Central

    Beattie, Kirsten E.; De Ferrari, Luna; Mitchell, John B. O.

    2015-01-01

    First, we identify InterPro sequence signatures representing evolutionary relatedness and, second, signatures identifying specific chemical machinery. Thus, we predict the chemical mechanisms of enzyme-catalyzed reactions from catalytic and non-catalytic subsets of InterPro signatures. We first scanned our 249 sequences using InterProScan and then used the MACiE database to identify those amino acid residues that are important for catalysis. The sequences were mutated in silico to replace these catalytic residues with glycine and then again scanned using InterProScan. Those signature matches from the original scan that disappeared on mutation were called catalytic. Mechanism was predicted using all signatures, only the 78 “catalytic” signatures, or only the 519 “non-catalytic” signatures. The non-catalytic signatures gave indistinguishable results from those for the whole feature set, with precision of 0.991 and sensitivity of 0.970. The catalytic signatures alone gave less impressive predictivity, with precision and sensitivity of 0.791 and 0.735, respectively. These results show that our successful prediction of enzyme mechanism is mostly by homology rather than by identifying catalytic machinery. PMID:26740739

  7. Reactive oxygen species–associated molecular signature predicts survival in patients with sepsis

    PubMed Central

    Zhou, Tong; Wang, Ting; Slepian, Marvin J.; Garcia, Joe G. N.; Hecker, Louise

    2016-01-01

    Abstract Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)–associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies. PMID:27252846

  8. A gene expression signature for insulin resistance.

    PubMed

    Konstantopoulos, Nicky; Foletta, Victoria C; Segal, David H; Shields, Katherine A; Sanigorski, Andrew; Windmill, Kelly; Swinton, Courtney; Connor, Tim; Wanyonyi, Stephen; Dyer, Thomas D; Fahey, Richard P; Watt, Rose A; Curran, Joanne E; Molero, Juan-Carlos; Krippner, Guy; Collier, Greg R; James, David E; Blangero, John; Jowett, Jeremy B; Walder, Ken R

    2011-02-11

    Insulin resistance is a heterogeneous disorder caused by a range of genetic and environmental factors, and we hypothesize that its etiology varies considerably between individuals. This heterogeneity provides significant challenges to the development of effective therapeutic regimes for long-term management of type 2 diabetes. We describe a novel strategy, using large-scale gene expression profiling, to develop a gene expression signature (GES) that reflects the overall state of insulin resistance in cells and patients. The GES was developed from 3T3-L1 adipocytes that were made "insulin resistant" by treatment with tumor necrosis factor-α (TNF-α) and then reversed with aspirin and troglitazone ("resensitized"). The GES consisted of five genes whose expression levels best discriminated between the insulin-resistant and insulin-resensitized states. We then used this GES to screen a compound library for agents that affected the GES genes in 3T3-L1 adipocytes in a way that most closely resembled the changes seen when insulin resistance was successfully reversed with aspirin and troglitazone. This screen identified both known and new insulin-sensitizing compounds including nonsteroidal anti-inflammatory agents, β-adrenergic antagonists, β-lactams, and sodium channel blockers. We tested the biological relevance of this GES in participants in the San Antonio Family Heart Study (n = 1,240) and showed that patients with the lowest GES scores were more insulin resistant (according to HOMA_IR and fasting plasma insulin levels; P < 0.001). These findings show that GES technology can be used for both the discovery of insulin-sensitizing compounds and the characterization of patients into subtypes of insulin resistance according to GES scores, opening the possibility of developing a personalized medicine approach to type 2 diabetes. PMID:21081660

  9. The 82-plex plasma protein signature that predicts increasing inflammation

    PubMed Central

    Tepel, Martin; Beck, Hans C.; Tan, Qihua; Borst, Christoffer; Rasmussen, Lars M.

    2015-01-01

    The objective of the study was to define the specific plasma protein signature that predicts the increase of the inflammation marker C-reactive protein from index day to next-day using proteome analysis and novel bioinformatics tools. We performed a prospective study of 91 incident kidney transplant recipients and quantified 359 plasma proteins simultaneously using nano-Liquid-Chromatography-Tandem Mass-Spectrometry in individual samples and plasma C-reactive protein on the index day and the next day. Next-day C-reactive protein increased in 59 patients whereas it decreased in 32 patients. The prediction model selected and validated 82 plasma proteins which determined increased next-day C-reactive protein (area under receiver-operator-characteristics curve, 0.772; 95% confidence interval, 0.669 to 0.876; P < 0.0001). Multivariable logistic regression showed that 82-plex protein signature (P < 0.001) was associated with observed increased next-day C-reactive protein. The 82-plex protein signature outperformed routine clinical procedures. The category-free net reclassification index improved with 82-plex plasma protein signature (total net reclassification index, 88.3%). Using the 82-plex plasma protein signature increased net reclassification index with a clinical meaningful 10% increase of risk mainly by the improvement of reclassification of subjects in the event group. An 82-plex plasma protein signature predicts an increase of the inflammatory marker C-reactive protein. PMID:26445912

  10. Predictive performance of microarray gene signatures: impact of tumor heterogeneity and multiple mechanisms of drug resistance

    PubMed Central

    A’Hern, Roger; Bidard, Francois-Clement; Lemetre, Christophe; Swanton, Charles; Shen, Ronglai; Reis-Filho, Jorge S.

    2014-01-01

    Gene signatures have failed to predict responses to breast cancer therapy in patients to date. In this study, we used bioinformatic methods to explore the hypothesis that the existence of multiple drug resistance mechanisms in different patients may limit the power of gene signatures to predict responses to therapy. Additionally, we explored whether sub-stratification of resistant cases could improve performance. Gene expression profiles from 1,550 breast cancers analyzed with the same microarray platform were retrieved from publicly available sources. Gene expression changes were introduced in cases defined as sensitive or resistant to a hypothetical therapy. In the resistant group, up to five different mechanisms of drug resistance causing distinct or overlapping gene expression changes were generated bioinformatically, and their impact on sensitivity, specificity and predictive values of the signatures was investigated. We found that increasing the number of resistance mechanisms corresponding to different gene expression changes weakened the performance of the predictive signatures generated, even if the resistance-induced changes in gene expression were sufficiently strong and informative. Performance was also affected by cohort composition and the proportion of sensitive versus resistant cases or resistant cases that were mechanistically distinct. It was possible to improve response prediction by sub-stratifying chemotherapy-resistant cases from actual datasets (non-bioinformatically-perturbed datasets), and by using outliers to model multiple resistance mechanisms. Our work supports the hypothesis that the presence of multiple resistance mechanisms to a given therapy in patients limits the ability of gene signatures to make clinically-useful predictions. PMID:24706696

  11. Spatiotemporal Signatures of Lexical-Semantic Prediction.

    PubMed

    Lau, Ellen F; Weber, Kirsten; Gramfort, Alexandre; Hämäläinen, Matti S; Kuperberg, Gina R

    2016-04-01

    Although there is broad agreement that top-down expectations can facilitate lexical-semantic processing, the mechanisms driving these effects are still unclear. In particular, while previous electroencephalography (EEG) research has demonstrated a reduction in the N400 response to words in a supportive context, it is often challenging to dissociate facilitation due to bottom-up spreading activation from facilitation due to top-down expectations. The goal of the current study was to specifically determine the cortical areas associated with facilitation due to top-down prediction, using magnetoencephalography (MEG) recordings supplemented by EEG and functional magnetic resonance imaging (fMRI) in a semantic priming paradigm. In order to modulate expectation processes while holding context constant, we manipulated the proportion of related pairs across 2 blocks (10 and 50% related). Event-related potential results demonstrated a larger N400 reduction when a related word was predicted, and MEG source localization of activity in this time-window (350-450 ms) localized the differential responses to left anterior temporal cortex. fMRI data from the same participants support the MEG localization, showing contextual facilitation in left anterior superior temporal gyrus for the high expectation block only. Together, these results provide strong evidence that facilitatory effects of lexical-semantic prediction on the electrophysiological response 350-450 ms postonset reflect modulation of activity in left anterior temporal cortex. PMID:25316341

  12. MicroRNA Expression Signature in Degenerative Aortic Stenosis

    PubMed Central

    2016-01-01

    Degenerative aortic stenosis, characterized by narrowing of the exit of the left ventricle of the heart, has become the most common valvular heart disease in the elderly. The aim of this study was to investigate the microRNA (miRNA) signature in degenerative AS. Through microarray analysis, we identified the miRNA expression signature in the tissue samples from healthy individuals (n = 4) and patients with degenerative AS (n = 4). Six miRNAs (hsa-miR-193a-3p, hsa-miR-29b-1-5p, hsa-miR-505-5p, hsa-miR-194-5p, hsa-miR-99b-3p, and hsa-miR-200b-3p) were overexpressed and 14 (hsa-miR-3663-3p, hsa-miR-513a-5p, hsa-miR-146b-5p, hsa-miR-1972, hsa-miR-718, hsa-miR-3138, hsa-miR-21-5p, hsa-miR-630, hsa-miR-575, hsa-miR-301a-3p, hsa-miR-636, hsa-miR-34a-3p, hsa-miR-21-3p, and hsa-miR-516a-5p) were downregulated in aortic tissue from AS patients. GeneSpring 13.1 was used to identify potential human miRNA target genes by comparing a 3-way comparison of predictions from TargetScan, PITA, and microRNAorg databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to identify potential pathways and functional annotations associated with AS. Twenty miRNAs were significantly differentially expressed between patients with AS samples and normal controls and identified potential miRNA targets and molecular pathways associated with this morbidity. This study describes the miRNA expression signature in degenerative AS and provides an improved understanding of the molecular pathobiology of this disease. PMID:27579316

  13. MicroRNA Expression Signature in Degenerative Aortic Stenosis.

    PubMed

    Shi, Jing; Liu, Hui; Wang, Hui; Kong, Xiangqing

    2016-01-01

    Degenerative aortic stenosis, characterized by narrowing of the exit of the left ventricle of the heart, has become the most common valvular heart disease in the elderly. The aim of this study was to investigate the microRNA (miRNA) signature in degenerative AS. Through microarray analysis, we identified the miRNA expression signature in the tissue samples from healthy individuals (n = 4) and patients with degenerative AS (n = 4). Six miRNAs (hsa-miR-193a-3p, hsa-miR-29b-1-5p, hsa-miR-505-5p, hsa-miR-194-5p, hsa-miR-99b-3p, and hsa-miR-200b-3p) were overexpressed and 14 (hsa-miR-3663-3p, hsa-miR-513a-5p, hsa-miR-146b-5p, hsa-miR-1972, hsa-miR-718, hsa-miR-3138, hsa-miR-21-5p, hsa-miR-630, hsa-miR-575, hsa-miR-301a-3p, hsa-miR-636, hsa-miR-34a-3p, hsa-miR-21-3p, and hsa-miR-516a-5p) were downregulated in aortic tissue from AS patients. GeneSpring 13.1 was used to identify potential human miRNA target genes by comparing a 3-way comparison of predictions from TargetScan, PITA, and microRNAorg databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to identify potential pathways and functional annotations associated with AS. Twenty miRNAs were significantly differentially expressed between patients with AS samples and normal controls and identified potential miRNA targets and molecular pathways associated with this morbidity. This study describes the miRNA expression signature in degenerative AS and provides an improved understanding of the molecular pathobiology of this disease. PMID:27579316

  14. Low Concordance between Gene Expression Signatures in ER Positive HER2 Negative Breast Carcinoma Could Impair Their Clinical Application

    PubMed Central

    Laas, Enora; Mallon, Peter; Duhoux, Francois P.; Hamidouche, Amina; Rouzier, Roman; Reyal, Fabien

    2016-01-01

    Background Numerous prognostic gene expression signatures have been recently described. Among the signatures there is variation in the constituent genes that are utilized. We aim to evaluate prognostic concordance among eight gene expression signatures, on a large dataset of ER positive HER2 negative breast cancers. Methods We analysed the performance of eight gene expression signatures on six different datasets of ER+ HER2- breast cancers. Survival analyses were performed using the Kaplan–Meier estimate of survival function. We assessed discrimination and concordance between the 8 signatures on survival and recurrence rates The Nottingham Prognostic Index (NPI) was used to to stratify the risk of recurrence/death. Results The discrimination ability of the whole signatures, showed fair discrimination performances, with AUC ranging from 0.64 (95%CI 0.55–0.73 for the 76-genes signatures, to 0.72 (95%CI 0.64–0.8) for the Molecular Prognosis Index T17. Low concordance was found in predicting events in the intermediate and high-risk group, as defined by the NPI. Low risk group was the only subgroup with a good signatures concordance. Conclusion Genomic signatures may be a good option to predict prognosis as most of them perform well at the population level. They exhibit, however, a high degree of discordance in the intermediate and high-risk groups. The major benefit that we could expect from gene expression signatures is the standardization of proliferation assessment. PMID:26895349

  15. Copy number variation signature to predict human ancestry

    PubMed Central

    2012-01-01

    Background Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. Results We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. Conclusions We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case–control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response. PMID:23270563

  16. IR signature prediction errors for skin-heated aerial targets

    NASA Astrophysics Data System (ADS)

    McGlynn, John D.; Auerbach, Steven P.

    1997-06-01

    The infrared signature of an aircraft is generally calculated as the sum of multiple components. These components are, typically: the aerodynamic skin heating, reflected solar and upwelling and downwelling radiation, engine hot parts, and exhaust gas emissions. For most airframes, the latter two components overwhelmingly dominate the IR signature. However, for small targets--such as small fighters and cruise missiles, particularly targets with masked hot parts, emissivity control, and suppressed plumes- -aerodynamic heating is the dominant term. This term is determined by the speed of the target, the sea-level air temperature, and the adiabatic lapse rate of the atmosphere, as a function of altitude. Simulations which use AFGL atmospheric codes (LOWTRAN and MODTRAN)--such as SPIRITS--to predict skin heating, may have an intrinsic error in the predicted skin heating component, due to the fixed number of discrete sea-level air temperatures implicit in the atmospheric models. Whenever the assumed background temperature deviates from the implicit model atmosphere sea- level temperature, there will be a measurable error. This error becomes significant in magnitude when trying to model the signatures of small, dim targets dominated by skin heating. This study quantifies the predicted signature errors and suggests simulation implementations which can minimize these errors.

  17. A Gene Expression Signature for Chemoradiosensitivity of Colorectal Cancer Cells

    SciTech Connect

    Spitzner, Melanie; Emons, Georg; Kramer, Frank; Gaedcke, Jochen; Rave-Fraenk, Margret; Scharf, Jens-Gerd; Burfeind, Peter; Becker, Heinz; Beissbarth, Tim; Ghadimi, B. Michael; Ried, Thomas; Grade, Marian

    2010-11-15

    Purpose: The standard treatment of patients with locally advanced rectal cancers comprises preoperative 5-fluorouracil-based chemoradiotherapy followed by standardized surgery. However, tumor response to multimodal treatment has varied greatly, ranging from complete resistance to complete pathologic regression. The prediction of the response is, therefore, an important clinical need. Methods and Materials: To establish in vitro models for studying the molecular basis of this heterogeneous tumor response, we exposed 12 colorectal cancer cell lines to 3 {mu}M of 5-fluorouracil and 2 Gy of radiation. The differences in treatment sensitivity were then correlated with the pretherapeutic gene expression profiles of these cell lines. Results: We observed a heterogeneous response, with surviving fractions ranging from 0.28 to 0.81, closely recapitulating clinical reality. Using a linear model analysis, we identified 4,796 features whose expression levels correlated significantly with the sensitivity to chemoradiotherapy (Q <.05), including many genes involved in the mitogen-activated protein kinase signaling pathway or cell cycle genes. These data have suggested a potential relevance of the insulin and Wnt signaling pathways for treatment response, and we identified STAT3, RASSF1, DOK3, and ERBB2 as potential therapeutic targets. The microarray measurements were independently validated for a subset of these genes using real-time polymerase chain reactions. Conclusion: We are the first to report a gene expression signature for the in vitro chemoradiosensitivity of colorectal cancer cells. We anticipate that this analysis will unveil molecular biomarkers predictive of the response of rectal cancers to chemoradiotherapy and enable the identification of genes that could serve as targets to sensitize a priori resistant primary tumors.

  18. Uncertainty of hydrological signatures predicted for ungauged basins

    NASA Astrophysics Data System (ADS)

    Westerberg, Ida; Coxon, Gemma; Wagener, Thorsten; McMillan, Hilary; Montanari, Alberto; Castellarin, Attilio; Freer, Jim

    2015-04-01

    Reliable information about the hydrological behaviour of an ungauged catchment is needed for a wide range of water resource management decisions, and it has been a central topic of research in hydrology for the last decade through the Predictions in Ungauged Basins initiative. Such information derived as an index value from observed data in a gauged basin is known as a hydrological signature, and has been used in a variety of studies for, e.g., change detection, model calibration and diagnostic model-structural evaluation. When signature values are predicted for ungauged catchments, they are not only affected by uncertainties in the regionalisation procedure, but also by uncertainties in the observed data for the gauged catchments used for the prediction. In this study we investigated a method for regionalisation of hydrological signatures to ungauged catchments that accounted for both of these uncertainty sources. This also enabled us to assess the role of the different uncertainty sources in defining the overall regionalisation uncertainty - e.g. for what signatures and conditions are the data uncertainties more important than the regionalisation uncertainties and vice versa? The study was made using an extensive dataset of catchments in England and Wales, incorporating gauging (stage-discharge) data from all the discharge stations. The uncertainties were assessed within a Monte Carlo framework that incorporated different types of uncertainties in the data as well as uncertainties in the regionalisation procedure. The regionalisation results had a high reliability when the gauged discharge uncertainties were accounted for. The magnitude of the gauged uncertainty was often larger than the differences between deterministic gauged and regionalised values, which shows that deterministic comparisons are insufficient for evaluation of regionalisation results. The results were better for medium and high-flow signatures than for low-flow signatures. The data

  19. Web-based interrogation of gene expression signatures using EXALT

    PubMed Central

    2009-01-01

    Background Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge. Results The EXALT (EXpression signature AnaLysis Tool) online program enables meta-analysis of gene expression profiles derived from publically accessible sources. Searches can be executed online against two large databases currently containing more than 28,000 gene expression signatures derived from GEO (Gene Expression Omnibus) and published expression profiles of human cancer. Comparisons among gene expression signatures can be performed with homology analysis and co-expression analysis. Results can be visualized instantly in a plot or a heat map. Three typical use cases are illustrated. Conclusions The EXALT online program is uniquely suited for discovering relationships among transcriptional profiles and searching gene expression patterns derived from diverse physiological and pathological settings. The EXALT online program is freely available for non-commercial users from http://seq.mc.vanderbilt.edu/exalt/. PMID:20003458

  20. Discovery of characteristic molecular signatures for the simultaneous prediction and detection of environmental pollutants.

    PubMed

    Song, Mi-Kyung; Choi, Han-Seam; Park, Yong-Keun; Ryu, Jae-Chun

    2014-02-01

    Gene expression data may be very promising for the classification of toxicant types, but the development and application of transcriptomic-based gene classifiers for environmental toxicological applications are lacking compared to the biomedical sciences. Also, simultaneous classification across a set of toxicant types has not been investigated extensively. In the present study, we determined the transcriptomic response to three types of ubiquitous toxicants exposure in two types of human cell lines (HepG2 and HL-60), which are useful in vitro human model for evaluation of toxic substances that may affect human hepatotoxicity (e.g., polycyclic aromatic hydrocarbon [PAH] and persistent organic pollutant [POP]) and human leukemic myelopoietic proliferation (e.g., volatile organic compound [VOC]). The findings demonstrate characteristic molecular signatures that facilitated discrimination and prediction of the toxicant type. To evaluate changes in gene expression levels after exposure to environmental toxicants, we utilized 18 chemical substances; nine PAH toxicants, six VOC toxicants, and three POP toxicants. Unsupervised gene expression analysis resulted in a characteristic molecular signature for each toxicant group, and combination analysis of two separate multi-classifications indicated 265 genes as surrogate markers for predicting each group of toxicants with 100 % accuracy. Our results suggest that these expression signatures can be used as predictable and discernible surrogate markers for detection and prediction of environmental toxicant exposure. Furthermore, this approach could easily be extended to screening for other types of environmental toxicants. PMID:24197968

  1. Multidrug Resistance-Linked Gene Signature Predicts Overall Survival of Patients With Primary Ovarian Serous Carcinoma

    PubMed Central

    Gillet, Jean-Pierre; Calcagno, Anna Maria; Varma, Sudhir; Davidson, Ben; Bunkholt Elstrand, Mari; Ganapathi, Ram; Kamat, Aparna A.; Sood, Anil K.; Ambudkar, Suresh V.; Seiden, Michael V.; Rueda, Bo R.; Gottesman, Michael M.

    2012-01-01

    Purpose This study assesses the ability of multidrug resistance (MDR)-associated gene expression patterns to predict survival in patients with newly diagnosed carcinoma of the ovary. The scope of this research differs substantially from that of previous reports, as a very large set of genes was evaluated whose expression has been shown to affect response to chemotherapy. Experimental Design We applied a customized TaqMan Low Density Array, a highly sensitive and specific assay, to study the expression profiles of 380 MDR-linked genes in 80 tumor specimens collected at initial surgery to debulk primary serous carcinoma. The RNA expression profiles of these drug resistance genes were correlated with clinical outcomes. Results Leave-one-out cross-validation was used to estimate the ability of MDR gene expression to predict survival. Although gene expression alone does not predict overall survival (P=0.06), four covariates (age, stage, CA125 level and surgical debulking) do (P=0.03). When gene expression was added to the covariates, we found an 11-gene signature that provides a major improvement in overall survival prediction (log-rank statistic P<0.003). The predictive power of this 11-gene signature was confirmed by dividing high and low risk patient groups, as defined by their clinical covariates, into four specific risk groups based on expression levels. Conclusion This study reveals an 11-gene signature that allows a more precise prognosis for patients with serous cancer of the ovary treated with carboplatin- and paclitaxel-based therapy. These 11 new targets offer opportunities for new therapies to improve clinical outcome in ovarian cancer. PMID:22492981

  2. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    PubMed Central

    Wang, Xi; Ning, Yujie; Zhang, Feng; Yu, Fangfang; Tan, Wuhong; Lei, Yanxia; Wu, Cuiyan; Zheng, Jingjing; Wang, Sen; Yu, Hanjie; Li, Zheng; Lammi, Mikko J.; Guo, Xiong

    2015-01-01

    Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD. PMID:25997002

  3. Development of Multigene Expression Signature Maps at the Protein Level from Digitized Immunohistochemistry Slides

    PubMed Central

    Metzger, Gregory J.; Dankbar, Stephen C.; Henriksen, Jonathan; Rizzardi, Anthony E.; Rosener, Nikolaus K.; Schmechel, Stephen C.

    2012-01-01

    Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC) is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps) of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions. PMID:22438942

  4. Gene-expression signatures of Atlantic salmon's plastic life cycle

    USGS Publications Warehouse

    Aubin-Horth, N.; Letcher, B.H.; Hofmann, H.A.

    2009-01-01

    How genomic expression differs as a function of life history variation is largely unknown. Atlantic salmon exhibits extreme alternative life histories. We defined the gene-expression signatures of wild-caught salmon at two different life stages by comparing the brain expression profiles of mature sneaker males and immature males, and early migrants and late migrants. In addition to life-stage-specific signatures, we discovered a surprisingly large gene set that was differentially regulated-at similar magnitudes, yet in opposite direction-in both life history transitions. We suggest that this co-variation is not a consequence of many independent cellular and molecular switches in the same direction but rather represents the molecular equivalent of a physiological shift orchestrated by one or very few master regulators. ?? 2009 Elsevier Inc. All rights reserved.

  5. Identification of Gene-Expression Signatures and Protein Markers for Breast Cancer Grading and Staging

    PubMed Central

    Yao, Fang; Zhang, Chi; Du, Wei; Liu, Chao; Xu, Ying

    2015-01-01

    The grade of a cancer is a measure of the cancer's malignancy level, and the stage of a cancer refers to the size and the extent that the cancer has spread. Here we present a computational method for prediction of gene signatures and blood/urine protein markers for breast cancer grades and stages based on RNA-seq data, which are retrieved from the TCGA breast cancer dataset and cover 111 pairs of disease and matching adjacent noncancerous tissues with pathologists-assigned stages and grades. By applying a differential expression and an SVM-based classification approach, we found that 324 and 227 genes in cancer have their expression levels consistently up-regulated vs. their matching controls in a grade- and stage-dependent manner, respectively. By using these genes, we predicted a 9-gene panel as a gene signature for distinguishing poorly differentiated from moderately and well differentiated breast cancers, and a 19-gene panel as a gene signature for discriminating between the moderately and well differentiated breast cancers. Similarly, a 30-gene panel and a 21-gene panel are predicted as gene signatures for distinguishing advanced stage (stages III-IV) from early stage (stages I-II) cancer samples and for distinguishing stage II from stage I samples, respectively. We expect these gene panels can be used as gene-expression signatures for cancer grade and stage classification. In addition, of the 324 grade-dependent genes, 188 and 66 encode proteins that are predicted to be blood-secretory and urine-excretory, respectively; and of the 227 stage-dependent genes, 123 and 51 encode proteins predicted to be blood-secretory and urine-excretory, respectively. We anticipate that some combinations of these blood and urine proteins could serve as markers for monitoring breast cancer at specific grades and stages through blood and urine tests. PMID:26375396

  6. Identification of Gene-Expression Signatures and Protein Markers for Breast Cancer Grading and Staging.

    PubMed

    Yao, Fang; Zhang, Chi; Du, Wei; Liu, Chao; Xu, Ying

    2015-01-01

    The grade of a cancer is a measure of the cancer's malignancy level, and the stage of a cancer refers to the size and the extent that the cancer has spread. Here we present a computational method for prediction of gene signatures and blood/urine protein markers for breast cancer grades and stages based on RNA-seq data, which are retrieved from the TCGA breast cancer dataset and cover 111 pairs of disease and matching adjacent noncancerous tissues with pathologists-assigned stages and grades. By applying a differential expression and an SVM-based classification approach, we found that 324 and 227 genes in cancer have their expression levels consistently up-regulated vs. their matching controls in a grade- and stage-dependent manner, respectively. By using these genes, we predicted a 9-gene panel as a gene signature for distinguishing poorly differentiated from moderately and well differentiated breast cancers, and a 19-gene panel as a gene signature for discriminating between the moderately and well differentiated breast cancers. Similarly, a 30-gene panel and a 21-gene panel are predicted as gene signatures for distinguishing advanced stage (stages III-IV) from early stage (stages I-II) cancer samples and for distinguishing stage II from stage I samples, respectively. We expect these gene panels can be used as gene-expression signatures for cancer grade and stage classification. In addition, of the 324 grade-dependent genes, 188 and 66 encode proteins that are predicted to be blood-secretory and urine-excretory, respectively; and of the 227 stage-dependent genes, 123 and 51 encode proteins predicted to be blood-secretory and urine-excretory, respectively. We anticipate that some combinations of these blood and urine proteins could serve as markers for monitoring breast cancer at specific grades and stages through blood and urine tests. PMID:26375396

  7. Nuclear factor, erythroid 2-like 2-associated molecular signature predicts lung cancer survival

    PubMed Central

    Qian, Zhongqing; Zhou, Tong; Gurguis, Christopher I.; Xu, Xiaoyan; Wen, Qing; Lv, Jingzhu; Fang, Fang; Hecker, Louise; Cress, Anne E.; Natarajan, Viswanathan; Jacobson, Jeffrey R.; Zhang, Donna D.; Garcia, Joe G. N.; Wang, Ting

    2015-01-01

    Nuclear factor, erythroid 2-like 2 (NFE2L2), a transcription factor also known as NF-E2-related factor 2 (Nrf2), is a key cytoprotective gene that regulates critical antioxidant and stress-responsive genes. Nrf2 has been demonstrated to be a promising therapeutic target and useful biomarker in malignant disease. We hypothesized that NFE2L2-mediated gene expression would reflect cancer severity and progression. We conducted a meta-analysis of microarray data for 240 NFE2L2-mediated genes that were enriched in tumor tissues. We then developed a risk scoring system based on NFE2L2 gene expression profiling and designated 50 tumor-associated genes as the NFE2L2-associated molecular signature (NAMS). We tested the relationship between this gene expression signature and both recurrence-free survival and overall survival in lung cancer patients. We find that NAMS predicts clinical outcome in the training cohort and in 12 out of 20 validation cohorts. Cox proportional hazard regressions indicate that NAMS is a robust prognostic gene signature, independent of other clinical and pathological factors including patient age, gender, smoking, gene alteration, MYC level, and cancer stage. NAMS is an excellent predictor of recurrence-free survival and overall survival in human lung cancer. This gene signature represents a promising prognostic biomarker in human lung cancer. PMID:26596768

  8. Nuclear factor, erythroid 2-like 2-associated molecular signature predicts lung cancer survival.

    PubMed

    Qian, Zhongqing; Zhou, Tong; Gurguis, Christopher I; Xu, Xiaoyan; Wen, Qing; Lv, Jingzhu; Fang, Fang; Hecker, Louise; Cress, Anne E; Natarajan, Viswanathan; Jacobson, Jeffrey R; Zhang, Donna D; Garcia, Joe G N; Wang, Ting

    2015-01-01

    Nuclear factor, erythroid 2-like 2 (NFE2L2), a transcription factor also known as NF-E2-related factor 2 (Nrf2), is a key cytoprotective gene that regulates critical antioxidant and stress-responsive genes. Nrf2 has been demonstrated to be a promising therapeutic target and useful biomarker in malignant disease. We hypothesized that NFE2L2-mediated gene expression would reflect cancer severity and progression. We conducted a meta-analysis of microarray data for 240 NFE2L2-mediated genes that were enriched in tumor tissues. We then developed a risk scoring system based on NFE2L2 gene expression profiling and designated 50 tumor-associated genes as the NFE2L2-associated molecular signature (NAMS). We tested the relationship between this gene expression signature and both recurrence-free survival and overall survival in lung cancer patients. We find that NAMS predicts clinical outcome in the training cohort and in 12 out of 20 validation cohorts. Cox proportional hazard regressions indicate that NAMS is a robust prognostic gene signature, independent of other clinical and pathological factors including patient age, gender, smoking, gene alteration, MYC level, and cancer stage. NAMS is an excellent predictor of recurrence-free survival and overall survival in human lung cancer. This gene signature represents a promising prognostic biomarker in human lung cancer. PMID:26596768

  9. Signature Product Code for Predicting Protein-Protein Interactions

    SciTech Connect

    Martin, Shawn B.; Brown, William M.

    2004-09-25

    The SigProdV1.0 software consists of four programs which together allow the prediction of protein-protein interactions using only amino acid sequences and experimental data. The software is based on the use of tensor products of amino acid trimers coupled with classifiers known as support vector machines. Essentially the program looks for amino acid trimer pairs which occur more frequently in protein pairs which are known to interact. These trimer pairs are then used to make predictions about unknown protein pairs. A detailed description of the method can be found in the paper: S. Martin, D. Roe, J.L. Faulon. "Predicting protein-protein interactions using signature products," Bioinformatics, available online from Advance Access, Aug. 19, 2004.

  10. A novel embryonic plasticity gene signature that predicts metastatic competence and clinical outcome

    PubMed Central

    Soundararajan, Rama; Paranjape, Anurag N.; Barsan, Valentin; Chang, Jeffrey T.; Mani, Sendurai A.

    2015-01-01

    Currently, very few prognosticators accurately predict metastasis in cancer patients. In order to complete the metastatic cascade and successfully colonize distant sites, carcinoma cells undergo dynamic epithelial-mesenchymal-transition (EMT) and its reversal, mesenchymal-epithelial-transition (MET). While EMT-centric signatures correlate with response to therapy, they are unable to predict metastatic outcome. One reason is due to the wide range of transient phenotypes required for a tumor cell to disseminate and recreate a similar histology at distant sites. Since such dynamic cellular processes are also seen during embryo development (epithelial-like epiblast cells undergo transient EMT to generate the mesoderm, which eventually redifferentiates into epithelial tissues by MET), we sought to utilize this unique and highly conserved property of cellular plasticity to predict metastasis. Here we present the identification of a novel prognostic gene expression signature derived from mouse embryonic day 6.5 that is representative of extensive cellular plasticity, and predicts metastatic competence in human breast tumor cells. This signature may thus complement conventional clinical parameters to offer accurate prediction for outcome among multiple classes of breast cancer patients. PMID:26123483

  11. Conserved Expression Signatures between Medaka and Human Pigment Cell Tumors

    PubMed Central

    Schartl, Manfred; Kneitz, Susanne; Wilde, Brigitta; Wagner, Toni; Henkel, Christiaan V.; Spaink, Herman P.; Meierjohann, Svenja

    2012-01-01

    Aberrations in gene expression are a hallmark of cancer cells. Differential tumor-specific transcript levels of single genes or whole sets of genes may be critical for the neoplastic phenotype and important for therapeutic considerations or useful as biomarkers. As an approach to filter out such relevant expression differences from the plethora of changes noted in global expression profiling studies, we searched for changes of gene expression levels that are conserved. Transcriptomes from massive parallel sequencing of different types of melanoma from medaka were generated and compared to microarray datasets from zebrafish and human melanoma. This revealed molecular conservation at various levels between fish models and human tumors providing a useful strategy for identifying expression signatures strongly associated with disease phenotypes and uncovering new melanoma molecules. PMID:22693581

  12. An MEG signature corresponding to an axiomatic model of reward prediction error.

    PubMed

    Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

    2012-01-01

    Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. PMID:21726648

  13. Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer

    PubMed Central

    Myers, Jennifer S.; von Lersner, Ariana K.; Robbins, Charles J.; Sang, Qing-Xiang Amy

    2015-01-01

    Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The “transforming growth factor-beta signaling” and “Ran regulation of mitotic spindle formation” pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran) for investigation in prostate cancer pathogenesis. PMID:26683658

  14. Signature Product Code for Predicting Protein-Protein Interactions

    Energy Science and Technology Software Center (ESTSC)

    2004-09-25

    The SigProdV1.0 software consists of four programs which together allow the prediction of protein-protein interactions using only amino acid sequences and experimental data. The software is based on the use of tensor products of amino acid trimers coupled with classifiers known as support vector machines. Essentially the program looks for amino acid trimer pairs which occur more frequently in protein pairs which are known to interact. These trimer pairs are then used to make predictionsmore » about unknown protein pairs. A detailed description of the method can be found in the paper: S. Martin, D. Roe, J.L. Faulon. "Predicting protein-protein interactions using signature products," Bioinformatics, available online from Advance Access, Aug. 19, 2004.« less

  15. Extracting reliable gene expression signatures through Stable Bootstrap Validation.

    PubMed

    Chlis, N K; Bei, E S; Moirogiorgou, K; Zervakis, M

    2015-08-01

    Identification of candidate genes responsible for specific phenotypes, such as cancer, has been a major challenge in the field of bioinformatics. Given a DNA Microarray dataset, traditional feature selection methods produce lists of candidate genes which vary significantly under variations of the training data. That instability hinders the validity of research findings and raises doubts about the reliability of such methods. In this study, we propose a framework for the extraction of stable genomic signatures. The proposed methodology enforces stability at the validation step, independent of the feature selection and classification methods used. The statistical significance of the selected gene set is also assessed. The results of this study demonstrate the importance of stability issues in genomic signatures, beyond their prediction capabilities. PMID:26737284

  16. A TCRβ Repertoire Signature Can Predict Experimental Cerebral Malaria

    PubMed Central

    Dulauroy, Sophie; Gorgette, Olivier; Klatzmann, David; Cazenave, Pierre-André; Pied, Sylviane; Six, Adrien

    2016-01-01

    Cerebral Malaria (CM) is associated with a pathogenic T cell response. Mice infected by P. berghei ANKA clone 1.49 (PbA) developing CM (CM+) present an altered PBL TCR repertoire, partly due to recurrently expanded T cell clones, as compared to non-infected and CM- infected mice. To analyse the relationship between repertoire alteration and CM, we performed a kinetic analysis of the TRBV repertoire during the course of the infection until CM-related death in PbA-infected mice. The repertoires of PBL, splenocytes and brain lymphocytes were compared between infected and non-infected mice using a high-throughput CDR3 spectratyping method. We observed a modification of the whole TCR repertoire in the spleen and blood of infected mice, from the fifth and the sixth day post-infection, respectively, while only three TRBV were significantly perturbed in the brain of infected mice. Using multivariate analysis and statistical modelling, we identified a unique TCRβ signature discriminating CM+ from CTR mice, enriched during the course of the infection in the spleen and the blood and predicting CM onset. These results highlight a dynamic modification and compartmentalization of the TCR diversity during the course of PbA infection, and provide a novel method to identify disease-associated TCRβ signature as diagnostic and prognostic biomarkers. PMID:26844551

  17. Transcriptome sequencing uncovers a three-long noncoding RNA signature in predicting breast cancer survival.

    PubMed

    Guo, Wenna; Wang, Qiang; Zhan, Yueping; Chen, Xijia; Yu, Qi; Zhang, Jiawei; Wang, Yi; Xu, Xin-Jian; Zhu, Liucun

    2016-01-01

    Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan-Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan-Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC = 0.752, 95% confidence intervals (CI): 0.651-0.854) and the microarray dataset (AUC = 0.714, 95%CI: 0.615-0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs. PMID:27338266

  18. Transcriptome sequencing uncovers a three–long noncoding RNA signature in predicting breast cancer survival

    PubMed Central

    Guo, Wenna; Wang, Qiang; Zhan, Yueping; Chen, Xijia; Yu, Qi; Zhang, Jiawei; Wang, Yi; Xu, Xin-jian; Zhu, Liucun

    2016-01-01

    Long noncoding RNAs (lncRNAs) play a crucial role in tumorigenesis. The aim of this study is to identify lncRNA signature that can predict breast cancer patient survival. RNA expression data from 1064 patients were downloaded from The Cancer Genome Atlas project. Cox regression, Kaplan–Meier, and receiver operating characteristic (ROC) analyses were performed to construct a model for predicting the overall survival (OS) of patients and evaluate it. A model consisting of three lncRNA genes (CAT104, LINC01234, and STXBP5-AS1) was identified. The Kaplan–Meier analysis and ROC curves proved that the model could predict the prognostic survival with good sensitivity and specificity in both the validation set (AUC = 0.752, 95% confidence intervals (CI): 0.651–0.854) and the microarray dataset (AUC = 0.714, 95%CI: 0.615–0.814). Further study showed the three-lncRNA signature was not only pervasive in different breast cancer stages, subtypes and age groups, but also provides more accurate prognostic information than some widely known biomarkers. The results suggested that RNA-seq transcriptome profiling provides that the three-lncRNA signature is an independent prognostic biomarker, and have clinical significance. In addition, lncRNA, miRNA, and mRNA interaction network indicated lncRNAs may intervene in breast cancer pathogenesis by binding to miR-190b, acting as competing endogenous RNAs. PMID:27338266

  19. An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation

    PubMed Central

    Pena, Olga M.; Hancock, David G.; Lyle, Ngan H.; Linder, Adam; Russell, James A.; Xia, Jianguo; Fjell, Christopher D.; Boyd, John H.; Hancock, Robert E.W.

    2014-01-01

    Background Sepsis involves aberrant immune responses to infection, but the exact nature of this immune dysfunction remains poorly defined. Bacterial endotoxins like lipopolysaccharide (LPS) are potent inducers of inflammation, which has been associated with the pathophysiology of sepsis, but repeated exposure can also induce a suppressive effect known as endotoxin tolerance or cellular reprogramming. It has been proposed that endotoxin tolerance might be associated with the immunosuppressive state that was primarily observed during late-stage sepsis. However, this relationship remains poorly characterised. Here we clarify the underlying mechanisms and timing of immune dysfunction in sepsis. Methods We defined a gene expression signature characteristic of endotoxin tolerance. Gene-set test approaches were used to correlate this signature with early sepsis, both newly and retrospectively analysing microarrays from 593 patients in 11 cohorts. Then we recruited a unique cohort of possible sepsis patients at first clinical presentation in an independent blinded controlled observational study to determine whether this signature was associated with the development of confirmed sepsis and organ dysfunction. Findings All sepsis patients presented an expression profile strongly associated with the endotoxin tolerance signature (p < 0.01; AUC 96.1%). Importantly, this signature further differentiated between suspected sepsis patients who did, or did not, go on to develop confirmed sepsis, and predicted the development of organ dysfunction. Interpretation Our data support an updated model of sepsis pathogenesis in which endotoxin tolerance-mediated immune dysfunction (cellular reprogramming) is present throughout the clinical course of disease and related to disease severity. Thus endotoxin tolerance might offer new insights guiding the development of new therapies and diagnostics for early sepsis. PMID:25685830

  20. A rank-based transcriptional signature for predicting relapse risk of stage II colorectal cancer identified with proper data sources

    PubMed Central

    Zhao, Wenyuan; Chen, Beibei; Guo, Xin; Wang, Ruiping; Chang, Zhiqiang; Dong, Yu; Song, Kai; Wang, Wen; Qi, Lishuang; Gu, Yunyan; Wang, Chenguang; Yang, Da; Guo, Zheng

    2016-01-01

    The irreproducibility problem seriously hinders the studies on transcriptional signatures for predicting relapse risk of early stage colorectal cancer (CRC) patients. Through reviewing recently published 34 literatures for the development of CRC prognostic signatures based on gene expression profiles, we revealed a surprising phenomenon that 33 of these studies analyzed CRC samples with and without adjuvant chemotherapy together in the training and/or validation datasets. This data misuse problem could be partially attributed to the unclear and incomplete data annotation in public data sources. Furthermore, all the signatures proposed by these studies were based on risk scores summarized from gene expression levels, which are sensitive to experimental batch effects and risk compositions of the samples analyzed together. To avoid the above-mentioned problems, we carefully selected three qualified large datasets to develop and validate a signature consisting of three pairs of genes. The within-sample relative expression orderings of these gene pairs could robustly predict relapse risk of stage II CRC samples assessed in different laboratories. The transcriptional and functional analyses provided clear evidence that the high risk patients predicted by the proposed signature represent patients with micro-metastases. PMID:26967049

  1. Irma 5.1 multisensor signature prediction model

    NASA Astrophysics Data System (ADS)

    Savage, James; Coker, Charles; Edwards, Dave; Thai, Bea; Aboutalib, Omar; Chow, Anthony; Yamaoka, Neil; Kim, Charles

    2006-05-01

    The Irma synthetic signature prediction code is being developed to facilitate the research and development of multi-sensor systems. Irma was one of the first high resolution, physics-based Infrared (IR) target and background signature models to be developed for tactical weapon applications. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel, and a Doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Irma is currently used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. In 2005, Irma version 5.1 was released to the community. In addition to upgrading the Ladar channel code to an object oriented language (C++) and providing a new graphical user interface to construct scenes, this new release significantly improves the modeling of the ladar channel and

  2. Irma 5.1 multisensor signature prediction model

    NASA Astrophysics Data System (ADS)

    Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Yamaoka, Neil; Kim, Charles

    2005-05-01

    The Irma synthetic signature prediction code is being developed to facilitate the research and development of multisensor systems. Irma was one of the first high resolution Infrared (IR) target and background signature models to be developed for tactical weapon application. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel and the doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Since 2000, additional capabilities and enhancements have been added to the ladar channel including polarization and speckle effect. Work is still ongoing to add time-jittering model to the ladar channel. A new user interface has been introduced to aid users in the mechanism of scene generation and running the Irma code. The user interface provides a canvas where a user can add and remove objects using mouse clicks to construct a scene. The scene can then be visualized to find the desired sensor position. The synthetic ladar

  3. 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

    2016-01-01

    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. PMID:27498762

  4. A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis

    PubMed Central

    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

    2016-01-01

    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. PMID:27498762

  5. Gene Expression Signature in Adipose Tissue of Acromegaly Patients

    PubMed Central

    Hochberg, Irit; Tran, Quynh T.; Barkan, Ariel L.; Saltiel, Alan R.; Chandler, William F.; Bridges, Dave

    2015-01-01

    To study the effect of chronic excess growth hormone on adipose tissue, we performed RNA sequencing in adipose tissue biopsies from patients with acromegaly (n = 7) or non-functioning pituitary adenomas (n = 11). The patients underwent clinical and metabolic profiling including assessment of HOMA-IR. Explants of adipose tissue were assayed ex vivo for lipolysis and ceramide levels. Patients with acromegaly had higher glucose, higher insulin levels and higher HOMA-IR score. We observed several previously reported transcriptional changes (IGF1, IGFBP3, CISH, SOCS2) that are known to be induced by GH/IGF-1 in liver but are also induced in adipose tissue. We also identified several novel transcriptional changes, some of which may be important for GH/IGF responses (PTPN3 and PTPN4) and the effects of acromegaly on growth and proliferation. Several differentially expressed transcripts may be important in GH/IGF-1-induced metabolic changes. Specifically, induction of LPL, ABHD5, and NRIP1 can contribute to enhanced lipolysis and may explain the elevated adipose tissue lipolysis in acromegalic patients. Higher expression of TCF7L2 and the fatty acid desaturases FADS1, FADS2 and SCD could contribute to insulin resistance. Ceramides were not different between the two groups. In summary, we have identified the acromegaly gene expression signature in human adipose tissue. The significance of altered expression of specific transcripts will enhance our understanding of the metabolic and proliferative changes associated with acromegaly. PMID:26087292

  6. Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders

    PubMed Central

    Shimizu-Motohashi, Yuko; Holm, Ingrid A.; Campbell, Malcolm G.; Lee, In-Hee; Brewster, Stephanie J.; Hanson, Ellen; Harris, Heather K.; Lowe, Kathryn R.; Saada, Adrianna; Mora, Andrea; Madison, Kimberly; Hundley, Rachel; Egan, Jessica; McCarthy, Jillian; Eran, Ally; Galdzicki, Michal; Rappaport, Leonard; Kunkel, Louis M.; Kohane, Isaac S.

    2012-01-01

    Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified. PMID:23227143

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

    SciTech Connect

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    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 datasets 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 prognostic

  8. BI-14GENOMIC PROFILING OF A PREDICTIVE SIGNATURE FOR MET-TARGETED THERAPY IN GLIOBLASTOMA

    PubMed Central

    Johnson, Jennifer; Ascierto, Maria Libera; Newsome, David; Mittal, Sandeep; Kang, Liang; Briggs, Michael; Tanner, Kirk; Berens, Michael E.; Marincola, Francesco M.; Vande Woude, George F.; Xie, Qian

    2014-01-01

    The success of molecular targeted therapy against cancer depends on discovering the tumor driver genes and the molecular determinants that control the pathway activity. Glioblastoma (GBM) is one of the most devastating cancers due to its highly infiltrating nature, and MET pathway activation is a major cause of invasion in both primary and recurrent tumors. Because MET inhibitors are in clinical trials against GBM, there may be clinical utility from developing more effective patient enrollment strategies tailored to targeted therapeutics. Previously, we reported (Xie et al., PNAS 2012) that GBM tumors with high levels of hepatocyte growth factor (HGF) often display HGF-autocrine activation through its receptor MET, which is a key molecular feature in sensitivity to MET inhibitors. In this study, we sought to develop a molecular signature that can be used as a biomarker to identify GBM patients whose tumor would be vulnerable to treatment with MET inhibitors. Because GBM is a heterogeneous disease in which drug response in the individual patient can be influenced by a variety of different mechanisms, the expression of a single gene was not anticipated to be sufficient to pinpoint sensitivity to the drug; rather, a hypothesis-driven, biomarker-based molecular signature would likely be of a higher value. We analyzed genomic data from GBM patients in The Cancer Genome Atlas (TCGA) Network as well as from preclinical tumor models. We found that GBM tumors sensitive to MET inhibitors share common genomic profiles. More importantly, using patient-derived xenograft models, a 25-gene molecular signature was identified that predicted sensitivity to MET inhibitors. Our findings are a proof-of-concept for the use of genomic signatures to identify GBM patients with greater vulnerability for MET-targeted therapy.

  9. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Almeida, Susana; Le Vine, Nataliya; McIntyre, Neil; Wagener, Thorsten; Buytaert, Wouter

    2016-02-01

    A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be misinformative.

  10. Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

    2016-04-01

    The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood

  11. An Orthologous Epigenetic Gene Expression Signature Derived from Differentiating Embryonic Stem Cells Identifies Regulators of Cardiogenesis

    PubMed Central

    Busser, Brian W.; Lin, Yongshun; Yang, Yanqin; Zhu, Jun; Chen, Guokai; Michelson, Alan M.

    2015-01-01

    Here we used predictive gene expression signatures within a multi-species framework to identify the genes that underlie cardiac cell fate decisions in differentiating embryonic stem cells. We show that the overlapping orthologous mouse and human genes are the most accurate candidate cardiogenic genes as these genes identified the most conserved developmental pathways that characterize the cardiac lineage. An RNAi-based screen of the candidate genes in Drosophila uncovered numerous novel cardiogenic genes. shRNA knockdown combined with transcriptome profiling of the newly-identified transcription factors zinc finger protein 503 and zinc finger E-box binding homeobox 2 and the well-known cardiac regulatory factor NK2 homeobox 5 revealed that zinc finger E-box binding homeobox 2 activates terminal differentiation genes required for cardiomyocyte structure and function whereas zinc finger protein 503 and NK2 homeobox 5 are required for specification of the cardiac lineage. We further demonstrated that an essential role of NK2 homeobox 5 and zinc finger protein 503 in specification of the cardiac lineage is the repression of gene expression programs characteristic of alternative cell fates. Collectively, these results show that orthologous gene expression signatures can be used to identify conserved cardiogenic pathways. PMID:26485529

  12. Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

    EPA Science Inventory

    Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

  13. Validation of an immunohistochemical signature predictive of 8-year outcome for patients with breast carcinoma.

    PubMed

    Charpin, Colette; Tavassoli, Fattaneh; Secq, Véronique; Giusiano, Sophie; Villeret, Julia; Garcia, Stéphane; Birnbaum, Daniel; Bonnier, Pascal; Lavaut, Marie-Noëlle; Boubli, Léon; Carcopino, Xavier; Iovanna, Juan

    2012-08-01

    We recently reported that standardized quantitative immunohistochemical (IHC) assays allowed prediction of an adverse outcome among 572 node negative (N-) patients with breast carcinoma (BrCa). To further validate our prior findings, we repeated the IHC stains including a second series of BrCa diagnosed at Yale University. Tissue microarrays (TMAs) of two cohorts of patients with BrCa (418 Marseille University and 303 Yale University) were respectively investigated for IHC expression of 15 markers (HIF-1α, PI3K, pAKT, pmTOR, moesin, P21, 4(E) BP-1, P27, Ker5-6, pMAPKAPK-2, SHARP2, claudin-1, ALDH, AF6 and CD24). Quantitative measurements of immunoprecipitates densitometry assessed with an image analyzer were correlated with 8-year patients' outcome and compared in the two cohorts. The best predictive signature consisted of a combination of five markers that included HIF-1α, PI3K, claudin-1, AF6 and pAKT in N- BrCa. This combination permitted an accurate prediction of outcome in 92.34% (386/418) of N- patients in the first set (Marseille) and 89.8% (158/176) in the second set (Yale). The close results in both cohorts confirmed the validity of this original IHC signature predictive of prognosis in node negative BrCa. This validation suggests that in clinical practice, it would be possible with standardized kits (i) to identify patients with poor prognosis at diagnosis time, particularly in the N- BrCa subset, who would require more aggressive adjuvant therapy and (ii) to avoid useless expensive therapies and their side effects in N- patients with favorable prognosis. PMID:22120430

  14. Multiclass cancer diagnosis using tumor gene expression signatures

    DOE PAGESBeta

    Ramaswamy, S.; Tamayo, P.; Rifkin, R.; Mukherjee, S.; Yeang, C. -H.; Angelo, M.; Ladd, C.; Reich, M.; Latulippe, E.; Mesirov, J. P.; et al

    2001-12-11

    The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a supportmore » vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.« less

  15. Multiclass cancer diagnosis using tumor gene expression signatures

    SciTech Connect

    Ramaswamy, S.; Tamayo, P.; Rifkin, R.; Mukherjee, S.; Yeang, C. -H.; Angelo, M.; Ladd, C.; Reich, M.; Latulippe, E.; Mesirov, J. P.; Poggio, T.; Gerald, W.; Loda, M.; Lander, E. S.; Golub, T. R.

    2001-12-11

    The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a support vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics.

  16. Development and evaluation of a genomic signature for the prediction and mechanistic assessment of nongenotoxic hepatocarcinogens in the rat.

    PubMed

    Fielden, Mark R; Adai, Alex; Dunn, Robert T; Olaharski, Andrew; Searfoss, George; Sina, Joe; Aubrecht, Jiri; Boitier, Eric; Nioi, Paul; Auerbach, Scott; Jacobson-Kram, David; Raghavan, Nandini; Yang, Yi; Kincaid, Andrew; Sherlock, Jon; Chen, Shen-Jue; Car, Bruce

    2011-11-01

    Evaluating the risk of chemical carcinogenesis has long been a challenge owing to the protracted nature of the pathology and the limited translatability of animal models. Although numerous short-term in vitro and in vivo assays have been developed, they have failed to reliably predict the carcinogenicity of nongenotoxic compounds. Extending upon previous microarray work (Fielden, M. R., Nie, A., McMillian, M., Elangbam, C. S., Trela, B. A., Yang, Y., Dunn, R. T., II, Dragan, Y., Fransson-Stehen, R., Bogdanffy, M., et al. (2008). Interlaboratory evaluation of genomic signatures for predicting carcinogenicity in the rat. Toxicol. Sci. 103, 28-34), we have developed and extensively evaluated a quantitative PCR-based signature to predict the potential for nongenotoxic compounds to induce liver tumors in the rat as a first step in the safety assessment of potential nongenotoxic carcinogens. The training set was derived from liver RNA from rats treated with 72 compounds and used to develop a 22-gene signature on the TaqMan array platform, providing an economical and standardized assay protocol. Independent testing on over 900 diverse samples (66 compounds) confirmed the interlaboratory precision of the assay and its ability to predict known nongenotoxic hepatocarcinogens (NGHCs). When tested under different experimental designs, strains, time points, dose setting criteria, and other preanalytical processes, the signature sensitivity and specificity was estimated to be 67% (95% confidence interval [CI] = 38-88%) and 59% (95% CI = 44-72%), respectively, with an area under the receiver operating characteristic curve of 0.65 (95% CI = 0.46-0.83%). Compounds were best classified using expression data from short-term repeat dose studies; however, the prognostic expression changes appeared to be preserved after longer term treatment. Exploratory evaluations also revealed that different modes of action for nongenotoxic and genotoxic compounds can be discriminated based on the

  17. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  18. A gene expression signature associated with metastatic cells in effusions of breast carcinoma patients.

    PubMed

    Dupont, Virginie N; Gentien, David; Oberkampf, Marine; De Rycke, Yann; Blin, Nathalie

    2007-09-01

    Malignant effusion in invasive breast carcinoma is associated with poor prognosis. To decipher molecular events leading to metastasis and to identify reliable markers for targeted therapies are of crucial need. Therefore, we have used cDNA microarrays to delineate molecular signatures associated with metastasis and relapse in breast carcinoma effusions. Taking advantage of an immunomagnetic method, we have purified to homogeneity EpCAM-positive cells from 34 malignant effusions. Immunopurified cells represented as much as 10% of the whole cell fraction and their epithelial and carcinoma features were confirmed by immunofluorescence labeling. Gene expression profiles of 19 immunopurified effusion samples, were analyzed using human pan-genomic microarrays, and compared with those of 4 corresponding primary tumors, 8 breast carcinoma effusion-derived cell lines, and 4 healthy mammary tissues. Principal component and multiple clustering analyses of microarray data, clearly identified distinctive molecular portraits corresponding to the 4 categories of specimens. Of uppermost interest, effusion samples were arranged in 2 subsets on the basis of their gene expression patterns. The first subset partly shares a gene expression signature with the different cell lines, and overexpresses CD24, CD44 and epithelial cytokeratins 8,18,19. The second subset overexpresses markers related to aggressive invasive carcinoma (uPA receptor, S100A4, vimentin, CXCR4). These findings demonstrate the importance of using pure cell fractions to accurately decipher in silico gene expression of clinical specimens. Further studies will lead to the identification of genes of oustanding importance to diagnose malignant effusion, predict survival and tailor appropriate therapies to the metastatic effusion disease in breast carcinoma patients. PMID:17450528

  19. Towards Simulating Non-Axisymmetric Influences on Aircraft Plumes for Signature Prediction

    NASA Technical Reports Server (NTRS)

    Kenzakowski, D. C.; Shipman, J. D.; Dash, S. M.

    2000-01-01

    A methodology for efficiently including three-dimensional effects on aircraft plume signature is presented. First, exploratory work on the use of passive mixing enhancement devices, namely chevrons and tabs, in IR signature reduction for external turbofan plumes is demonstrated numerically and experimentally. Such small attachments, when properly designed, cause an otherwise axisymmetric plume to have significant 3D structures, affecting signature prediction. Second, an approach for including non-axisymmetric and installation effects in plume signature prediction is discussed using unstructured methodology. Unstructured flow solvers, using advanced turbulence modeling and plume thermochemistry, facilitate the modeling of aircraft effects on plume structure that previously have been neglected due to gridding complexities. The capabilities of the CRUNCH unstructured Navier-Stokes solver for plume modeling is demonstrated for a passively mixed turbofan nozzle, a generic fighter nozzle, and a complete aircraft.

  20. Combining Clinical, Pathology, and Gene Expression Data to Predict Recurrence of Hepatocellular Carcinoma

    PubMed Central

    Villanueva, Augusto; Hoshida, Yujin; Battiston, Carlo; Tovar, Victoria; Sia, Daniela; Alsinet, Clara; Cornella, Helena; Liberzon, Arthur; Kobayashi, Masahiro; Kumada, Hiromitsu; Thung, Swan N.; Bruix, Jordi; Newell, Philippa; April, Craig; Fan, Jian-Bing; Roayaie, Sasan; Mazzaferro, Vincenzo; Schwartz, Myron E.; Llovet, Josep M.

    2011-01-01

    Background & Aims In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early-stage (BCLC 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. Methods We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n=287) and adjacent non-tumor, cirrhotic tissue (n=226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. Results Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from non-tumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature “G3-proliferation” (hazard ratio [HR]=1.75, P=0.003) and an adjacent “poor-survival” signature (HR=1.74, P=0.004) were independent predictors of HCC recurrence, along with satellites (HR=1.66, P=0.04). Samples from different sites in the same tumor nodule were reproducibly classified. Conclusions We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. PMID:21320499

  1. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    PubMed Central

    2011-01-01

    Background The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Methods Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. Results HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. Conclusion When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome. PMID:22070665

  2. Using glint to perform geometric signature prediction and pose estimation

    NASA Astrophysics Data System (ADS)

    Paulson, Christopher; Zelnio, Edmund; Gorham, LeRoy; Wu, Dapeng

    2012-05-01

    We consider two problems in this paper. The rst problem is to construct a dictionary of elements without using synthetic data or a subset of the data collection; the second problem is to estimate the orientation of the vehicle, independent of the elevation angle. These problems are important to the SAR community because it will alleviate the cost to create the dictionary and reduce the number of elements in the dictionary needed for classication. In order to accomplish these tasks, we utilize the glint phenomenology, which is usually viewed as a hindrance in most algorithms but is valuable information in our research. One way to capitalize on the glint information is to predict the location of the int by using geometry of the single and double bounce phenomenology. After qualitative examination of the results, we were able to deduce that the geometry information was sucient for accurately predicting the location of the glint. Another way that we exploited the glint characteristics was by using it to extract the angle feature which we will use to do the pose estimation. Using this technique we were able to predict the cardinal heading of the vehicle within +/-2° with 96:6% having 0° error. Now this research will have an impact on the classication of SAR images because the geometric prediction will reduce the cost and time to develop and maintain the database for SAR ATR systems and the pose estimation will reduce the computational time and improve accuracy of vehicle classication.

  3. ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (Developing Predictive Bioactivity Signatures from ToxCasts HTS Data)

    EPA Science Inventory

    ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

  4. Improved signature prediction through coupling of ShipIR and CFD

    NASA Astrophysics Data System (ADS)

    Vaitekunas, David A.; Sideroff, Chris; Moussa, Christine

    2011-05-01

    Most existing platform signature models use semi-empirical correlations to predict flow convection on internal and external surfaces, a key element in the prediction of accurate skin signature. Although these convection algorithms are capable of predicting bulk heat transfer coefficients between each surface and the designated flow region, they are not capable of capturing local effects such as flow stagnation, flow separation, and flow history. Most computational fluid dynamics (CFD) codes lack the ability to predict changes in background solar and thermal irradiation with the environment and sun location, nor do they include multi-bounce radiative surface exchanges by default in their solvers. Existing interfaces between CFD and signature prediction typically involve a one-directional mapping of CFD predicted temperatures to the signature model. This paper describes a new functional interface between the NATO-standard ship signature model (ShipIR) and the ANSYS Fluent model, where a bi-directional mapping is used to transfer the thermal radiation predictions from ShipIR to Fluent, and after re-iteration of the CFD solution, transfer the wall and fluid temperatures back to ShipIR for further refinement of local-area heat transfer coefficients, and re-iteration of the ShipIR thermal solution. Both models converge to an RMS difference of 0.3 °C within a few successive iterations (5-6). This new functional interface is described through a detailed thermal/IR simulation of an unclassified research vessel, the Canadian Forces Auxiliary Vessel (CFAV) Quest. Future efforts to validate this new modelling approach using shipboard measurements are also discussed.

  5. A signature microRNA expression profile for the cellular response to thermal stress

    NASA Astrophysics Data System (ADS)

    Wilmink, Gerald J.; Roth, Caleb C.; Ketchum, Norma; Ibey, Bennett L.; Waterworth, Angela; Suarez, Maria; Roach, William P.

    2009-02-01

    Recently, an extensive layer of intra-cellular signals was discovered that was previously undetected by genetic radar. It is now known that this layer consists primarily of a class of short noncoding RNA species that are referred to as microRNAs (miRNAs). MiRNAs regulate protein synthesis at the post-transcriptional level, and studies have shown that they are involved in many fundamental cellular processes. In this study, we hypothesized that miRNAs may be involved in cellular stress response mechanisms, and that cells exposed to thermal stress may exhibit a signature miRNA expression profile indicative of their functional involvement in such mechanisms. To test our hypothesis, human dermal fibroblasts were exposed to an established hyperthermic protocol, and the ensuing miRNA expression levels were evaluated 4 hr post-exposure using microRNA microarray gene chips. The microarray data shows that 123 miRNAs were differentially expressed in cells exposed to thermal stress. We collectively refer to these miRNAs as thermalregulated microRNAs (TRMs). Since miRNA research is in its infancy, it is interesting to note that only 27 of the 123 TRMs are currently annotated in the Sanger miRNA registry. Prior to publication, we plan to submit the remaining novel 96 miRNA gene sequences for proper naming. Computational and thermodynamic modeling algorithms were employed to identify putative mRNA targets for the TRMs, and these studies predict that TRMs regulate the mRNA expression of various proteins that are involved in the cellular stress response. Future empirical studies will be conducted to validate these theoretical predictions, and to further examine the specific role that TRMs play in the cellular stress response.

  6. Whole Genome Transcript Profiling of Drug Induced Steatosis in Rats Reveals a Gene Signature Predictive of Outcome

    PubMed Central

    Sahini, Nishika; Selvaraj, Saravanakumar; Borlak, Jürgen

    2014-01-01

    Drug induced steatosis (DIS) is characterised by excess triglyceride accumulation in the form of lipid droplets (LD) in liver cells. To explore mechanisms underlying DIS we interrogated the publically available microarray data from the Japanese Toxicogenomics Project (TGP) to study comprehensively whole genome gene expression changes in the liver of treated rats. For this purpose a total of 17 and 12 drugs which are diverse in molecular structure and mode of action were considered based on their ability to cause either steatosis or phospholipidosis, respectively, while 7 drugs served as negative controls. In our efforts we focused on 200 genes which are considered to be mechanistically relevant in the process of lipid droplet biogenesis in hepatocytes as recently published (Sahini and Borlak, 2014). Based on mechanistic considerations we identified 19 genes which displayed dose dependent responses while 10 genes showed time dependency. Importantly, the present study defined 9 genes (ANGPTL4, FABP7, FADS1, FGF21, GOT1, LDLR, GK, STAT3, and PKLR) as signature genes to predict DIS. Moreover, cross tabulation revealed 9 genes to be regulated ≥10 times amongst the various conditions and included genes linked to glucose metabolism, lipid transport and lipogenesis as well as signalling events. Additionally, a comparison between drugs causing phospholipidosis and/or steatosis revealed 26 genes to be regulated in common including 4 signature genes to predict DIS (PKLR, GK, FABP7 and FADS1). Furthermore, a comparison between in vivo single dose (3, 6, 9 and 24 h) and findings from rat hepatocyte studies (2 h, 8 h, 24 h) identified 10 genes which are regulated in common and contained 2 DIS signature genes (FABP7, FGF21). Altogether, our studies provide comprehensive information on mechanistically linked gene expression changes of a range of drugs causing steatosis and phospholipidosis and encourage the screening of DIS signature genes at the preclinical stage. PMID:25470483

  7. A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.

    PubMed

    Iorio, Francesco; Shrestha, Roshan L; Levin, Nicolas; Boilot, Viviane; Garnett, Mathew J; Saez-Rodriguez, Julio; Draviam, Viji M

    2015-01-01

    We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells-consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel. PMID:26452147

  8. A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions

    PubMed Central

    Iorio, Francesco; Shrestha, Roshan L.; Levin, Nicolas; Boilot, Viviane; Garnett, Mathew J.; Saez-Rodriguez, Julio; Draviam, Viji M.

    2015-01-01

    We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells–consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel. PMID:26452147

  9. Network-based biomarkers enhance classical approaches to prognostic gene expression signatures

    PubMed Central

    2014-01-01

    Background Classical approaches to predicting patient clinical outcome via gene expression information are primarily based on differential expression of unrelated genes (single-gene approaches) or genes related by, for example, biologic pathway or function (gene-sets). Recently, network-based approaches utilising interaction information between genes have emerged. An open problem is whether such approaches add value to the more traditional methods of signature modelling. We explored this question via comparison of the most widely employed single-gene, gene-set, and network-based methods, using gene expression microarray data from two different cancers: melanoma and ovarian. We considered two kinds of network approaches. The first of these identifies informative genes using gene expression and network connectivity information combined, the latter drawn from prior knowledge of protein-protein interactions. The second approach focuses on identification of informative sub-networks (small networks of interacting proteins, again from prior knowledge networks). For all methods we performed 100 rounds of 5-fold cross-validation under 3 different classifiers. For network-based approaches, we considered two different protein-protein interaction networks. We quantified resulting patterns of misclassification and discussed the relative value of each relative to ongoing development of prognostic biomarkers. Results We found that single-gene, gene-set and network methods yielded similar error rates in melanoma and ovarian cancer data. Crucially, however, our novel and detailed patient-level analyses revealed that the different methods were correctly classifying alternate subsets of patients in each cohort. We also found that the network-based NetRank feature selection method was the most stable. Conclusions Next-generation methods of gene expression signature modelling harness data from external networks and are foreshadowed as a standard mode of analysis. But what do they add

  10. Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

    EPA Science Inventory

    EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

  11. Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis

    PubMed Central

    Rosenberg, Alan M.; Yeung, Rae S. M.; Morris, Quaid

    2016-01-01

    Gene expression-based signatures help identify pathways relevant to diseases and treatments, but are challenging to construct when there is a diversity of disease mechanisms and treatments in patients with complex diseases. To overcome this challenge, we present a new application of an in silico gene expression deconvolution method, ISOpure-S1, and apply it to identify a common gene expression signature corresponding to response to treatment in 33 juvenile idiopathic arthritis (JIA) patients. Using pre- and post-treatment gene expression profiles only, we found a gene expression signature that significantly correlated with a reduction in the number of joints with active arthritis, a measure of clinical outcome (Spearman rho = 0.44, p = 0.040, Bonferroni correction). This signature may be associated with a decrease in T-cells, monocytes, neutrophils and platelets. The products of most differentially expressed genes include known biomarkers for JIA such as major histocompatibility complexes and interleukins, as well as novel biomarkers including α-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples. PMID:27244050

  12. Prediction of the TNT signature from buried UXO/landmines

    SciTech Connect

    Webb, S.W.; Phelan, J.M.; Finsterle, S.A.; Pruess, K.

    1998-06-01

    The detection and removal of buried unexploded ordnance (UXO) and landmines is one of the most important problems facing the world today. Numerous detection strategies are being developed, including infrared, electrical conductivity, ground-penetrating radar, and chemical sensors. Chemical sensors rely on the detection of TNT molecules, which are transported from buried UXO/landmines by advection and diffusion in the soil. As part of this effort, numerical models are being developed to predict TNT transport in soils including the effect of precipitation and evaporation. Modifications will be made to TOUGH2 for application to the TNT chemical sensing problem. Understanding the fate and transport of TNT in the soil will affect the design, performance and operation of chemical sensors by indicating preferred sensing strategies.

  13. Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants

    SciTech Connect

    Leone, Angelique; Nie, Alex; Brandon Parker, J.; Sawant, Sharmilee; Piechta, Leigh-Anne; Kelley, Michael F. Mark Kao, L.; Jim Proctor, S.; Verheyen, Geert; Johnson, Mark D.; Lord, Peter G.; McMillian, Michael K.

    2014-03-15

    Previously we reported a gene expression signature in rat liver for detecting a specific type of oxidative stress (OS) related to reactive metabolites (RM). High doses of the drugs disulfiram, ethinyl estradiol and nimesulide were used with another dozen paradigm OS/RM compounds, and three other drugs flutamide, phenacetin and sulindac were identified by this signature. In a second study, antiepileptic drugs were compared for covalent binding and their effects on OS/RM; felbamate, carbamazepine, and phenobarbital produced robust OS/RM gene expression. In the present study, liver RNA samples from drug-treated rats from more recent experiments were examined for statistical fit to the OS/RM signature. Of all 97 drugs examined, in addition to the nine drugs noted above, 19 more were identified as OS/RM-producing compounds—chlorpromazine, clozapine, cyproterone acetate, dantrolene, dipyridamole, glibenclamide, isoniazid, ketoconazole, methapyrilene, naltrexone, nifedipine, sulfamethoxazole, tamoxifen, coumarin, ritonavir, amitriptyline, valproic acid, enalapril, and chloramphenicol. Importantly, all of the OS/RM drugs listed above have been linked to idiosyncratic hepatotoxicity, excepting chloramphenicol, which does not have a package label for hepatotoxicity, but does have a black box warning for idiosyncratic bone marrow suppression. Most of these drugs are not acutely toxic in the rat. The OS/RM signature should be useful to avoid idiosyncratic hepatotoxicity of drug candidates. - Highlights: • 28 of 97 drugs gave a positive OS/RM gene expression signature in rat liver. • The specificity of the signature for human idiosyncratic hepatotoxicants was 98%. • The sensitivity of the signature for human idiosyncratic hepatotoxicants was 75%. • The signature can help eliminate hepatotoxicants from drug development.

  14. Hybrid Method for Prediction of Metastasis in Breast Cancer Patients Using Gene Expression Signals

    PubMed Central

    Dehnavi, Alireza Mehri; Sehhati, Mohammad Reza; Rabbani, Hossein

    2013-01-01

    Using primary tumor gene expression has been shown to have the ability of finding metastasis-driving gene markers for prediction of breast cancer recurrence (BCR). However, there are some difficulties associated with analysis of microarray data, which led to poor predictive power and inconsistency of previously introduced gene signatures. In this study, a hybrid method was proposed for identifying more predictive gene signatures from microarray datasets. Initially, the parameters of a Rough-Set (RS) theory based feature selection method were tuned to construct a customized gene extraction algorithm. Afterward, using RS gene selection method the most informative genes selected from six independent breast cancer datasets. Then, combined set of these six signature sets, containing 114 genes, was evaluated for prediction of BCR. In final, a meta-signature, containing 18 genes, selected from the combination of datasets and its prediction accuracy compared to the combined signature. The results of 10-fold cross-validation test showed acceptable misclassification error rate (MCR) over 1338 cases of breast cancer patients. In comparison to a recent similar work, our approach reached more than 5% reduction in MCR using a fewer number of genes for prediction. The results also demonstrated 7% improvement in average accuracy in six utilized datasets, using the combined set of 114 genes in comparison with 18-genes meta-signature. In this study, a more informative gene signature was selected for prediction of BCR using a RS based gene extraction algorithm. To conclude, combining different signatures demonstrated more stable prediction over independent datasets. PMID:24098861

  15. An mRNA expression signature for prognostication in de novo acute myeloid leukemia patients with normal karyotype

    PubMed Central

    Chou, Wen-Chien; Hou, Hsin-An; Tseng, Mei-Hsuan; Kuo, Yi-Yi; Chen, Yidong; Chuang, Eric Y.; Tien, Hwei-Fang

    2015-01-01

    Although clinical features, cytogenetics, and mutations are widely used to predict prognosis in patients with acute myeloid leukemia (AML), further refinement of risk stratification is necessary for optimal treatment, especially in cytogenetically normal (CN) patients. We sought to generate a simple gene expression signature as a predictor of clinical outcome through analyzing the mRNA arrays of 158 de novo CN AML patients. We compared the gene expression profiles of patients with poor response to induction chemotherapy with those who responded well. Forty-six genes expressed differentially between the two groups. Among them, expression of 11 genes was significantly associated with overall survival (OS) in univariate Cox regression analysis in 104 patients who received standard intensive chemotherapy. We integrated the z-transformed expression levels of these 11 genes to generate a risk scoring system. Higher risk scores were significantly associated with shorter OS (median 17.0 months vs. not reached, P < 0.001) in ours and another 3 validation cohorts. In addition, it was an independent unfavorable prognostic factor by multivariate analysis (HR 1.116, 95% CI 1.035~1.204, P = 0.004). In conclusion, we developed a simple mRNA expression signature for prognostication in CN-AML patients. This prognostic biomarker will help refine the treatment strategies for this group of patients. PMID:26517675

  16. Cluster Multipoint Observations of Magnetotail Current Instabilities Reveal Signatures Predicted by SIMULATION!

    NASA Astrophysics Data System (ADS)

    Buechner, J.; Nikutowski, B.; Daly, P.; Mall, U.; Balogh, A.; Glassmeier, K.; Fornacon, K.; Korth, A.; Sauvaud, J.; Reme, H.

    2002-05-01

    Utilizing CLUSTER-multipoint observations during tail passages of the four s/c we found evidence for thin current sheet traversals. At the center of the sheet a plasma wave was found to propagate in the current direction. We compare the wave features with signatures of thin current sheet instabilities and reconnection which we obtained by kinetic plasma simulation. It appears that several instability signatures predicted by simulation can be found in CLUSTER observations. Thus the observations seem to indicate that thin current sheets develop an unstable wave mode propagating in the current direction. In the observation the current instability was followed by an outbreak of reconnection.

  17. Expression Signatures of Long Noncoding RNAs in Adolescent Idiopathic Scoliosis

    PubMed Central

    Liu, Xiao-Yang; Wang, Liang; Yu, Bin; Zhuang, Qian-yu; Wang, Yi-Peng

    2015-01-01

    Purpose. Adolescent idiopathic scoliosis (AIS), the most common pediatric spinal deformity, is considered a complex genetic disease. Causing genes and pathogenesis of AIS are still unclear. This study was designed to identify differentially expressed long noncoding RNAs (lncRNAs) involving the pathogenesis of AIS. Methods. We first performed comprehensive screening of lncRNA and mRNA in AIS patients and healthy children using Agilent human lncRNA + mRNA Array V3.0 microarray. LncRNAs expression in different AIS patients was further evaluated using quantitative PCR. Results. A total of 139 lncRNAs and 546 mRNAs were differentially expressed between AIS patients and healthy control. GO and Pathway analysis showed that these mRNAs might be involved in bone mineralization, neuromuscular junction, skeletal system morphogenesis, nucleotide and nucleic acid metabolism, and regulation of signal pathway. Four lncRNAs (ENST00000440778.1, ENST00000602322.1, ENST00000414894.1, and TCONS_00028768) were differentially expressed between different patients when grouped according to age, height, classification, severity of scoliosis, and Risser grade. Conclusions. This study demonstrates the abnormal expression of lncRNAs and mRNAs in AIS, and the expression of some lncRNAs was related to clinical features. This study is helpful for further understanding of lncRNAs in pathogenesis, treatment, and prognosis of AIS. PMID:26421281

  18. Pulmonary arteriole gene expression signature in idiopathic pulmonary fibrosis.

    PubMed

    Patel, Nina M; Kawut, Steven M; Jelic, Sanja; Arcasoy, Selim M; Lederer, David J; Borczuk, Alain C

    2013-06-01

    A third of patients with idiopathic pulmonary fibrosis (IPF) develop pulmonary hypertension (PH-IPF), which is associated with increased mortality. Whether an altered gene expression profile in the pulmonary vasculature precedes the clinical onset of PH-IPF is unknown. We compared gene expression in the pulmonary vasculature of IPF patients with and without PH with controls. Pulmonary arterioles were isolated using laser capture microdissection from 16 IPF patients: eight with PH (PH-IPF) and eight with no PH (NPH-IPF), and seven controls. Probe was prepared from extracted RNA, and hybridised to Affymetrix Hu133 2.0 Plus genechips. Biometric Research Branch array tools and Ingenuity Pathway Analysis software were used for analysis of the microarray data. Univariate analysis revealed 255 genes that distinguished IPF arterioles from controls (p<0.001). Mediators of vascular smooth muscle and endothelial cell proliferation, Wnt signalling and apoptosis were differentially expressed in IPF arterioles. Unsupervised and supervised clustering analyses revealed similar gene expression in PH-IPF and NPH-IPF arterioles. The pulmonary arteriolar gene expression profile is similar in IPF patients with and without coexistent PH. Pathways involved in vascular proliferation and aberrant apoptosis, which may contribute to pulmonary vascular remodelling, are activated in IPF patients. PMID:23728404

  19. Prediction of B-strand packing interactions using the signature product.

    SciTech Connect

    Brown, W. Michael; Martin, Shawn Bryan; Faulon, Jean-Loup Michel; Strauss, Charlie

    2005-03-01

    The prediction of {beta}-sheet topology requires the consideration of long-range interactions between {beta}-strands that are not necessarily consecutive in sequence. Since these interactions are difficult to simulate using ab initio methods, we propose a supplementary method able to assign {beta}-sheet topology using only sequence information. We envision using the results of our method to reduce the three-dimensional search space of ab initio methods. Our method is based on the signature molecular descriptor, which has been used previously to predict protein-protein interactions successfully, and to develop quantitative structure-activity relationships for small organic drugs and peptide inhibitors. Here, we show how the signature descriptor can be used in a Support Vector Machine to predict whether or not two {beta}-strands will pack adjacently within a protein. We then show how these predictions can be used to order {beta}-strands within {beta}-sheets. Using the entire PDB database with ten-fold cross-validation, we have achieved 74.0% accuracy in packing prediction and 75.6% accuracy in the prediction of edge strands. For the case of {beta}-strand ordering, we are able to predict the correct ordering accurately for 51.3% of the {beta}-sheets. Furthermore, using a simple confidence metric, we can determine those sheets for which accurate predictions can be obtained. For the top 25% highest confidence predictions, we are able to achieve 95.7% accuracy in {beta}-strand ordering.

  20. Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes

    PubMed Central

    Dozmorov, Mikhail G

    2015-01-01

    Although age-associated gene expression and methylation changes have been reported throughout the literature, the unifying epigenomic principles of aging remain poorly understood. Recent explosion in availability and resolution of functional/regulatory genome annotation data (epigenomic data), such as that provided by the ENCODE and Roadmap Epigenomics projects, provides an opportunity for the identification of epigenomic mechanisms potentially altered by age-associated differentially methylated regions (aDMRs) and regulatory signatures in the promoters of age-associated genes (aGENs). In this study we found that aDMRs and aGENs identified in multiple independent studies share a common Polycomb Repressive Complex 2 signature marked by EZH2, SUZ12, CTCF binding sites, repressive H3K27me3, and activating H3K4me1 histone modification marks, and a “poised promoter” chromatin state. This signature is depleted in RNA Polymerase II-associated transcription factor binding sites, activating H3K79me2, H3K36me3, H3K27ac marks, and an “active promoter” chromatin state. The PRC2 signature was shown to be generally stable across cell types. When considering the directionality of methylation changes, we found the PRC2 signature to be associated with aDMRs hypermethylated with age, while hypomethylated aDMRs were associated with enhancers. In contrast, aGENs were associated with the PRC2 signature independently of the directionality of gene expression changes. In this study we demonstrate that the PRC2 signature is the common epigenomic context of genomic regions associated with hypermethylation and gene expression changes in aging. PMID:25880792

  1. A new molecular signature method for prediction of driver cancer pathways from transcriptional data

    PubMed Central

    Rykunov, Dmitry; Beckmann, Noam D.; Li, Hui; Uzilov, Andrew; Schadt, Eric E.; Reva, Boris

    2016-01-01

    Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways. PMID:27098033

  2. A new molecular signature method for prediction of driver cancer pathways from transcriptional data.

    PubMed

    Rykunov, Dmitry; Beckmann, Noam D; Li, Hui; Uzilov, Andrew; Schadt, Eric E; Reva, Boris

    2016-06-20

    Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways. PMID:27098033

  3. A four gene signature predicts benefit from anthracyclines: evidence from the BR9601 and MA.5 clinical trials.

    PubMed

    Spears, Melanie; Yousif, Fouad; Lyttle, Nicola; Boutros, Paul C; Munro, Alison F; Twelves, Chris; Pritchard, Kathleen I; Levine, Mark N; Shepherd, Lois; Bartlett, John M S

    2015-10-13

    Chromosome instability (CIN) in solid tumours results in multiple numerical and structural chromosomal aberrations and is associated with poor prognosis in multiple tumour types. Recent evidence demonstrated CEP17 duplication, a CIN marker, is a predictive marker of anthracycline benefit. An analysis of the BR9601 and MA.5 clinical trials was performed to test the role of existing CIN gene expression signatures as predictive markers of anthracycline sensitivity in breast cancer. Univariate analysis demonstrated, high CIN25 expression score was associated with improved distant relapse free survival (DRFS) (HR: 0.74, 95% CI 0.54-0.99, p = 0.046). High tumour CIN70 and CIN25 scores were associated with aggressive clinicopathological phenotype and increased sensitivity to anthracycline therapy compared to low CIN scores. However, in a prospectively planned multivariate analysis only pathological grade, nodal status and tumour size were significant predictors of outcome for CIN25/CIN70. A limited gene signature was generated, patients with low tumour CIN4 scores benefited from anthracycline treatment significantly more than those with high CIN4 scores (HR 0.37, 95% CI 0.20-0.56, p = 0.001). In multivariate analyses the treatment by marker interaction for CIN4/anthracyclines demonstrated hazard ratio of 0.35 (95% CI 0.15-0.80, p = 0.012) for DRFS. This data shows CIN4 is independent predictor of anthracycline benefit for DRFS in breast cancer. PMID:26372731

  4. A four gene signature predicts benefit from anthracyclines: evidence from the BR9601 and MA.5 clinical trials

    PubMed Central

    Spears, Melanie; Yousif, Fouad; Lyttle, Nicola; Boutros, Paul C.; Munro, Alison F.; Twelves, Chris; Pritchard, Kathleen I.; Levine, Mark N.; Shepherd, Lois; Bartlett, John MS.

    2015-01-01

    Chromosome instability (CIN) in solid tumours results in multiple numerical and structural chromosomal aberrations and is associated with poor prognosis in multiple tumour types. Recent evidence demonstrated CEP17 duplication, a CIN marker, is a predictive marker of anthracycline benefit. An analysis of the BR9601 and MA.5 clinical trials was performed to test the role of existing CIN gene expression signatures as predictive markers of anthracycline sensitivity in breast cancer. Univariate analysis demonstrated, high CIN25 expression score was associated with improved distant relapse free survival (DRFS) (HR: 0.74, 95% CI 0.54-0.99, p = 0.046). High tumour CIN70 and CIN25 scores were associated with aggressive clinicopathological phenotype and increased sensitivity to anthracycline therapy compared to low CIN scores. However, in a prospectively planned multivariate analysis only pathological grade, nodal status and tumour size were significant predictors of outcome for CIN25/CIN70. A limited gene signature was generated, patients with low tumour CIN4 scores benefited from anthracycline treatment significantly more than those with high CIN4 scores (HR 0.37, 95% CI 0.20-0.56, p = 0.001). In multivariate analyses the treatment by marker interaction for CIN4/anthracyclines demonstrated hazard ratio of 0.35 (95% CI 0.15-0.80, p = 0.012) for DRFS. This data shows CIN4 is independent predictor of anthracycline benefit for DRFS in breast cancer. PMID:26372731

  5. Gene Expression Signatures Diagnose Influenza and Other Symptomatic Respiratory Viral Infection in Humans

    PubMed Central

    Zaas, Aimee K.; Chen, Minhua; Varkey, Jay; Veldman, Timothy; Hero, Alfred O.; Lucas, Joseph; Huang, Yongsheng; Turner, Ronald; Gilbert, Anthony; Lambkin-Williams, Robert; Øien, N. Christine; Nicholson, Bradly; Kingsmore, Stephen; Carin, Lawrence; Woods, Christopher W.; Ginsburg, Geoffrey S.

    2010-01-01

    Summary Acute respiratory infections (ARI) are a common reason for seeking medical attention and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARI from uninfected individuals with > 95% accuracy. We validated this “acute respiratory viral” signature - encompassing genes with a known role in host defense against viral infections - across each viral challenge. We also validated the signature in an independently acquired dataset for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same dataset, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals. PMID:19664979

  6. Identification of gene expression signature for cigarette smoke exposure response--from man to mouse.

    PubMed

    Martin, F; Talikka, M; Hoeng, J; Peitsch, M C

    2015-12-01

    Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol. PMID:26614807

  7. A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs

    PubMed Central

    Beuvink, Iwan; Kolb, Fabrice A.; Budach, Wolfgang; Garnier, Arlette; Lange, Joerg; Natt, Francois; Dengler, Uwe; Hall, Jonathan; Weiler, Jan

    2007-01-01

    Microarrays to examine the global expression levels of microRNAs (miRNAs) in a systematic in-parallel manner have become important tools to help unravel the functions of miRNAs and to understand their roles in RNA-based regulation and their implications in human diseases. We have established a novel miRNA-specific microarray platform that enables the simultaneous expression analysis of both known and predicted miRNAs obtained from human or mouse origin. Chemically modified 2′-O-(2-methoxyethyl)-(MOE) oligoribonucleotide probes were arrayed onto Evanescent Resonance (ER) microchips by robotic spotting. Supplementing the complementary probes against miRNAs with carefully designed mismatch controls allowed for accurate sequence-specific determination of miRNA expression profiles obtained from a panel of mouse tissues. This revealed new expression signatures of known miRNAs as well as of novel miRNAs previously predicted using bioinformatic methods. Systematic confirmation of the array data with northern blotting and, in particular, real-time PCR suggests that the described microarray platform is a powerful tool to analyze miRNA expression patterns with rapid throughput and high fidelity. PMID:17355992

  8. Brain Gene Expression Signatures From Cerebrospinal Fluid Exosome RNA Profiling

    NASA Technical Reports Server (NTRS)

    Zanello, S. B.; Stevens, B.; Calvillo, E.; Tang, R.; Gutierrez Flores, B.; Hu, L.; Skog, J.; Bershad, E.

    2016-01-01

    While the Visual Impairment and Intracranial Pressure (VIIP) syndrome observations have focused on ocular symptoms, spaceflight has been also associated with a number of other performance and neurologic signs, such as headaches, cognitive changes, vertigo, nausea, sleep/circadian disruption and mood alterations, which, albeit likely multifactorial, can also result from elevation of intracranial pressure (ICP). We therefore hypothesize that these various symptoms are caused by disturbances in the neurophysiology of the brain structures and are correlated with molecular markers in the cerebrospinal fluid (CSF) as indicators of neurophysiological changes. Exosomes are 30-200 nm microvesicles shed into all biofluids, including blood, urine, and CSF, carrying a highly rich source of intact protein and RNA cargo. Exosomes have been identified in human CSF, and their proteome and RNA pool is a potential new reservoir for biomarker discovery in neurological disorders. The purpose of this study is to investigate changes in brain gene expression via exosome analysis in patients suffering from ICP elevation of varied severity (idiopathic intracranial hypertension -IIH), a condition which shares some of the neuroophthalmological features of VIIP, as a first step toward obtaining evidence suggesting that cognitive function and ICP levels can be correlated with biomarkers in the CSF. Our preliminary work, reported last year, validated the exosomal technology applicable to CSF analysis and demonstrated that it was possible to obtain gene expression evidence of inflammation processes in traumatic brain injury patients. We are now recruiting patients with suspected IIH requiring lumbar puncture at Baylor College of Medicine. Both CSF (5 ml) and human plasma (10 ml) are being collected in order to compare the pattern of differentially expressed genes observed in CSF and in blood. Since blood is much more accessible than CSF, we would like to determine whether plasma biomarkers for

  9. CFD predictions of near-field pressure signatures of a low-boom aircraft

    NASA Technical Reports Server (NTRS)

    Fouladi, Kamran; Baize, Daniel G.

    1992-01-01

    A three dimensional Euler marching code has been utilized to predict near-field pressure signatures of an aircraft with low boom characteristics. Computations were extended to approximately six body lengths aft of the aircraft in order to obtain pressure data at three body lengths below the aircraft for a cruise Mach number of 1.6. The near-field pressure data were extrapolated to the ground using a Whitham based method. The distance below the aircraft where the pressure data are attained is defined in this paper as the 'separation distance.' The influences of separation distances and the still highly three-dimensional flow field on the predicted ground pressure signatures and boom loudness are presented in this paper.

  10. Signature predictions of surface targets undergoing turning maneuvers in spotlight synthetic aperture radar imagery

    NASA Astrophysics Data System (ADS)

    Garren, David A.

    2015-05-01

    This paper investigates methodologies for predicting the smear signatures in broadside spotlight synthetic aperture radar imagery collections due to surface targets that are undergoing turning maneuvers. This analysis examines the case of broadside geometry wherein the radar moves with constant speed and heading on a level flight path. This investigation concentrates moving target smear issues that yield some defocus in the range direction, although much smaller in magnitude than the motion induced smearing in the radar cross-range direction. This paper focuses on the case of a target that executes a turning maneuver during the SAR collection interval. The SAR simulations are shown to give excellent agreement between the moving target signatures and the predicted shapes of the central contours.

  11. FLT3-ITD-associated gene-expression signatures in NPM1-mutated cytogenetically normal acute myeloid leukemia.

    PubMed

    Huang, Liang; Zhou, Kuangguo; Yang, Yunfan; Shang, Zhen; Wang, Jue; Wang, Di; Wang, Na; Xu, Danmei; Zhou, Jianfeng

    2012-08-01

    Concomitance of the FLT3-ITD mutation is associated with poor prognosis in NPM1-mutated cytogenetically normal acute myeloid leukemia (CN-AML) patients, and precise studies on its role in leukemogenesis are needed; these may be elucidated at the molecular level by gene express profiling. In the present study, we built a gene-expression-based classifier using prediction analysis of microarray to characterize the FLT3-ITD signature in NPM1-mutated CN-AML patients, which comprised 10 annotated genes, and demonstrated an overall accuracy of 83.8 % in cross-validation. To characterize the signature in another way, differential expression was revealed for 34 genes by class comparison, and the up-regulation of LAPTM4B and MIR155HG was validated by quantitative RT-PCR in our small cohort of NPM1-mutated CN-AML samples, which appeared to be associated with this specific subtype. The 10-gene classifier and differentially expressed genes identified in this study indicate a potential utility for risk-assessed treatment stratification, and suggest new therapeutic targets for these high-risk AML patients. PMID:22688855

  12. Subtype-specific micro-RNA expression signatures in breast cancer progression.

    PubMed

    Haakensen, Vilde D; Nygaard, Vegard; Greger, Liliana; Aure, Miriam R; Fromm, Bastian; Bukholm, Ida R K; Lüders, Torben; Chin, Suet-Feung; Git, Anna; Caldas, Carlos; Kristensen, Vessela N; Brazma, Alvis; Børresen-Dale, Anne-Lise; Hovig, Eivind; Helland, Åslaug

    2016-09-01

    Robust markers of invasiveness may help reduce the overtreatment of in situ carcinomas. Breast cancer is a heterogeneous disease and biological mechanisms for carcinogenesis vary between subtypes. Stratification by subtype is therefore necessary to identify relevant and robust signatures of invasive disease. We have identified microRNA (miRNA) alterations during breast cancer progression in two separate datasets and used stratification and external validation to strengthen the findings. We analyzed two separate datasets (METABRIC and AHUS) consisting of a total of 186 normal breast tissue samples, 18 ductal carcinoma in situ (DCIS) and 1,338 invasive breast carcinomas. Validation in a separate dataset and stratification by molecular subtypes based on immunohistochemistry, PAM50 and integrated cluster classifications were performed. We propose subtype-specific miRNA signatures of invasive carcinoma and a validated signature of DCIS. miRNAs included in the invasive signatures include downregulation of miR-139-5p in aggressive subtypes and upregulation of miR-29c-5p expression in the luminal subtypes. No miRNAs were differentially expressed in the transition from DCIS to invasive carcinomas on the whole, indicating the need for subtype stratification. A total of 27 miRNAs were included in our proposed DCIS signature. Significant alterations of expression included upregulation of miR-21-5p and the miR-200 family and downregulation of let-7 family members in DCIS samples. The signatures proposed here can form the basis for studies exploring DCIS samples with increased invasive potential and serum biomarkers for in situ and invasive breast cancer. PMID:27082076

  13. A Simple and Efficient Computational Approach to Chafed Cable Time-Domain Reflectometry Signature Prediction

    NASA Technical Reports Server (NTRS)

    Kowalski, Marc Edward

    2009-01-01

    A method for the prediction of time-domain signatures of chafed coaxial cables is presented. The method is quasi-static in nature, and is thus efficient enough to be included in inference and inversion routines. Unlike previous models proposed, no restriction on the geometry or size of the chafe is required in the present approach. The model is validated and its speed is illustrated via comparison to simulations from a commercial, three-dimensional electromagnetic simulator.

  14. Genetically diverse CC-founder mouse strains replicate the human influenza gene expression signature

    PubMed Central

    Elbahesh, Husni; Schughart, Klaus

    2016-01-01

    Influenza A viruses (IAV) are zoonotic pathogens that pose a major threat to human and animal health. Influenza virus disease severity is influenced by viral virulence factors as well as individual differences in host response. We analyzed gene expression changes in the blood of infected mice using a previously defined set of signature genes that was derived from changes in the blood transcriptome of IAV-infected human volunteers. We found that the human signature was reproduced well in the founder strains of the Collaborative Cross (CC) mice, thus demonstrating the relevance and importance of mouse experimental model systems for studying human influenza disease. PMID:27193691

  15. Genetically diverse CC-founder mouse strains replicate the human influenza gene expression signature.

    PubMed

    Elbahesh, Husni; Schughart, Klaus

    2016-01-01

    Influenza A viruses (IAV) are zoonotic pathogens that pose a major threat to human and animal health. Influenza virus disease severity is influenced by viral virulence factors as well as individual differences in host response. We analyzed gene expression changes in the blood of infected mice using a previously defined set of signature genes that was derived from changes in the blood transcriptome of IAV-infected human volunteers. We found that the human signature was reproduced well in the founder strains of the Collaborative Cross (CC) mice, thus demonstrating the relevance and importance of mouse experimental model systems for studying human influenza disease. PMID:27193691

  16. Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma

    PubMed Central

    Sun, Yifeng; Hou, Likun; Yang, Yu; Xie, Huikang; Yang, Yang; Li, Zhigang; Zhao, Heng; Gao, Wen; Su, Bo

    2016-01-01

    Background In this study, we investigated the contribution of a gene expression–based signature (composed of BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, SH3BGR) to survival prediction for early-stage lung adenocarcinoma categorized by the new International Association for the Study of Lung Cancer (IASLC)/the American Thoracic Society (ATS)/the European Respiratory Society (ERS) classification. We also aimed to verify whether gene signature improves the risk discrimination of IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. Patients and methods Total RNA was extracted from 93 patients with pathologically confirmed TNM stage Ia and Ib lung adenocarcinoma. The mRNA expression levels of ten genes in the signature (BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, and SH3BGR) were detected using real-time polymerase chain reaction. Each patient was categorized according to the new IASLC/ATS/ERS classification by accessing hematoxylin–eosin-stained slides. The corresponding Kaplan–Meier survival analysis by the log-rank statistic, multivariate Cox proportional hazards modeling, and c-index calculation were conducted using the programming language R (Version 2.15.1) with the “risksetROC” package. Results The multivariate analysis demonstrated that the risk factor of the ten-gene expression signature can significantly improve the discriminatory value of TNM staging in survival prediction, but not the value of the IASLC/ATS/ERS classification. Further analysis suggested that only BRCA1 and ERBB3 in the signature were independent risk factors after adjusting for the IASLC/ATS/ERS classification by Cox regression. A new algorithm of the two-gene expression signature containing BRCA1 and ERBB3 was generated. Adding the two-gene signature into the IASLC/ATS/ERS classification model further improved the discriminatory c-statistic from 0.728 to 0.756. Conclusion The two-gene signature composed of BRCA1 and ERBB3 was an independent

  17. Challenges of incorporating gene expression data to predict HCC prognosis in the age of systems biology

    PubMed Central

    Du, Yan; Cao, Guang-Wen

    2012-01-01

    Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The recurrence of HCC after curative treatments is currently a major hurdle. Identification of subsets of patients with distinct prognosis provides an opportunity to tailor therapeutic approaches as well as to select the patients with specific sub-phenotypes for targeted therapy. Thus, the development of gene expression profiles to improve the prediction of HCC prognosis is important for HCC management. Although several gene signatures have been evaluated for the prediction of HCC prognosis, there is no consensus on the predictive power of these signatures. Using systematic approaches to evaluate these signatures and combine them with clinicopathologic information may provide more accurate prediction of HCC prognosis. Recently, Villanueva et al[13] developed a composite prognostic model incorporating gene expression patterns in both tumor and adjacent tissues to predict HCC recurrence. In this commentary, we summarize the current progress in using gene signatures to predict HCC prognosis, and discuss the importance, existing issues and future research directions in this field. PMID:22912544

  18. Expression signature distinguishing two tumour transcriptome classes associated with progression-free survival among rare histological types of epithelial ovarian cancer

    PubMed Central

    Wang, Chen; Winterhoff, Boris J; Kalli, Kimberly R; Block, Matthew S; Armasu, Sebastian M; Larson, Melissa C; Chen, Hsiao-Wang; Keeney, Gary L; Hartmann, Lynn C; Shridhar, Viji; Konecny, Gottfried E; Goode, Ellen L; Fridley, Brooke L

    2016-01-01

    Background: The mechanisms of recurrence have been under-studied in rare histologies of invasive epithelial ovarian cancer (EOC) (endometrioid, clear cell, mucinous, and low-grade serous). We hypothesised the existence of an expression signature predictive of outcome in the rarer histologies. Methods: In split discovery and validation analysis of 131 Mayo Clinic EOC cases, we used clustering to determine clinically relevant transcriptome classes using microarray gene expression measurements. The signature was validated in 967 EOC tumours (91 rare histological subtypes) with recurrence information. Results: We found two validated transcriptome classes associated with progression-free survival (PFS) in the Mayo Clinic EOC cases (P=8.24 × 10−3). This signature was further validated in the public expression data sets involving the rare EOC histologies, where these two classes were also predictive of PFS (P=1.43 × 10−3). In contrast, the signatures were not predictive of PFS in the high-grade serous EOC cases. Moreover, genes upregulated in Class-1 (with better outcome) were showed enrichment in steroid hormone biosynthesis (false discovery rate, FDR=0.005%) and WNT signalling pathway (FDR=1.46%); genes upregulated in Class-2 were enriched in cell cycle (FDR=0.86%) and toll-like receptor pathways (FDR=2.37%). Conclusions: These findings provide important biological insights into the rarer EOC histologies that may aid in the development of targeted treatment options for the rarer histologies. PMID:27253175

  19. Pathway-based gene signatures predicting clinical outcome of lung adenocarcinoma.

    PubMed

    Chang, Ya-Hsuan; Chen, Chung-Ming; Chen, Hsuan-Yu; Yang, Pan-Chyr

    2015-01-01

    Lung adenocarcinoma is often diagnosed at an advanced stage with poor prognosis. Patients with different clinical outcomes may have similar clinico-pathological characteristics. The results of previous studies for biomarkers for lung adenocarcinoma have generally been inconsistent and limited in clinical application. In this study, we used inverse-variance weighting to combine the hazard ratios for the four datasets and performed pathway analysis to identify prognosis-associated gene signatures. A total of 2,418 genes were found to be significantly associated with overall survival. Of these, a 21-gene signature in the HMGB1/RAGE signalling pathway and a 31-gene signature in the clathrin-coated vesicle cycle pathway were significantly associated with prognosis of lung adenocarcinoma across all four datasets (all p-values < 0.05, log-rank test). We combined the scores for the three pathways to derive a combined pathway-based risk (CPBR) score. Three pathway-based signatures and CPBR score also had more predictive power than single genes. Finally, the CPBR score was validated in two independent cohorts (GSE14814 and GSE13213 in the GEO database) and had significant adjusted hazard ratios 2.72 (p-value < 0.0001) and 1.71 (p-value < 0.0001), respectively. These results could provide a more complete picture of the lung cancer pathogenesis. PMID:26042604

  20. Pathway-based gene signatures predicting clinical outcome of lung adenocarcinoma

    PubMed Central

    Chang, Ya-Hsuan; Chen, Chung-Ming; Chen, Hsuan-Yu; Yang, Pan-Chyr

    2015-01-01

    Lung adenocarcinoma is often diagnosed at an advanced stage with poor prognosis. Patients with different clinical outcomes may have similar clinico-pathological characteristics. The results of previous studies for biomarkers for lung adenocarcinoma have generally been inconsistent and limited in clinical application. In this study, we used inverse-variance weighting to combine the hazard ratios for the four datasets and performed pathway analysis to identify prognosis-associated gene signatures. A total of 2,418 genes were found to be significantly associated with overall survival. Of these, a 21-gene signature in the HMGB1/RAGE signalling pathway and a 31-gene signature in the clathrin-coated vesicle cycle pathway were significantly associated with prognosis of lung adenocarcinoma across all four datasets (all p-values < 0.05, log-rank test). We combined the scores for the three pathways to derive a combined pathway-based risk (CPBR) score. Three pathway-based signatures and CPBR score also had more predictive power than single genes. Finally, the CPBR score was validated in two independent cohorts (GSE14814 and GSE13213 in the GEO database) and had significant adjusted hazard ratios 2.72 (p-value < 0.0001) and 1.71 (p-value < 0.0001), respectively. These results could provide a more complete picture of the lung cancer pathogenesis. PMID:26042604

  1. Assessing the Biological Significance of Gene Expression Signatures and Co-Expression Modules by Studying Their Network Properties

    PubMed Central

    Minguez, Pablo; Dopazo, Joaquin

    2011-01-01

    Microarray experiments have been extensively used to define signatures, which are sets of genes that can be considered markers of experimental conditions (typically diseases). Paradoxically, in spite of the apparent functional role that might be attributed to such gene sets, signatures do not seem to be reproducible across experiments. Given the close relationship between function and protein interaction, network properties can be used to study to what extent signatures are composed of genes whose resulting proteins show a considerable level of interaction (and consequently a putative common functional role). We have analysed 618 signatures and 507 modules of co-expression in cancer looking for significant values of four main protein-protein interaction (PPI) network parameters: connection degree, cluster coefficient, betweenness and number of components. A total of 3904 gene ontology (GO) modules, 146 KEGG pathways, and 263 Biocarta pathways have been used as functional modules of reference. Co-expression modules found in microarray experiments display a high level of connectivity, similar to the one shown by conventional modules based on functional definitions (GO, KEGG and Biocarta). A general observation for all the classes studied is that the networks formed by the modules improve their topological parameters when an external protein is allowed to be introduced within the paths (up to the 70% of GO modules show network parameters beyond the random expectation). This fact suggests that functional definitions are incomplete and some genes might still be missing. Conversely, signatures are clearly not capturing the altered functions in the corresponding studies. This is probably because the way in which the genes have been selected in the signatures is too conservative. These results suggest that gene selection methods which take into account relationships among genes should be superior to methods that assume independence among genes outside their functional

  2. Validation Study: Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro

    PubMed Central

    Moeckel, Sylvia; Vollmann-Zwerenz, Arabel; Proescholdt, Martin; Brawanski, Alexander; Riemenschneider, Markus J.; Bogdahn, Ulrich; Bosserhoff, Anja-Katrin; Spang, Rainer; Hau, Peter

    2016-01-01

    Background In a previous publication we introduced a novel approach to identify genes that hold predictive information about treatment outcome. A linear regression model was fitted by using the least angle regression algorithm (LARS) with the expression profiles of a construction set of 18 glioma progenitor cells enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed predicting therapy-induced impairment of proliferation in vitro. Prediction performance was validated in leave one out cross validation. Methods In this study, we used an additional validation set of 18 serum-free short-term treated in vitro cell cultures to test the predictive properties of the signature in an independent cohort. We assessed proliferation rates together with transcriptome-wide expression profiles after Sunitinib treatment of each individual cell culture, following the methods of the previous publication. Results We confirmed treatment-induced expression changes in our validation set, but our signature failed to predict proliferation inhibition. Neither re-calculation of the combined dataset with all 36 BTIC cultures nor separation of samples into TCGA subclasses did generate a proliferation prediction. Conclusion Although the gene signature published from our construction set exhibited good prediction accuracy in cross validation, we were not able to validate the signature in an independent validation data set. Reasons could be regression to the mean, the moderate numbers of samples, or too low differences in the response to proliferation inhibition in the validation set. At this stage and based on the presented results, we conclude that the signature does not warrant further developmental steps towards clinical application. PMID:26978262

  3. Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants.

    PubMed

    Leone, Angelique; Nie, Alex; Brandon Parker, J; Sawant, Sharmilee; Piechta, Leigh-Anne; Kelley, Michael F; Mark Kao, L; Jim Proctor, S; Verheyen, Geert; Johnson, Mark D; Lord, Peter G; McMillian, Michael K

    2014-03-15

    Previously we reported a gene expression signature in rat liver for detecting a specific type of oxidative stress (OS) related to reactive metabolites (RM). High doses of the drugs disulfiram, ethinyl estradiol and nimesulide were used with another dozen paradigm OS/RM compounds, and three other drugs flutamide, phenacetin and sulindac were identified by this signature. In a second study, antiepileptic drugs were compared for covalent binding and their effects on OS/RM; felbamate, carbamazepine, and phenobarbital produced robust OS/RM gene expression. In the present study, liver RNA samples from drug-treated rats from more recent experiments were examined for statistical fit to the OS/RM signature. Of all 97 drugs examined, in addition to the nine drugs noted above, 19 more were identified as OS/RM-producing compounds-chlorpromazine, clozapine, cyproterone acetate, dantrolene, dipyridamole, glibenclamide, isoniazid, ketoconazole, methapyrilene, naltrexone, nifedipine, sulfamethoxazole, tamoxifen, coumarin, ritonavir, amitriptyline, valproic acid, enalapril, and chloramphenicol. Importantly, all of the OS/RM drugs listed above have been linked to idiosyncratic hepatotoxicity, excepting chloramphenicol, which does not have a package label for hepatotoxicity, but does have a black box warning for idiosyncratic bone marrow suppression. Most of these drugs are not acutely toxic in the rat. The OS/RM signature should be useful to avoid idiosyncratic hepatotoxicity of drug candidates. PMID:24486436

  4. Early Transcriptome Signatures from Immunized Mouse Dendritic Cells Predict Late Vaccine-Induced T-Cell Responses

    PubMed Central

    Dérian, Nicolas; Bellier, Bertrand; Pham, Hang Phuong; Tsitoura, Eliza; Kazazi, Dorothea; Huret, Christophe; Mavromara, Penelope; Klatzmann, David; Six, Adrien

    2016-01-01

    Systems biology offers promising approaches for identifying response-specific signatures to vaccination and assessing their predictive value. Here, we designed a modelling strategy aiming to predict the quality of late T-cell responses after vaccination from early transcriptome analysis of dendritic cells. Using standardized staining with tetramer, we first quantified antigen-specific T-cell expansion 5 to 10 days after vaccination with one of a set of 41 different vaccine vectors all expressing the same antigen. Hierarchical clustering of the responses defined sets of high and low T cell response inducers. We then compared these responses with the transcriptome of splenic dendritic cells obtained 6 hours after vaccination with the same vectors and produced a random forest model capable of predicting the quality of the later antigen-specific T-cell expansion. The model also successfully predicted vector classification as low or strong T-cell response inducers of a novel set of vaccine vectors, based on the early transcriptome results obtained from spleen dendritic cells, whole spleen and even peripheral blood mononuclear cells. Finally, our model developed with mouse datasets also accurately predicted vaccine efficacy from literature-mined human datasets. PMID:26998760

  5. Genome-Wide Prediction and Validation of Intergenic Enhancers in Arabidopsis Using Open Chromatin Signatures[OPEN

    PubMed Central

    Zhu, Bo; Zhang, Wenli; Jiang, Jiming

    2015-01-01

    Enhancers are important regulators of gene expression in eukaryotes. Enhancers function independently of their distance and orientation to the promoters of target genes. Thus, enhancers have been difficult to identify. Only a few enhancers, especially distant intergenic enhancers, have been identified in plants. We developed an enhancer prediction system based exclusively on the DNase I hypersensitive sites (DHSs) in the Arabidopsis thaliana genome. A set of 10,044 DHSs located in intergenic regions, which are away from any gene promoters, were predicted to be putative enhancers. We examined the functions of 14 predicted enhancers using the β-glucuronidase gene reporter. Ten of the 14 (71%) candidates were validated by the reporter assay. We also designed 10 constructs using intergenic sequences that are not associated with DHSs, and none of these constructs showed enhancer activities in reporter assays. In addition, the tissue specificity of the putative enhancers can be precisely predicted based on DNase I hypersensitivity data sets developed from different plant tissues. These results suggest that the open chromatin signature-based enhancer prediction system developed in Arabidopsis may serve as a universal system for enhancer identification in plants. PMID:26373455

  6. Predictors of primary breast cancers responsiveness to preoperative Epirubicin/Cyclophosphamide-based chemotherapy: translation of microarray data into clinically useful predictive signatures

    PubMed Central

    Modlich, Olga; Prisack, Hans-Bernd; Munnes, Marc; Audretsch, Werner; Bojar, Hans

    2005-01-01

    Background Our goal was to identify gene signatures predictive of response to preoperative systemic chemotherapy (PST) with epirubicin/cyclophosphamide (EC) in patients with primary breast cancer. Methods Needle biopsies were obtained pre-treatment from 83 patients with breast cancer and mRNA was profiled on Affymetrix HG-U133A arrays. Response ranged from pathologically confirmed complete remission (pCR), to partial remission (PR), to stable or progressive disease, "No Change" (NC). A primary analysis was performed in breast tissue samples from 56 patients and 5 normal healthy individuals as a training cohort for predictive marker identification. Gene signatures identifying individuals most likely to respond completely to PST-EC were extracted by combining several statistical methods and filtering criteria. In order to optimize prediction of non responding tumors Student's t-test and Wilcoxon test were also applied. An independent cohort of 27 patients was used to challenge the predictive signatures. A k-Nearest neighbor algorithm as well as two independent linear partial least squares determinant analysis (PLS-DA) models based on the training cohort were selected for classification of the test samples. The average specificity of these predictions was greater than 74% for pCR, 100% for PR and greater than 62% for NC. All three classification models could identify all pCR cases. Results The differential expression of 59 genes in the training and the test cohort demonstrated capability to predict response to PST-EC treatment. Based on the training cohort a classifier was constructed following a decision tree. First, a transcriptional profile capable to distinguish cancerous from normal tissue was identified. Then, a "favorable outcome signature" (31 genes) and a "poor outcome signature" (26 genes) were extracted from the cancer specific signatures. This stepwise implementation could predict pCR and distinguish between NC and PR in a subsequent set of patients. Both

  7. Computing Molecular Signatures as Optima of a Bi-Objective Function: Method and Application to Prediction in Oncogenomics

    PubMed Central

    Gardeux, Vincent; Chelouah, Rachid; Wanderley, Maria F Barbosa; Siarry, Patrick; Braga, Antônio P; Reyal, Fabien; Rouzier, Roman; Pusztai, Lajos; Natowicz, René

    2015-01-01

    BACKGROUND Filter feature selection methods compute molecular signatures by selecting subsets of genes in the ranking of a valuation function. The motivations of the valuation functions choice are almost always clearly stated, but those for selecting the genes according to their ranking are hardly ever explicit. METHOD We addressed the computation of molecular signatures by searching the optima of a bi-objective function whose solution space was the set of all possible molecular signatures, ie, the set of subsets of genes. The two objectives were the size of the signature–to be minimized–and the interclass distance induced by the signature–to be maximized–. RESULTS We showed that: 1) the convex combination of the two objectives had exactly n optimal non empty signatures where n was the number of genes, 2) the n optimal signatures were nested, and 3) the optimal signature of size k was the subset of k top ranked genes that contributed the most to the interclass distance. We applied our feature selection method on five public datasets in oncology, and assessed the prediction performances of the optimal signatures as input to the diagonal linear discriminant analysis (DLDA) classifier. They were at the same level or better than the best-reported ones. The predictions were robust, and the signatures were almost always significantly smaller. We studied in more details the performances of our predictive modeling on two breast cancer datasets to predict the response to a preoperative chemotherapy: the performances were higher than the previously reported ones, the signatures were three times smaller (11 versus 30 gene signatures), and the genes member of the signature were known to be involved in the response to chemotherapy. CONCLUSIONS Defining molecular signatures as the optima of a bi-objective function that combined the signature size and the interclass distance was well founded and efficient for prediction in oncogenomics. The complexity of the computation

  8. Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

    PubMed Central

    Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

    2011-01-01

    Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing

  9. Quantitative proteomics reveals the novel co-expression signatures in early brain development for prognosis of glioblastoma multiforme

    PubMed Central

    Yu, Xuexin; Feng, Lin; Liu, Dianming; Zhang, Lianfeng; Wu, Bo; Jiang, Wei; Han, Zujing; Cheng, Shujun

    2016-01-01

    Although several researches have explored the similarity across development and tumorigenesis in cellular behavior and underlying molecular mechanisms, not many have investigated the developmental characteristics at proteomic level and further extended to cancer clinical outcome. In this study, we used iTRAQ to quantify the protein expression changes during macaque rhesus brain development from fetuses at gestation 70 days to after born 5 years. Then, we performed weighted gene co-expression network analysis (WGCNA) on protein expression data of brain development to identify co-expressed modules that highly expressed on distinct development stages, including early stage, middle stage and late stage. Moreover, we used the univariate cox regression model to evaluate the prognostic potentials of these genes in two independent glioblastoma multiforme (GBM) datasets. The results showed that the modules highly expressed on early stage contained more reproducible prognostic genes, including ILF2, CCT7, CCT4, RPL10A, MSN, PRPS1, TFRC and APEX1. These genes were not only associated with clinical outcome, but also tended to influence chemoresponse. These signatures identified from embryonic brain development might contribute to precise prediction of GBM prognosis and identification of novel drug targets in GBM therapies. Thus, the development could become a viable reference model for researching cancers, including identifying novel prognostic markers and promoting new therapies. PMID:26895104

  10. Quantitative proteomics reveals the novel co-expression signatures in early brain development for prognosis of glioblastoma multiforme.

    PubMed

    Yu, Xuexin; Feng, Lin; Liu, Dianming; Zhang, Lianfeng; Wu, Bo; Jiang, Wei; Han, Zujing; Cheng, Shujun

    2016-03-22

    Although several researches have explored the similarity across development and tumorigenesis in cellular behavior and underlying molecular mechanisms, not many have investigated the developmental characteristics at proteomic level and further extended to cancer clinical outcome. In this study, we used iTRAQ to quantify the protein expression changes during macaque rhesus brain development from fetuses at gestation 70 days to after born 5 years. Then, we performed weighted gene co-expression network analysis (WGCNA) on protein expression data of brain development to identify co-expressed modules that highly expressed on distinct development stages, including early stage, middle stage and late stage. Moreover, we used the univariate cox regression model to evaluate the prognostic potentials of these genes in two independent glioblastoma multiforme (GBM) datasets. The results showed that the modules highly expressed on early stage contained more reproducible prognostic genes, including ILF2, CCT7, CCT4, RPL10A, MSN, PRPS1, TFRC and APEX1. These genes were not only associated with clinical outcome, but also tended to influence chemoresponse. These signatures identified from embryonic brain development might contribute to precise prediction of GBM prognosis and identification of novel drug targets in GBM therapies. Thus, the development could become a viable reference model for researching cancers, including identifying novel prognostic markers and promoting new therapies. PMID:26895104

  11. Long noncoding RNA expression profiles in gut tissues constitute molecular signatures that reflect the types of microbes.

    PubMed

    Liang, Lunxi; Ai, Luoyan; Qian, Jin; Fang, Jing-Yuan; Xu, Jie

    2015-01-01

    The gut microbiota is commonly referred to as a hidden organ due to its pivotal effects on host physiology, metabolism, nutrition and immunity. The gut microbes may be shaped by environmental and host genetic factors, and previous studies have focused on the roles of protein-coding genes. Here we show a link between long non-coding RNA (lncRNA) expression and gut microbes. By repurposing exon microarrays and comparing the lncRNA expression profiles between germ-free, conventional and different gnotobiotic mice, we revealed subgroups of lncRNAs that were specifically enriched in each condition. A nearest shrunken centroid methodology was applied to obtain lncRNA-based signatures to identify mice in different conditions. The lncRNA-based prediction model successfully identified different gnotobiotic mice from conventional and germ-free mice, and also discriminated mice harboring transplanted microbes from fecal samples of mice or zebra fishes. To achieve optimal prediction accuracy, fewer lncRNAs were required in the prediction model than protein-coding genes. Taken together, our study demonstrated the effecacy of lncRNA expression profiles in discriminating the types of microbes in the gut. These results also provide a resource of gut microbe-associated lncRNAs for the development of lncRNA biomarkers and the identification of functional lncRNAs in host-microbes interactions. PMID:26123364

  12. A seven-gene signature can predict distant recurrence in patients with triple-negative breast cancers who receive adjuvant chemotherapy following surgery.

    PubMed

    Park, Yeon Hee; Jung, Hae Hyun; Do, In-Gu; Cho, Eun Yoon; Sohn, Insuk; Jung, Sin-Ho; Kil, Won Ho; Kim, Seok Won; Lee, Jeong Eon; Nam, Seok Jin; Ahn, Jin Seok; Im, Young-Hyuck

    2015-04-15

    The aim of this study was to investigate candidate genes that might function as biomarkers to differentiate triple negative breast cancers (TNBCs) among patients, who received adjuvant chemotherapy after curative surgery. We tested whether the results of a NanoString expression assay that targeted 250 prospectively selected genes and used mRNA extracted from formalin-fixed, paraffin-embedded would predict distant recurrence in patients with TNBC. The levels of expression of seven genes were used in a prospectively defined algorithm to allocate each patient to a risk group (low or high). NanoString expression profiles were obtained for 203 tumor tissue blocks. Increased expressions of the five genes (SMAD2, HRAS, KRT6A, TP63 and ETV6) and decreased expression of the two genes (NFKB1 and MDM4) were associated favorable prognosis and were validated with cross-validation. The Kaplan-Meier estimates of the rates of distant recurrence at 10 years in the low- and high-risk groups according to gene expression signature were 62% [95% confidence interval (CI), 48.6-78.9%] and 85% (95% CI, 79.2-90.7%), respectively. When adjusting for TNM stage, the distant recurrence-free survival (DRFS)s in the low-risk group was significantly longer than that in the high-risk group (p <0.001) for early stage (I and II) and advanced stage (III) tumors. In a multivariate Cox regression model, the gene expression signature provided significant predictive power jointly with the TNM staging system. A seven-gene signature could be used as a prognostic model to predict DRFS in patients with TNBC who received curative surgery followed by adjuvant chemotherapy. PMID:25537444

  13. Prediction of buried mine-like target radar signatures using wideband electromagnetic modeling

    SciTech Connect

    Warrick, A.L.; Azevedo, S.G.; Mast, J.E.

    1998-04-06

    Current ground penetrating radars (GPR) have been tested for land mine detection, but they have generally been costly and have poor performance. Comprehensive modeling and experimentation must be done to predict the electromagnetic (EM) signatures of mines to access the effect of clutter on the EM signature of the mine, and to understand the merit and limitations of using radar for various mine detection scenarios. This modeling can provide a basis for advanced radar design and detection techniques leading to superior performance. Lawrence Livermore National Laboratory (LLNL) has developed a radar technology that when combined with comprehensive modeling and detection methodologies could be the basis of an advanced mine detection system. Micropower Impulse Radar (MIR) technology exhibits a combination of properties, including wideband operation, extremely low power consumption, extremely small size and low cost, array configurability, and noise encoded pulse generation. LLNL is in the process of developing an optimal processing algorithm to use with the MIR sensor. In this paper, we use classical numerical models to obtain the signature of mine-like targets and examine the effect of surface roughness on the reconstructed signals. These results are then qualitatively compared to experimental data.

  14. Performance evaluation of merged satellite rainfall products based on spatial and seasonal signatures of hydrologic predictability

    NASA Astrophysics Data System (ADS)

    Gebregiorgis, Abebe; Hossain, Faisal

    2013-10-01

    Despite the inherent estimation uncertainty, remote sensing based rainfall data have enormous value for stream flow simulation. Recent investigations have shown that the historical performance of satellite products in hydrologic prediction can be a useful (diagnostic) proxy for merging products to a more superior performing state for prognostic simulations (i.e., forward in time). Using a hydrologic model set-up over the entire Mississippi River Basin (MRB) and three widely used satellite rainfall products (3B42RT, CMORPH and PERSIANN-CCS), this study explored a merging scheme based on runoff predictability. The spatial and temporal signatures of variability were closely investigated to understand the impact on prediction skill of the merging scheme. The spatial variability (i.e., non-uniform) considered the grid box by grid box variation at the native resolution of individual satellite products, while the temporal variability (i.e., non-stationary) was confined to variation in 3 month-long seasons (winter, spring, summer and fall). When both the spatial and temporal variability in runoff predictability was leveraged, the merging scheme yielded the largest improvement over individual product's performance forward in time. During an independent validation assessment, the stream flow simulated by the merged product was more strongly correlated with observed discharge (than individual products) at 12 gauging stations. In terms of reduction in root mean squared error (RMSE), the merged product showed an improvement of 57% for 3B42RT, 63% for CMORPH and 68% for PERSIANN-CCS products. The investigation clearly showed that any ‘operational’ and hydrologic predictability-based merging scheme for unifying available satellite rainfall products must factor in both the spatial and temporal signatures of runoff predictability to achieve consistently more superior prognostic skill.

  15. pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

    PubMed Central

    2015-01-01

    Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties. PMID:25860834

  16. pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures.

    PubMed

    Pires, Douglas E V; Blundell, Tom L; Ascher, David B

    2015-05-14

    Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties. PMID:25860834

  17. MAOA expression predicts vulnerability for alcohol use.

    PubMed

    Cervera-Juanes, R; Wilhem, L J; Park, B; Lee, R; Locke, J; Helms, C; Gonzales, S; Wand, G; Jones, S R; Grant, K A; Ferguson, B

    2016-04-01

    The role of the monoamines dopamine (DA) and serotonin (5HT) and the monoamine-metabolizing enzyme monoamine oxidase A (MAOA) have been repeatedly implicated in studies of alcohol use and dependence. Genetic investigations of MAOA have yielded conflicting associations between a common polymorphism (MAOA-LPR) and risk for alcohol abuse. The present study provides direct comparison of tissue-specific MAOA expression and the level of alcohol consumption. We analyzed rhesus macaque MAOA (rhMAOA) expression in blood from males before and after 12 months of alcohol self-administration. In addition, nucleus accumbens core (NAc core) and cerebrospinal fluid (CSF) were collected from alcohol access and control (no alcohol access) subjects at the 12-month time point for comparison. The rhMAOA expression level in the blood of alcohol-naive subjects was negatively correlated with subsequent alcohol consumption level. The mRNA expression was independent of rhMAOA-LPR genotype and global promoter methylation. After 12 months of alcohol use, blood rhMAOA expression had decreased in an alcohol dose-dependent manner. Also after 12 months, rhMAOA expression in the NAc core was significantly lower in the heavy drinkers, as compared with control subjects. The CSF measured higher levels of DA and lower DOPAC/DA ratios among the heavy drinkers at the same time point. These results provide novel evidence that blood MAOA expression predicts alcohol consumption and that heavy alcohol use is linked to low MAOA expression in both the blood and NAc core. Together, the findings suggest a mechanistic link between dampened MAOA expression, elevated DA and alcohol abuse. PMID:26148813

  18. MAOA EXPRESSION PREDICTS VULNERABILITY FOR ALCOHOL USE

    PubMed Central

    Cervera-Juanes, Rita; Wilhem, Larry J.; Park, Byung; Lee, Richard; Locke, Jason; Helms, Christa; Gonzales, Steven; Wand, Gary; Jones, Sara R.; Grant, Kathleen A.; Ferguson, Betsy

    2015-01-01

    The role of the monoamines dopamine (DA) and serotonin (5HT) and the monoamine-metabolizing enzyme monoamine oxidase A (MAOA) have been repeatedly implicated in studies of alcohol use and dependence. Genetic investigations of MAOA have yielded conflicting associations between a common polymorphism (MAOA-LPR) and risk for alcohol abuse. The present study provides direct comparison of tissue-specific MAOA expression and the level of alcohol consumption. We analyzed rhesus macaque MAOA (rhMAOA) expression in blood from males before and after 12-months of alcohol self-administration. In addition, nucleus accumbens core (NAc core) and cerebrospinal fluid (CSF) were collected from alcohol-access and control (no alcohol access) subjects at the 12-month time point for comparison. The rhMAOA expression level in the blood of alcohol-naïve subjects was negatively correlated with subsequent alcohol consumption level. The mRNA expression was independent of rhMAOA-LPR genotype and global promoter methylation. After 12 months of alcohol use, blood rhMAOA expression had decreased in an alcohol dose-dependent manner. Also after 12 months, rhMAOA expression in the NAc core was significantly lower in the heavy drinkers, as compared to control subjects. The CSF measured higher levels of DA and lower DOPAC/DA ratios amongst the heavy drinkers at the same time point. These results provide novel evidence that blood MAOA expression predicts alcohol consumption and that heavy alcohol use is linked to low MAOA expression in both the blood and NAc core. Together, the findings suggest a mechanistic link between dampened MAOA expression, elevated DA and alcohol abuse. PMID:26148813

  19. Immune signatures and disorder-specific patterns in a cross-disorder gene expression analysis

    PubMed Central

    de Jong, Simone; Newhouse, Stephen J.; Patel, Hamel; Lee, Sanghyuck; Dempster, David; Curtis, Charles; Paya-Cano, Jose; Murphy, Declan; Wilson, C. Ellie; Horder, Jamie; Mendez, M. Andreina; Asherson, Philip; Rivera, Margarita; Costello, Helen; Maltezos, Stefanos; Whitwell, Susannah; Pitts, Mark; Tye, Charlotte; Ashwood, Karen L.; Bolton, Patrick; Curran, Sarah; McGuffin, Peter; Dobson, Richard; Breen, Gerome

    2016-01-01

    Background Recent studies point to overlap between neuropsychiatric disorders in symptomatology and genetic aetiology. Aims To systematically investigate genomics overlap between childhood and adult attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and major depressive disorder (MDD). Method Analysis of whole-genome blood gene expression and genetic risk scores of 318 individuals. Participants included individuals affected with adult ADHD (n = 93), childhood ADHD (n = 17), MDD (n = 63), ASD (n = 51), childhood dual diagnosis of ADHD–ASD (n = 16) and healthy controls (n = 78). Results Weighted gene co-expression analysis results reveal disorder-specific signatures for childhood ADHD and MDD, and also highlight two immune-related gene co-expression modules correlating inversely with MDD and adult ADHD disease status. We find no significant relationship between polygenic risk scores and gene expression signatures. Conclusions Our results reveal disorder overlap and specificity at the genetic and gene expression level. They suggest new pathways contributing to distinct pathophysiology in psychiatric disorders and shed light on potential shared genomic risk factors. PMID:27151072

  20. Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge

    PubMed Central

    Tarca, Adi L.; Lauria, Mario; Unger, Michael; Bilal, Erhan; Boue, Stephanie; Kumar Dey, Kushal; Hoeng, Julia; Koeppl, Heinz; Martin, Florian; Meyer, Pablo; Nandy, Preetam; Norel, Raquel; Peitsch, Manuel; Rice, Jeremy J.; Romero, Roberto; Stolovitzky, Gustavo; Talikka, Marja; Xiang, Yang; Zechner, Christoph

    2013-01-01

    Motivation: After more than a decade since microarrays were used to predict phenotype of biological samples, real-life applications for disease screening and identification of patients who would best benefit from treatment are still emerging. The interest of the scientific community in identifying best approaches to develop such prediction models was reaffirmed in a competition style international collaboration called IMPROVER Diagnostic Signature Challenge whose results we describe herein. Results: Fifty-four teams used public data to develop prediction models in four disease areas including multiple sclerosis, lung cancer, psoriasis and chronic obstructive pulmonary disease, and made predictions on blinded new data that we generated. Teams were scored using three metrics that captured various aspects of the quality of predictions, and best performers were awarded. This article presents the challenge results and introduces to the community the approaches of the best overall three performers, as well as an R package that implements the approach of the best overall team. The analyses of model performance data submitted in the challenge as well as additional simulations that we have performed revealed that (i) the quality of predictions depends more on the disease endpoint than on the particular approaches used in the challenge; (ii) the most important modeling factor (e.g. data preprocessing, feature selection and classifier type) is problem dependent; and (iii) for optimal results datasets and methods have to be carefully matched. Biomedical factors such as the disease severity and confidence in diagnostic were found to be associated with the misclassification rates across the different teams. Availability: The lung cancer dataset is available from Gene Expression Omnibus (accession, GSE43580). The maPredictDSC R package implementing the approach of the best overall team is available at www.bioconductor.org or http://bioinformaticsprb.med.wayne.edu/. Contact

  1. Evaluating Predictive Pharmacogenetic Signatures of Adverse Events in Colorectal Cancer Patients Treated with Fluoropyrimidines

    PubMed Central

    Skinner, Jane; Keane, Melanie; Chu, Gavin S.; Turner, Richard; Epurescu, Daniel; Barrett, Ann; Willis, Gavin

    2013-01-01

    The potential clinical utility of genetic markers associated with response to fluoropyrimidine treatment in colorectal cancer patients remains controversial despite extensive study. Our aim was to test the clinical validity of both novel and previously identified markers of adverse events in a broad clinical setting. We have conducted an observational pharmacogenetic study of early adverse events in a cohort study of 254 colorectal cancer patients treated with 5-fluorouracil or capecitabine. Sixteen variants of nine key folate (pharmacodynamic) and drug metabolising (pharmacokinetic) enzymes have been analysed as individual markers and/or signatures of markers. We found a significant association between TYMP S471L (rs11479) and early dose modifications and/or severe adverse events (adjusted OR = 2.02 [1.03; 4.00], p = 0.042, adjusted OR = 2.70 [1.23; 5.92], p = 0.01 respectively). There was also a significant association between these phenotypes and a signature of DPYD mutations (Adjusted OR = 3.96 [1.17; 13.33], p = 0.03, adjusted OR = 6.76 [1.99; 22.96], p = 0.002 respectively). We did not identify any significant associations between the individual candidate pharmacodynamic markers and toxicity. If a predictive test for early adverse events analysed the TYMP and DPYD variants as a signature, the sensitivity would be 45.5 %, with a positive predictive value of just 33.9 % and thus poor clinical validity. Most studies to date have been under-powered to consider multiple pharmacokinetic and pharmacodynamic variants simultaneously but this and similar individualised data sets could be pooled in meta-analyses to resolve uncertainties about the potential clinical utility of these markers. PMID:24167597

  2. A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy

    PubMed Central

    Gillet, Jean-Pierre; Andersen, Jesper B.; Madigan, James P.; Varma, Sudhir; Bagni, Rachel K.; Powell, Katie; Burgan, William E.; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V.; Thorgeirsson, Snorri S.

    2016-01-01

    Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. PMID:26668215

  3. A Gene Expression Signature Associated with Overall Survival in Patients with Hepatocellular Carcinoma Suggests a New Treatment Strategy.

    PubMed

    Gillet, Jean-Pierre; Andersen, Jesper B; Madigan, James P; Varma, Sudhir; Bagni, Rachel K; Powell, Katie; Burgan, William E; Wu, Chung-Pu; Calcagno, Anna Maria; Ambudkar, Suresh V; Thorgeirsson, Snorri S; Gottesman, Michael M

    2016-02-01

    Despite improvements in the management of liver cancer, the survival rate for patients with hepatocellular carcinoma (HCC) remains dismal. The survival benefit of systemic chemotherapy for the treatment of liver cancer is only marginal. Although the reasons for treatment failure are multifactorial, intrinsic resistance to chemotherapy plays a primary role. Here, we analyzed the expression of 377 multidrug resistance (MDR)-associated genes in two independent cohorts of patients with advanced HCC, with the aim of finding ways to improve survival in this poor-prognosis cancer. Taqman-based quantitative polymerase chain reaction revealed a 45-gene signature that predicts overall survival (OS) in patients with HCC. Using the Connectivity Map Tool, we were able to identify drugs that converted the gene expression profiles of HCC cell lines from ones matching patients with poor OS to profiles associated with good OS. We found three compounds that convert the gene expression profiles of three HCC cell lines to gene expression profiles associated with good OS. These compounds increase histone acetylation, which correlates with the synergistic sensitization of those MDR tumor cells to conventional chemotherapeutic agents, including cisplatin, sorafenib, and 5-fluorouracil. Our results indicate that it is possible to modulate gene expression profiles in HCC cell lines to those associated with better outcome. This approach also increases sensitization of HCC cells toward conventional chemotherapeutic agents. This work suggests new treatment strategies for a disease for which few therapeutic options exist. PMID:26668215

  4. Signature gene expression reveals novel clues to the molecular mechanisms of dimorphic transition in Penicillium marneffei.

    PubMed

    Yang, Ence; Chow, Wang-Ngai; Wang, Gang; Woo, Patrick C Y; Lau, Susanna K P; Yuen, Kwok-Yung; Lin, Xiaorong; Cai, James J

    2014-10-01

    Systemic dimorphic fungi cause more than one million new infections each year, ranking them among the significant public health challenges currently encountered. Penicillium marneffei is a systemic dimorphic fungus endemic to Southeast Asia. The temperature-dependent dimorphic phase transition between mycelium and yeast is considered crucial for the pathogenicity and transmission of P. marneffei, but the underlying mechanisms are still poorly understood. Here, we re-sequenced P. marneffei strain PM1 using multiple sequencing platforms and assembled the genome using hybrid genome assembly. We determined gene expression levels using RNA sequencing at the mycelial and yeast phases of P. marneffei, as well as during phase transition. We classified 2,718 genes with variable expression across conditions into 14 distinct groups, each marked by a signature expression pattern implicated at a certain stage in the dimorphic life cycle. Genes with the same expression patterns tend to be clustered together on the genome, suggesting orchestrated regulations of the transcriptional activities of neighboring genes. Using qRT-PCR, we validated expression levels of all genes in one of clusters highly expressed during the yeast-to-mycelium transition. These included madsA, a gene encoding MADS-box transcription factor whose gene family is exclusively expanded in P. marneffei. Over-expression of madsA drove P. marneffei to undergo mycelial growth at 37°C, a condition that restricts the wild-type in the yeast phase. Furthermore, analyses of signature expression patterns suggested diverse roles of secreted proteins at different developmental stages and the potential importance of non-coding RNAs in mycelium-to-yeast transition. We also showed that RNA structural transition in response to temperature changes may be related to the control of thermal dimorphism. Together, our findings have revealed multiple molecular mechanisms that may underlie the dimorphic transition in P. marneffei

  5. Graph-based identification of cancer signaling pathways from published gene expression signatures using PubLiME.

    PubMed

    Finocchiaro, Giacomo; Mancuso, Francesco Mattia; Cittaro, Davide; Muller, Heiko

    2007-01-01

    Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are identified. Significantly co-occurring genes are linked by an edge in an undirected graph. Edge-betweenness and k-clique clustering combined with graph modularity as a quality measure are used to identify communities in the resulting graph. The identified communities consist of cell cycle, apoptosis, phosphorylation cascade, extra cellular matrix, interferon and immune response regulators as well as communities of unknown function. The genes constituting different communities are characterized by common genomic features and strongly enriched cis-regulatory modules in their upstream regulatory regions that are consistent with pathway assignment of those genes. PMID:17389643

  6. A Core MYC Gene Expression Signature Is Prominent in Basal-Like Breast Cancer but Only Partially Overlaps the Core Serum Response

    PubMed Central

    Chandriani, Sanjay; Frengen, Eirik; Cowling, Victoria H.; Pendergrass, Sarah A.; Perou, Charles M.; Whitfield, Michael L.; Cole, Michael D.

    2009-01-01

    Background The MYC oncogene contributes to induction and growth of many cancers but the full spectrum of the MYC transcriptional response remains unclear. Methodology/Principal Findings Using microarrays, we conducted a detailed kinetic study of genes that respond to MYCN or MYCNΔMBII induction in primary human fibroblasts. In parallel, we determined the response to steady state overexpression of MYCN and MYCNΔMBII in the same cell type. An overlapping set of 398 genes from the two protocols was designated a ‘Core MYC Signature’ and used for further analysis. Comparison of the Core MYC Signature to a published study of the genes induced by serum stimulation revealed that only 7.4% of the Core MYC Signature genes are in the Core Serum Response and display similar expression changes to both MYC and serum. Furthermore, more than 50% of the Core MYC Signature genes were not influenced by serum stimulation. In contrast, comparison to a panel of breast cancers revealed a strong concordance in gene expression between the Core MYC Signature and the basal-like breast tumor subtype, which is a subtype with poor prognosis. This concordance was supported by the higher average level of MYC expression in the same tumor samples. Conclusions/Significance The Core MYC Signature has clinical relevance as this profile can be used to deduce an underlying genetic program that is likely to contribute to a clinical phenotype. Therefore, the presence of the Core MYC Signature may predict clinical responsiveness to therapeutics that are designed to disrupt MYC-mediated phenotypes. PMID:19690609

  7. Protein signatures as potential surrogate biomarkers for stratification and prediction of treatment response in chronic myeloid leukemia patients

    PubMed Central

    Alaiya, Ayodele A.; Aljurf, Mahmoud; Shinwari, Zakia; Almohareb, Fahad; Malhan, Hafiz; Alzahrani, Hazzaa; Owaidah, Tarek; Fox, Jonathan; Alsharif, Fahad; Mohamed, Said Y.; Rasheed, Walid; Aldawsari, Ghuzayel; Hanbali, Amr; Ahmed, Syed Osman; Chaudhri, Naeem

    2016-01-01

    There is unmet need for prediction of treatment response for chronic myeloid leukemia (CML) patients. The present study aims to identify disease-specific/disease-associated protein biomarkers detectable in bone marrow and peripheral blood for objective prediction of individual’s best treatment options and prognostic monitoring of CML patients. Bone marrow plasma (BMP) and peripheral blood plasma (PBP) samples from newly-diagnosed chronic-phase CML patients were subjected to expression-proteomics using quantitative two-dimensional gel electrophoresis (2-DE) and label-free liquid chromatography tandem mass spectrometry (LC-MS/MS). Analysis of 2-DE protein fingerprints preceding therapy commencement accurately predicts 13 individuals that achieved major molecular response (MMR) at 6 months from 12 subjects without MMR (No-MMR). Results were independently validated using LC-MS/MS analysis of BMP and PBP from patients that have more than 24 months followed-up. One hundred and sixty-four and 138 proteins with significant differential expression profiles were identified from PBP and BMP, respectively and only 54 proteins overlap between the two datasets. The protein panels also discriminates accurately patients that stay on imatinib treatment from patients ultimately needing alternative treatment. Among the identified proteins are TYRO3, a member of TAM family of receptor tyrosine kinases (RTKs), the S100A8, and MYC and all of which have been implicated in CML. Our findings indicate analyses of a panel of protein signatures is capable of objective prediction of molecular response and therapy choice for CML patients at diagnosis as ‘personalized-medicine-model’. PMID:27573699

  8. Protein signatures as potential surrogate biomarkers for stratification and prediction of treatment response in chronic myeloid leukemia patients.

    PubMed

    Alaiya, Ayodele A; Aljurf, Mahmoud; Shinwari, Zakia; Almohareb, Fahad; Malhan, Hafiz; Alzahrani, Hazzaa; Owaidah, Tarek; Fox, Jonathan; Alsharif, Fahad; Mohamed, Said Y; Rasheed, Walid; Aldawsari, Ghuzayel; Hanbali, Amr; Ahmed, Syed Osman; Chaudhri, Naeem

    2016-09-01

    There is unmet need for prediction of treatment response for chronic myeloid leukemia (CML) patients. The present study aims to identify disease-specific/disease-associated protein biomarkers detectable in bone marrow and peripheral blood for objective prediction of individual's best treatment options and prognostic monitoring of CML patients. Bone marrow plasma (BMP) and peripheral blood plasma (PBP) samples from newly-diagnosed chronic-phase CML patients were subjected to expression-proteomics using quantitative two-dimensional gel electrophoresis (2-DE) and label-free liquid chromatography tandem mass spectrometry (LC-MS/MS). Analysis of 2-DE protein fingerprints preceding therapy commencement accurately predicts 13 individuals that achieved major molecular response (MMR) at 6 months from 12 subjects without MMR (No-MMR). Results were independently validated using LC-MS/MS analysis of BMP and PBP from patients that have more than 24 months followed-up. One hundred and sixty-four and 138 proteins with significant differential expression profiles were identified from PBP and BMP, respectively and only 54 proteins overlap between the two datasets. The protein panels also discriminates accurately patients that stay on imatinib treatment from patients ultimately needing alternative treatment. Among the identified proteins are TYRO3, a member of TAM family of receptor tyrosine kinases (RTKs), the S100A8, and MYC and all of which have been implicated in CML. Our findings indicate analyses of a panel of protein signatures is capable of objective prediction of molecular response and therapy choice for CML patients at diagnosis as 'personalized-medicine-model'. PMID:27573699

  9. Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

    PubMed

    Tuller, T; Atar, S; Ruppin, E; Gurevich, M; Achiron, A

    2013-03-01

    different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases. PMID:23190644

  10. Gene expression patterns predict exposure to PCBs in developing Xenopus laevis tadpoles.

    PubMed

    Jelaso, Anna M; Lehigh-Shirey, Elisabeth; Means, Jay; Ide, Charles F

    2003-01-01

    Polychlorinated biphenyls (PCBs) are ubiquitous environmental contaminants that pose global ecological and human health problems. Although it is well established that PCBs are associated with a variety of adverse health effects in wildlife and in humans, it is often difficult to determine direct cause-and-effect relationships between exposure and specific health outcomes. In this study, gene expression signatures were used to relate exposure to PCBs with altered physiological responses and/or specific health effects. Real-time PCR was used to measure gene expression levels for 10 genes in Xenopus laevis tadpoles (18 days postfertilization, PF) after acute exposure (2 days) to the PCB mixture Aroclor 1254. Specific gene expression signatures correlated with exposure and were predictive of adverse health effects. Exposure to low levels of Aroclor 1254 (5-50 ppb) significantly increased expression of six genes, independent of any health effects; exposure to midlevel concentrations (300-400 ppb) significantly decreased expression levels of two genes, NGF and beta-actin, prior to the onset of observable health effects; exposure to higher doses (500-700 ppb) significantly decreased NGF and beta-actin expression concomitant with the appearance of gross morphological abnormalities, behavioral deficits, and a statistically significant decrease in survival. This study expands upon our previous work that demonstrated an age-dependent susceptibility to Aroclor 1254 in Xenopus laevis tadpoles and that defined specific gene expression signatures as useful bioindicators of exposure and as predictors of overt or impending health effects. PMID:12874807

  11. MUC1-associated proliferation signature predicts outcomes in lung adenocarcinoma patients

    PubMed Central

    2010-01-01

    Background MUC1 protein is highly expressed in lung cancer. The cytoplasmic domain of MUC1 (MUC1-CD) induces tumorigenesis and resistance to DNA-damaging agents. We characterized MUC1-CD-induced transcriptional changes and examined their significance in lung cancer patients. Methods Using DNA microarrays, we identified 254 genes that were differentially expressed in cell lines transformed by MUC1-CD compared to control cell lines. We then examined expression of these genes in 441 lung adenocarcinomas from a publicly available database. We employed statistical analyses independent of clinical outcomes, including hierarchical clustering, Student's t-tests and receiver operating characteristic (ROC) analysis, to select a seven-gene MUC1-associated proliferation signature (MAPS). We demonstrated the prognostic value of MAPS in this database using Kaplan-Meier survival analysis, log-rank tests and Cox models. The MAPS was further validated for prognostic significance in 84 lung adenocarcinoma patients from an independent database. Results MAPS genes were found to be associated with proliferation and cell cycle regulation and included CCNB1, CDC2, CDC20, CDKN3, MAD2L1, PRC1 and RRM2. MAPS expressors (MAPS+) had inferior survival compared to non-expressors (MAPS-). In the initial data set, 5-year survival was 65% (MAPS-) vs. 45% (MAPS+, p < 0.0001). Similarly, in the validation data set, 5-year survival was 57% (MAPS-) vs. 28% (MAPS+, p = 0.005). Conclusions The MAPS signature, comprised of MUC1-CD-dependent genes involved in the control of cell cycle and proliferation, is associated with poor outcomes in patients with adenocarcinoma of the lung. These data provide potential new prognostic biomarkers and treatment targets for lung adenocarcinoma. PMID:20459602

  12. A Predictive Metabolic Signature for the Transition From Gestational Diabetes Mellitus to Type 2 Diabetes.

    PubMed

    Allalou, Amina; Nalla, Amarnadh; Prentice, Kacey J; Liu, Ying; Zhang, Ming; Dai, Feihan F; Ning, Xian; Osborne, Lucy R; Cox, Brian J; Gunderson, Erica P; Wheeler, Michael B

    2016-09-01

    Gestational diabetes mellitus (GDM) affects 3-14% of pregnancies, with 20-50% of these women progressing to type 2 diabetes (T2D) within 5 years. This study sought to develop a metabolomics signature to predict the transition from GDM to T2D. A prospective cohort of 1,035 women with GDM pregnancy were enrolled at 6-9 weeks postpartum (baseline) and were screened for T2D annually for 2 years. Of 1,010 women without T2D at baseline, 113 progressed to T2D within 2 years. T2D developed in another 17 women between 2 and 4 years. A nested case-control design used 122 incident case patients matched to non-case patients by age, prepregnancy BMI, and race/ethnicity. We conducted metabolomics with baseline fasting plasma and identified 21 metabolites that significantly differed by incident T2D status. Machine learning optimization resulted in a decision tree modeling that predicted T2D incidence with a discriminative power of 83.0% in the training set and 76.9% in an independent testing set, which is far superior to measuring fasting plasma glucose levels alone. The American Diabetes Association recommends T2D screening in the early postpartum period via oral glucose tolerance testing after GDM, which is a time-consuming and inconvenient procedure. Our metabolomics signature predicted T2D incidence from a single fasting blood sample. This study represents the first metabolomics study of the transition from GDM to T2D validated in an independent testing set, facilitating early interventions. PMID:27338739

  13. Semantic Signature: Comparative Interpretation of Gene Expression on a Semantic Space

    PubMed Central

    2016-01-01

    Background. Interpretation of microarray data remains challenging because biological meaning should be extracted from enormous numeric matrices and be presented explicitly. Moreover, huge public repositories of microarray dataset are ready to be exploited for comparative analysis. This study aimed to provide a platform where essential implication of a microarray experiment could be visually expressed and various microarray datasets could be intuitively compared. Results. On the semantic space, gene sets from Molecular Signature Database (MSigDB) were plotted as landmarks and their relative distances were calculated by Lin's semantic similarity measure. By formal concept analysis, a microarray dataset was transformed into a concept lattice with gene clusters as objects and Gene Ontology terms as attributes. Concepts of a lattice were located on the semantic space reflecting semantic distance from landmarks and edges between concepts were drawn; consequently, a specific geographic pattern could be observed from a microarray dataset. We termed a distinctive geography shared by microarray datasets of the same category as “semantic signature.” Conclusions. “Semantic space,” a map of biological entities, could serve as a universal platform for comparative microarray analysis. When microarray data were displayed on the semantic space as concept lattices, “semantic signature,” characteristic geography for a microarray experiment, could be discovered. PMID:27242916

  14. Semantic Signature: Comparative Interpretation of Gene Expression on a Semantic Space.

    PubMed

    Kim, Jihun; Kim, Keewon; Kim, Ju Han

    2016-01-01

    Background. Interpretation of microarray data remains challenging because biological meaning should be extracted from enormous numeric matrices and be presented explicitly. Moreover, huge public repositories of microarray dataset are ready to be exploited for comparative analysis. This study aimed to provide a platform where essential implication of a microarray experiment could be visually expressed and various microarray datasets could be intuitively compared. Results. On the semantic space, gene sets from Molecular Signature Database (MSigDB) were plotted as landmarks and their relative distances were calculated by Lin's semantic similarity measure. By formal concept analysis, a microarray dataset was transformed into a concept lattice with gene clusters as objects and Gene Ontology terms as attributes. Concepts of a lattice were located on the semantic space reflecting semantic distance from landmarks and edges between concepts were drawn; consequently, a specific geographic pattern could be observed from a microarray dataset. We termed a distinctive geography shared by microarray datasets of the same category as "semantic signature." Conclusions. "Semantic space," a map of biological entities, could serve as a universal platform for comparative microarray analysis. When microarray data were displayed on the semantic space as concept lattices, "semantic signature," characteristic geography for a microarray experiment, could be discovered. PMID:27242916

  15. An Immune-Inflammation Gene Expression Signature in Prostate Tumors of Smokers.

    PubMed

    Prueitt, Robyn L; Wallace, Tiffany A; Glynn, Sharon A; Yi, Ming; Tang, Wei; Luo, Jun; Dorsey, Tiffany H; Stagliano, Katherine E; Gillespie, John W; Hudson, Robert S; Terunuma, Atsushi; Shoe, Jennifer L; Haines, Diana C; Yfantis, Harris G; Han, Misop; Martin, Damali N; Jordan, Symone V; Borin, James F; Naslund, Michael J; Alexander, Richard B; Stephens, Robert M; Loffredo, Christopher A; Lee, Dong H; Putluri, Nagireddy; Sreekumar, Arun; Hurwitz, Arthur A; Ambs, Stefan

    2016-03-01

    Smokers develop metastatic prostate cancer more frequently than nonsmokers, suggesting that a tobacco-derived factor is driving metastatic progression. To identify smoking-induced alterations in human prostate cancer, we analyzed gene and protein expression patterns in tumors collected from current, past, and never smokers. By this route, we elucidated a distinct pattern of molecular alterations characterized by an immune and inflammation signature in tumors from current smokers that were either attenuated or absent in past and never smokers. Specifically, this signature included elevated immunoglobulin expression by tumor-infiltrating B cells, NF-κB activation, and increased chemokine expression. In an alternate approach to characterize smoking-induced oncogenic alterations, we also explored the effects of nicotine in human prostate cancer cells and prostate cancer-prone TRAMP mice. These investigations showed that nicotine increased glutamine consumption and invasiveness of cancer cells in vitro and accelerated metastatic progression in tumor-bearing TRAMP mice. Overall, our findings suggest that nicotine is sufficient to induce a phenotype resembling the epidemiology of smoking-associated prostate cancer progression, illuminating a novel candidate driver underlying metastatic prostate cancer in current smokers. Cancer Res; 76(5); 1055-65. ©2015 AACR. PMID:26719530

  16. The conformational signature of β-arrestin2 predicts its trafficking and signalling functions.

    PubMed

    Lee, Mi-Hye; Appleton, Kathryn M; Strungs, Erik G; Kwon, Joshua Y; Morinelli, Thomas A; Peterson, Yuri K; Laporte, Stephane A; Luttrell, Louis M

    2016-03-31

    Arrestins are cytosolic proteins that regulate G-protein-coupled receptor (GPCR) desensitization, internalization, trafficking and signalling. Arrestin recruitment uncouples GPCRs from heterotrimeric G proteins, and targets the proteins for internalization via clathrin-coated pits. Arrestins also function as ligand-regulated scaffolds that recruit multiple non-G-protein effectors into GPCR-based 'signalsomes'. Although the dominant function(s) of arrestins vary between receptors, the mechanism whereby different GPCRs specify these divergent functions is unclear. Using a panel of intramolecular fluorescein arsenical hairpin (FlAsH) bioluminescence resonance energy transfer (BRET) reporters to monitor conformational changes in β-arrestin2, here we show that GPCRs impose distinctive arrestin 'conformational signatures' that reflect the stability of the receptor-arrestin complex and role of β-arrestin2 in activating or dampening downstream signalling events. The predictive value of these signatures extends to structurally distinct ligands activating the same GPCR, such that the innate properties of the ligand are reflected as changes in β-arrestin2 conformation. Our findings demonstrate that information about ligand-receptor conformation is encoded within the population average β-arrestin2 conformation, and provide insight into how different GPCRs can use a common effector for different purposes. This approach may have application in the characterization and development of functionally selective GPCR ligands and in identifying factors that dictate arrestin conformation and function. PMID:27007854

  17. MicroRNA Expression Signature Is Altered in the Cardiac Remodeling Induced by High Fat Diets.

    PubMed

    Guedes, Elaine Castilho; França, Gustavo Starvaggi; Lino, Caroline Antunes; Koyama, Fernanda Christtanini; Moreira, Luana do Nascimento; Alexandre, Juliana Gomes; Barreto-Chaves, Maria Luiza M; Galante, Pedro Alexandre Favoretto; Diniz, Gabriela Placoná

    2016-08-01

    Recent studies have revealed the involvement of microRNAs (miRNAs) in the control of cardiac hypertrophy and myocardial function. In addition, several reports have demonstrated that high fat (HF) diet induces cardiac hypertrophy and remodeling. In the current study, we investigated the effect of diets containing different percentages of fat on the cardiac miRNA expression signature. To address this question, male C57Bl/6 mice were fed with a low fat (LF) diet or two HF diets, containing 45 kcal% fat (HF45%) and 60 kcal% fat (HF60%) for 10 and 20 weeks. HF60% diet promoted an increase on body weight, fasting glycemia, insulin, leptin, total cholesterol, triglycerides, and induced glucose intolerance. HF feeding promoted cardiac remodeling, as evidenced by increased cardiomyocyte transverse diameter and interstitial fibrosis. RNA sequencing analysis demonstrated that HF feeding induced distinct miRNA expression patterns in the heart. HF45% diet for 10 and 20 weeks changed the abundance of 64 and 26 miRNAs in the heart, respectively. On the other hand, HF60% diet for 10 and 20 weeks altered the abundance of 27 and 88 miRNAs in the heart, respectively. Bioinformatics analysis indicated that insulin signaling pathway was overrepresented in response to HF diet. An inverse correlation was observed between cardiac levels of GLUT4 and miRNA-29c. Similarly, we found an inverse correlation between expression of GSK3β and the expression of miRNA-21a-3p, miRNA-29c-3p, miRNA-144-3p, and miRNA-195a-3p. In addition, miRNA-1 overexpression prevented cardiomyocyte hypertrophy. Taken together, our results revealed differentially expressed miRNA signatures in the heart in response to different HF diets. J. Cell. Physiol. 231: 1771-1783, 2016. © 2015 Wiley Periodicals, Inc. PMID:26638879

  18. microRNA expression profiling identifies molecular signatures associated with anaplastic large cell lymphoma

    PubMed Central

    Liu, Cuiling; Iqbal, Javeed; Teruya-Feldstein, Julie; Shen, Yulei; Dabrowska, Magdalena Julia; Dybkaer, Karen; Lim, Megan S.; Piva, Roberto; Barreca, Antonella; Pellegrino, Elisa; Spaccarotella, Elisa; Lachel, Cynthia M.; Kucuk, Can; Jiang, Chun-Sun; Hu, Xiaozhou; Bhagavathi, Sharathkumar; Greiner, Timothy C.; Weisenburger, Dennis D.; Aoun, Patricia; Perkins, Sherrie L.; McKeithan, Timothy W.; Inghirami, Giorgio

    2013-01-01

    Anaplastic large-cell lymphomas (ALCLs) encompass at least 2 systemic diseases distinguished by the presence or absence of anaplastic lymphoma kinase (ALK) expression. We performed genome-wide microRNA (miRNA) profiling on 33 ALK-positive (ALK[+]) ALCLs, 25 ALK-negative (ALK[−]) ALCLs, 9 angioimmunoblastic T-cell lymphomas, 11 peripheral T-cell lymphomas not otherwise specified (PTCLNOS), and normal T cells, and demonstrated that ALCLs express many of the miRNAs that are highly expressed in normal T cells with the prominent exception of miR-146a. Unsupervised hierarchical clustering demonstrated distinct clustering of ALCL, PTCL-NOS, and the AITL subtype of PTCL. Cases of ALK(+) ALCL and ALK(–) ALCL were interspersed in unsupervised analysis, suggesting a close relationship at the molecular level. We identified an miRNA signature of 7 miRNAs (5 upregulated: miR-512-3p, miR-886-5p, miR-886-3p, miR-708, miR-135b; 2 downregulated: miR-146a, miR-155) significantly associated with ALK(+) ALCL cases. In addition, we derived an 11-miRNA signature (4 upregulated: miR-210, miR-197, miR-191, miR-512-3p; 7 downregulated: miR-451, miR-146a, miR-22, miR-455-3p, miR-455-5p, miR-143, miR-494) that differentiates ALK(–) ALCL from other PTCLs. Our in vitro studies identified a set of 32 miRNAs associated with ALK expression. Of these, the miR-17∼92 cluster and its paralogues were also highly expressed in ALK(+) ALCL and may represent important downstream effectors of the ALK oncogenic pathway. PMID:23801630

  19. Embryonic stem cell gene expression signatures in the canine mammary tumor: a bioinformatics approach.

    PubMed

    Zamani-Ahmadmahmudi, Mohamad

    2016-08-01

    Canine breast cancer was considered as an ideal model of comparative oncology for the human breast cancer, as there is significant overlap between biological and clinical characteristics of the human and canine breast cancer. We attempt to clarify expression profile of the embryonic stem cell (ES) gene signatures in canine breast cancer. Using microarray datasets (GSE22516 and GSE20718), expression of the three major ES gene signatures (modules or gene-sets), including Myc, ESC-like, and PRC modules, was primarily analyzed through Gene-Set Enrichment Analysis (GSEA) method in tumor and healthy datasets. For confirmation of the primary results, an additional 13 ES gene-sets which were categorized into four groups including ES expressed (ES exp1 and ES exp2), NOS targets (Nanog targets, Oct4 targets, Sox2 targets, NOS targets, and NOS TFs), Polycomb targets (Suz12 targets, Eed targets, H3K27 bound, and PRC2 targets), and Myc targets (Myc targets1, and Myc targets2) were tested in the tumor and healthy datasets. Our results revealed that there is a valuable overlap between canine and human breast cancer ES gene-sets expression profile, where Myc and ESC-like modules were up-regulated and PRC module was down-regulated in metastatic canine mammary gland tumors. Further analysis of the secondary gene-sets indicated overexpression of the ES expressed, NOS targets (Nanog targets, Oct4 targets, Sox2 targets, and NOS targets), and Myc targets and underexpression of the Polycomb targets in metastatic canine breast cancer. PMID:27307036

  20. Gut Microbiota Signatures Predict Host and Microbiota Responses to Dietary Interventions in Obese Individuals

    PubMed Central

    Korpela, Katri; Flint, Harry J.; Johnstone, Alexandra M.; Lappi, Jenni; Poutanen, Kaisa; Dewulf, Evelyne; Delzenne, Nathalie; de Vos, Willem M.; Salonen, Anne

    2014-01-01

    Background Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host. Methodology Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set – test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters. Principal Findings Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC  =  0.77–1; predicted vs. observed correlation  =  0.67–0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health. Conclusion This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of

  1. A DNA Hypomethylation Signature Predicts Antitumor Activity of LSD1 Inhibitors in SCLC.

    PubMed

    Mohammad, Helai P; Smitheman, Kimberly N; Kamat, Chandrashekhar D; Soong, David; Federowicz, Kelly E; Van Aller, Glenn S; Schneck, Jess L; Carson, Jeffrey D; Liu, Yan; Butticello, Michael; Bonnette, William G; Gorman, Shelby A; Degenhardt, Yan; Bai, Yuchen; McCabe, Michael T; Pappalardi, Melissa B; Kasparec, Jiri; Tian, Xinrong; McNulty, Kenneth C; Rouse, Meagan; McDevitt, Patrick; Ho, Thau; Crouthamel, Michelle; Hart, Timothy K; Concha, Nestor O; McHugh, Charles F; Miller, William H; Dhanak, Dashyant; Tummino, Peter J; Carpenter, Christopher L; Johnson, Neil W; Hann, Christine L; Kruger, Ryan G

    2015-07-13

    Epigenetic dysregulation has emerged as an important mechanism in cancer. Alterations in epigenetic machinery have become a major focus for targeted therapies. The current report describes the discovery and biological activity of a cyclopropylamine containing inhibitor of Lysine Demethylase 1 (LSD1), GSK2879552. This small molecule is a potent, selective, orally bioavailable, mechanism-based irreversible inactivator of LSD1. A proliferation screen of cell lines representing a number of tumor types indicated that small cell lung carcinoma (SCLC) is sensitive to LSD1 inhibition. The subset of SCLC lines and primary samples that undergo growth inhibition in response to GSK2879552 exhibit DNA hypomethylation of a signature set of probes, suggesting this may be used as a predictive biomarker of activity. PMID:26175415

  2. Genome-wide analysis of microRNA and mRNA expression signatures in cancer

    PubMed Central

    Li, Ming-hui; Fu, Sheng-bo; Xiao, Hua-sheng

    2015-01-01

    Cancer is an extremely diverse and complex disease that results from various genetic and epigenetic changes such as DNA copy-number variations, mutations, and aberrant mRNA and/or protein expression caused by abnormal transcriptional regulation. The expression profiles of certain microRNAs (miRNAs) and messenger RNAs (mRNAs) are closely related to cancer progression stages. In the past few decades, DNA microarray and next-generation sequencing techniques have been widely applied to identify miRNA and mRNA signatures for cancers on a genome-wide scale and have provided meaningful insights into cancer diagnosis, prognosis and personalized medicine. In this review, we summarize the progress in genome-wide analysis of miRNAs and mRNAs as cancer biomarkers, highlighting their diagnostic and prognostic roles. PMID:26299954

  3. Visualization and analysis for multidimensional gene expressions signature of cigarette smoking

    NASA Astrophysics Data System (ADS)

    Wang, Changbo; Xiao, Zhao; Zhang, Tianlun; Cui, Jin; Pang, Chenming

    2011-11-01

    Biologists often use gene chip to get massive experimental data in the field of bioscience and chemical sciences. Facing a large amount of experimental data, researchers often need to find out a few interesting data or simple regulations. This paper presents a set of methods to visualize and analyze the data for gene expression signatures of people who smoke. We use the latest research data from National Center for Biotechnology Information. Totally, there are more than 400 thousand expressions data. Using these data, we can use parallel coordinates method to visualize the different gene expressions between smokers and nonsmokers and we can distinguish non-smokers, former smokers and current smokers by using the different colors. It can be easy to find out which gene is more important during the lung cancer angiogenesis in the smoking people. In another way, we can use a hierarchical model to visualize the inner relation of different genes. The location of the nodes shows different expression moment and the distance to the root shows the sequence of the expression. We can use the ring layout to represent all the nodes, and connect the different nodes which are related with color lines. Combined with the parallel coordinates method, the visualization result show the important genes and some inner relation obviously, which is useful for examination and prevention of lung cancer.

  4. Gene Expression Signatures in Polyarticular Juvenile Idiopathic Arthritis Demonstrate Disease Heterogeneity and Offer a Molecular Classification of Disease Subsets

    PubMed Central

    Griffin, Thomas A.; Barnes, Michael G.; Ilowite, Norman T.; Olson, Judyann C.; Sherry, David D.; Gottlieb, Beth S.; Aronow, Bruce J.; Pavlidis, Paul; Hinze, Claas; Thornton, Sherry; Thompson, Susan D.; Grom, Alexei A.; Colbert, Robert A.; Glass, David N.

    2009-01-01

    Objective Microarray analysis was used to determine whether children with recent onset polyarticular juvenile idiopathic arthritis (JIA) exhibit biologically or clinically informative gene expression signatures in peripheral blood mononuclear cells (PBMC). Methods Peripheral blood samples were obtained from 59 healthy children and 61 children with polyarticular JIA prior to treatment with second-line medications, such as methotrexate or biological agents. RNA was extracted from Ficoll-isolated mononuclear cells, fluorescently labeled and hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were analyzed using ANOVA at a 5% false discovery rate threshold after Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. Results Initial analysis revealed 873 probe sets for genes that were differentially expressed between polyarticular JIA and controls. Hierarchical clustering of these probe sets distinguished three subgroups within polyarticular JIA. Prototypical subjects within each subgroup were identified and used to define subgroup-specific gene expression signatures. One of these signatures was associated with monocyte markers, another with transforming growth factor β-inducible genes, and a third with immediate-early genes. Correlation of gene expression signatures with clinical and biological features of JIA subgroups suggests relevance to aspects of disease activity and supports the division of polyarticular JIA into distinct subsets. Conclusions PBMC gene expression signatures in recent onset polyarticular JIA reflect discrete disease processes and offer a molecular classification of disease. PMID:19565504

  5. Gene Expression Profiling during Early Acute Febrile Stage of Dengue Infection Can Predict the Disease Outcome

    PubMed Central

    Calzavara-Silva, Carlos E.; Gomes, Ana L. V.; Brito, Carlos A. A.; Cordeiro, Marli T.; Silva, Ana M.; Magalhães, Cecilia; Andrade, Raoni; Gil, Laura H. V. G.; Marques, Ernesto T. A.

    2009-01-01

    Background We report the detailed development of biomarkers to predict the clinical outcome under dengue infection. Transcriptional signatures from purified peripheral blood mononuclear cells were derived from whole-genome gene-expression microarray data, validated by quantitative PCR and tested in independent samples. Methodology/Principal Findings The study was performed on patients of a well-characterized dengue cohort from Recife, Brazil. The samples analyzed were collected prospectively from acute febrile dengue patients who evolved with different degrees of disease severity: classic dengue fever or dengue hemorrhagic fever (DHF) samples were compared with similar samples from other non-dengue febrile illnesses. The DHF samples were collected 2–3 days before the presentation of the plasma leakage symptoms. Differentially-expressed genes were selected by univariate statistical tests as well as multivariate classification techniques. The results showed that at early stages of dengue infection, the genes involved in effector mechanisms of innate immune response presented a weaker activation on patients who later developed hemorrhagic fever, whereas the genes involved in apoptosis were expressed in higher levels. Conclusions/Significance Some of the gene expression signatures displayed estimated accuracy rates of more than 95%, indicating that expression profiling with these signatures may provide a useful means of DHF prognosis at early stages of infection. PMID:19936257

  6. A novel five gene signature derived from stem-like side population cells predicts overall and recurrence-free survival in NSCLC.

    PubMed

    Perumal, Deepak; Singh, Sandeep; Yoder, Sean J; Bloom, Gregory C; Chellappan, Srikumar P

    2012-01-01

    Gene expression profiling has been used to characterize prognosis in various cancers. Earlier studies had shown that side population cells isolated from Non-Small Cell Lung Cancer (NSCLC) cell lines exhibit cancer stem cell properties. In this study we apply a systems biology approach to gene expression profiling data from cancer stem like cells isolated from lung cancer cell lines to identify novel gene signatures that could predict prognosis. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stem like properties. Differentially expressed genes that were over or under-expressed at least two fold commonly in all 4 cell lines were identified. We found 354 were upregulated and 126 were downregulated in SP cells compared to MP cells; of these, 89 up and 62 downregulated genes (average 2 fold changes) were used for Principle Component Analysis (PCA) and MetaCore pathway analysis. The pathway analysis demonstrated representation of 4 up regulated genes (TOP2A, AURKB, BRRN1, CDK1) in chromosome condensation pathway and 1 down regulated gene FUS in chromosomal translocation. Microarray data was validated using qRT-PCR on the 5 selected genes and all showed robust correlation between microarray and qRT-PCR. Further, we analyzed two independent gene expression datasets that included 360 lung adenocarcinoma patients from NCI Director's Challenge Set for overall survival and 63 samples from Sungkyunkwan University (SKKU) for recurrence free survival. Kaplan-Meier and log-rank test analysis predicted poor survival of patients in both data sets. Our results suggest that genes involved in chromosome condensation are likely related with stem-like properties and might predict survival in lung adenocarcinoma. Our findings highlight a gene signature for effective identification of lung adenocarcinoma patients with poor prognosis and designing

  7. An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

    SciTech Connect

    Holmes, Aimee E.; Sego, Landon H.; Webb-Robertson, Bobbie-Jo M.; Kreuzer, Helen W.; Anderson, Richard M.; Unwin, Stephen D.; Weimar, Mark R.; Tardiff, Mark F.; Corley, Courtney D.

    2013-02-01

    We demonstrate an approach for assessing the quality of a signature system designed to predict the culture medium used to grow a microorganism. The system was comprised of four chemical assays designed to identify various ingredients that could be used to produce the culture medium. The analytical measurements resulting from any combination of these four assays can be used in a Bayesian network to predict the probabilities that the microorganism was grown using one of eleven culture media. We evaluated combinations of the signature system by removing one or more of the assays from the Bayes network. We measured and compared the quality of the various Bayes nets in terms of fidelity, cost, risk, and utility, a method we refer to as Signature Quality Metrics

  8. From molecular signatures to predictive biomarkers: modeling disease pathophysiology and drug mechanism of action

    PubMed Central

    Heinzel, Andreas; Perco, Paul; Mayer, Gert; Oberbauer, Rainer; Lukas, Arno; Mayer, Bernd

    2014-01-01

    Omics profiling significantly expanded the molecular landscape describing clinical phenotypes. Association analysis resulted in first diagnostic and prognostic biomarker signatures entering clinical utility. However, utilizing Omics for deepening our understanding of disease pathophysiology, and further including specific interference with drug mechanism of action on a molecular process level still sees limited added value in the clinical setting. We exemplify a computational workflow for expanding from statistics-based association analysis toward deriving molecular pathway and process models for characterizing phenotypes and drug mechanism of action. Interference analysis on the molecular model level allows identification of predictive biomarker candidates for testing drug response. We discuss this strategy on diabetic nephropathy (DN), a complex clinical phenotype triggered by diabetes and presenting with renal as well as cardiovascular endpoints. A molecular pathway map indicates involvement of multiple molecular mechanisms, and selected biomarker candidates reported as associated with disease progression are identified for specific molecular processes. Selective interference of drug mechanism of action and disease-associated processes is identified for drug classes in clinical use, in turn providing precision medicine hypotheses utilizing predictive biomarkers. PMID:25364744

  9. Reprogramming LCLs to iPSCs Results in Recovery of Donor-Specific Gene Expression Signature

    PubMed Central

    Thomas, Samantha M.; Kagan, Courtney; Pavlovic, Bryan J.; Burnett, Jonathan; Patterson, Kristen; Pritchard, Jonathan K.; Gilad, Yoav

    2015-01-01

    Renewable in vitro cell cultures, such as lymphoblastoid cell lines (LCLs), have facilitated studies that contributed to our understanding of genetic influence on human traits. However, the degree to which cell lines faithfully maintain differences in donor-specific phenotypes is still debated. We have previously reported that standard cell line maintenance practice results in a loss of donor-specific gene expression signatures in LCLs. An alternative to the LCL model is the induced pluripotent stem cell (iPSC) system, which carries the potential to model tissue-specific physiology through the use of differentiation protocols. Still, existing LCL banks represent an important source of starting material for iPSC generation, and it is possible that the disruptions in gene regulation associated with long-term LCL maintenance could persist through the reprogramming process. To address this concern, we studied the effect of reprogramming mature LCL cultures from six unrelated donors to iPSCs on the ensuing gene expression patterns within and between individuals. We show that the reprogramming process results in a recovery of donor-specific gene regulatory signatures, increasing the number of genes with a detectable donor effect by an order of magnitude. The proportion of variation in gene expression statistically attributed to donor increases from 6.9% in LCLs to 24.5% in iPSCs (P < 10-15). Since environmental contributions are unlikely to be a source of individual variation in our system of highly passaged cultured cell lines, our observations suggest that the effect of genotype on gene regulation is more pronounced in iPSCs than in LCLs. Our findings indicate that iPSCs can be a powerful model system for studies of phenotypic variation across individuals in general, and the genetic association with variation in gene regulation in particular. We further conclude that LCLs are an appropriate starting material for iPSC generation. PMID:25950834

  10. Gene Expression Profiling Specifies Chemokine, Mitochondrial and Lipid Metabolism Signatures in Leprosy

    PubMed Central

    Guerreiro, Luana Tatiana Albuquerque; Robottom-Ferreira, Anna Beatriz; Ribeiro-Alves, Marcelo; Toledo-Pinto, Thiago Gomes; Rosa Brito, Tiana; Rosa, Patrícia Sammarco; Sandoval, Felipe Galvan; Jardim, Márcia Rodrigues; Antunes, Sérgio Gomes; Shannon, Edward J.; Sarno, Euzenir Nunes; Pessolani, Maria Cristina Vidal; Williams, Diana Lynn; Moraes, Milton Ozório

    2013-01-01

    Herein, we performed microarray experiments in Schwann cells infected with live M. leprae and identified novel differentially expressed genes (DEG) in M. leprae infected cells. Also, we selected candidate genes associated or implicated with leprosy in genetic studies and biological experiments. Forty-seven genes were selected for validation in two independent types of samples by multiplex qPCR. First, an in vitro model using THP-1 cells was infected with live Mycobacterium leprae and M. bovis bacillus Calmette-Guérin (BCG). In a second situation, mRNA obtained from nerve biopsies from patients with leprosy or other peripheral neuropathies was tested. We detected DEGs that discriminate M. bovis BCG from M. leprae infection. Specific signatures of susceptible responses after M. leprae infection when compared to BCG lead to repression of genes, including CCL2, CCL3, IL8 and SOD2. The same 47-gene set was screened in nerve biopsies, which corroborated the down-regulation of CCL2 and CCL3 in leprosy, but also evidenced the down-regulation of genes involved in mitochondrial metabolism, and the up-regulation of genes involved in lipid metabolism and ubiquitination. Finally, a gene expression signature from DEG was identified in patients confirmed of having leprosy. A classification tree was able to ascertain 80% of the cases as leprosy or non-leprous peripheral neuropathy based on the expression of only LDLR and CCL4. A general immune and mitochondrial hypo-responsive state occurs in response to M. leprae infection. Also, the most important genes and pathways have been highlighted providing new tools for early diagnosis and treatment of leprosy. PMID:23798993

  11. MicroRNA GENE EXPRESSION SIGNATURES IN THE DEVELOPING NEURAL TUBE

    PubMed Central

    Mukhopadhyay, Partha; Brock, Guy; Appana, Savitri; Webb, Cynthia; Greene, Robert M.; Pisano, M. Michele

    2011-01-01

    BACKGROUND Neurulation requires precise, spatio-temporal expression of numerous genes and coordinated interaction of signal transduction and gene regulatory networks, disruption of which may contribute to the etiology of neural tube (NT) defects. MicroRNAs are key modulators of cell and tissue differentiation. In order to define potential roles of miRNAs in development of the murine NT, miRNA microarray analysis was conducted to establish expression profiles, and identify miRNA target genes and functional gene networks. METHODS miRNA expression profiles in murine embryonic NTs derived from gestational days 8.5, 9.0 and 9.5 were defined and compared utilizing miRXplore™ microarrays from Miltenyi Biotech GmbH. Gene expression changes were verified by TaqMan™ quantitative Real-Time PCR. clValid R package and the UPGMA (hierarchical) clustering method were utilized for cluster analysis of the microarray data. Functional associations among selected miRNAs were examined via Ingenuity Pathway Analysis. RESULTS miRXplore™ chips enabled examination of 609 murine miRNAs. Expression of approximately 12% of these was detected in murine embryonic NTs. Clustering analysis revealed several developmentally regulated expression clusters among these expressed genes. Target analysis of differentially expressed miRNAs enabled identification of numerous target genes associated with cellular processes essential for normal NT development. Utilization of Ingenuity Pathway Analysis revealed interactive biological networks which connected differentially expressed miRNAs with their target genes, and highlighted functional relationships. CONCLUSIONS The present study defined unique gene expression signatures of a range of miRNAs in the developing NT during the critical period of NT morphogenesis. Analysis of miRNA target genes and gene interaction pathways revealed that specific miRNAs may direct expression of numerous genes encoding proteins which have been shown to be indispensable

  12. 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

  13. The mucosal expression signatures of g-type lysozyme in turbot (Scophthalmus maximus) following bacterial challenge.

    PubMed

    Gao, Chengbin; Fu, Qiang; Zhou, Shun; Song, Lin; Ren, Yichao; Dong, Xiaoyu; Su, Baofeng; Li, Chao

    2016-07-01

    The mucosal surfaces constitute the first line of host defense against infection, and also serve as the dynamic interfaces that simultaneously mediate a diverse array of critical physiological processes, while in constantly contact with a wide range of pathogens. The lysozymes are considered as key components for innate immune response to pathogen infection with their strong antibacterial activities. But their activities in mucosal immune responses were always overlooked, especially for g-type lysozymes, whose expression patterns in mucosal tissues following bacterial challenge are still limited. Towards to this end, here, we characterized the g-type lysozymes, Lyg1 and Lyg2 in turbot, and determined their expression patterns in mucosal barriers following different bacterial infection. The phylogenetic analysis revealed the turbot g-type lysozyme genes showed the closest relationship to Cynoglossus semilaevis. The two lysozyme genes showed different expression patterns following challenge. Lyg2 was significantly up-regulated in mucosal tissues following Vibrio anguillarum and Streptococcus iniae challenge, while Lyg1 showed a general trend of down-regulation. The significant mucosal expression signatures of g-type lysozyme genes indicated their key roles to prevent pathogen attachment and entry in the first line of host defense system. Further functional studies should be carried out to better characterize the availability of utilization of g-type lysozyme to increase the disease resistance in the mucosal surfaces and facilitate the disease resistant breeding selection. PMID:27189917

  14. Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

    PubMed Central

    2016-01-01

    Gene Expression Music Algorithm (GEMusicA) is a method for the transformation of DNA microarray data into melodies that can be used for the characterization of differentially expressed genes. Using this method we compared gene expression profiles from endothelial cells (EC), hematopoietic stem cells, neuronal stem cells, embryonic stem cells (ESC), and mesenchymal stem cells (MSC) and defined a set of genes that can discriminate between the different stem cell types. We analyzed the behavior of public microarray data sets from Ewing sarcoma (“Ewing family tumors,” EFT) cell lines and biopsies in GEMusicA after prefiltering DNA microarray data for the probe sets from the stem cell signature. Our results demonstrate that individual Ewing sarcoma cell lines have a high similarity to ESC or EC. Ewing sarcoma cell lines with inhibited Ewing sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWSR1-FLI1) oncogene retained the similarity to ESC and EC. However, correlation coefficients between GEMusicA-processed expression data between EFT and ESC decreased whereas correlation coefficients between EFT and EC as well as between EFT and MSC increased after knockdown of EWSR1-FLI1. Our data support the concept of EFT being derived from cells with features of embryonic and endothelial cells. PMID:27446218

  15. Airway basal cells of healthy smokers express an embryonic stem cell signature relevant to lung cancer.

    PubMed

    Shaykhiev, Renat; Wang, Rui; Zwick, Rachel K; Hackett, Neil R; Leung, Roland; Moore, Malcolm A S; Sima, Camelia S; Chao, Ion Wa; Downey, Robert J; Strulovici-Barel, Yael; Salit, Jacqueline; Crystal, Ronald G

    2013-09-01

    Activation of the human embryonic stem cell (hESC) signature genes has been observed in various epithelial cancers. In this study, we found that the hESC signature is selectively induced in the airway basal stem/progenitor cell population of healthy smokers (BC-S), with a pattern similar to that activated in all major types of human lung cancer. We further identified a subset of 6 BC-S hESC genes, whose coherent overexpression in lung adenocarcinoma (AdCa) was associated with reduced lung function, poorer differentiation grade, more advanced tumor stage, remarkably shorter survival, and higher frequency of TP53 mutations. BC-S shared with hESC and a considerable subset of lung carcinomas a common TP53 inactivation molecular pattern which strongly correlated with the BC-S hESC gene expression. These data provide transcriptome-based evidence that smoking-induced reprogramming of airway BC toward the hESC-like phenotype might represent a common early molecular event in the development of aggressive lung carcinomas in humans. PMID:23857717

  16. A germline predictive signature of response to platinum chemotherapy in esophageal cancer.

    PubMed

    Rumiato, Enrica; Boldrin, Elisa; Malacrida, Sandro; Battaglia, Giorgio; Bocus, Paolo; Castoro, Carlo; Cagol, Matteo; Chiarion-Sileni, Vanna; Ruol, Alberto; Amadori, Alberto; Saggioro, Daniela

    2016-05-01

    Platinum-based neoadjuvant therapy is the standard treatment for esophageal cancer (EC). At present, no reliable response markers exist, and patient therapeutic outcome is variable and very often unpredictable. The aim of this study was to understand the contribution of host constitutive DNA polymorphisms in discriminating between responder and nonresponder patients. DNA collected from 120 EC patients treated with platinum-based neoadjuvant chemotherapy was analyzed using drug metabolism enzymes and transporters (DMET) array platform that interrogates polymorphisms in 225 genes of drug metabolism and disposition. Four gene variants of DNA repair machinery, 2 in ERCC1 (rs11615; rs3212986), and 2 in XPD (rs1799793; rs13181) were also studied. Association analysis was performed with pTest software and corrected by permutation test. Predictive models of response were created using the receiver-operating characteristics curve approach and adjusted by the bootstrap procedure. Sixteen single nucleotide polymorphisms (SNPs) of the DMET array resulted significantly associated with either good or poor response; no association was found for the 4 variants mapping in DNA repair genes. The predictive power of 5 DMET SNPs mapping in ABCC2, ABCC3, CYP2A6, PPARG, and SLC7A8 genes was greater than that of clinical factors alone (area under the curve [AUC] = 0.74 vs 0.62). Interestingly, their combination with the clinical variables significantly increased the predictivity of the model (AUC = 0.78 vs 0.62, P = 0.0016). In conclusion, we identified a genetic signature of response to platinum-based neoadjuvant chemotherapy in EC patients. Our results also disclose the potential benefit of combining genetic and clinical variables for personalized EC management. PMID:26772957

  17. A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension

    PubMed Central

    Chen, Brian H.; Liu, Chunyu; Joehanes, Roby; Johnson, Andrew D.; Yao, Chen; Ying, Sai-xia; Courchesne, Paul; Milani, Lili; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Reinmaa, Eva; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G.; Hernandez, Dena G.; Bandinelli, Stefania; Singleton, Andrew; Melzer, David; Metspalu, Andres; Carstensen, Maren; Grallert, Harald; Herder, Christian; Meitinger, Thomas; Peters, Annette; Roden, Michael; Waldenberger, Melanie; Dörr, Marcus; Felix, Stephan B.; Zeller, Tanja; Vasan, Ramachandran; O'Donnell, Christopher J.; Munson, Peter J.; Yang, Xia; Prokisch, Holger; Völker, Uwe; van Meurs, Joyce B. J.; Ferrucci, Luigi; Levy, Daniel

    2015-01-01

    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension. PMID:25785607

  18. A meta-analysis of gene expression signatures of blood pressure and hypertension.

    PubMed

    Huan, Tianxiao; Esko, Tõnu; Peters, Marjolein J; Pilling, Luke C; Schramm, Katharina; Schurmann, Claudia; Chen, Brian H; Liu, Chunyu; Joehanes, Roby; Johnson, Andrew D; Yao, Chen; Ying, Sai-Xia; Courchesne, Paul; Milani, Lili; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Reinmaa, Eva; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; Hernandez, Dena G; Bandinelli, Stefania; Singleton, Andrew; Melzer, David; Metspalu, Andres; Carstensen, Maren; Grallert, Harald; Herder, Christian; Meitinger, Thomas; Peters, Annette; Roden, Michael; Waldenberger, Melanie; Dörr, Marcus; Felix, Stephan B; Zeller, Tanja; Vasan, Ramachandran; O'Donnell, Christopher J; Munson, Peter J; Yang, Xia; Prokisch, Holger; Völker, Uwe; van Meurs, Joyce B J; Ferrucci, Luigi; Levy, Daniel

    2015-03-01

    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension. PMID:25785607

  19. Meta-Analysis of Gene Expression Signatures Defining the Epithelial to Mesenchymal Transition during Cancer Progression

    PubMed Central

    Gröger, Christian J.; Grubinger, Markus; Waldhör, Thomas; Vierlinger, Klemens; Mikulits, Wolfgang

    2012-01-01

    The epithelial to mesenchymal transition (EMT) represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES) have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression. PMID:23251436

  20. Bladder Cancer Associated Gene Expression Signatures Identified by Profiling of Exfoliated Urothelia

    PubMed Central

    Rosser, Charles J.; Liu, Li; Sun, Yijun; Villicana, Patrick; McCullers, Molly; Porvasnik, Stacy; Young, Paul R.; Parker, Alexander S.; Goodison, Steve

    2009-01-01

    Bladder cancer is the fifth most commonly diagnosed malignancy in the United States and one of the most prevalent worldwide. It harbors a probability of recurrence of >50%, thus rigorous, long-term surveillance of patients is advocated. Flexible cystoscopy coupled with voided urine cytology (VUC) is the primary diagnostic approach, but cystoscopy is an uncomfortable, invasive procedure and the sensitivity of VUC is poor in all but high-grade tumors. Thus, improvements in non-invasive urinalysis assessment strategies would benefit patients. We applied gene expression microarray analysis to exfoliated urothelia recovered from bladder washes obtained prospectively from 46 patients with subsequently confirmed presence or absence of bladder cancer. Data from microarrays containing 56,000 targets was subjected to a panel of statistical analyses to identify bladder cancer-associated gene signatures. Hierarchical clustering and supervised learning algorithms were used to classify samples on the basis of tumor burden. A differentially expressed geneset of 319 gene probes was associated with the presence of bladder cancer (P<0.01), and visualization of protein interaction networks revealed VEGF and AGT as pivotal factors in tumor cells. Supervised machine learning and a cross-validation approach were used to build a 14-gene molecular classifier that was able to classify patients with and without bladder cancer with an overall accuracy of 76%. Our results show that it is possible to achieve the detection of bladder cancer using molecular signatures present in exfoliated tumor urothelia. Further investigation and validation of the cancer-associated profiles may reveal important biomarkers for the non-invasive detection and surveillance of bladder cancer. PMID:19190164

  1. Predictive Gene Signature of Response to the Anti-TweakR mAb PDL192 in Patient-Derived Breast Cancer Xenografts

    PubMed Central

    de Plater, Ludmilla; Vincent-Salomon, Anne; Berger, Frédérique; Nicolas, André; Vacher, Sophie; Gravier, Eléonore; Thuleau, Aurélie; Karboul, Narjesse; Richardson, Marion; Elbaz, Clément; Marangoni, Elisabetta; Bièche, Ivan; Paoletti, Xavier; Roman-Roman, Sergio; Culp, Patricia A.; Asselain, Bernard; Diéras, Véronique; Decaudin, Didier

    2014-01-01

    Purpose (1) To determine TweakR expression in human breast cancers (BC), (2) evaluate the antitumor effect of the anti-TweakR antibody PDL192, used alone or after chemotherapy-induced complete remission (CR), on patient-derived BC xenografts (PDX) and (3) define predictive markers of response. Experimental Design TweakR expression was analyzed by IHC on patients and PDXs BC samples. In vivo antitumor effect of PDL192 was evaluated on eight TweakR-positive BC PDXs alone or after complete remission induced by a combination of doxorubicin and cyclophosphamide. Using both responding and resistant PDX tumors after PDL192 administration, RT-QPCR were performed on a wide list of selected candidate genes to identify predictive markers of response. Results TweakR protein was expressed in about half of human BC samples. In vivo PDL192 treatment had significantly anti-tumor activity in 4 of 8 TweakR-positive BC PDXs, but no correlation between the expression level of the Tweak receptor and response to therapy was observed. PDL192 also significantly delayed tumor relapse after CR. Finally, an 8 gene signature was defined from sensitive and resistant PDXs. Conclusions PDL192 was highly efficient in some BC PDXs. We found 8 genes that were differentially expressed in responding and resistant tumors and could constitute a gene expression signature which would need to be extended to other xenograft models for confirmation. These data confirm the therapeutic potential of TweakR targeting in BC and the possibility of prospectively selecting patients who might benefit from therapy. PMID:25375638

  2. High-resolution prediction of mouse brain connectivity using gene expression patterns.

    PubMed

    Fakhry, Ahmed; Ji, Shuiwang

    2015-02-01

    The brain is a multi-level system in which the high-level functions are generated by low-level genetic mechanisms. Thus, elucidating the relationship among multiple brain levels via correlative and predictive analytics is an important area in brain research. Currently, studies in multiple species have indicated that the spatiotemporal gene expression patterns are predictive of brain wiring. Specifically, results on the worm Caenorhabditis elegans have shown that the prediction of neuronal connectivity using gene expression signatures yielded statistically significant results. Recent studies on the mammalian brain produced similar results at the coarse regional level. In this study, we provide the first high-resolution, large-scale integrative analysis of the transcriptome and connectome in a single mammalian brain at a fine voxel level. By using the Allen Brain Atlas data, we predict voxel-level brain connectivity based on the gene expressions in the adult mouse brain. We employ regularized models to show that gene expression is predictive of connectivity at the voxel-level with an accuracy of 93%. We also identify a set of genes playing the most important role in connectivity prediction. We use only this small number of genes to predict the brain wiring with an accuracy over 80%. We discover that these important genes are enriched in neurons as compared to glia, and they perform connectivity-related functions. We perform several interesting correlative studies to further elucidate the transcriptome-connectome relationship. PMID:25109429

  3. HPV-related methylation signature predicts survival in oropharyngeal squamous cell carcinomas.

    PubMed

    Kostareli, Efterpi; Holzinger, Dana; Bogatyrova, Olga; Hielscher, Thomas; Wichmann, Gunnar; Keck, Michaela; Lahrmann, Bernd; Grabe, Niels; Flechtenmacher, Christa; Schmidt, Christopher R; Seiwert, Tanguy; Dyckhoff, Gerhard; Dietz, Andreas; Höfler, Daniela; Pawlita, Michael; Benner, Axel; Bosch, Franz X; Plinkert, Peter; Plass, Christoph; Weichenhan, Dieter; Hess, Jochen

    2013-06-01

    High-risk types of human papilloma virus (HPV) are increasingly associated with oropharyngeal squamous cell carcinoma (OPSCC). Strikingly, patients with HPV-positive OPSCC are highly curable with ionizing radiation and have better survival compared with HPV-negative patients, but the underlying molecular mechanisms remain poorly understood. We applied an array-based approach to monitor global changes in CpG island hypermethylation between HPV-negative and HPV-positive OPSCCs and identified a specific pattern of differentially methylated regions that critically depends on the presence of viral transcripts. HPV-related alterations were confirmed for the majority of candidate gene promoters by mass spectrometric, quantitative methylation analysis. There was a significant inverse correlation between promoter hypermethylation of ALDH1A2, OSR2, GATA4, GRIA4, and IRX4 and transcript levels. Interestingly, Kaplan-Meier analysis revealed that a combined promoter methylation pattern of low methylation levels in ALDH1A2 and OSR2 promoters and high methylation levels in GATA4, GRIA4, and IRX4 promoters was significantly correlated with improved survival in 3 independent patient cohorts. ALDH1A2 protein levels, determined by immunohistochemistry on tissue microarrays, confirmed the association with clinical outcome. In summary, our study highlights specific alterations in global gene promoter methylation in HPV-driven OPSCCs and identifies a signature that predicts the clinical outcome in OPSCCs. PMID:23635773

  4. Beller Lectureship: Predictions for Observational Signatures of the Tidal Disruption of Stars

    NASA Astrophysics Data System (ADS)

    Strubbe, Linda

    2013-04-01

    A star that wanders too close to a massive black hole (BH) is shredded by the BH's tidal gravity; soon afterwards, stellar gas starts falling back to the BH, releasing a flare of energy as gas accretes. For days to months following disruption, the gas feeds the BH at a highly super-Eddington rate; i.e., radiation pressure in the flow is strong compared to the BH's gravity. During this phase, radiation pressure likely drives gas back outwards in a wind and produces a large optical luminosity and characteristic spectrum of blueshifted absorption lines. In some cases, magnetic fields may drive a relativistic jet as well, bright in radio and hard X-rays. Then weeks to months later, the BH feeding rate falls to sub-Eddington, and should produce a radiative accretion disk, bright in soft X-rays to ultraviolet. A few years or more after that, the feeding rate falls below ˜0.01 of the Eddington rate, and the flow may transition to a radiatively inefficient disk, perhaps accompanied once again by a jet. I will review panchromatic predictions for emission signatures from all of these structures, discuss their observability in new and upcoming transient surveys, and compare with observations of tidal disruption event candidates so far.

  5. Numerical Predictions of Sonic Boom Signatures for a Straight Line Segmented Leading Edge Model

    NASA Technical Reports Server (NTRS)

    Elmiligui, Alaa A.; Wilcox, Floyd J.; Cliff, Susan; Thomas, Scott

    2012-01-01

    A sonic boom wind tunnel test was conducted on a straight-line segmented leading edge (SLSLE) model in the NASA Langley 4- by 4- Foot Unitary Plan Wind Tunnel (UPWT). The purpose of the test was to determine whether accurate sonic boom measurements could be obtained while continuously moving the SLSLE model past a conical pressure probe. Sonic boom signatures were also obtained using the conventional move-pause data acquisition method for comparison. The continuous data acquisition approach allows for accurate signatures approximately 15 times faster than a move-pause technique. These successful results provide an incentive for future testing with greatly increased efficiency using the continuous model translation technique with the single probe to measure sonic boom signatures. Two widely used NASA codes, USM3D (Navier-Stokes) and CART3D-AERO (Euler, adjoint-based adaptive mesh), were used to compute off-body sonic boom pressure signatures of the SLSLE model at several different altitudes below the model at Mach 2.0. The computed pressure signatures compared well with wind tunnel data. The effect of the different altitude for signature extraction was evaluated by extrapolating the near field signatures to the ground and comparing pressure signatures and sonic boom loudness levels.

  6. A surprising cross-species conservation in the genomic landscape of mouse and human oral cancer identifies a transcriptional signature predicting metastatic disease

    PubMed Central

    Onken, Michael D.; Winkler, Ashley E.; Kanchi, Krishna-Latha; Chalivendra, Varun; Law, Jonathan H.; Rickert, Charles G.; Kallogjeri, Dorina; Judd, Nancy P.; Dunn, Gavin P.; Piccirillo, Jay F.; Lewis, James S.; Mardis, Elaine R.; Uppaluri, Ravindra

    2014-01-01

    Purpose Improved understanding of the molecular basis underlying oral squamous cell carcinoma (OSCC) aggressive growth has significant clinical implications. Herein, cross-species genomic comparison of carcinogen-induced murine and human OSCCs with indolent or metastatic growth yielded results with surprising translational relevance. Experimental Design Murine OSCC cell lines were subjected to next-generation sequencing (NGS) to define their mutational landscape, to define novel candidate cancer genes and to assess for parallels with known drivers in human OSCC. Expression arrays identified a mouse metastasis signature and we assessed its representation in 4 independent human datasets comprising 324 patients using weighted voting and Gene Set Enrichment Analysis (GSEA). Kaplan-Meier analysis and multivariate Cox proportional hazards modeling were used to stratify outcomes. A qRT-PCR assay based on the mouse signature coupled to a machine-learning algorithm was developed and used to stratify an independent set of 31 patients with respect to metastatic lymphadenopathy. Results NGS revealed conservation of human driver pathway mutations in mouse OSCC including in Trp53, MAPK, PI3K, NOTCH, JAK/STAT and FAT1–4. Moreover, comparative analysis between The Cancer Genome Atlas (TCGA) and mouse samples defined AKAP9, MED12L and MYH6 as novel putative cancer genes. Expression analysis identified a transcriptional signature predicting aggressiveness and clinical outcomes, which were validated in 4 independent human OSCC datasets. Finally, we harnessed the translational potential of this signature by creating a clinically feasible assay that stratified OSCC patients with a 93.5% accuracy. Conclusions These data demonstrate surprising cross-species genomic conservation that has translational relevance for human oral squamous cell cancer. PMID:24668645

  7. Colon Cancer Cells Gene Expression Signature As Response to 5- Fluorouracil, Oxaliplatin, and Folinic Acid Treatment

    PubMed Central

    Negrei, Carolina; Hudita, Ariana; Ginghina, Octav; Galateanu, Bianca; Voicu, Sorina Nicoleta; Stan, Miriana; Costache, Marieta; Fenga, Concettina; Drakoulis, Nikolaos; Tsatsakis, Aristidis M.

    2016-01-01

    5-FU cytotoxicity mechanism has been assigned both to the miss-incorporation of fluoronucleotides into RNA and DNA and to the inhibition of thymidylate synthase. 5-FU is one of the most widely used chemotherapeutic drugs, although it has severe side effects that may vary between patients. Pharmacogenetic studies related to 5-FU have been traditionally focused on the rate-limiting catabolic enzyme, dihydropyrimidine dehydrogenase that breaks 80–85% of 5-FU into its inactive metabolite. Choosing the right dosing scheme and chemotherapy strategy for each individual patient remains challenging for personalized chemotherapy management. In the general effort toward reduction of colorectal cancer mortality, in vitro screening studies play a very important role. To accelerate translation research, increasing interest has been focused on using in vivo-like models such as three-dimensional spheroids. The development of higher throughput assays to quantify phenotypic changes in spheroids is an active research area. Consequently, in this study we used the microarray technology to reveal the HT-29 colorectal adenocarcinoma cells gene expression signature as response to 5-FU/OXP/FA treatment in a state of the art 3D culture system. We report here an increased reactive oxygen species production under treatment, correlated with a decrease in cell viability and proliferation potential. With respect to the HT-29 cells gene expression under the treatment with 5-FU/OXP/FA, we found 15.247 genes that were significantly differentially expressed (p < 0.05) with a fold change higher that two-fold. Among these, 7136 genes were upregulated and 8111 genes were downregulated under experimental conditions as compared to untreated cells. The most relevant and statistic significant (p < 0.01) pathways in the experiment are associated with the genes that displayed significant differential expression and are related to intracellular signaling, oxidative stress, apoptosis, and cancer. PMID

  8. Lung tumor microenvironment induces specific gene expression signature in intratumoral NK cells.

    PubMed

    Gillard-Bocquet, Mélanie; Caer, Charles; Cagnard, Nicolas; Crozet, Lucile; Perez, Mikael; Fridman, Wolf Herman; Sautès-Fridman, Catherine; Cremer, Isabelle

    2013-01-01

    Natural killer (NK) cells are able to recognize and kill tumor cells, however whether they contribute to tumor immunosurveillance is still debated. Our previous studies demonstrated the presence of NK cells in human lung tumors. Their comparison with NK cells from non-tumoral lung tissues and with blood NK cells from the same individuals revealed a decreased expression of some NK receptors and impaired ex vivo cytotoxic functions occurring specifically in NK cells isolated from the tumor microenvironment. The aim of the present study was to characterize the transcriptional profile of such intratumoral NK cells, by comparative microarray analysis of sorted NK cells isolated from non-tumoral (Non-Tum-NK) and tumoral (Tum-NK) lung tissues of 12 Non-Small Cell Lung Cancer patients. Our results reveal a specific gene expression signature of Tum-NK cells particularly in activation processes and cytotoxicity, confirming that tumor environment induces modifications in NK cells biology. Indeed, intratumoral NK cells display higher expression levels of NKp44, NKG2A, Granzymes A and K, and Fas mRNA. A particular pattern of receptors involved in chemotaxis was also observed, with an overexpression of CXCR5 and CXCR6, and a lower expression of CX3CR1 and S1PR1 genes in Tum-NK as compared to Non-Tum-NK cells. The precise identification of the molecular pathways modulated in the tumor environment will help to decipher the role of NK cells in tumor immunosurveillance and will open future investigations to manipulate their antitumoral functions. PMID:23382731

  9. Age gene expression and coexpression progressive signatures in peripheral blood leukocytes.

    PubMed

    Irizar, Haritz; Goñi, Joaquín; Alzualde, Ainhoa; Castillo-Triviño, Tamara; Olascoaga, Javier; Lopez de Munain, Adolfo; Otaegui, David

    2015-12-01

    Both cellular senescence and organismic aging are known to be dynamic processes that start early in life and progress constantly during the whole life of the individual. In this work, with the objective of identifying signatures of age-related progressive change at the transcriptomic level, we have performed a whole-genome gene expression analysis of peripheral blood leukocytes in a group of healthy individuals with ages ranging from 14 to 93 years. A set of genes with progressively changing gene expression (either increase or decrease with age) has been identified and contextualized in a coexpression network. A modularity analysis has been performed on this network and biological-term and pathway enrichment analyses have been used for biological interpretation of each module. In summary, the results of the present work reveal the existence of a transcriptomic component that shows progressive expression changes associated to age in peripheral blood leukocytes, highlighting both the dynamic nature of the process and the need to complement young vs. elder studies with longitudinal studies that include middle aged individuals. From the transcriptional point of view, immunosenescence seems to be occurring from a relatively early age, at least from the late 20s/early 30s, and the 49-56 year old age-range appears to be critical. In general, the genes that, according to our results, show progressive expression changes with aging are involved in pathogenic/cellular processes that have classically been linked to aging in humans: cancer, immune processes and cellular growth vs. maintenance. PMID:26362218

  10. Gene expression signature of DMBA-induced hamster buccal pouch carcinomas: modulation by chlorophyllin and ellagic acid.

    PubMed

    Vidya Priyadarsini, Ramamurthi; Kumar, Neeraj; Khan, Imran; Thiyagarajan, Paranthaman; Kondaiah, Paturu; Nagini, Siddavaram

    2012-01-01

    Chlorophyllin (CHL), a water-soluble, semi-synthetic derivative of chlorophyll and ellagic acid (EA), a naturally occurring polyphenolic compound in berries, grapes, and nuts have been reported to exert anticancer effects in various human cancer cell lines and in animal tumour models. The present study was undertaken to examine the mechanism underlying chemoprevention and changes in gene expression pattern induced by dietary supplementation of chlorophyllin and ellagic acid in the 7,12-dimethylbenz[a]anthracene (DMBA)-induced hamster buccal pouch (HBP) carcinogenesis model by whole genome profiling using pangenomic microarrays. In hamsters painted with DMBA, the expression of 1,700 genes was found to be altered significantly relative to control. Dietary supplementation of chlorophyllin and ellagic acid modulated the expression profiles of 104 and 37 genes respectively. Microarray analysis also revealed changes in the expression of TGFβ receptors, NF-κB, cyclin D1, and matrix metalloproteinases (MMPs) that may play a crucial role in the transformation of the normal buccal pouch to a malignant phenotype. This gene expression signature was altered on treatment with chlorophyllin and ellagic acid. Our study has also revealed patterns of gene expression signature specific for chlorophyllin and ellagic acid exposure. Thus dietary chlorophyllin and ellagic acid that can reverse gene expression signature associated with carcinogenesis are novel candidates for cancer prevention and therapy. PMID:22485181

  11. Gene Expression Signature of DMBA-Induced Hamster Buccal Pouch Carcinomas: Modulation by Chlorophyllin and Ellagic Acid

    PubMed Central

    Vidya Priyadarsini, Ramamurthi; Kumar, Neeraj; Khan, Imran; Thiyagarajan, Paranthaman; Kondaiah, Paturu; Nagini, Siddavaram

    2012-01-01

    Chlorophyllin (CHL), a water-soluble, semi-synthetic derivative of chlorophyll and ellagic acid (EA), a naturally occurring polyphenolic compound in berries, grapes, and nuts have been reported to exert anticancer effects in various human cancer cell lines and in animal tumour models. The present study was undertaken to examine the mechanism underlying chemoprevention and changes in gene expression pattern induced by dietary supplementation of chlorophyllin and ellagic acid in the 7,12-dimethylbenz[a]anthracene (DMBA)-induced hamster buccal pouch (HBP) carcinogenesis model by whole genome profiling using pangenomic microarrays. In hamsters painted with DMBA, the expression of 1,700 genes was found to be altered significantly relative to control. Dietary supplementation of chlorophyllin and ellagic acid modulated the expression profiles of 104 and 37 genes respectively. Microarray analysis also revealed changes in the expression of TGFβ receptors, NF-κB, cyclin D1, and matrix metalloproteinases (MMPs) that may play a crucial role in the transformation of the normal buccal pouch to a malignant phenotype. This gene expression signature was altered on treatment with chlorophyllin and ellagic acid. Our study has also revealed patterns of gene expression signature specific for chlorophyllin and ellagic acid exposure. Thus dietary chlorophyllin and ellagic acid that can reverse gene expression signature associated with carcinogenesis are novel candidates for cancer prevention and therapy. PMID:22485181

  12. Lupus anti-ribosomal P autoantibody proteomes express convergent biclonal signatures.

    PubMed

    Al Kindi, M A; Colella, A D; Beroukas, D; Chataway, T K; Gordon, T P

    2016-04-01

    Lupus-specific anti-ribosomal P (anti-Rib-P) autoantibodies have been implicated in the pathogenesis of neurological complications in systemic lupus erythematosus (SLE). The aim of the present study was to determine variable (V)-region signatures of secreted autoantibody proteomes specific for the Rib-P heterocomplex and investigate the molecular basis of the reported cross-reactivity with Sm autoantigen. Anti-Rib-P immunoglobulins (IgGs) were purified from six anti-Rib-P-positive sera by elution from enzyme-linked immunosorbent assay (ELISA) plates coated with either native Rib-P proteins or an 11-amino acid peptide (11-C peptide) representing the conserved COOH-terminal P epitope. Rib-P- and 11-C peptide-specific IgGs were analysed for heavy (H) and light (L) chain clonality and V-region expression using an electrophoretic and de-novo and database-driven mass spectrometric sequencing workflow. Purified anti-Rib-P and anti-SmD IgGs were tested for cross-reactivity on ELISA and their proteome data sets analysed for shared clonotypes. Anti-Rib-P autoantibody proteomes were IgG1 kappa-restricted and comprised two public clonotypes defined by unique H/L chain pairings. The major clonotypic population was specific for the common COOH-terminal epitope, while the second shared the same pairing signature as a recently reported anti-SmD clonotype, accounting for two-way immunoassay cross-reactivity between these lupus autoantibodies. Sequence convergence of anti-Rib-P proteomes suggests common molecular pathways of autoantibody production and identifies stereotyped clonal populations that are thought to play a pathogenic role in neuropsychiatric lupus. Shared clonotypic structures for anti-Rib-P and anti-Sm responses suggest a common B cell clonal origin for subsets of these lupus-specific autoantibodies. PMID:26646815

  13. Stem cells and germ cells: microRNA and gene expression signatures.

    PubMed

    Dyce, Paul William; Toms, Derek; Li, Julang

    2010-04-01

    The study of primordial germ cell development in vivo is hampered by their low numbers and inaccessibility. Recent research has shown the ability of embryonic and adult stem cells to differentiate into primordial germ cells and more mature gametes and this generation of germ cells in vitro may be an attractive model for their study. One of the biggest challenges facing in vitro differentiation of stem cells into primordial germ cells is the lack of markers to clearly distinguish the two. As both cell types originate early in embryonic development they share many pluripotent markers such as OCT4, VASA, FRAGILIS, and NANOG. Genome wide microarray profiling has been used to identify transcriptome patterns unique to primordial germ cells. A more thorough analysis of the temporal and quantitative expression of a panel of genes may be more robust in distinguishing these two cell populations. MicroRNAs, short RNA molecules that have been shown to regulate translation through interactions with mRNA transcripts, have also recently come under investigation for the role they may play in pluripotency. Attempts to elucidate key microRNAs responsible for both stem cell and primordial germ cell characteristics have recently been undertaken. Unique microRNAs, either individually or as global profiles, may also help to distinguish differentiated primordial germ cells from stem cells in vitro. This review will examine gene expression and microRNA signatures in stem cells and germ cells as ways to distinguish these closely related cell types. PMID:20183803

  14. Gene Expression and Methylation Signatures of MAN2C1 are Associated with PTSD

    PubMed Central

    Uddin, Monica; Galea, Sandro; Chang, Shun-Chiao; Aiello, Allison E.; Wildman, Derek E.; de los Santos, Regina; Koenen, Karestan C.

    2011-01-01

    As potential regulators of DNA accessibility and activity, epigenetic modifications offer a mechanism by which the environment can moderate the effects of genes. To date, however, there have been relatively few studies assessing epigenetic modifications associated with post-traumatic stress disorder (PTSD). Here we investigate PTSD-associated methylation differences in 33 genes previously shown to differ in whole blood-derived gene expression levels between those with vs. without the disorder. Drawing on DNA samples similarly obtained from whole blood in 100 individuals, 23 with and 77 without lifetime PTSD, we used methylation microarray data to assess whether these 33 candidate genes showed epigenetic signatures indicative of increased risk for, or resilience to, PTSD. Logistic regression analyses were performed to assess the main and interacting effects of candidate genes’ methylation values and number of potentially traumatic events (PTEs), adjusting for age and other covariates. Results revealed that only one candidate gene–MAN2C1–showed a significant methylation x PTE interaction, such that those with both higher MAN2C1 methylation and greater exposure to PTEs showed a marked increase in risk of lifetime PTSD (OR 4.35, 95% CI: 1.07, 17.77, p = 0.04). These results indicate that MAN2C1 methylation levels modify cumulative traumatic burden on risk of PTSD, and suggest that both gene expression and epigenetic changes at specific loci are associated with this disorder. PMID:21508515

  15. A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients

    PubMed Central

    Cheng, Wen; Ren, Xiufang; Cai, Jinquan; Zhang, Chuanbao; Li, Mingyang; Wang, Kuanyu; Liu, Yang; Han, Sheng; Wu, Anhua

    2015-01-01

    Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management. PMID:26320189

  16. A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients.

    PubMed

    Cheng, Wen; Ren, Xiufang; Cai, Jinquan; Zhang, Chuanbao; Li, Mingyang; Wang, Kuanyu; Liu, Yang; Han, Sheng; Wu, Anhua

    2015-10-01

    Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management. PMID:26320189

  17. Prediction of Chemical Respiratory Sensitizers Using GARD, a Novel In Vitro Assay Based on a Genomic Biomarker Signature

    PubMed Central

    Albrekt, Ann-Sofie; Borrebaeck, Carl A. K.; Lindstedt, Malin

    2015-01-01

    Background Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers. Results Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers. Conclusions We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample. PMID:25760038

  18. A serum microRNA signature as a prognostic factor for patients with advanced NSCLC and its association with tissue microRNA expression profiles

    PubMed Central

    GUO, JING; MENG, RUI; YIN, ZHONGYUAN; LI, PENGCHENG; ZHOU, RUI; ZHANG, SHENG; DONG, XIAORONG; LIU, LI; WU, GANG

    2016-01-01

    The aim of the present study was to detect microRNA (miRNA) signatures in advanced non-small cell lung cancer (NSCLC), and to study the association between miRNA expression levels in serum and tissue. A cohort of patients who had previously been diagnosed with advanced NSCLC was enrolled in the present study. miRNAs associated with prognosis, which had previously been detected in early stage NSCLC samples, were measured in the serum of the patient groups using a cross-validation method. In addition, serum miRNAs associated with progression-free survival (PFS) were detected in paired fresh tissue samples, in order to analyze the correlation between serum and tissue expression levels. A risk-score analysis was used to develop a four-miRNA signature to predict PFS. miR-1, miR-30d, miR-221 and miR-486 were identified as having a significant correlation with PFS in advanced NSCLC. miR-221 and miR-486 exhibited significant positive correlations between serum and tissue expression. Furthermore, overexpression of miR-221 and reduced expression of miR-486 increased cell proliferation, migration and invasion in vitro. In conclusion, the miRNA signature identified in the present study may be considered an independent prognostic factor of PFS in advanced NSCLC. In addition, the expression levels of miR-221 and miR-486 were significantly correlated between serum and tissue. miR-221 was identified as an oncogenic risk factor, whereas miR-486 exerted protective effects against cancer cell proliferation, migration and invasion. PMID:27081922

  19. EMERGE: a flexible modelling framework to predict genomic regulatory elements from genomic signatures

    PubMed Central

    van Duijvenboden, Karel; de Boer, Bouke A.; Capon, Nicolas; Ruijter, Jan M.; Christoffels, Vincent M.

    2016-01-01

    Regulatory DNA elements, short genomic segments that regulate gene expression, have been implicated in developmental disorders and human disease. Despite this clinical urgency, only a small fraction of the regulatory DNA repertoire has been confirmed through reporter gene assays. The overall success rate of functional validation of candidate regulatory elements is low. Moreover, the number and diversity of datasets from which putative regulatory elements can be identified is large and rapidly increasing. We generated a flexible and user-friendly tool to integrate the information from different types of genomic datasets, e.g. ATAC-seq, ChIP-seq, conservation, aiming to increase the ease and success rate of functional prediction. To this end, we developed the EMERGE program that merges all datasets that the user considers informative and uses a logistic regression framework, based on validated functional elements, to set optimal weights to these datasets. ROC curve analysis shows that a combination of datasets leads to improved prediction of tissue-specific enhancers in human, mouse and Drosophila genomes. Functional assays based on this prediction can be expected to have substantially higher success rates. The resulting integrated signal for prediction of functional elements can be plotted in a build-in genome browser or exported for further analysis. PMID:26531828

  20. Predictable tuning of protein expression in bacteria.

    PubMed

    Bonde, Mads T; Pedersen, Margit; Klausen, Michael S; Jensen, Sheila I; Wulff, Tune; Harrison, Scott; Nielsen, Alex T; Herrgård, Markus J; Sommer, Morten O A

    2016-03-01

    We comprehensively assessed the contribution of the Shine-Dalgarno sequence to protein expression and used the data to develop EMOPEC (Empirical Model and Oligos for Protein Expression Changes; http://emopec.biosustain.dtu.dk). EMOPEC is a free tool that makes it possible to modulate the expression level of any Escherichia coli gene by changing only a few bases. Measured protein levels for 91% of our designed sequences were within twofold of the desired target level. PMID:26752768

  1. Signatures of MRI-driven Turbulence in Protoplanetary Disks: Predictions for ALMA Observations

    NASA Astrophysics Data System (ADS)

    Simon, Jacob B.; Hughes, A. Meredith; Flaherty, Kevin M.; Bai, Xue-Ning; Armitage, Philip J.

    2015-08-01

    Spatially resolved observations of molecular line emission have the potential to yield unique constraints on the nature of turbulence within protoplanetary disks. Using a combination of local non-ideal magnetohydrodynamics (MHD) simulations and radiative transfer calculations, tailored to properties of the disk around HD 163296, we assess the ability of ALMA to detect turbulence driven by the magnetorotational instability (MRI). Our local simulations show that the MRI produces small-scale turbulent velocity fluctuations that increase in strength with height above the mid-plane. For a set of simulations at different disk radii, we fit a Maxwell-Boltzmann distribution to the turbulent velocity and construct a turbulent broadening parameter as a function of radius and height. We input this broadening into radiative transfer calculations to quantify observational signatures of MRI-driven disk turbulence. We find that the ratio of the peak line flux to the flux at line center is a robust diagnostic of turbulence that is only mildly degenerate with systematic uncertainties in disk temperature. For the CO(3-2) line, which we expect to probe the most magnetically active slice of the disk column, variations in the predicted peak-to-trough ratio between our most and least turbulent models span a range of approximately 15%. Additional independent constraints can be derived from the morphology of spatially resolved line profiles, and we estimate the resolution required to detect turbulence on different spatial scales. We discuss the role of lower optical depth molecular tracers, which trace regions closer to the disk mid-plane where velocities in MRI-driven models are systematically lower.

  2. Mining the Dynamic Genome: A Method for Identifying Multiple Disease Signatures Using Quantitative RNA Expression Analysis of a Single Blood Sample

    PubMed Central

    Chao, Samuel; Cheng, Changming; Liew, Choong-Chin

    2015-01-01

    Background: Blood has advantages over tissue samples as a diagnostic tool, and blood mRNA transcriptomics is an exciting research field. To realize the full potential of blood transcriptomic investigations requires improved methods for gene expression measurement and data interpretation able to detect biological signatures within the “noisy” variability of whole blood. Methods: We demonstrate collection tube bias compensation during the process of identifying a liver cancer-specific gene signature. The candidate probe set list of liver cancer was filtered, based on previous repeatability performance obtained from technical replicates. We built a prediction model using differential pairs to reduce the impact of confounding factors. We compared prediction performance on an independent test set against prediction on an alternative model derived by Weka. The method was applied to an independent set of 157 blood samples collected in PAXgene tubes. Results: The model discriminated liver cancer equally well in both EDTA and PAXgene collected samples, whereas the Weka-derived model (using default settings) was not able to compensate for collection tube bias. Cross-validation results show our procedure predicted membership of each sample within the disease groups and healthy controls. Conclusion: Our versatile method for blood transcriptomic investigation overcomes several limitations hampering research in blood-based gene tests.

  3. Ontology based molecular signatures for immune cell types via gene expression analysis

    PubMed Central

    2013-01-01

    Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

  4. Type 3 iodothyronine deiodinase in neonatal goats: molecular cloning, expression, localization, and methylation signature.

    PubMed

    Zhong, Tao; Jin, Peng-Fei; Zhao, Wei; Wang, Lin-Jie; Li, Li; Zhang, Hong-Ping

    2016-07-01

    Type 3 iodothyronine deiodinase (DIO3) is an important enzyme in the metabolism of thyroid hormones. It plays critical roles in fetal development and neonatal growth and is especially important for brain development in mammals. In the present study, we profiled the expression pattern and methylation signature of the DIO3 gene in goats. The complete coding sequence of caprine DIO3 encoded a protein of 301 amino acids and harbored an internal selenocysteine-encoding TGA codon. The DIO3 messenger RNA (mRNA) was predominantly expressed in the neonatal goat liver (P < 0.01), while expression in other tissues was quite low, with the lowest levels in the lung. In in situ hybridization, the DIO3 mRNA was predominantly localized in the liver and the lowest content was detected in the lung. The DIO3 transcript was widely localized in neurons and the neuropil. Methylation profiling of the DIO3 CpG island showed a significant difference between the 5' region (CpGs_1∼24) and the 3' region (CpG_25∼51) of the coding region. Furthermore, no significant difference in methylation status was observed among the six tested tissues with levels in the range of 29.11-33.12 %. The CpG islands in the intergenic-differentially methylated region (IG-DMR) showed significantly different methylated levels among tissues, and the highest methylated level was observed in lung (CpG island 1, 69.34 %) and longissimus dorsi (LD) (CpG island 2, 52.62 %) tissues. Our study lays a foundation for understanding DIO3 function and the diseases caused by altered methylation profiles of the DIO3 gene. PMID:27108114

  5. Baseline Gene Expression Signatures in Monocytes from Multiple Sclerosis Patients Treated with Interferon-beta

    PubMed Central

    Bustamante, Marta F.; Nurtdinov, Ramil N.; Río, Jordi; Montalban, Xavier; Comabella, Manuel

    2013-01-01

    Background A relatively large proportion of relapsing-remitting multiple sclerosis (RRMS) patients do not respond to interferon-beta (IFNb) treatment. In previous studies with peripheral blood mononuclear cells (PBMC), we identified a subgroup of IFNb non-responders that was characterized by a baseline over-expression of type I IFN inducible genes. Additional mechanistic experiments carried out in IFNb non-responders suggested a selective alteration of the type I IFN signaling pathway in the population of blood monocytes. Here, we aimed (i) to investigate whether the type I IFN signaling pathway is up-regulated in isolated monocytes from IFNb non-responders at baseline; and (ii) to search for additional biological pathways in this cell population that may be implicated in the response to IFNb treatment. Methods Twenty RRMS patients classified according to their clinical response to IFNb treatment and 10 healthy controls were included in the study. Monocytes were purified from PBMC obtained before treatment by cell sorting and the gene expression profiling was determined with oligonucleotide microarrays. Results and discussion Purified monocytes from IFNb non-responders were characterized by an over-expression of type I IFN responsive genes, which confirms the type I IFN signature in monocytes suggested from previous studies. Other relevant signaling pathways that were up-regulated in IFNb non-responders were related with the mitochondrial function and processes such as protein synthesis and antigen presentation, and together with the type I IFN signaling pathway, may also be playing roles in the response to IFNb. PMID:23637780

  6. A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

    PubMed Central

    2011-01-01

    Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests. PMID:21824406

  7. A CD8 T cell transcription signature predicts prognosis in autoimmune disease

    PubMed Central

    McKinney, Eoin F.; Lyons, Paul A.; Carr, Edward J.; Hollis, Jane L.; Jayne, David R. W.; Willcocks, Lisa C.; Koukoulaki, Maria; Brazma, Alvis; Jovanovic, Vojislav; Kemeny, D. Michael; Pollard, Andrew J.; MacAry, Paul A.; Chaudhry, Afzal N.; Smith, Kenneth G. C.

    2010-01-01

    Autoimmune diseases are common and debilitating, but their severe manifestations could be reduced if biomarkers were available to allow individual tailoring of the potentially toxic immunosuppressive therapy required for their control. Gene expression-based biomarkers facilitating individual tailoring of chemotherapy in cancer, but not autoimmunity, have been identified and translated into clinical practice1,2. We show that transcriptional profiling of purified CD8 T cells, which avoids the confounding influences of unseparated cells3,4, identifies two distinct patient subgroups predicting long-term prognosis in two different autoimmune diseases, anti-neutrophil cytoplasmic antibody (ANCA) – associated vasculitis (AAV), a chronic, severe disease characterized by inflammation of medium and small blood vessels5, and systemic lupus erythematosus (SLE), characterized by autoantibodies, immune complex deposition and diverse clinical manifestations ranging from glomerulonephritis to neurological dysfunction6. We show that genes defining the poor prognostic group are enriched for genes of the IL7R pathway, TCR signalling and those expressed by memory T cells. Furthermore, the poor prognostic group is associated with an expanded CD8 T cell memory population. These subgroups, which are also found in the normal population and can be identified by measuring expression of only three genes, raise the prospect of individualized therapy and suggest novel potential therapeutic targets in autoimmunity. PMID:20400961

  8. Long non-coding RNAs as novel expression signatures modulate DNA damage and repair in cadmium toxicology

    PubMed Central

    Zhou, Zhiheng; Liu, Haibai; Wang, Caixia; Lu, Qian; Huang, Qinhai; Zheng, Chanjiao; Lei, Yixiong

    2015-01-01

    Increasing evidence suggests that long non-coding RNAs (lncRNAs) are involved in a variety of physiological and pathophysiological processes. Our study was to investigate whether lncRNAs as novel expression signatures are able to modulate DNA damage and repair in cadmium(Cd) toxicity. There were aberrant expression profiles of lncRNAs in 35th Cd-induced cells as compared to untreated 16HBE cells. siRNA-mediated knockdown of ENST00000414355 inhibited the growth of DNA-damaged cells and decreased the expressions of DNA-damage related genes (ATM, ATR and ATRIP), while increased the expressions of DNA-repair related genes (DDB1, DDB2, OGG1, ERCC1, MSH2, RAD50, XRCC1 and BARD1). Cadmium increased ENST00000414355 expression in the lung of Cd-exposed rats in a dose-dependent manner. A significant positive correlation was observed between blood ENST00000414355 expression and urinary/blood Cd concentrations, and there were significant correlations of lncRNA-ENST00000414355 expression with the expressions of target genes in the lung of Cd-exposed rats and the blood of Cd exposed workers. These results indicate that some lncRNAs are aberrantly expressed in Cd-treated 16HBE cells. lncRNA-ENST00000414355 may serve as a signature for DNA damage and repair related to the epigenetic mechanisms underlying the cadmium toxicity and become a novel biomarker of cadmium toxicity. PMID:26472689

  9. Long non-coding RNAs as novel expression signatures modulate DNA damage and repair in cadmium toxicology

    NASA Astrophysics Data System (ADS)

    Zhou, Zhiheng; Liu, Haibai; Wang, Caixia; Lu, Qian; Huang, Qinhai; Zheng, Chanjiao; Lei, Yixiong

    2015-10-01

    Increasing evidence suggests that long non-coding RNAs (lncRNAs) are involved in a variety of physiological and pathophysiological processes. Our study was to investigate whether lncRNAs as novel expression signatures are able to modulate DNA damage and repair in cadmium(Cd) toxicity. There were aberrant expression profiles of lncRNAs in 35th Cd-induced cells as compared to untreated 16HBE cells. siRNA-mediated knockdown of ENST00000414355 inhibited the growth of DNA-damaged cells and decreased the expressions of DNA-damage related genes (ATM, ATR and ATRIP), while increased the expressions of DNA-repair related genes (DDB1, DDB2, OGG1, ERCC1, MSH2, RAD50, XRCC1 and BARD1). Cadmium increased ENST00000414355 expression in the lung of Cd-exposed rats in a dose-dependent manner. A significant positive correlation was observed between blood ENST00000414355 expression and urinary/blood Cd concentrations, and there were significant correlations of lncRNA-ENST00000414355 expression with the expressions of target genes in the lung of Cd-exposed rats and the blood of Cd exposed workers. These results indicate that some lncRNAs are aberrantly expressed in Cd-treated 16HBE cells. lncRNA-ENST00000414355 may serve as a signature for DNA damage and repair related to the epigenetic mechanisms underlying the cadmium toxicity and become a novel biomarker of cadmium toxicity.

  10. Prediction of survival of diffuse large B-cell lymphoma patients via the expression of three inflammatory genes.

    PubMed

    Zhao, Shuangtao; Bai, Nan; Cui, Jianlin; Xiang, Rong; Li, Na

    2016-08-01

    Currently, several gene-expression signatures that were used to predict survival of diffuse large B-cell lymphoma (DLBCL) patients, showed a restriction on the practical work for lack of convenient operation. In this study, we screened inflammatory genes whose expression correlated with survival of DLBCL and established a predictive model including IL6, IL1A and CSF3 through multivariate Cox regression based on the expression of these three genes. We validated the model at protein level in our clinical serum cohort composed of 101 patients of DLBCL and 50 healthy controls and 534 DLBCL patients at mRNA level from three independent Gene Expression Omnibus (GEO) data sets. We found our model to be independent of the International Prognostic Index (IPI), moreover, it can augment the predictive power of IPI. In summary, our three-gene model is sufficient to predict survival of DLBCL patients via measuring the concentration of three inflammatory cytokines in peripheral blood. PMID:27394196

  11. Focused and Steady-State Characteristics of Shaped Sonic Boom Signatures: Prediction and Analysis

    NASA Technical Reports Server (NTRS)

    Maglieri, Domenic J.; Bobbitt, Percy J.; Massey, Steven J.; Plotkin, Kenneth J.; Kandil, Osama A.; Zheng, Xudong

    2011-01-01

    The objective of this study is to examine the effect of flight, at off-design conditions, on the propagated sonic boom pressure signatures of a small "low-boom" supersonic aircraft. The amplification, or focusing, of the low magnitude "shaped" signatures produced by maneuvers such as the accelerations from transonic to supersonic speeds, climbs, turns, pull-up and pushovers is the concern. To analyze these effects, new and/or improved theoretical tools have been developed, in addition to the use of existing methodology. Several shaped signatures are considered in the application of these tools to the study of selected maneuvers and off-design conditions. The results of these applications are reported in this paper as well as the details of the new analytical tools. Finally, the magnitude of the focused boom problem for "low boom" supersonic aircraft designs has been more accurately quantified and potential "mitigations" suggested. In general, "shaped boom" signatures, designed for cruise flight, such as asymmetric and symmetric flat-top and initial-shock ramp waveforms retain their basic shape during transition flight. Complex and asymmetric and symmetric initial shock ramp waveforms provide lower magnitude focus boom levels than N-waves or asymmetric and symmetric flat-top signatures.

  12. Expression of p53 in endometrial polyps with special reference to the p53 signature.

    PubMed

    Sho, Tomoko; Hachisuga, Toru; Kawagoe, Toshinori; Urabe, Rie; Kurita, Tomoko; Kagami, Seiji; Shimajiri, Shohei; Fujino, Yoshihisa

    2016-07-01

    We herein examined the significance of the p53 expression in endometrial polyps (EMPs). A total of 133 EMPs, including 62 premenopausal and 71 postmenopausal women with EMP, were immunohistochemically studied for the expression of estrogen receptor (ER)-alpha, Ki-67 and p53. Apoptotic cells were identified using a TUNEL assay. A DNA sequence analysis of TP53 exons 5 to 9 was performed. Among the premenopausal EMPs, a multivariate analysis showed the labeling index (LI) for Ki-67 to correlate significantly with that for p53 (P<0.001), but not that for apoptosis. On the contrary, among the postmenopausal EMPs, the LI for Ki-67 correlated significantly with that for apoptosis (P<0.001). The p53 signature (p53S) was defined by endometrial epithelial cells, which are morphologically benign in appearance but display 12 or more consecutive epithelial cell nuclei with strong p53 immunostaining. The p53S was found in nine (12.7%) postmenopausal EMPs (mean age: 70.2 years). The median Ki-67 index for the p53S was 7%, with no significant difference from that of the glands of the postmenopausal EMPs without the p53S (P=0.058). The median apoptotic index for the p53S was 0%, which was significantly lower than that of the postmenopausal EMPs without the p53S (P=0.002). Two of four p53Ss showed TP53 mutations according to the DNA sequence analysis. The presence of the p53S is not rare in postmenopausal EMPs with an advanced age. Among postmenopausal EMPs, the LI of Ki-67 significantly correlates with that of apoptosis. However, such a positive correlation between the LI of Ki-67 and apoptosis is not observed in p53S. PMID:26727623

  13. Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients

    PubMed Central

    Haibe-Kains, B.; Desmedt, C.; Di Leo, A.; Azambuja, E.; Larsimont, D.; Selleslags, J.; Delaloge, S.; Duhem, C.; Kains, J.P.; Carly, B.; Maerevoet, M.; Vindevoghel, A.; Rouas, G.; Lallemand, F.; Durbecq, V.; Cardoso, F.; Salgado, R.; Rovere, R.; Bontempi, G.; Michiels, S.; Buyse, M.; Nogaret, J.M.; Qi, Y.; Symmans, F.; Pusztai, L.; D'Hondt, V.; Piccart-Gebhart, M.; Sotiriou, C.

    2013-01-01

    Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER)–negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-alpha (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. Here we describe in details the contents and quality controls for the gene expression and clinical data associated with the study published by Desmedt and colleagues in the Journal of Clinical Oncology in 2011 (Desmedt et al., 2011). We also provide R code to easily access the data and perform the quality controls and basic analyses relevant to this dataset. PMID:26484051

  14. Genome-wide gene expression profiling to predict resistance to anthracyclines in breast cancer patients.

    PubMed

    Haibe-Kains, B; Desmedt, C; Di Leo, A; Azambuja, E; Larsimont, D; Selleslags, J; Delaloge, S; Duhem, C; Kains, J P; Carly, B; Maerevoet, M; Vindevoghel, A; Rouas, G; Lallemand, F; Durbecq, V; Cardoso, F; Salgado, R; Rovere, R; Bontempi, G; Michiels, S; Buyse, M; Nogaret, J M; Qi, Y; Symmans, F; Pusztai, L; D'Hondt, V; Piccart-Gebhart, M; Sotiriou, C

    2013-12-01

    Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER)-negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-alpha (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. Here we describe in details the contents and quality controls for the gene expression and clinical data associated with the study published by Desmedt and colleagues in the Journal of Clinical Oncology in 2011 (Desmedt et al., 2011). We also provide R code to easily access the data and perform the quality controls and basic analyses relevant to this dataset. PMID:26484051

  15. Identification of a neuronal gene expression signature: role of cell cycle arrest in murine neuronal differentiation in vitro

    PubMed Central

    Felfly, Hady; Xue, Jin; Zambon, Alexander C.; Muotri, Alysson; Zhou, Dan

    2011-01-01

    Stem cells are a potential key strategy for treating neurodegenerative diseases in which the generation of new neurons is critical. A better understanding of the characteristics and molecular properties of neural stem cells (NSCs) and differentiated neurons can help with assessing neuronal maturity and, possibly, in devising better therapeutic strategies. We have performed an in-depth gene expression profiling study of murine NSCs and primary neurons derived from embryonic mouse brains. Microarray analysis revealed a neuron-specific gene expression signature that distinguishes primary neurons from NSCs, with elevated levels of transcripts involved in neuronal functions, such as neurite development and axon guidance in primary neurons and decreased levels of multiple cytokine transcripts. Among the differentially expressed genes, we found a statistically significant enrichment of genes in the ephrin, neurotrophin, CDK5, and actin pathways, which control multiple neuronal-specific functions. We then artificially blocked the cell cycle of NSCs with mitomycin C (MMC) and examined cellular morphology and gene expression signatures. Although these MMC-treated NSCs displayed a neuronal morphology and expressed some neuronal differentiation marker genes, their gene expression patterns were very different from primary neurons. We conclude that 1) fully differentiated mouse primary neurons display a specific neuronal gene expression signature; 2) cell cycle block at the S phase in NSCs with MMC does not induce the formation of fully differentiated neurons; 3) cytokines change their expression pattern during differentiation of NSCs into neurons; and 4) signaling pathways of ephrin, neurotrophin, CDK5, and actin, related to major neuronal features, are dynamically enriched in genes showing changes in expression level. PMID:21677276

  16. MicroRNA Expression Signatures Associated With BRAF-Mutated Versus KRAS-Mutated Colorectal Cancers

    PubMed Central

    Choi, Yong Won; Song, Young Soo; Lee, Hyunwoo; Yi, Kijong; Kim, Young-Bae; Suh, Kwang Wook; Lee, Dakeun

    2016-01-01

    Abstract BRAF and KRAS genes are known to play a similar role in the activation of RAS-RAF-MEK-ERK signaling pathway in colorectal tumorigenesis. However, BRAF-mutated colorectal cancers (CRCs) have distinct clinicopathologic characteristics different from those of the KRAS mutated ones as in comparison the BRAF-mutated CRCs are associated with a much worse prognosis for the afflicted patients. This study aimed to determine the different miRNA expression signatures associated with BRAF-mutated CRCs in comparison to KRAS-mutated ones, and to identify the specific miRNAs possibly mediating the aggressive phenotype of the BRAF-mutated CRCs. We screened 535 formalin-fixed paraffin-embedded CRC tissue samples for the BRAF V600E mutation, and selected 7 BRAF-mutated and 7 KRAS-mutated CRCs that were tumor size, stage, and microsatellite status-matched. Affymetrix GeneChip® miRNA 4.0 Array was used for detection of miRNA expression differences in the selected samples. We validated the array results by quantitative reverse transcription polymerase chain reaction (qRT-PCR) for selected miRNAs. A total of 10 differentially expressed (DE) miRNAs associated with BRAF-mutated CRCs were obtained, including miR-31-5p, miR-877-5p, miR-362-5p, and miR-425-3p. miR-31-5p showed the highest fold change (8.3-fold) among all of the miRNAs analyzed. From the analyses of GO biological processes, the DE-miRNAs were functionally relevant to cellular proliferation such as positive regulation of gene expression (P = 1.26 × 10−10), transcription (P = 9.70 × 10−10), and RNA metabolic process (P = 1.97 × 10−9). Bioinformatics analysis showed that the DE-miRNAs were significantly enriched in cancer-associated pathways including neutrophin signaling (P = 6.84 × 10−5), pathways in cancer (P = 0.0016), Wnt signaling (P = 0.0027), and MAPK signaling pathway (P = 0.0036). Our results suggest that the DE-miRNAs in BRAF-mutated CRCs in comparison

  17. Effect of Weather on the Predicted PMN Landmine Chemical Signature for Kabul, Afghanistan

    SciTech Connect

    WEBB, STEPHEN W.; PHELAN, JAMES M.

    2002-11-01

    Buried landmines are often detected through the chemical signature in the air above the soil surface by mine detection dogs. Environmental processes play a significant role in the chemical signature available for detection. Due to the shallow burial depth of landmines, the weather influences the release of chemicals from the landmine, transport through the soil to the surface, and degradation processes in the soil. The effect of weather on the landmine chemical signature from a PMN landmine was evaluated with the T2TNT code for Kabul, Afghanistan. Results for TNT and DNT gas-phase and soil solid-phase concentrations are presented as a function of time of the day and time of the year.

  18. Gene expression profile alone is inadequate in predicting complete response in multiple myeloma.

    PubMed

    Amin, S B; Yip, W-K; Minvielle, S; Broyl, A; Li, Y; Hanlon, B; Swanson, D; Shah, P K; Moreau, P; van der Holt, B; van Duin, M; Magrangeas, F; Pieter Sonneveld, P; Anderson, K C; Li, C; Avet-Loiseau, H; Munshi, N C

    2014-11-01

    With advent of several treatment options in multiple myeloma (MM), a selection of effective regimen has become an important issue. Use of gene expression profile (GEP) is considered an important tool in predicting outcome; however, it is unclear whether such genomic analysis alone can adequately predict therapeutic response. We evaluated the ability of GEP to predict complete response (CR) in MM. GEP from pretreatment MM cells from 136 uniformly treated MM patients with response data on an IFM, France led study were analyzed. To evaluate variability in predictive power due to microarray platform or treatment types, additional data sets from three different studies (n=511) were analyzed using same methods. We used several machine learning methods to derive a prediction model using training and test subsets of the original four data sets. Among all methods employed for GEP-based CR predictive capability, we got accuracy range of 56-78% in test data sets and no significant difference with regard to GEP platforms, treatment regimens or in newly diagnosed or relapsed patients. Importantly, permuted P-value showed no statistically significant CR predictive information in GEP data. This analysis suggests that GEP-based signature has limited power to predict CR in MM, highlighting the need to develop comprehensive predictive model using integrated genomics approach. PMID:24732597

  19. Probing the ToxCast Chemical Library for Predictive Signatures of Developmental Toxicity

    EPA Science Inventory

    EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

  20. Probing the ToxCastTM Chemical Library for Predictive Signatures of Developmental Toxicity -NLTO Poster

    EPA Science Inventory

    EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

  1. Proteomic Analysis of MG132-Treated Germinating Pollen Reveals Expression Signatures Associated with Proteasome Inhibition

    PubMed Central

    Vannini, Candida; Bracale, Marcella; Crinelli, Rita; Marconi, Valerio; Campomenosi, Paola; Marsoni, Milena; Scoccianti, Valeria

    2014-01-01

    Chemical inhibition of the proteasome has been previously found to effectively impair pollen germination and tube growth in vitro. However, the mediators of these effects at the molecular level are unknown. By performing 2DE proteomic analysis, 24 differentially expressed protein spots, representing 14 unique candidate proteins, were identified in the pollen of kiwifruit (Actinidia deliciosa) germinated in the presence of the MG132 proteasome inhibitor. qPCR analysis revealed that 11 of these proteins are not up-regulated at the mRNA level, but are most likely stabilized by proteasome inhibition. These differentially expressed proteins are predicted to function in various pathways including energy and lipid metabolism, cell wall synthesis, protein synthesis/degradation and stress responses. In line with this evidence, the MG132-induced changes in the proteome were accompanied by an increase in ATP and ROS content and by an alteration in fatty acid composition. PMID:25265451

  2. Identification of Gene Expression Signatures in the Chicken Intestinal Intraepithelial Lymphocytes in Response to Herb Additive Supplementations.

    PubMed

    Won, Kyeong-Hye; Song, Ki-Duk; Park, Jong-Eun; Kim, Duk-Kyung; Na, Chong-Sam

    2016-10-01

    Anethole and garlic have an immune modulatory effects on avian coccidiosis, and these effects are correlated with gene expression changes in intestinal epithelial lymphocytes (IELs). In this study, we integrated gene expression datasets from two independent experiments and investigated gene expression profile changes by anethole and garlic respectively, and identified gene expression signatures, which are common targets of these herbs as they might be used for the evaluation of the effect of plant herbs on immunity toward avian coccidiosis. We identified 4,382 and 371 genes, which were differentially expressed in IELs of chickens supplemented with garlic and anethole respectively. The gene ontology (GO) term of differentially expressed genes (DEGs) from garlic treatment resulted in the biological processes (BPs) related to proteolysis, e.g., "modification-dependent protein catabolic process", "proteolysis involved in cellular protein catabolic process", "cellular protein catabolic process", "protein catabolic process", and "ubiquitin-dependent protein catabolic process". In GO analysis, one BP term, "Proteolysis", was obtained. Among DEGs, 300 genes were differentially regulated in response to both garlic and anethole, and 234 and 59 genes were either up- or down-regulated in supplementation with both herbs. Pathway analysis resulted in enrichment of the pathways related to digestion such as "Starch and sucrose metabolism" and "Insulin signaling pathway". Taken together, the results obtained in the present study could contribute to the effective development of evaluation system of plant herbs based on molecular signatures related with their immunological functions in chicken IELs. PMID:26954117

  3. A predictive signature for therapy assignment and risk assessment in prostate cancer

    PubMed Central

    Bonci, Désirée; De Maria, Ruggero

    2015-01-01

    Prostate cancer remains the second leading cause of death in men. It is imperative to improve patient management in identifying bio-markers for personalized treatment. We demonstrated miR-15/miR-16 loss and miR-21 up-regulation and deregulation of their target genes, which represent a promising signature for ameliorating therapy assignment and risk assessment in prostate cancer. PMID:26697526

  4. Development of a Transient Acoustic Boundary Element Method to Predict the Noise Signature of Swimming Fish

    NASA Astrophysics Data System (ADS)

    Wagenhoffer, Nathan; Moored, Keith; Jaworski, Justin

    2015-11-01

    Animals have evolved flexible wings and fins to efficiently and quietly propel themselves through the air and water. The design of quiet and efficient bio-inspired propulsive concepts requires a rapid, unified computational framework that integrates three essential features: the fluid mechanics, the elastic structural response, and the noise generation. This study focuses on the development, validation, and demonstration of a transient, two-dimensional acoustic boundary element solver accelerated by a fast multipole algorithm. The resulting acoustic solver is used to characterize the acoustic signature produced by a vortex street advecting over a NACA 0012 airfoil, which is representative of vortex-body interactions that occur in schools of swimming fish. Both 2S and 2P canonical vortex streets generated by fish are investigated over the range of Strouhal number 0 . 2 < St < 0 . 4 , and the acoustic signature of the airfoil is quantified. This study provides the first estimate of the noise signature of a school of swimming fish. Lehigh University CORE Grant.

  5. Distinct MicroRNA Expression Signatures of Porcine Induced Pluripotent Stem Cells under Mouse and Human ESC Culture Conditions

    PubMed Central

    Wang, Jing; Han, Jianyong

    2016-01-01

    It is well known that microRNAs play a very important role in regulating reprogramming, pluripotency and cell fate decisions. Porcine induced pluripotent stem cells (piPSCs) are now available for studying the pluripotent regulation network in pigs. Two types of piPSCs have been derived from human and mouse embryonic stem cell (ESC) culture conditions: hpiPSCs and mpiPSCs, respectively. The hpiPSCs were morphologically similar to human ESCs, and the mpiPSCs resembled mouse ESCs. However, our current understanding of the role of microRNAs in the development of piPSCs is still very limited. Here, we performed small RNA sequencing to profile the miRNA expression in porcine fibroblasts (pEFs), hpiPSCs and mpiPSCs. There were 22 differential expressed (DE) miRNAs down-regulated in both types of piPSCs compared with pEFs, such as ssc-miR-145-5p and ssc-miR-98. There were 27 DE miRNAs up-regulated in both types of piPSCs compared with pEFs. Among these up-regulated DE miRNAs in piPSCs, ssc-miR-217, ssc-miR-216, ssc-miR-142-5p, ssc-miR-182, ssc-miR-183 and ssc-miR-96-5p have much higher expression levels in mpiPSCs, while ssc-miR-106a, ssc-miR-363, ssc-miR-146b, ssc-miR-195, ssc-miR-497, ssc-miR-935 and ssc-miR-20b highly expressed in hpiPSCs. Quantitative stem-loop RT-PCR was performed to confirm selected DE miRNAs expression levels. The results were consistent with small RNA sequencing. Different expression patterns were observed for key miRNA clusters, such as the miR-17-92 cluster, the let-7 family, the miR-106a-363 cluster and the miR-182-183 cluster, in the mpiPSCs and hpiPSCs. Novel miRNAs were also predicted in this study, including a putative porcine miR-302 cluster: ssc_38503, ssc_38503 and ssc_38501 (which resemble human miR-302a and miR-302b) found in both types of piPSCs. The miR-106a-363 cluster and putative miR-302 cluster increased the reprogramming efficiency of pEFs. The study revealed significant differences in the miRNA signatures of hpiPSCs and mpi

  6. Macaques can predict social outcomes from facial expressions.

    PubMed

    Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

    2016-09-01

    There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present. PMID:27155662

  7. Molecular classification of melanomas and nevi using gene expression microarray signatures and formalin-fixed and paraffin-embedded tissue.

    PubMed

    Koh, Stephen S; Opel, Michael L; Wei, Jia-Perng J; Yau, Kenneth; Shah, Rashmi; Gorre, Mercedes E; Whitman, Eric; Shitabata, Paul K; Tao, Yong; Cochran, Alistair J; Abrishami, Payam; Binder, Scott W

    2009-04-01

    Melanoma may be difficult to identify histologically and relatively high rates of misdiagnosis leads to many malpractice claims. Currently separation of melanomas from nevi is based primarily on light microscopic interpretation of hematoxylin and eosin stained sections with limited assistance from immunohistology. To increase the accuracy of discrimination of benign and malignant melanocytic lesions we identified DNA microarray-derived gene expression profiles of different melanocytic lesions and evaluated the performance of these gene signatures as molecular diagnostic tools in the molecular classification and separation of melanomas and nevi. Melanocyte-derived cells were isolated by laser capture microdissection from 165 formalin-fixed and paraffin-embedded melanocytic nevi and melanoma tissue sections. RNA was isolated, amplified, labeled, and hybridized to a custom DNA microarray. In all 120 samples were used to identify differentially expressed genes and generate a gene expression classifier capable of distinguishing between melanomas and nevi. These classifiers were tested by the leave-one-out method and in a blinded study. RT-PCR verified the results. Unsupervised hierarchical clustering identified two distinct lesional groups that closely correlated with the histopathologically identified melanomas and nevi. Analysis of gene expression levels identified 36 significant differentially expressed genes. In comparison with nevi, melanomas expressed higher levels of genes promoting signal transduction, transcription, and cell growth. In contrast, expression of L1CAM (homolog) was reduced in melanomas relative to nevi. Genes differentially expressed in melanomas and nevi, on the basis of molecular signal, sub classified a group of unknown melanocytic lesions as melanomas or nevi and had high concordance rates with histopathology. Gene signatures established using DNA microarray gene expression profiling can distinguish melanomas from nevi, indicating the

  8. Interrogating differences in expression of targeted gene sets to predict breast cancer outcome

    PubMed Central

    2013-01-01

    Background Genomics provides opportunities to develop precise tests for diagnostics, therapy selection and monitoring. From analyses of our studies and those of published results, 32 candidate genes were identified, whose expression appears related to clinical outcome of breast cancer. Expression of these genes was validated by qPCR and correlated with clinical follow-up to identify a gene subset for development of a prognostic test. Methods RNA was isolated from 225 frozen invasive ductal carcinomas,and qRT-PCR was performed. Univariate hazard ratios and 95% confidence intervals for breast cancer mortality and recurrence were calculated for each of the 32 candidate genes. A multivariable gene expression model for predicting each outcome was determined using the LASSO, with 1000 splits of the data into training and testing sets to determine predictive accuracy based on the C-index. Models with gene expression data were compared to models with standard clinical covariates and models with both gene expression and clinical covariates. Results Univariate analyses revealed over-expression of RABEP1, PGR, NAT1, PTP4A2, SLC39A6, ESR1, EVL, TBC1D9, FUT8, and SCUBE2 were all associated with reduced time to disease-related mortality (HR between 0.8 and 0.91, adjusted p < 0.05), while RABEP1, PGR, SLC39A6, and FUT8 were also associated with reduced recurrence times. Multivariable analyses using the LASSO revealed PGR, ESR1, NAT1, GABRP, TBC1D9, SLC39A6, and LRBA to be the most important predictors for both disease mortality and recurrence. Median C-indexes on test data sets for the gene expression, clinical, and combined models were 0.65, 0.63, and 0.65 for disease mortality and 0.64, 0.63, and 0.66 for disease recurrence, respectively. Conclusions Molecular signatures consisting of five genes (PGR, GABRP, TBC1D9, SLC39A6 and LRBA) for disease mortality and of six genes (PGR, ESR1, GABRP, TBC1D9, SLC39A6 and LRBA) for disease recurrence were identified. These signatures

  9. Comparative proteomic analysis of four Bacillus clausii strains: proteomic expression signature distinguishes protein profile of the strains.

    PubMed

    Lippolis, Rosa; Gnoni, Antonio; Abbrescia, Anna; Panelli, Damiano; Maiorano, Stefania; Paternoster, Maria Stefania; Sardanelli, Anna Maria; Papa, Sergio; Gaballo, Antonio

    2011-11-18

    A comparative proteomic approach, using two dimensional gel electrophoresis and mass spectrometry, has been developed to compare and elucidate the differences among the cellular proteomes of four closely related isogenic O/C, SIN, N/R and T, B. clausii strains during both exponential and stationary phases of growth. Image analysis of the electropherograms reveals a high degree of concordance among the four proteomes, some proteins result, however, differently expressed. The proteins spots exhibiting high different expression level were identified, by mass-spectrometry analysis, as alcohol dehydrogenase (ADHA, EC1.2.1.3; ABC0046 isoform) aldehyde dehydrogenase (DHAS, EC 1.2.1.3; ABC0047 isoform) and flagellin-protein of B. clausii KSM-k16. The different expression levels of the two dehydrogenases were confirmed by quantitative RT-PCR and dehydrogenases enzymatic activity. The different patterns of protein expression can be considered as cell proteome signatures of the different strains. PMID:21810490

  10. Peripheral Blood Cell Gene Expression Diagnostic for Identifying Symptomatic Transthyretin Amyloidosis Patients: Male and Female Specific Signatures

    PubMed Central

    Kurian, Sunil M.; Novais, Marta; Whisenant, Thomas; Gelbart, Terri; Buxbaum, Joel N.; Kelly, Jeffery W.; Coelho, Teresa; Salomon, Daniel R.

    2016-01-01

    Background: Early diagnosis of familial transthyretin (TTR) amyloid diseases remains challenging because of variable disease penetrance. Currently, patients must have an amyloid positive tissue biopsy to be eligible for disease-modifying therapies. Endomyocardial biopsies are typically amyloid positive when cardiomyopathy is suspected, but this disease manifestation is generally diagnosed late. Early diagnosis is often difficult because patients exhibit apparent symptoms of polyneuropathy, but have a negative amyloid biopsy. Thus, there is a pressing need for an additional early diagnostic strategy for TTR-aggregation-associated polyneuropathy and cardiomyopathy. Methods and Findings: Global peripheral blood cell mRNA expression profiles from 263 tafamidis-treated and untreated V30M Familiar Amyloid Neuropathy patients, asymptomatic V30M carriers, and healthy, age- and sex-matched controls without TTR mutations were used to differentiate symptomatic from asymptomatic patients. We demonstrate that blood cell gene expression patterns reveal sex-independent, as well as male- and female-specific inflammatory signatures in symptomatic FAP patients, but not in asymptomatic carriers. These signatures differentiated symptomatic patients from asymptomatic V30M carriers with >80% accuracy. There was a global downregulation of the eIF2 pathway and its associated genes in all symptomatic FAP patients. We also demonstrated that the molecular scores based on these signatures significantly trended toward normalized values in an independent cohort of 46 FAP patients after only 3 months of tafamidis treatment. Conclusions: This study identifies novel molecular signatures that differentiate symptomatic FAP patients from asymptomatic V30M carriers as well as affected males and females. We envision using this approach, initially in parallel with amyloid biopsies, to identify individuals who are asymptomatic gene carriers that may convert to FAP patients. Upon further validation

  11. Precise Predictions for Top-Quark-Plus-Missing-Energy Signatures at the LHC

    NASA Astrophysics Data System (ADS)

    Boughezal, Radja; Schulze, Markus

    2013-05-01

    We study the pair production of scalar top-quark partners decaying to a top-quark pair plus large missing energy at the LHC, a signature which appears in numerous models that address outstanding problems at the TeV scale. The severe experimental search cuts require a description which combines higher-order corrections to both production and decay dynamics for a realistic final state. We do this at next-to-leading order in QCD. We find large, kinematic-dependent QCD corrections that differ dramatically depending upon the observable under consideration, potentially impacting the search for and interpretation of these states.

  12. Expression of Polycomb Targets Predicts Breast Cancer Prognosis

    PubMed Central

    Jene-Sanz, Alba; Váraljai, Renáta; Vilkova, Alexandra V.; Khramtsova, Galina F.; Khramtsov, Andrey I.; Olopade, Olufunmilayo I.

    2013-01-01

    Global changes in the epigenome are increasingly being appreciated as key events in cancer progression. The pathogenic role of enhancer of zeste homolog 2 (EZH2) has been connected to its histone 3 lysine 27 (H3K27) methyltransferase activity and gene repression; however, little is known about relationship of changes in expression of EZH2 target genes to cancer characteristics and patient prognosis. Here we show that through expression analysis of genomic regions with H3K27 trimethylation (H3K27me3) and EZH2 binding, breast cancer patients can be stratified into good and poor prognostic groups independent of known cancer gene signatures. The EZH2-bound regions were downregulated in tumors characterized by aggressive behavior, high expression of cell cycle genes, and low expression of developmental and cell adhesion genes. Depletion of EZH2 in breast cancer cells significantly increased expression of the top altered genes, decreased proliferation, and improved cell adhesion, indicating a critical role played by EZH2 in determining the cancer phenotype. PMID:23918806

  13. EX-PRESS Glaucoma Filtration Device: efficacy, safety, and predictability

    PubMed Central

    Chan, Jessica E; Netland, Peter A

    2015-01-01

    Trabeculectomy has been the traditional primary surgical therapy for open-angle glaucoma. While trabeculectomy is effective in lowering intraocular pressure, complications associated with the procedure have motivated the development of alternative techniques and devices, including the EX-PRESS Glaucoma Filtration Device. This review describes the efficacy, safety, complication rates, and potential advantages and disadvantages of the EX-PRESS Glaucoma Filtration Device. EX-PRESS implantation is technically simpler compared with that of trabeculectomy, with fewer surgical steps. Vision recovery has been more rapid after EX-PRESS implantation compared with trabeculectomy. Intraocular pressure variation is lower during the early postoperative period, indicating a more predictable procedure. While efficacy of the EX-PRESS implant has been comparable to trabeculectomy, postoperative complications appear less common after EX-PRESS implantation compared with trabeculectomy. The EX-PRESS Glaucoma Filtration Device appears to be safe and effective in the surgical management of open-angle glaucoma. PMID:26366105

  14. Microbial Forensics: Predicting Phenotypic Characteristics and Environmental Conditions from Large-Scale Gene Expression Profiles

    PubMed Central

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-01-01

    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. PMID:25774498

  15. Diagnostic value of a plasma microRNA signature in gastric cancer: a microRNA expression analysis

    PubMed Central

    Zhou, Xin; Zhu, Wei; Li, Hai; Wen, Wei; Cheng, Wenfang; Wang, Fang; Wu, Yinxia; Qi, Lianwen; Fan, Yong; Chen, Yan; Ding, Yin; Xu, Jing; Qian, Jiaqi; Huang, Zebo; Wang, Tongshan; Zhu, Danxia; Shu, Yongqian; Liu, Ping

    2015-01-01

    The differential expression of microRNAs (miRNAs) in plasma of gastric cancer (GC) patients may serve as a diagnostic biomarker. A total of 33 miRNAs were identified through the initial screening phase (3 GC pools vs. 1 normal control (NC) pool) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based Exiqon panel (miRCURY-Ready-to-Use-PCR-Human-panel-I + II-V1.M). By qRT-PCR, these miRNAs were further assessed in training (30 GC VS. 30 NCs) and testing stages (71 GC VS. 61 NCs). We discovered a plasma miRNA signature including five up-regulated miRNAs (miR-185, miR-20a, miR-210, miR-25 and miR-92b), and this signature was evaluated to be a potential diagnostic marker of GC. The areas under the receiver operating characteristic curve of the signature were 0.86, 0.74 and 0.87 for the training, testing and the external validation stages (32 GC VS. 18 NCs), respectively. The five miRNAs were consistently dysregulated in GC tissues (n = 30). Moreover, miR-185 was decreased while miR-20a, miR-210 and miR-92b were increased in arterial plasma (n = 38). However, none of the miRNAs in the exosomes showed different expression between 10 GC patients and 10 NCs. In conclusion, we identified a five-miRNA signature in the peripheral plasma which could serve as a non-invasive biomarker in detection of GC. PMID:26059512

  16. LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures.

    PubMed

    Duan, Qiaonan; Flynn, Corey; Niepel, Mario; Hafner, Marc; Muhlich, Jeremy L; Fernandez, Nicolas F; Rouillard, Andrew D; Tan, Christopher M; Chen, Edward Y; Golub, Todd R; Sorger, Peter K; Subramanian, Aravind; Ma'ayan, Avi

    2014-07-01

    For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites. PMID:24906883

  17. Dynamic classification using case-specific training cohorts outperforms static gene expression signatures in breast cancer

    PubMed Central

    Győrffy, Balázs; Karn, Thomas; Sztupinszki, Zsófia; Weltz, Boglárka; Müller, Volkmar; Pusztai, Lajos

    2015-01-01

    The molecular diversity of breast cancer makes it impossible to identify prognostic markers that are applicable to all breast cancers. To overcome limitations of previous multigene prognostic classifiers, we propose a new dynamic predictor: instead of using a single universal training cohort and an identical list of informative genes to predict the prognosis of new cases, a case-specific predictor is developed for each test case. Gene expression data from 3,534 breast cancers with clinical annotation including relapse-free survival is analyzed. For each test case, we select a case-specific training subset including only molecularly similar cases and a case-specific predictor is generated. This method yields different training sets and different predictors for each new patient. The model performance was assessed in leave-one-out validation and also in 325 independent cases. Prognostic discrimination was high for all cases (n = 3,534, HR = 3.68, p = 1.67 E−56). The dynamic predictor showed higher overall accuracy (0.68) than genomic surrogates for Oncotype DX (0.64), Genomic Grade Index (0.61) or MammaPrint (0.47). The dynamic predictor was also effective in triple-negative cancers (n = 427, HR = 3.08, p = 0.0093) where the above classifiers all failed. Validation in independent patients yielded similar classification power (HR = 3.57). The dynamic classifier is available online at http://www.recurrenceonline.com/?q=Re_training. In summary, we developed a new method to make personalized prognostic prediction using case-specific training cohorts. The dynamic predictors outperform static models developed from single historical training cohorts and they also predict well in triple-negative cancers. PMID:25274406

  18. Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease

    PubMed Central

    Bouquet, Jerome; Soloski, Mark J.; Swei, Andrea; Cheadle, Chris; Federman, Scot; Billaud, Jean-Noel; Rebman, Alison W.; Kabre, Beniwende; Halpert, Richard; Boorgula, Meher

    2016-01-01

    ABSTRACT Lyme disease is a tick-borne illness caused by the bacterium Borrelia burgdorferi, and approximately 10 to 20% of patients report persistent symptoms lasting months to years despite appropriate treatment with antibiotics. To gain insights into the molecular basis of acute Lyme disease and the ensuing development of post-treatment symptoms, we conducted a longitudinal transcriptome study of 29 Lyme disease patients (and 13 matched controls) enrolled at the time of diagnosis and followed for up to 6 months. The differential gene expression signature of Lyme disease following the acute phase of infection persisted for at least 3 weeks and had fewer than 44% differentially expressed genes (DEGs) in common with other infectious or noninfectious syndromes. Early Lyme disease prior to antibiotic therapy was characterized by marked upregulation of Toll-like receptor signaling but lack of activation of the inflammatory T-cell apoptotic and B-cell developmental pathways seen in other acute infectious syndromes. Six months after completion of therapy, Lyme disease patients were found to have 31 to 60% of their pathways in common with three different immune-mediated chronic diseases. No differential gene expression signature was observed between Lyme disease patients with resolved illness to those with persistent symptoms at 6 months post-treatment. The identification of a sustained differential gene expression signature in Lyme disease suggests that a panel of selected human host-based biomarkers may address the need for sensitive clinical diagnostics during the “window period” of infection prior to the appearance of a detectable antibody response and may also inform the development of new therapeutic targets. PMID:26873097

  19. Penicillin-Binding Protein Transpeptidase Signatures for Tracking and Predicting β-Lactam Resistance Levels in Streptococcus pneumoniae

    PubMed Central

    Metcalf, Benjamin J.; Chochua, Sopio; Li, Zhongya; Gertz, Robert E.; Walker, Hollis; Hawkins, Paulina A.; Tran, Theresa; Whitney, Cynthia G.; McGee, Lesley; Beall, Bernard W.

    2016-01-01

    ABSTRACT β-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of β-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking β-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a “PBP type” based on sequence signatures in the transpeptidase domains (TPDs) of the three critical penicillin-binding proteins (PBPs), PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six β-lactams based on broth microdilution. We found that increased β-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to β-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution) of >98%, category agreement (interpretive results agree) of >94%, a major discrepancy (sensitive isolate predicted as resistant) rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive) rate of <2% for all six β-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different β-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing. PMID:27302760

  20. Signature changes in ubiquilin expression in the R6/2 mouse model of Huntington’s disease

    PubMed Central

    Safren, Nathaniel; Chang, Lydia; Dziki, Kristina M.; Monteiro, Mervyn J.

    2014-01-01

    Ubiquilin proteins have been implicated in the cause and the pathology of neurodegenerative diseases. In the R6/2 mouse model of Huntington’s disease (HD), ubiquilin levels decline during disease progression. Restoration of their levels by transgenic expression of ubiquilin-1 extends survival. Here we provide a comprehensive assessment of the expression and localization of all four ubiquilin proteins in both normal and R6/2-affected mice brains, using antibodies specific for each protein. Ubiquilin-1, 2 and 4 proteins were detected throughout the brain, with increased expression seen in the hippocampus and cerebellum. Ubiquilin-3 expression was not detected. All three ubiquilins expressed in the brain were found in Htt inclusions. Their expression changed during development and disease. Ubiquilin-1 and ubiquilin-2 protein levels decreased from 6 to 18 weeks of mouse development, independent of disease. Ubiquilin-1 and ubiquilin-4 protein levels also changed during HD disease progression. Ubiquilin-4 proteins that are normally expressed in the brain were lost and instead replaced by a novel 115 kDa higher molecular weight immunoreactive band. Taken together, our results demonstrate that all ubiquilin proteins are involved in HD pathology and that distinct changes in the signature of ubiquilin-4 expression could be useful for monitoring end-stage of HD disease. PMID:25511991

  1. A gene expression signature of emphysema-related lung destruction and its reversal by the tripeptide GHK

    PubMed Central

    2012-01-01

    Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease consisting of emphysema, small airway obstruction, and/or chronic bronchitis that results in significant loss of lung function over time. Methods In order to gain insights into the molecular pathways underlying progression of emphysema and explore computational strategies for identifying COPD therapeutics, we profiled gene expression in lung tissue samples obtained from regions within the same lung with varying amounts of emphysematous destruction from smokers with COPD (8 regions × 8 lungs = 64 samples). Regional emphysema severity was quantified in each tissue sample using the mean linear intercept (Lm) between alveolar walls from micro-CT scans. Results We identified 127 genes whose expression levels were significantly associated with regional emphysema severity while controlling for gene expression differences between individuals. Genes increasing in expression with increasing emphysematous destruction included those involved in inflammation, such as the B-cell receptor signaling pathway, while genes decreasing in expression were enriched in tissue repair processes, including the transforming growth factor beta (TGFβ) pathway, actin organization, and integrin signaling. We found concordant differential expression of these emphysema severity-associated genes in four cross-sectional studies of COPD. Using the Connectivity Map, we identified GHK as a compound that can reverse the gene-expression signature associated with emphysematous destruction and induce expression patterns consistent with TGFβ pathway activation. Treatment of human fibroblasts with GHK recapitulated TGFβ-induced gene-expression patterns, led to the organization of the actin cytoskeleton, and elevated the expression of integrin β1. Furthermore, addition of GHK or TGFβ restored collagen I contraction and remodeling by fibroblasts derived from COPD lungs compared to fibroblasts from former smokers without

  2. Predicting protein phosphorylation from gene expression: top methods from the IMPROVER Species Translation Challenge

    PubMed Central

    Biehl, Michael; Bilal, Erhan; Hormoz, Sahand; Meyer, Pablo; Norel, Raquel; Rhrissorrakrai, Kahn; Bhanot, Gyan; Luo, Feng; Tarca, Adi L.

    2015-01-01

    Motivation: Using gene expression to infer changes in protein phosphorylation levels induced in cells by various stimuli is an outstanding problem. The intra-species protein phosphorylation challenge organized by the IMPROVER consortium provided the framework to identify the best approaches to address this issue. Results: Rat lung epithelial cells were treated with 52 stimuli, and gene expression and phosphorylation levels were measured. Competing teams used gene expression data from 26 stimuli to develop protein phosphorylation prediction models and were ranked based on prediction performance for the remaining 26 stimuli. Three teams were tied in first place in this challenge achieving a balanced accuracy of about 70%, indicating that gene expression is only moderately predictive of protein phosphorylation. In spite of the similar performance, the approaches used by these three teams, described in detail in this article, were different, with the average number of predictor genes per phosphoprotein used by the teams ranging from 3 to 124. However, a significant overlap of gene signatures between teams was observed for the majority of the proteins considered, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched in the union of the predictor genes of the three teams for multiple proteins. Availability and implementation: Gene expression and protein phosphorylation data are available from ArrayExpress (E-MTAB-2091). Software implementation of the approach of Teams 49 and 75 are available at http://bioinformaticsprb.med.wayne.edu and http://people.cs.clemson.edu/∼luofeng/sbv.rar, respectively. Contact: gyanbhanot@gmail.com or luofeng@clemson.edu or atarca@med.wayne.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25061067

  3. Radar Differential Phase Signatures of Ice Orientation for the Prediction of Lightning Initiation and Cessation

    NASA Technical Reports Server (NTRS)

    Carey, L.D.; Petersen, W.A.; Deierling, W.

    2009-01-01

    other co-polar back-scattering radar measurements like differential reflectivity (Z(sub dr)) typically measured by operational dual-polarimetric radars are not sensitive to these changes in ice crystal orientation. However, prior research has demonstrated that oriented ice crystals cause significant propagation effects that can be routinely measured by most dual-polarimetric radars from X-band (3 cm) to S-band (10 cm) wavelengths using the differential propagation phase shift (often just called differential phase, phi(sub dp)) or its range derivative, the specific differential phase (K(sub dp)). Advantages of the differential phase include independence from absolute or relative power calibration, attenuation, differential attenuation and relative insensitivity to ground clutter and partial beam occultation effects (as long as the signal remains above noise). In research mode, these sorts of techniques have been used to anticipate initial cloud electrification, lightning initiation, and cessation. In this study, we develop a simplified model of ice crystal size, shape, orientation, dielectric, and associated radar scattering and propagation effects in order to simulate various idealized scenarios of ice crystals responding to a hypothetical electric field and their dual-polarimetric radar signatures leading up to lightning initiation and particularly cessation. The sensitivity of the K(sub dp) ice orientation signature to various ice properties and radar wavelength will be explored. Since K(sub dp) is proportional to frequency in the Rayleigh- Gans scattering regime, the ice orientation signatures should be more obvious at higher (lower) frequencies (wavelengths). As a result, simulations at radar wavelengths from 10 cm down to 1 cm (Ka-band) will be conducted. Resonance effects will be considered using the T-matrix method. Since most K(sub dp) Vbased observations have been shown at S-band, we will present ice orientation signatures from C-band (UAH/NASA ARMOR) and X

  4. Transcriptome profiling reveals novel gene expression signatures and regulating transcription factors of TGFβ-induced epithelial-to-mesenchymal transition.

    PubMed

    Du, Liutao; Yamamoto, Shota; Burnette, Barry L; Huang, Danshang; Gao, Kun; Jamshidi, Neema; Kuo, Michael D

    2016-08-01

    Dysregulated epithelial to mesenchymal transition (EMT) in cancer cells endows invasive and metastatic properties upon cancer cells that favor successful colonization of distal target organs and therefore play a critical role in transforming early-stage carcinomas into invasive malignancies. EMT has also been associated with tumor recurrence and drug resistance and cancer stem cell initiation. Therefore, better understanding of the mechanisms behind EMT could ultimately contribute to the development of novel prognostic approaches and individualized therapies that specifically target EMT processes. As an effort to characterize the central transcriptome changes during EMT, we have developed a Transforming growth factor (TGF)-beta-based in vitro EMT model and used it to profile EMT-related gene transcriptional changes in two different cell lines, a non-small cell lung cancer cell line H358, and a breast cell line MCF10a. After 7 days of TGF-beta/Oncostatin M (OSM) treatment, changes in cell morphology to a mesenchymal phenotype were observed as well as concordant EMT-associated changes in mRNA and protein expression. Further, increased motility was noted and flow cytometry confirmed enrichment in cancer stem cell-like populations. Microarray-based differential expression analysis identified an EMT-associated gene expression signature which was confirmed by RT-qPCR and which significantly overlapped with a previously published EMT core signature. Finally, two novel EMT-regulating transcription factors, IRF5 and LMCD1, were identified and independently validated. PMID:27318801

  5. A Gene Expression and Pre-mRNA Splicing Signature That Marks the Adenoma-Adenocarcinoma Progression in Colorectal Cancer

    PubMed Central

    Pesson, Marine; Volant, Alain; Uguen, Arnaud; Trillet, Kilian; De La Grange, Pierre; Aubry, Marc; Daoulas, Mélanie; Robaszkiewicz, Michel; Le Gac, Gérald; Morel, Alain; Simon, Brigitte; Corcos, Laurent

    2014-01-01

    It is widely accepted that most colorectal cancers (CRCs) arise from colorectal adenomas (CRAs), but transcriptomic data characterizing the progression from colorectal normal mucosa to adenoma, and then to adenocarcinoma are scarce. These transition steps were investigated using microarrays, both at the level of gene expression and alternative pre-mRNA splicing. Many genes and exons were abnormally expressed in CRAs, even more than in CRCs, as compared to normal mucosae. Known biological pathways involved in CRC were altered in CRA, but several new enriched pathways were also recognized, such as the complement and coagulation cascades. We also identified four intersectional transcriptional signatures that could distinguish CRAs from normal mucosae or CRCs, including a signature of 40 genes differentially deregulated in both CRA and CRC samples. A majority of these genes had been described in different cancers, including FBLN1 or INHBA, but only a few in CRC. Several of these changes were also observed at the protein level. In addition, 20% of these genes (i.e. CFH, CRYAB, DPT, FBLN1, ITIH5, NR3C2, SLIT3 and TIMP1) showed altered pre-mRNA splicing in CRAs. As a global variation occurring since the CRA stage, and maintained in CRC, the expression and splicing changes of this 40-gene set may mark the risk of cancer occurrence from analysis of CRA biopsies. PMID:24516561

  6. Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging

    PubMed Central

    Fernandes, Armando; Vinga, Susana

    2016-01-01

    The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields predictions that surpass those of PLS. It is shown that it is possible to improve the models predictive ability by using two more input features, codon identification number and codon count, besides the already used codon bias and minimum free energy. In addition, applying ensemble averaging to the SVR or PLS models also improves the results even further. The present work motivates the test of different ensembles and features with the aim of improving the prediction models whose correlation coefficients are still far from perfect. These results are relevant for the optimization of codon usage and enhancement of protein expression levels in synthetic biology problems. PMID:26934190

  7. Isotopic Signature Transfer and Mass Pattern Prediction (IsoStamp): An Enabling Technique for Chemically-Directed Proteomics

    PubMed Central

    2011-01-01

    Directed proteomics applies mass spectrometry analysis to a subset of information-rich proteins. Here we describe a method for targeting select proteins by chemical modification with a tag that imparts a distinct isotopic signature detectable in a full-scan mass spectrum. Termed isotopic signature transfer and mass pattern prediction (IsoStamp), the technique exploits the perturbing effects of a dibrominated chemical tag on a peptide’s mass envelope, which can be detected with high sensitivity and fidelity using a computational method. Applying IsoStamp, we were able to detect femtomole quantities of a single tagged protein from total mammalian cell lysates at signal-to-noise ratios as low as 2.5:1. To identify a tagged-peptide’s sequence, we performed an inclusion list-driven shotgun proteomics experiment where peptides bearing a recoded mass envelope were targeted for fragmentation, allowing for direct site mapping. Using this approach, femtomole quantities of several targeted peptides were identified in total mammalian cell lysate, while traditional data-dependent methods were unable to identify as many peptides. Additionally, the isotopic signature imparted by the dibromide tag was detectable on a 12-kDa protein, suggesting applications in identifying large peptide fragments, such as those containing multiple or large posttranslational modifications (e.g., glycosylation). IsoStamp has the potential to enhance any proteomics platform that employs chemical labeling for targeted protein identification, including isotope coded affinity tagging, isobaric tagging for relative and absolute quantitation, and chemical tagging strategies for posttranslational modification. PMID:21604797

  8. Expression of Cell Competition Markers at the Interface between p53 Signature and Normal Epithelium in the Human Fallopian Tube

    PubMed Central

    Kito, Masahiko; Maeda, Daichi; Kudo-Asabe, Yukitsugu; Sato, Naoki; Shih, Ie-Ming; Wang, Tian-Li; Tanaka, Masamitsu; Terada, Yukihiro; Goto, Akiteru

    2016-01-01

    There is a growing body of evidence regarding cell competition between normal and mutant mammalian cells, which suggest that it may play a defensive role in the early phase of carcinogenesis. In vitro study in the past has shown that overexpression of vimentin in normal epithelial cells at the contact surface with transformed cells is essential for the cell competition involved in epithelial defense against cancer. In this study, we attempted to examine cell competition in human tissue in vivo by investigating surgically resected human fallopian tubes that contain p53 signatures and serous tubal intraepithelial lesions (STILs), a linear expansion of p53-immunopositive/TP53 mutant tubal epithelial cells that are considered as precursors of pelvic high grade serous carcinoma. Immunofluorescence double staining for p53 and the cell competition marker vimentin was performed in 21 sections of human fallopian tube tissue containing 17 p53 signatures and 4 STILs. The intensities of vimentin expression at the interface between p53-positive cells at the end of the p53 signature/STIL and adjacent p53-negative normal tubal epithelial cells were compared with the background tubal epithelium. As a result, the average vimentin intensity at the interfaces relative to the background intensity was 1.076 (95% CI, 0.9412 – 1.211 for p53 signature and 0.9790 (95% CI, 0.7206 – 1.237) for STIL. Thus, it can be concluded that overexpression of the cell competition marker vimentin are not observed in human tissue with TP53 alterations. PMID:27258067

  9. RepurposeVS: A Drug Repurposing-Focused Computational Method for Accurate Drug-Target Signature Predictions.

    PubMed

    Issa, Naiem T; Peters, Oakland J; Byers, Stephen W; Dakshanamurthy, Sivanesan

    2015-01-01

    We describe here RepurposeVS for the reliable prediction of drug-target signatures using X-ray protein crystal structures. RepurposeVS is a virtual screening method that incorporates docking, drug-centric and protein-centric 2D/3D fingerprints with a rigorous mathematical normalization procedure to account for the variability in units and provide high-resolution contextual information for drug-target binding. Validity was confirmed by the following: (1) providing the greatest enrichment of known drug binders for multiple protein targets in virtual screening experiments, (2) determining that similarly shaped protein target pockets are predicted to bind drugs of similar 3D shapes when RepurposeVS is applied to 2,335 human protein targets, and (3) determining true biological associations in vitro for mebendazole (MBZ) across many predicted kinase targets for potential cancer repurposing. Since RepurposeVS is a drug repurposing-focused method, benchmarking was conducted on a set of 3,671 FDA approved and experimental drugs rather than the Database of Useful Decoys (DUDE) so as to streamline downstream repurposing experiments. We further apply RepurposeVS to explore the overall potential drug repurposing space for currently approved drugs. RepurposeVS is not computationally intensive and increases performance accuracy, thus serving as an efficient and powerful in silico tool to predict drug-target associations in drug repurposing. PMID:26234515

  10. Radar Differential Phase Signatures of Ice Orientation for the Prediction of Lightning Initiation and Cessation

    NASA Technical Reports Server (NTRS)

    Carey, L.D.; Petersen, W.A.; Deierling, W.

    2009-01-01

    other co-polar back-scattering radar measurements like differential reflectivity (Z(sub dr)) typically measured by operational dual-polarimetric radars are not sensitive to these changes in ice crystal orientation. However, prior research has demonstrated that oriented ice crystals cause significant propagation effects that can be routinely measured by most dual-polarimetric radars from X-band (3 cm) to S-band (10 cm) wavelengths using the differential propagation phase shift (often just called differential phase, phi(sub dp)) or its range derivative, the specific differential phase (K(sub dp)). Advantages of the differential phase include independence from absolute or relative power calibration, attenuation, differential attenuation and relative insensitivity to ground clutter and partial beam occultation effects (as long as the signal remains above noise). In research mode, these sorts of techniques have been used to anticipate initial cloud electrification, lightning initiation, and cessation. In this study, we develop a simplified model of ice crystal size, shape, orientation, dielectric, and associated radar scattering and propagation effects in order to simulate various idealized scenarios of ice crystals responding to a hypothetical electric field and their dual-polarimetric radar signatures leading up to lightning initiation and particularly cessation. The sensitivity of the K(sub dp) ice orientation signature to various ice properties and radar wavelength will be explored. Since K(sub dp) is proportional to frequency in the Rayleigh- Gans scattering regime, the ice orientation signatures should be more obvious at higher (lower) frequencies (wavelengths). As a result, simulations at radar wavelengths from 10 cm down to 1 cm (Ka-band) will be conducted. Resonance effects will be considered using the T-matrix method. Since most K(sub dp) Vbased observations have been shown at S-band, we will present ice orientation signatures from C-band (UAH/NASA ARMOR) and X

  11. ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (S)

    EPA Science Inventory

    ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

  12. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    PubMed

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P < 0.0001). We further built a least absolute shrinkage and selection operator (LASSO)-Cox proportional hazards model that stratified patients into early relapse and late relapse groups (P = 0.00013). The top proteomic features indicative of platinum response were involved in ATP synthesis pathways and Ran GTPase binding. Overall, we demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  13. Germline genes hypomethylation and expression define a molecular signature in peripheral blood of ICF patients: implications for diagnosis and etiology

    PubMed Central

    2014-01-01

    Background Immunodeficiency Centromeric Instability and Facial anomalies (ICF) is a rare autosomal recessive disease characterized by reduction in serum immunoglobulins with severe recurrent infections, facial dysmorphism, and more variable symptoms including mental retardation. ICF is directly related to a genomic methylation defect that mainly affects juxtacentromeric heterochromatin regions of certain chromosomes, leading to chromosomal rearrangements that constitute a hallmark of this syndrome upon cytogenetic testing. Mutations in the de novo DNA methyltransferase DNMT3B, the protein ZBTB24 of unknown function, or loci that remain to be identified, lie at its origin. Despite unifying features, common or distinguishing molecular signatures are still missing for this disease. Method We used the molecular signature that we identified in a mouse model for ICF1 to establish transcriptional biomarkers to facilitate diagnosis and understanding of etiology of the disease. We assayed the expression and methylation status of a set of genes whose expression is normally restricted to germ cells, directly in whole blood samples and epithelial cells of ICF patients. Results We report that DNA hypomethylation and expression of MAEL and SYCE1 represent robust biomarkers, easily testable directly from uncultured cells to diagnose the most prevalent sub-type of the syndrome. In addition, we identified the first unifying molecular signatures for ICF patients. Of importance, we validated the use of our biomarkers to diagnose a baby born to a family with a sick child. Finally, our analysis revealed unsuspected complex molecular signatures in two ICF patients suggestive of a novel genetic etiology for the disease. Conclusions Early diagnosis of ICF syndrome is crucial since early immunoglobulin supplementation can improve the course of disease. However, ICF is probably underdiagnosed, especially in patients that present with incomplete phenotype or born to families with no affected

  14. Signature MicroRNA expression patterns identified in humans with 22q11.2 deletion/DiGeorge syndrome

    PubMed Central

    de la Morena, M. Teresa; Eitson, Jennifer L.; Dozmorov, Igor M.; Belkaya, Serkan; Hoover, Ashley R.; Anguiano, Esperanza; Pascual, M. Virginia; van Oers, Nicolai S.C.

    2013-01-01

    Patients with 22q11.2 deletion syndrome have heterogeneous clinical presentations including immunodeficiency, cardiac anomalies, and hypocalcemia. The syndrome arises from hemizygous deletions of up to 3 Mb on chromosome 22q11.2, a region that contains 60 genes and 4 microRNAs. MicroRNAs are important post-transcriptional regulators of gene expression, with mutations in several microRNAs causal to specific human diseases. We characterized the microRNA expression patterns in the peripheral blood of patients with 22q11.2 deletion syndrome (n=31) compared to normal controls (n=22). Eighteen microRNAs had a statistically significant differential expression (p<0.05), with miR-185 expressed at 0.4× normal levels. The 22q11.2 deletion syndrome cohort exhibited microRNA expression hyper-variability and group dysregulation. Selected microRNAs distinguished patients with cardiac anomalies, hypocalcemia, and/or low circulating T cell counts. In summary, microRNA profiling of chromosome 22q11.2 deletion syndrome/DiGeorge patients revealed a signature microRNA expression pattern distinct from normal controls with clinical relevance. PMID:23454892

  15. Myeloid cell signatures in tumor microenvironment predicts therapeutic response in cancer

    PubMed Central

    Achyut, Bhagelu R; Arbab, Ali S

    2016-01-01

    Tumor microenvironment (TME) consists of several immune and nonimmune cell populations including tumor cells. For many decades, experimental studies have depicted profound contribution of TME toward cancer progression and metastasis development. Several therapeutic strategies have been tested against TME through preclinical studies and clinical trials. Unfortunately, most of them have shown transient effect, and have largely failed due to aggressive tumor growth and without improving survival. Solid tumors are known to have a strong myeloid component (eg, tumor-associated macrophages) in tumor development. Recent data suggest that therapeutic responses in tumor are characterized by alterations in immune cell signatures, including tumor-associated myeloid cells. Polarized tumor-associated myeloid cells (M1–M2) are critical in impairing therapeutic effect and promoting tumor growth. The present review is intended to compile all the literatures related to the emerging contribution of different populations of myeloid cells in the development of tumor and therapeutic failures. Finally, we have discussed targeting of myeloid cell populations as a combination therapy with chemo-, targeted-, or radiation therapies. PMID:27042097

  16. Immune-related gene signatures predict the outcome of neoadjuvant chemotherapy

    PubMed Central

    Stoll, Gautier; Enot, David; Mlecnik, Bernhard; Galon, Jérôme; Zitvogel, Laurence; Kroemer, Guido

    2014-01-01

    There is ample evidence that neoadjuvant chemotherapy of breast carcinoma is particularly efficient if the tumor presents signs of either a pre-existent or therapy-induced anticancer immune response. Antineoplastic chemotherapies are particularly beneficial if they succeed in inducing immunogenic cell death, hence converting the tumor into its own therapeutic vaccine. Immunogenic cell death is characterized by a pre-mortem stress response including endoplasmic reticulum stress and autophagy. Based on these premises, we attempted to identify metagenes that reflect an intratumoral immune response or local stress responses in the transcriptomes of breast cancer patients. No consistent correlations between immune- and stress-related metagenes could be identified across several cohorts of patients, representing a total of 1045 mammary carcinomas. Moreover, few if any, of the stress-relevant metagenes influenced the probability of pathological complete response to chemotherapy. In contrast, several immune-relevant metagenes had a significant positive impact on response rates. This applies in particular to a CXCL13-centered, highly reproducible metagene signature reflecting the intratumoral presence of interferon-γ-producing T cells. PMID:24790795

  17. Pharmacologic inhibition of RORγt regulates Th17 signature gene expression and suppresses cutaneous inflammation in vivo.

    PubMed

    Skepner, Jill; Ramesh, Radha; Trocha, Mark; Schmidt, Darby; Baloglu, Erkan; Lobera, Mercedes; Carlson, Thaddeus; Hill, Jonathan; Orband-Miller, Lisa A; Barnes, Ashley; Boudjelal, Mohamed; Sundrud, Mark; Ghosh, Shomir; Yang, Jianfei

    2014-03-15

    IL-17-producing CD4(+)Th17 cells, CD8(+)Tc17 cells, and γδ T cells play critical roles in the pathogenesis of autoimmune psoriasis. RORγt is required for the differentiation of Th17 cells and expression of IL-17. In this article, we describe a novel, potent, and selective RORγt inverse agonist (TMP778), and its inactive diastereomer (TMP776). This chemistry, for the first time to our knowledge, provides a unique and powerful set of tools to probe RORγt-dependent functions. TMP778, but not TMP776, blocked human Th17 and Tc17 cell differentiation and also acutely modulated IL-17A production and inflammatory Th17-signature gene expression (Il17a, Il17f, Il22, Il26, Ccr6, and Il23) in mature human Th17 effector/memory T cells. In addition, TMP778, but not TMP776, inhibited IL-17A production in both human and mouse γδ T cells. IL-23-induced IL-17A production was also blocked by TMP778 treatment. In vivo targeting of RORγt in mice via TMP778 administration reduced imiquimod-induced psoriasis-like cutaneous inflammation. Further, TMP778 selectively regulated Th17-signature gene expression in mononuclear cells isolated from both the blood and affected skin of psoriasis patients. In summary, to our knowledge, we are the first to demonstrate that RORγt inverse agonists: 1) inhibit Tc17 cell differentiation, as well as IL-17 production by γδ T cells and CD8(+) Tc17 cells; 2) block imiquimod-induced cutaneous inflammation; 3) inhibit Th17 signature gene expression by cells isolated from psoriatic patient samples; and 4) block IL-23-induced IL-17A expression. Thus, RORγt is a tractable drug target for the treatment of cutaneous inflammatory disorders, which may afford additional therapeutic benefit over existing modalities that target only IL-17A. PMID:24516202

  18. Dual RNA Sequencing Reveals the Expression of Unique Transcriptomic Signatures in Lipopolysaccharide-Induced BV-2 Microglial Cells

    PubMed Central

    Kim, Sun Hwa; Park, Kyoung Sun; Lee, Young Seek; Jung, Kyoung Hwa; Chai, Young Gyu

    2015-01-01

    Microglial cells become rapidly activated through interactions with pathogens, and the persistent activation of these cells is associated with various neurodegenerative diseases. Previous studies have investigated the transcriptomic signatures in microglia or macrophages using microarray technologies. However, this method has numerous restrictions, such as spatial biases, uneven probe properties, low sensitivity, and dependency on the probes spotted. To overcome this limitation and identify novel transcribed genes in response to LPS, we used RNA Sequencing (RNA-Seq) to determine the novel transcriptomic signatures in BV-2 microglial cells. Sequencing assessment and quality evaluation showed that approximately 263 and 319 genes (≥ 1.5 log2-fold), such as cytokines and chemokines, were strongly induced after 2 and 4 h, respectively, and the induction of several genes with unknown immunological functions was also observed. Importantly, we observed that previously unidentified transcription factors (TFs) (irf1, irf7, and irf9), histone demethylases (kdm4a) and DNA methyltransferases (dnmt3l) were significantly and selectively expressed in BV-2 microglial cells. The gene expression levels, transcription start sites (TSS), isoforms, and differential promoter usage revealed a complex pattern of transcriptional and post-transcriptional gene regulation upon infection with LPS. In addition, gene ontology, molecular networks and pathway analyses identified the top significantly regulated functional classification, canonical pathways and network functions at each activation status. Moreover, we further analyzed differentially expressed genes to identify transcription factor (TF) motifs (−950 to +50 bp of the 5’ upstream promoters) and epigenetic mechanisms. Furthermore, we confirmed that the expressions of key inflammatory genes as well as pro-inflammatory mediators in the supernatants were significantly induced in LPS treated primary microglial cells. This

  19. An Encapsulation of Gene Signatures for Hepatocellular Carcinoma, MicroRNA-132 Predicted Target Genes and the Corresponding Overlaps

    PubMed Central

    Chen, Gang; Ren, Fanghui; Liang, Haiwei; Dang, Yiwu; Rong, Minhua

    2016-01-01

    Objectives Previous studies have demonstrated that microRNA-132 plays a vital part in and is actively associated with several cancers, with its tumor-suppressive role in hepatocellular carcinoma confirmed. The current study employed multiple bioinformatics techniques to establish gene signatures for hepatocellular carcinoma, microRNA-132 predicted target genes and the corresponding overlaps. Methods Various assays were performed to explore the role and cellular functions of miR-132 in HCC and a successive panel of tasks was completed, including NLP analysis, miR-132 target genes prediction, comprehensive analyses (gene ontology analysis, pathway analysis, network analysis and connectivity analysis), and analytical integration. Later, HCC-related and miR-132-related potential targets, pathways, networks and highlighted hub genes were revealed as well as those of the overlapped section. Results MiR-132 was effective in both impeding cell growth and boosting apoptosis in HCC cell lines. A total of fifty-nine genes were obtained from the analytical integration, which were considered to be both HCC- and miR-132-related. Moreover, four specific pathways were unveiled in the network analysis of the overlaps, i.e. adherens junction, VEGF signaling pathway, neurotrophin signaling pathway, and MAPK signaling pathway. Conclusions The tumor-suppressive role of miR-132 in HCC has been further confirmed by in vitro experiments. Gene signatures in the study identified the potential molecular mechanisms of HCC, miR-132 and their established associations, which might be effective for diagnosis, individualized treatments and prognosis of HCC patients. However, combined detections of miR-132 with other bio-indicators in clinical practice and further in vitro experiments are needed. PMID:27467251

  20. Keratinocyte Growth Factor Induces Gene Expression Signature Associated with Suppression of Malignant Phenotype of Cutaneous Squamous Carcinoma Cells

    PubMed Central

    Toriseva, Mervi; Ala-aho, Risto; Peltonen, Sirkku; Peltonen, Juha; Grénman, Reidar; Kähäri, Veli-Matti

    2012-01-01

    Keratinocyte growth factor (KGF, fibroblast growth factor-7) is a fibroblast-derived mitogen, which stimulates proliferation of epithelial cells. The expression of KGF by dermal fibroblasts is induced following injury and it promotes wound repair. However, the role of KGF in cutaneous carcinogenesis and cancer progression is not known. We have examined the role of KGF in progression of squamous cell carcinoma (SCC) of the skin. The expression of KGF receptor (KGFR) mRNA was lower in cutaneous SCCs (n = 6) than in normal skin samples (n = 6). Expression of KGFR mRNA was detected in 6 out of 8 cutaneous SCC cell lines and the levels were downregulated by 24-h treatment with KGF. KGF did not stimulate SCC cell proliferation, but it reduced invasion of SCC cells through collagen. Gene expression profiling of three cutaneous SCC cell lines treated with KGF for 24 h revealed a specific gene expression signature characterized by upregulation of a set of genes specifically downregulated in SCC cells compared to normal epidermal keratinocytes, including genes with tumor suppressing properties (SPRY4, DUSP4, DUSP6, LRIG1, PHLDA1). KGF also induced downregulation of a set of genes specifically upregulated in SCC cells compared to normal keratinocytes, including genes associated with tumor progression (MMP13, MATN2, CXCL10, and IGFBP3). Downregulation of MMP-13 and KGFR expression in SCC cells and HaCaT cells was mediated via ERK1/2. Activation of ERK1/2 in HaCaT cells and tumorigenic Ha-ras-transformed HaCaT cells resulted in downregulation of MMP-13 and KGFR expression. These results provide evidence, that KGF does not promote progression of cutaneous SCC, but rather suppresses the malignant phenotype of cutaneous SCC cells by regulating the expression of several genes differentially expressed in SCC cells, as compared to normal keratinocytes. PMID:22427941

  1. Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures.

    PubMed

    Eipel, Monika; Mayer, Felix; Arent, Tanja; Ferreira, Marcelo R P; Birkhofer, Carina; Gerstenmaier, Uwe; Costa, Ivan G; Ritz-Timme, Stefanie; Wagner, Wolfgang

    2016-05-01

    Aging is reflected by highly reproducible DNA methylation (DNAm) changes that open new perspectives for estimation of chronological age in legal medicine. DNA can be harvested non-invasively from cells at the inside of a person's cheek using buccal swabs - but these specimens resemble heterogeneous mixtures of buccal epithelial cells and leukocytes with different epigenetic makeup. In this study, we have trained an age predictor based on three age-associated CpG sites (associated with the genesPDE4C, ASPA, and ITGA2B) for swab samples to reach a mean absolute deviation (MAD) between predicted and chronological age of 4.3 years in a training set and of 7.03 years in a validation set. Subsequently, the composition of buccal epithelial cells versus leukocytes was estimated by two additional CpGs (associated with the genes CD6 and SERPINB5). Results of this "Buccal-Cell-Signature" correlated with cell counts in cytological stains (R2 = 0.94). Combination of cell type-specific and age-associated CpGs into one multivariate model enabled age predictions with MADs of 5.09 years and 5.12 years in two independent validation sets. Our results demonstrate that the cellular composition in buccal swab samples can be determined by DNAm at two cell type-specific CpGs to improve epigenetic age predictions. PMID:27249102

  2. Gene promoter methylation signature predicts survival of head and neck squamous cell carcinoma patients.

    PubMed

    Kostareli, Efterpi; Hielscher, Thomas; Zucknick, Manuela; Baboci, Lorena; Wichmann, Gunnar; Holzinger, Dana; Mücke, Oliver; Pawlita, Michael; Del Mistro, Annarosa; Boscolo-Rizzo, Paolo; Da Mosto, Maria Cristina; Tirelli, Giancarlo; Plinkert, Peter; Dietz, Andreas; Plass, Christoph; Weichenhan, Dieter; Hess, Jochen

    2016-01-01

    Infection with high-risk types of human papilloma virus (HPV) is currently the best-established prognostic marker for head and neck squamous cell carcinoma (HNSCC), one of the most common and lethal human malignancies worldwide. Clinical trials have been launched to address the concept of treatment de-escalation for HPV-positive HNSCC with the final aim to reduce treatment related toxicity and debilitating long-term impacts on the quality of life. However, HPV-related tumors are mainly restricted to oropharyngeal SCC (OPSCC) and there is an urgent need to establish reliable biomarkers for all patients at high risk for treatment failure. A patient cohort (n = 295) with mainly non-OPSCC (72.9%) and a low prevalence of HPV16-related tumors (8.8%) was analyzed by MassARRAY to determine a previously established prognostic methylation score (MS). Kaplan-Meier revealed a highly significant correlation between a high MS and a favorable survival for OPSCC (P = 0.0004) and for non-OPSCC (P<0.0001), which was confirmed for all HNSCC by multivariate Cox regression models (HR: 9.67, 95% CI [4.61-20.30], P<0.0001). Next, we established a minimal methylation signature score (MMSS), which consists of ten most informative of the originally 62 CpG units used for the MS. The prognostic value of the MMSS was confirmed by Kaplan-Meier analysis for all HNSCC (P<0.0001) and non-OPSCC (P = 0.0002), and was supported by multivariate Cox regression models for all HNSCC (HR: 2.15, 95% CI [1.36-3.41], P = 0.001). In summary, the MS and the MMSS exhibit an excellent performance as prognosticators for survival, which is not limited by the anatomical site, and both could be implemented in future clinical trials. PMID:26786582

  3. An Integrative Model of miRNA and mRNA Expression Signature for Patients of Breast Invasive Carcinoma with Radiotherapy Prognosis.

    PubMed

    Bing, Zhitong; Tian, Jinhui; Zhang, Jingyun; Li, Xiuxia; Wang, Xiaohu; Yang, Kehu

    2016-09-01

    Radiotherapy is widely used in breast cancer treatment. The radiotherapy for breast invasive carcinoma (BRCA) presents challenges with the complex clinical factors, and too many genes have been found to be associated with BRCA radiotherapy prognosis. The aim of this study was to construct an integrative model to combine the clinical data and RNA expression data (including microRNA and mRNA) to predict the survival durations of BRCA patients with radiotherapy. Also, the authors try to find the key regulation pairs between mRNA and miRNA from prediction. They collected mRNA and microRNA expression profiles and gathered the corresponding clinical data of 73 BRCA patients with radiotherapy from The Cancer Genome Atlas (TCGA). According to an integrative model from univariate Cox regression between RNA expression and patient survival, they classified the patients with radiotherapy into low-risk and high-risk groups. The results showed that nine mRNAs were considered as protective genes and five miRNAs and eight mRNAs were considered as high-risk genes. Moreover, the high-risk group has a significantly shorter survival time in comparison with the low-risk group by the log-rank test (p = 0.0039). The reliability of the gene signature was validated by an independent data set from the Gene Expression Omnibus (GEO). Furthermore, three pairs of miRNA-mRNA, closely associated to survival, were identified. These findings and method may prove valuable for improving the clinical management of BRCA patients with radiotherapy. PMID:27610468

  4. Predictive Signatures of Developmental Toxicity Modeled with HTS Data from ToxCast™ Bioactivity Profiles

    EPA Science Inventory

    The EPA ToxCast™ research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I contains 309 well-characterized chemicals which are mostly pesticides tested in over 600 assays of different molecular targets, cel...

  5. Predictive Signatures from ToxCast Data for Chronic, Developmental and Reproductive Toxicity Endpoints

    EPA Science Inventory

    The EPA ToxCast program is using in vitro assay data and chemical descriptors to build predictive models for in vivo toxicity endpoints. In vitro assays measure activity of chemicals against molecular targets such as enzymes and receptors (measured in cell-free and cell-based sys...

  6. Developing Predictive Toxicity Signatures Using In Vitro Data from the EPA ToxCast Program

    EPA Science Inventory

    A major focus in toxicology research is the development of in vitro methods to predict in vivo chemical toxicity. Numerous studies have evaluated the use of targeted biochemical, cell-based and genomic assay approaches. Each of these techniques is potentially helpful, but provide...

  7. Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival

    PubMed Central

    von Rundstedt, Friedrich-Carl; Rajapakshe, Kimal; Ma, Jing; Arnold, James M.; Gohlke, Jie; Putluri, Vasanta; Krishnapuram, Rashmi; Piyarathna, D. Badrajee; Lotan, Yair; Gödde, Daniel; Roth, Stephan; Störkel, Stephan; Levitt, Jonathan M.; Michailidis, George; Sreekumar, Arun; Lerner, Seth P.; Coarfa, Cristian; Putluri, Nagireddy

    2016-01-01

    Purpose We used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis gene signature would have a predictive value in independent cohorts of patients with bladder cancer. Materials and Methods Pathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differential metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival. Results We identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p = 0.0458). Conclusions Targeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression. PMID:26802582

  8. Long non-coding RNA SOX2OT: expression signature, splicing patterns, and emerging roles in pluripotency and tumorigenesis

    PubMed Central

    Shahryari, Alireza; Jazi, Marie Saghaeian; Samaei, Nader M.; Mowla, Seyed J.

    2015-01-01

    SOX2 overlapping transcript (SOX2OT) is a long non-coding RNA which harbors one of the major regulators of pluripotency, SOX2 gene, in its intronic region. SOX2OT gene is mapped to human chromosome 3q26.3 (Chr3q26.3) locus and is extended in a high conserved region of over 700 kb. Little is known about the exact role of SOX2OT; however, recent studies have demonstrated a positive role for it in transcription regulation of SOX2 gene. Similar to SOX2, SOX2OT is highly expressed in embryonic stem cells and down-regulated upon the induction of differentiation. SOX2OT is dynamically regulated during the embryogenesis of vertebrates, and delimited to the brain in adult mice and human. Recently, the disregulation of SOX2OT expression and its concomitant expression with SOX2 have become highlighted in some somatic cancers including esophageal squamous cell carcinoma, lung squamous cell carcinoma, and breast cancer. Interestingly, SOX2OT is differentially spliced into multiple mRNA-like transcripts in stem and cancer cells. In this review, we are describing the structural and functional features of SOX2OT, with an emphasis on its expression signature, its splicing patterns and its critical function in the regulation of SOX2 expression during development and tumorigenesis. PMID:26136768

  9. 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

  10. 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

  11. Expression of Tumor Necrosis Factor-Alpha-Mediated Genes Predicts Recurrence-Free Survival in Lung Cancer

    PubMed Central

    Zhou, Lianya; Zhang, Helin; Duan, Lin; He, Wenshu; Zhu, Yihua; Bai, Yunfei; Zhu, Miao

    2014-01-01

    In this study, we conducted a meta-analysis on high-throughput gene expression data to identify TNF-α-mediated genes implicated in lung cancer. We first investigated the gene expression profiles of two independent TNF-α/TNFR KO murine models. The EGF receptor signaling pathway was the top pathway associated with genes mediated by TNF-α. After matching the TNF-α-mediated mouse genes to their human orthologs, we compared the expression patterns of the TNF-α-mediated genes in normal and tumor lung tissues obtained from humans. Based on the TNF-α-mediated genes that were dysregulated in lung tumors, we developed a prognostic gene signature that effectively predicted recurrence-free survival in lung cancer in two validation cohorts. Resampling tests suggested that the prognostic power of the gene signature was not by chance, and multivariate analysis suggested that this gene signature was independent of the traditional clinical factors and enhanced the identification of lung cancer patients at greater risk for recurrence. PMID:25548907

  12. Discriminating the molecular basis of hepatotoxicity using the large-scale characteristic molecular signatures of toxicants by expression profiling analysis.

    PubMed

    Eun, Jung Woo; Ryu, So Yeon; Noh, Ji Heon; Lee, Min-Jae; Jang, Ja-Jun; Ryu, Jae Chun; Jung, Kwang Hwa; Kim, Jeong Kyu; Bae, Hyun Jin; Xie, Hongjian; Kim, Su Young; Lee, Sug Hyung; Park, Won Sang; Yoo, Nam Jin; Lee, Jung Young; Nam, Suk Woo

    2008-07-30

    Predicting the potential human health risk posed by chemical stressors has long been a major challenge for toxicologists, and the use of microarrays to measure responses to toxicologically relevant genes, and to identify selective, sensitive biomarkers of toxicity is a major application of predictive and discovery toxicology. To investigate this possibility, we investigated whether carcinogens (at doses known to induce liver tumors in chronic exposure bioassays) deregulate characteristic sets of genes in mice. Male C3H/He mice were dosed with two hepatocarcinogens (vinyl chloride (VC, 50-25 mg/kg), aldrin (AD, 0.8-0.4 mg/kg)), or two non-hepatocarcinogens (copper sulfate (CS, 150-60 mg/kg), 2,4,5-trichlorophenoxyacetic acid (2,4,5-T, 150-60 mg/kg)). Large-scale molecular changes elicited by these four hepatotoxicants in liver tissues were analyzed using DNA microarray. Three days after administration, no significant phenotypic changes were induced by these four different hepatotoxicants in terms of histological examination or blood biochemical assay. However, unsupervised hierarchical analysis of gene expressional changes induced by hepatotoxicants resulted in two major gene subclusters on dendrogram, i.e., a carcinogen (VN, AD) and non-carcinogen group (CS, 2,4,5-T), and also revealed that distinct molecular signatures exist. These signatures were founded on well-defined functional gene categories and may differentiate genotoxic and non-genotoxic carcinogens. Furthermore, Venn diagram analysis allowed us to identify carcinogen and non-carcinogen-associated molecular signatures. Using statistical methods, we analyzed outlier genes for four different classes (genotoxic-, non-genotoxic-carcinogen, genotoxic-, non-genotoxic non-carcinogen) in terms of their potential to predict different modes-of-action. In conclusion, the identification of large-scale molecular changes in different hepatocarcinogen exposure models revealed that different types of hepatotoxicants are

  13. Monocyte Gene Expression Signature of Patients with Early Onset Coronary Artery Disease

    PubMed Central

    Sivapalaratnam, Suthesh; Basart, Hanneke; Watkins, Nicholas A.; Maiwald, Stepanie; Rendon, Augusto; Krishnan, Unni; Sondermeijer, Brigitte M.; Creemers, Esther E.; Pinto-Sietsma, Sara J.; Hovingh, Kees; Ouwehand, Willem H.; Kastelein, John J. P.; Goodall, Alison H.; Trip, Mieke D.

    2012-01-01

    The burden of cardiovascular disease (CVD) cannot be fully addressed by therapy targeting known pathophysiological pathways. Even with stringent control of all risk factors CVD events are only diminished by half. A number of additional pathways probably play a role in the development of CVD and might serve as novel therapeutic targets. Genome wide expression studies represent a powerful tool to identify such novel pathways. We compared the expression profiles in monocytes from twenty two young male patients with premature familial CAD with those from controls matched for age, sex and smoking status, without a family history of CVD. Since all patients were on statins and aspirin treatment, potentially affecting the expression of genes in monocytes, twelve controls were subsequently treated with simvastatin and aspirin for 6 and 2 weeks, respectively. By whole genome expression arrays six genes were identified to have differential expression in the monocytes of patients versus controls; ABCA1, ABCG1 and RGS1 were downregulated in patients, whereas ADRB2, FOLR3 and GSTM1 were upregulated. Differential expression of all genes, apart from GSTM1, was confirmed by qPCR. Aspirin and statins altered gene expression of ABCG1 and ADBR2. All finding were validated in a second group of twenty four patients and controls. Differential expression of ABCA1, RSG1 and ADBR2 was replicated. In conclusion, we identified these 3 genes to be expressed differently in CAD cases which might play a role in the pathogenesis of atherosclerotic vascular disease. PMID:22363809

  14. Gene expression profile class prediction using linear Bayesian classifiers.

    PubMed

    Asyali, Musa H

    2007-12-01

    Due to recent advances in DNA microarray technology, using gene expression profiles, diagnostic category of tissue samples can be predicted with high accuracy. In this study, we discuss shortcomings of some existing gene expression profile classification methods and propose a new approach based on linear Bayesian classifiers. In our approach, we first construct gene-level linear classifiers to identify genes that provide high class-prediction accuracies, i.e., low error rates. After this screening phase, starting with the gene that offers the lowest error rate, we construct a multi-dimensional linear classifier by incorporating next best-performing genes, until the prediction error becomes minimum or 0, if possible. When we compared classification performance of our approach against prediction analysis of microarrays (PAM) and support vector machines (SVM) based approaches, we found that our method outperforms PAM and produces comparable results with SVM. In addition, we observed that the gene selection scheme of PAM could be misleading. Albeit SVM achieves relatively higher prediction performance, it has two major disadvantages: Complexity and lack of insight about important genes. Our intuitive approach offers competing performance and also an efficient means for finding important genes. PMID:17517385

  15. Signatures of infinity: Nonergodicity and resource scaling in prediction, complexity, and learning

    NASA Astrophysics Data System (ADS)

    Crutchfield, James P.; Marzen, Sarah

    2015-05-01

    We introduce a simple analysis of the structural complexity of infinite-memory processes built from random samples of stationary, ergodic finite-memory component processes. Such processes are familiar from the well known multiarm Bandit problem. We contrast our analysis with computation-theoretic and statistical inference approaches to understanding their complexity. The result is an alternative view of the relationship between predictability, complexity, and learning that highlights the distinct ways in which informational and correlational divergences arise in complex ergodic and nonergodic processes. We draw out consequences for the resource divergences that delineate the structural hierarchy of ergodic processes and for processes that are themselves hierarchical.

  16. Transcriptome profiling of the whitefly Bemisia tabaci reveals stage-specific gene expression signatures for thiamethoxam resistance

    PubMed Central

    Yang, N; Xie, W; Jones, CM; Bass, C; Jiao, X; Yang, X; Liu, B; Li, R; Zhang, Y

    2013-01-01

    Bemisia tabaci has developed high levels of resistance to many insecticides including the neonicotinoids and there is strong evidence that for some compounds resistance is stage-specific. To investigate the molecular basis of B. tabaci resistance to the neonicotinoid thiamethoxam we used a custom whitefly microarray to compare gene expression in the egg, nymph and adult stages of a thiamethoxam-resistant strain (TH-R) with a susceptible strain (TH-S). Gene ontology and bioinformatic analyses revealed that in all life stages many of the differentially expressed transcripts encoded enzymes involved in metabolic processes and/or metabolism of xenobiotics. Several of these are candidate resistance genes and include the cytochrome P450 CYP6CM1, which has been shown to confer resistance to several neonicotinoids previously, a P450 belonging to the Cytochrome P450s 4 family and a glutathione S-transferase (GST) belonging to the sigma class. Finally several ATP-binding cassette transporters of the ABCG subfamily were highly over-expressed in the adult stage of the TH-R strain and may play a role in resistance by active efflux. Here, we evaluated both common and stage-specific gene expression signatures and identified several candidate resistance genes that may underlie B. tabaci resistance to thiamethoxam. PMID:23889345

  17. Long Noncoding RNA Expression Signatures of Metastatic Nasopharyngeal Carcinoma and Their Prognostic Value

    PubMed Central

    Zhang, Wei; Wang, Lin; Zheng, Fang; Zou, Ruhai; Xie, Changqing; Guo, Qiannan; Hu, Qian; Chen, Jianing; Yang, Xing; Yao, Herui; Song, Erwei; Xiang, Yanqun

    2015-01-01

    Long noncoding RNAs (lncRNAs) have recently been found to play important roles in various cancer types. The elucidation of genome-wide lncRNA expression patterns in metastatic nasopharyngeal carcinoma (NPC) could reveal novel mechanisms underlying NPC carcinogenesis and progression. In this study, lncRNA expression profiling was performed on metastatic and primary NPC tumors, and the differentially expressed lncRNAs between these samples were identified. A total of 33,045 lncRNA probes were generated for our microarray based on authoritative data sources, including RefSeq, UCSC Knowngenes, Ensembl, and related literature. Using these probes, 8,088 lncRNAs were found to be significantly differentially expressed (≥2-fold). To identify the prognostic value of these differentially expressed lncRNAs, four lncRNAs (LOC84740, ENST00000498296, AL359062, and ENST00000438550) were selected; their expression levels were measured in an independent panel of 106 primary NPC samples via QPCR. Among these lncRNAs, ENST00000438550 expression was demonstrated to be significantly correlated with NPC disease progression. A survival analysis showed that a high expression level of ENST00000438550 was an independent indicator of disease progression in NPC patients (P = 0.01). In summary, this study may provide novel diagnostic and prognostic biomarkers for NPC, as well as a novel understanding of the mechanism underlying NPC metastasis and potential targets for future treatment. PMID:26448942

  18. MiRNA expression signatures induced by Marek disease virus infection in chickens

    Technology Transfer Automated Retrieval System (TEKTRAN)

    MMicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression at the post-transcriptional level. Emerging evidence suggests that differential miRNA expression is associated with viral infection and cancer. Marek's disease virus infection induces lymphoma in chickens. However, the host...

  19. Predicting the Arrival of ICME Signatures at L1 with Stereoscopic Measurement and Drag-Based Modelling

    NASA Astrophysics Data System (ADS)

    Hess, Phillip; Zhang, Jie

    2015-04-01

    We present a new technique for predicting the arrival of Interplanetary Coronal Mass Ejection (ICME) signatures, including the compression/shock front and the magnetic cloud, at the L1 point using arrival times obtained from the ACE satellite. The method is based on obtaining accurate height measurements of the CME based on observations from multiple observing points and fitting these measurements into a drag-based model. Unlike previous work with the drag-based model, our technique does not fit the data assuming static model parameters and instead varies the characteristics of aerodynamic drag as a function of distance into the heliosphere, using physical assumptions to simplify the model terms. This correction, as well as a geometric correction based on the propagation direction of the eruption and flux rope geometry allow for an improved prediction at L1. The method is currently dependent on white-light images from the STEREO spacecraft, but demonstrates the great benefit to space weather forecasting that could be derived from a mission to the L5 point. Combining coronagraph and heliospheric imager observations from L5 with SOHO data to allow for stereoscopic imaging of all Earth directed CMEs could greatly improve our forecasting capabilities.

  20. Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans

    PubMed Central

    Rhee, Eugene P.; Cheng, Susan; Larson, Martin G.; Walford, Geoffrey A.; Lewis, Gregory D.; McCabe, Elizabeth; Yang, Elaine; Farrell, Laurie; Fox, Caroline S.; O’Donnell, Christopher J.; Carr, Steven A.; Vasan, Ramachandran S.; Florez, Jose C.; Clish, Clary B.; Wang, Thomas J.; Gerszten, Robert E.

    2011-01-01

    Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry–based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment. PMID:21403394

  1. Operator Dependent Choice of Prostate Cancer Biopsy Has Limited Impact on a Gene Signature Analysis for the Highly Expressed Genes IGFBP3 and F3 in Prostate Cancer Epithelial Cells

    PubMed Central

    Peng, Zhuochun; Andersson, Karl; Lindholm, Johan; Bodin, Inger; Pramana, Setia; Pawitan, Yudi; Nistér, Monica; Nilsson, Sten; Li, Chunde

    2014-01-01

    Background Predicting the prognosis of prostate cancer disease through gene expression analysis is receiving increasing interest. In many cases, such analyses are based on formalin-fixed, paraffin embedded (FFPE) core needle biopsy material on which Gleason grading for diagnosis has been conducted. Since each patient typically has multiple biopsy samples, and since Gleason grading is an operator dependent procedure known to be difficult, the impact of the operator's choice of biopsy was evaluated. Methods Multiple biopsy samples from 43 patients were evaluated using a previously reported gene signature of IGFBP3, F3 and VGLL3 with potential prognostic value in estimating overall survival at diagnosis of prostate cancer. A four multiplex one-step qRT-PCR test kit, designed and optimized for measuring the signature in FFPE core needle biopsy samples was used. Concordance of gene expression levels between primary and secondary Gleason tumor patterns, as well as benign tissue specimens, was analyzed. Results The gene expression levels of IGFBP3 and F3 in prostate cancer epithelial cell-containing tissue representing the primary and secondary Gleason patterns were high and consistent, while the low expressed VGLL3 showed more variation in its expression levels. Conclusion The assessment of IGFBP3 and F3 gene expression levels in prostate cancer tissue is independent of Gleason patterns, meaning that the impact of operator's choice of biopsy is low. PMID:25296164

  2. Linking ULIRGS and Quasars: Looking for Predicted Morphological Signatures of AGN Feedback

    NASA Astrophysics Data System (ADS)

    Steward, Nicole; Hicks, E. K. S.; Davies, R. I.

    2012-01-01

    Current leading theories propose a galactic evolutionary tract linking ultra-luminous infrared galaxies (ULIRGS) with quasars via a `blowout’ stage, during which the energy output resulting from accretion of material onto the central black hole expels the gas obscuring the central quasar. However, this phase would be short-lived and therefore difficult to directly observe, meaning evidence that this is indeed how galaxies evolve is scare. We obtained 2-D K-band integral field data with SINFONI on the VLT for a sample of six quasars that are divided into 'pre-' and 'post-blowout' by comparing their ratios of infrared luminosity to the luminosity of the optical 'big blue bump'. By measuring the spatial distribution and column density of the warm molecular gas on scales down to less than 1 kpc we determine if a correlation exists between these quantities and the `pre-’ an `post-blowout’ subsamples as predicted by evolutionary models.

  3. Comparison of Magnetospheric Multiscale ion jet signatures with predicted reconnection site locations at the magnetopause

    NASA Astrophysics Data System (ADS)

    Petrinec, S. M.; Burch, J. L.; Fuselier, S. A.; Gomez, R. G.; Lewis, W.; Trattner, K. J.; Ergun, R.; Mauk, B.; Pollock, C. J.; Schiff, C.; Strangeway, R. J.; Russell, C. T.; Phan, T.-D.; Young, D.

    2016-06-01

    Magnetic reconnection at the Earth's magnetopause is the primary process by which solar wind plasma and energy gains access to the magnetosphere. One indication that magnetic reconnection is occurring is the observation of accelerated plasma as a jet tangential to the magnetopause. The direction of ion jets along the magnetopause surface as observed by the Fast Plasma Instrument (FPI) and the Hot Plasma Composition Analyzer (HPCA) instrument on board the recently launched Magnetospheric Multiscale (MMS) set of spacecraft is examined. For those cases where ion jets are clearly discerned, the direction of origin compares well statistically with the predicted location of magnetic reconnection using convected solar wind observations in conjunction with the Maximum Magnetic Shear model.

  4. Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning.

    PubMed

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-07-01

    Often the world is structured such that distinct sensory contexts signify the same abstract rule set. Learning from feedback thus informs us not only about the value of stimulus-action associations but also about which rule set applies. Hierarchical clustering models suggest that learners discover structure in the environment, clustering distinct sensory events into a single latent rule set. Such structure enables a learner to transfer any newly acquired information to other contexts linked to the same rule set, and facilitates re-use of learned knowledge in novel contexts. Here, we show that humans exhibit this transfer, generalization and clustering during learning. Trial-by-trial model-based analysis of EEG signals revealed that subjects' reward expectations incorporated this hierarchical structure; these structured neural signals were predictive of behavioral transfer and clustering. These results further our understanding of how humans learn and generalize flexibly by building abstract, behaviorally relevant representations of the complex, high-dimensional sensory environment. PMID:27082659

  5. Predictive modelling of gene expression from transcriptional regulatory elements.

    PubMed

    Budden, David M; Hurley, Daniel G; Crampin, Edmund J

    2015-07-01

    Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. PMID:25231769

  6. Predicting stochastic gene expression dynamics in single cells.

    PubMed

    Mettetal, Jerome T; Muzzey, Dale; Pedraza, Juan M; Ozbudak, Ertugrul M; van Oudenaarden, Alexander

    2006-05-01

    Fluctuations in protein numbers (noise) due to inherent stochastic effects in single cells can have large effects on the dynamic behavior of gene regulatory networks. Although deterministic models can predict the average network behavior, they fail to incorporate the stochasticity characteristic of gene expression, thereby limiting their relevance when single cell behaviors deviate from the population average. Recently, stochastic models have been used to predict distributions of steady-state protein levels within a population but not to predict the dynamic, presteady-state distributions. In the present work, we experimentally examine a system whose dynamics are heavily influenced by stochastic effects. We measure population distributions of protein numbers as a function of time in the Escherichia coli lactose uptake network (lac operon). We then introduce a dynamic stochastic model and show that prediction of dynamic distributions requires only a few noise parameters in addition to the rates that characterize a deterministic model. Whereas the deterministic model cannot fully capture the observed behavior, our stochastic model correctly predicts the experimental dynamics without any fit parameters. Our results provide a proof of principle for the possibility of faithfully predicting dynamic population distributions from deterministic models supplemented by a stochastic component that captures the major noise sources. PMID:16648266

  7. Association Between a Prognostic Gene Signature and Functional Gene Sets

    PubMed Central

    Hummel, Manuela; Metzeler, Klaus H.; Buske, Christian; Bohlander, Stefan K.; Mansmann, Ulrich

    2008-01-01

    Background The development of expression-based gene signatures for predicting prognosis or class membership is a popular and challenging task. Besides their stringent validation, signatures need a functional interpretation and must be placed in a biological context. Popular tools such as Gene Set Enrichment have drawbacks because they are restricted to annotated genes and are unable to capture the information hidden in the signature’s non-annotated genes. Methodology We propose concepts to relate a signature with functional gene sets like pathways or Gene Ontology categories. The connection between single signature genes and a specific pathway is explored by hierarchical variable selection and gene association networks. The risk score derived from an individual patient’s signature is related to expression patterns of pathways and Gene Ontology categories. Global tests are useful for these tasks, and they adjust for other factors. GlobalAncova is used to explore the effect on gene expression in specific functional groups from the interaction of the score and selected mutations in the patient’s genome. Results We apply the proposed methods to an expression data set and a corresponding gene signature for predicting survival in Acute Myeloid Leukemia (AML). The example demonstrates strong relations between the signature and cancer-related pathways. The signature-based risk score was found to be associated with development-related biological processes. Conclusions Many authors interpret the functional aspects of a gene signature by linking signature genes to pathways or relevant functional gene groups. The method of gene set enrichment is preferred to annotating signature genes to specific Gene Ontology categories. The strategies proposed in this paper go beyond the restriction of annotation and deepen the insights into the biological mechanisms reflected in the information given by a signature. PMID:19812786

  8. MGMT expression predicts response to temozolomide in pancreatic neuroendocrine tumors.

    PubMed

    Cros, J; Hentic, O; Rebours, V; Zappa, M; Gille, N; Theou-Anton, N; Vernerey, D; Maire, F; Lévy, P; Bedossa, P; Paradis, V; Hammel, P; Ruszniewski, P; Couvelard, A

    2016-08-01

    Temozolomide (TEM) showed encouraging results in well-differentiated pancreatic neuroendocrine tumors (WDPNETs). Low O(6)-methylguanine-DNA methyltransferase (MGMT) expression and MGMT promoter methylation within tumors correlate with a better outcome under TEM-based chemotherapy in glioblastoma. We aimed to assess whether MGMT expression and MGMT promoter methylation could help predict the efficacy of TEM-based chemotherapy in patients with WDPNET. Consecutive patients with progressive WDPNET and/or liver involvement over 50% who received TEM between 2006 and 2012 were retrospectively studied. Tumor response was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 guidelines. Nuclear expression of MGMT was assessed by immunochemistry (H-score, 0-300) and MGMT promoter methylation by pyrosequencing. Forty-three patients (21 men, 58years (27-84)) with grade 1 WDPNET (n=6) or 2 (n=36) were analyzed. Objective response, stable disease, and progression rates were seen in 17 patients (39.5%), 18 patients (41.9%), and 8 patients (18.6%), respectively. Low MGMT expression (≤50) was associated with radiological objective response (P=0.04) and better progression-free survival (PFS) (HR=0.35 (0.15-0.81), P=0.01). Disease control rate at 18months of treatment remained satisfying with an MGMT score up to 100 (74%) but dropped with a higher expression. High MGMT promoter methylation was associated with a low MGMT expression and longer PFS (HR=0.37 (0.29-1.08), P=0.05). Low MGMT score (≤50) appears to predict an objective tumor response, whereas an intermediate MGMT score (50-100) seems to be associated with prolonged stable disease. PMID:27353036

  9. Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel

    PubMed Central

    Kharaziha, Pedram; Chioureas, Dimitris; Rutishauser, Dorothea; Baltatzis, George; Lennartsson, Lena; Fonseca, Pedro; Azimi, Alireza; Hultenby, Kjell; Zubarev, Roman; Ullén, Anders; Yachnin, Jeffrey; Nilsson, Sten; Panaretakis, Theocharis

    2015-01-01

    Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy. PMID:25844599

  10. Transcriptome Analysis of Triple-Negative Breast Cancer Reveals an Integrated mRNA-lncRNA Signature with Predictive and Prognostic Value.

    PubMed

    Jiang, Yi-Zhou; Liu, Yi-Rong; Xu, Xiao-En; Jin, Xi; Hu, Xin; Yu, Ke-Da; Shao, Zhi-Ming

    2016-04-15

    While recognized as a generally aggressive disease, triple-negative breast cancer (TNBC) is highly diverse in different patients with variable outcomes. In this prospective observational study, we aimed to develop an RNA signature of TNBC patients to improve risk stratification and optimize the choice of adjuvant therapy. Transcriptome microarrays for 33 paired TNBC and adjacent normal breast tissue revealed tumor-specific mRNAs and long noncoding RNAs (lncRNA) that were associated with recurrence-free survival. Using the Cox regression model, we developed an integrated mRNA-lncRNA signature based on the mRNA species for FCGR1A, RSAD2, CHRDL1, and the lncRNA species for HIF1A-AS2 and AK124454 The prognostic and predictive accuracy of this signature was evaluated in a training set of 137 TNBC patients and then validated in a second independent set of 138 TNBC patients. In addition, we enrolled 82 TNBC patients who underwent taxane-based neoadjuvant chemotherapy (NCT) to further verify the predictive value of the signature. In both the training and validation sets, the integrated signature had better prognostic value than clinicopathologic parameters. We also confirmed the interaction between the administration of taxane-based NCT and different risk groups. In the NCT cohort, patients in the low-risk group were more likely to achieve pathologic complete remission after taxane-based NCT (P = 0.014). Functionally, we showed that HIF1A-AS2 and AK124454 promoted cell proliferation and invasion in TNBC cells and contributed there to paclitaxel resistance. Overall, our results established an integrated mRNA-lncRNA signature as a reliable tool to predict tumor recurrence and the benefit of taxane chemotherapy in TNBC, warranting further investigation in larger populations to help frame individualized treatments for TNBC patients. Cancer Res; 76(8); 2105-14. ©2016 AACR. PMID:26921339

  11. DEEP--a tool for differential expression effector prediction.

    PubMed

    Degenhardt, Jost; Haubrock, Martin; Dönitz, Jürgen; Wingender, Edgar; Crass, Torsten

    2007-07-01

    High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH database on signal transduction, to predict additional--and not necessarily differentially expressed--genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules

  12. MicroRNA gene expression signatures in long-surviving malignant pleural mesothelioma patients.

    PubMed

    Lin, Ruby C Y; Kirschner, Michaela B; Cheng, Yuen Yee; van Zandwijk, Nico; Reid, Glen

    2016-09-01

    Malignant pleural mesothelioma (MPM) is a tumor originating in the mesothelium, the membrane lining the thoracic cavities, and is induced by exposure to asbestos. Australia suffers one of the world's highest rates of MPM and the incidence is yet to peak. The prognosis for patients with MPM is poor and median survival following diagnosis is 4-18 months. Currently, no or few effective therapies exist for MPM. Trials of targeted agents such as antiangiogenic agents (VEGF, EGFR) or ribonuclease inhibitors (ranpirnase) largely failed to show efficacy in MPM Tsao et al. (2009) [1]. A recent study, however, showed that cisplatin/pemetrexed + bevacizumab (a recombinant humanized monoclonal antibody that inhibit VEGF) treatment has a survival benefit of 2.7 months Zalcman et al. (2016) [2]. It remains to be seen if this targeted therapy will be accepted as a new standard for MPM. Thus the unmet needs of MPM patients remain very pronounced and almost every patient will be confronted with drug resistance and recurrence of disease. We have identified unique gene signatures associated with prolonged survival in mesothelioma patients undergoing radical surgery (EPP, extrapleural pneumonectomy), as well as patients who underwent palliative surgery (pleurectomy/decortication). In addition to data published in Molecular Oncology, 2015;9:715-26 (GSE59180) Kirschner et al. (2015) , we describe here additional data using a system-based approach that support our previous observations. This data provides a resource to further explore microRNA dynamics in MPM. PMID:27408810

  13. A transgenic zebrafish liver tumor model with inducible Myc expression reveals conserved Myc signatures with mammalian liver tumors

    PubMed Central

    Li, Zhen; Zheng, Weiling; Wang, Zhengyuan; Zeng, Zhiqiang; Zhan, Huiqing; Li, Caixia; Zhou, Li; Yan, Chuan; Spitsbergen, Jan M.; Gong, Zhiyuan

    2013-01-01

    SUMMARY Myc is a pleiotropic transcription factor that is involved in many cellular activities relevant to carcinogenesis, including hepatocarcinogenesis. The zebrafish has been increasingly used to model human diseases and it is particularly valuable in helping to identify common and conserved molecular mechanisms in vertebrates. Here we generated a liver tumor model in transgenic zebrafish by liver-specific expression of mouse Myc using a Tet-On system. Dosage-dependent induction of Myc expression specifically in the liver was observed in our Myc transgenic zebrafish, TO(Myc), and the elevated Myc expression caused liver hyperplasia, which progressed to hepatocellular adenoma and carcinoma with prolonged induction. Next generation sequencing-based transcriptomic analyses indicated that ribosome proteins were overwhelmingly upregulated in the Myc-induced liver tumors. Cross-species analyses showed that the zebrafish Myc model correlated well with Myc transgenic mouse models for liver cancers. The Myc-induced zebrafish liver tumors also possessed molecular signatures highly similar to human those of hepatocellular carcinoma. Finally, we found that a small Myc target gene set of 16 genes could be used to identify liver tumors due to Myc upregulation. Thus, our zebrafish model demonstrated the conserved role of Myc in promoting hepatocarcinogenesis in all vertebrate species. PMID:23038063

  14. Conditional entropy in variation-adjusted windows detects selection signatures associated with expression quantitative trait loci (eQTLs)

    PubMed Central

    2015-01-01

    Background Over the past 50,000 years, shifts in human-environmental or human-human interactions shaped genetic differences within and among human populations, including variants under positive selection. Shaped by environmental factors, such variants influence the genetics of modern health, disease, and treatment outcome. Because evolutionary processes tend to act on gene regulation, we test whether regulatory variants are under positive selection. We introduce a new approach to enhance detection of genetic markers undergoing positive selection, using conditional entropy to capture recent local selection signals. Results We use conditional logistic regression to compare our Adjusted Haplotype Conditional Entropy (H|H) measure of positive selection to existing positive selection measures. H|H and existing measures were applied to published regulatory variants acting in cis (cis-eQTLs), with conditional logistic regression testing whether regulatory variants undergo stronger positive selection than the surrounding gene. These cis-eQTLs were drawn from six independent studies of genotype and RNA expression. The conditional logistic regression shows that, overall, H|H is substantially more powerful than existing positive-selection methods in identifying cis-eQTLs against other Single Nucleotide Polymorphisms (SNPs) in the same genes. When broken down by Gene Ontology, H|H predictions are particularly strong in some biological process categories, where regulatory variants are under strong positive selection compared to the bulk of the gene, distinct from those GO categories under overall positive selection. . However, cis-eQTLs in a second group of genes lack positive selection signatures detectable by H|H, consistent with ancient short haplotypes compared to the surrounding gene (for example, in innate immunity GO:0042742); under such other modes of selection, H|H would not be expected to be a strong predictor.. These conditional logistic regression models are

  15. CAERUS: Predicting CAncER oUtcomeS Using Relationship between Protein Structural Information, Protein Networks, Gene Expression Data, and Mutation Data

    PubMed Central

    Zhang, Kelvin Xi; Ouellette, B. F. Francis

    2011-01-01

    Carcinogenesis is a complex process with multiple genetic and environmental factors contributing to the development of one or more tumors. Understanding the underlying mechanism of this process and identifying related markers to assess the outcome of this process would lead to more directed treatment and thus significantly reduce the mortality rate of cancers. Recently, molecular diagnostics and prognostics based on the identification of patterns within gene expression profiles in the context of protein interaction networks were reported. However, the predictive performances of these approaches were limited. In this study we propose a novel integrated approach, named CAERUS, for the identification of gene signatures to predict cancer outcomes based on the domain interaction network in human proteome. We first developed a model to score each protein by quantifying the domain connections to its interacting partners and the somatic mutations present in the domain. We then defined proteins as gene signatures if their scores were above a preset threshold. Next, for each gene signature, we quantified the correlation of the expression levels between this gene signature and its neighboring proteins. The results of the quantification in each patient were then used to predict cancer outcome by a modified naïve Bayes classifier. In this study we achieved a favorable accuracy of 88.3%, sensitivity of 87.2%, and specificity of 88.9% on a set of well-documented gene expression profiles of 253 consecutive breast cancer patients with different outcomes. We also compiled a list of cancer-associated gene signatures and domains, which provided testable hypotheses for further experimental investigation. Our approach proved successful on different independent breast cancer data sets as well as an ovarian cancer data set. This study constitutes the first predictive method to classify cancer outcomes based on the relationship between the domain organization and protein network. PMID

  16. A potential panel of six-long non-coding RNA signature to improve survival prediction of diffuse large-B-cell lymphoma

    PubMed Central

    Sun, Jie; Cheng, Liang; Shi, Hongbo; Zhang, Zhaoyue; Zhao, Hengqiang; Wang, Zhenzhen; Zhou, Meng

    2016-01-01

    Long non-coding RNAs (lncRNAs) represent an emerging layer of cancer biology and have been implicated in the development and progression of cancers. However, the prognostic significance of lncRNAs in diffuse large-B-cell lymphoma (DLBCL) remains unclear and needs to be systematically investigated. In this study, we obtained and analyzed lncRNA expression profiles in three cohorts of 1043 DLBCL patients by repurposing the publicly available microarray datasets from the Gene Expression Omnibus (GEO) database. In the discovery series of 207 patients, we identified a set of six lncRNAs that was significantly associated with patients’ overall survival (OS) using univariate Cox regression analysis. The six prognostic lncRNAs were combined to form an expression-based six-lncRNA signature which classified patients of the discovery series into the high-risk group and low-risk group with significantly different survival outcome (HR = 2.31, 95% CI = 1.8 to 2.965, p < 0.001). The six-lncRNA signature was further confirmed in the internal testing series and two additional independent datasets with different array platform. Moreover, the prognostic value of the six-lncRNA signature is independent of conventional clinical factors. Functional analysis suggested that six-lncRNA signature may be involved with DLBCL through exerting their regulatory roles in known cancer-related pathways, immune system and signaling molecules interaction. PMID:27292966

  17. Obesity and prostate cancer: gene expression signature of human periprostatic adipose tissue

    PubMed Central

    2012-01-01

    Background Periprostatic (PP) adipose tissue surrounds the prostate, an organ with a high predisposition to become malignant. Frequently, growing prostatic tumor cells extend beyond the prostatic organ towards this fat depot. This study aimed to determine the genome-wide expression of genes in PP adipose tissue in obesity/overweight (OB/OW) and prostate cancer patients. Methods Differentially expressed genes in human PP adipose tissue were identified using microarrays. Analyses were conducted according to the donors' body mass index characteristics (OB/OW versus lean) and prostate disease (extra prostatic cancer versus organ confined prostate cancer versus benign prostatic hyperplasia). Selected genes with altered expression were validated by real-time PCR. Ingenuity Pathway Analysis (IPA) was used to investigate gene ontology, canonical pathways and functional networks. Results In the PP adipose tissue of OB/OW subjects, we found altered expression of genes encoding molecules involved in adipogenic/anti-lipolytic, proliferative/anti-apoptotic, and mild immunoinflammatory processes (for example, FADS1, down-regulated, and LEP and ANGPT1, both up-regulated). Conversely, in the PP adipose tissue of subjects with prostate cancer, altered genes were related to adipose tissue cellular activity (increased cell proliferation/differentiation, cell cycle activation and anti-apoptosis), whereas a downward impact on immunity and inflammation was also observed, mostly related to the complement (down-regulation of CFH). Interestingly, we found that the microRNA MIRLET7A2 was overexpressed in the PP adipose tissue of prostate cancer patients. Conclusions Obesity and excess adiposity modified the expression of PP adipose tissue genes to ultimately foster fat mass growth. In patients with prostate cancer the expression profile of PP adipose tissue accounted for hypercellularity and reduced immunosurveillance. Both findings may be liable to promote a favorable environment for

  18. A gene expression signature that distinguishes desmoid tumours from nodular fasciitis.

    PubMed

    Bacac, M; Migliavacca, E; Stehle, J-C; McKee, T; Delorenzi, M; Coindre, J-M; Guillou, L; Stamenkovic, I

    2006-03-01

    Nodular fasciitis (NF) is a rapidly growing cellular mass composed of fibroblasts/myofibroblasts, usually localized in subcutaneous tissues, that typically undergoes fibrosis and almost never recurs. Desmoid tumours (DTs) are rare forms of fibroblastic/myofibroblastic growth that arise in deep soft tissues, display a propensity for local infiltration and recurrence, but fail to metastasize. Given that both entities are primarily fibroblastic/myofibroblastic lesions with overlapping histological features, their gene expression profiles were compared to identify differentially expressed genes that may provide not only potential diagnostic markers, but also clues as to the pathogenesis of each disorder. Differentially expressed transcripts (89 clones displaying increased expression in DTs and 246 clones displaying increased expression in NF) included genes encoding several receptor and non-receptor tyrosine kinases (EPHB3, PTPRF, GNAZ, SYK, LYN, EPHA4, BIRC3), transcription factors (TWIST1, PITX2, EYA2, OAS1, MITF, TCF20), and members of the Wnt signalling pathway (AXIN2, WISP1, SFRP). Remarkably, almost one-quarter of the differentially expressed genes encode proteins associated with inflammation and tissue remodelling, including members of the interferon (IFN), tumour necrosis factor (TNF), and transforming growth factor beta (TGF-beta) signalling pathways as well as metalloproteinases (MMP1, 9, 13, 23), urokinase plasminogen activator (PLAU), and cathepsins. The observations provide the first comparative molecular characterization of desmoid tumours and nodular fasciitis and suggest that selected tyrosine kinases, transcription factors, and members of the Wnt, TGF-beta, IFN, and TNF signalling pathways may be implicated in influencing and distinguishing their fate. PMID:16440290

  19. Mucosal expression signatures of two Cathepsin L in channel catfish (Ictalurus punctatus) following bacterial challenge.

    PubMed

    Wang, Renjie; Song, Lin; Su, Baofeng; Zhao, Honggang; Zhang, Dongdong; Peatman, Eric; Li, Chao

    2015-11-01

    The mucosal surfaces of fish are the first line of host defense against various pathogens. The mucosal immune responses are the most critical events to prevent pathogen attachment and invasion. Cathepsins are a group of peptidases that involved in different levels of immune responses, but the knowledge of the roles of Cathepsin in mucosal immune responses against bacterial infection are still lacking. Therefore, in the present study we characterized the Cathepsin L gene family in channel catfish, and profiled their expression levels after challenging with two different Gram-negative bacterial pathogens. Here, two Cathepsin L genes were identified from channel catfish and were designated CTSL1a and CTSL.1. Comparing to other fish species, the catfish CTSL genes are highly conserved in their structural features. Phylogenetic analysis was conducted to confirm the identification of CTSL genes. Expression analysis revealed that the CTSL genes were ubiquitously expressed in all tested tissues. Following infection, the CTSL genes were significantly induced at most timepoints in mucosal tissues. But the expression patterns varied depending on both pathogen and tissue types, suggesting that CTSL genes may exert disparate functions or exhibit distinct tissue-selective roles in mucosal immune responses. Our findings here, clearly revealed the key roles of CTSL in catfish mucosal immunity; however, further studies are needed to expand functional characterization and examine whether CTSL may also play additional physiological roles in catfish mucosal tissues. PMID:26434716

  20. Blood-Based Gene Expression Signatures of Infants and Toddlers with Autism

    ERIC Educational Resources Information Center

    Glatt, Stephen J.; Tsuang, Ming T.; Winn, Mary; Chandler, Sharon D.; Collins, Melanie; Lopez, Linda; Weinfeld, Melanie; Carter, Cindy; Schork, Nicholas; Pierce, Karen; Courchesne, Eric

    2012-01-01

    Objective: Autism spectrum disorders (ASDs) are highly heritable neurodevelopmental disorders that onset clinically during the first years of life. ASD risk biomarkers expressed early in life could significantly impact diagnosis and treatment, but no transcriptome-wide biomarker classifiers derived from fresh blood samples from children with…

  1. 76 FR 75461 - Express Mail Domestic Postage Refund Policy and Waiver of Signature

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-02

    ... Service, Domestic Mail Manual (DMM ) throughout various sections to modify the policy for filing claims... published a Federal Register proposed rule (76 FR 62000-62002) inviting comments on revisions to the... Service is revising the DMM to align the refund policy for domestic Express Mail with the...

  2. Gene expression profiles of small-cell lung cancers: molecular signatures of lung cancer.

    PubMed

    Taniwaki, Masaya; Daigo, Yataro; Ishikawa, Nobuhisa; Takano, Atsushi; Tsunoda, Tatsuhiko; Yasui, Wataru; Inai, Kouki; Kohno, Nobuoki; Nakamura, Yusuke

    2006-09-01

    To characterize the molecular mechanisms involved in the carcinogenesis and progression of small-cell lung cancer (SCLC) and identify molecules to be applied as novel diagnostic markers and/or for development of molecular-targeted drugs, we applied cDNA microarray profile analysis coupled with purification of cancer cells by laser-microbeam microdissection (LMM). Expression profiles of 32,256 genes in 15 SCLCs identified 252 genes that were commonly up-regulated and 851 transcripts that were down-regulated in SCLC cells compared with non-cancerous lung tissue cells. An unsupervised clustering algorithm applied to the expression data easily distinguished SCLC from the other major histological type of non-small cell lung cancer (NSCLC) and identified 475 genes that may represent distinct molecular features of each of the two histological types. In particular, SCLC was characterized by altered expression of genes related to neuroendocrine cell differentiation and/or growth such as ASCL1, NRCAM, and INSM1. We also identified 68 genes that were abundantly expressed both in advanced SCLCs and advanced adenocarcinomas (ADCs), both of which had been obtained from patients with extensive chemotherapy treatment. Some of them are known to be transcription factors and/or gene expression regulators such as TAF5L, TFCP2L4, PHF20, LMO4, TCF20, RFX2, and DKFZp547I048 as well as those encoding nucleotide-binding proteins such as C9orf76, EHD3, and GIMAP4. Our data provide valuable information for better understanding of lung carcinogenesis and chemoresistance. PMID:16865272

  3. microRNA expression signatures of gastrointestinal stromal tumours: associations with imatinib resistance and patient outcome

    PubMed Central

    Akçakaya, P; Caramuta, S; Åhlen, J; Ghaderi, M; Berglund, E; Östman, A; Bränström, R; Larsson, C; Lui, W-O

    2014-01-01

    Background: Gastrointestinal stromal tumour (GIST) is mainly initialised by receptor tyrosine kinase gene mutations. Although the tyrosine kinase inhibitor imatinib mesylate considerably improved the outcome of patients, imatinib resistance still remains a major therapeutic challenge in GIST therapy. Herein we evaluated the clinical impact of microRNAs in imatinib-treated GISTs. Methods: The expression levels of microRNAs were quantified using microarray and RT–qPCR in GIST specimens from patients treated with neoadjuvant imatinib. The functional roles of miR-125a-5p and PTPN18 were evaluated in GIST cells. PTPN18 expression was quantified by western blotting in GIST samples. Results: We showed that overexpression levels of miR-125a-5p and miR-107 were associated with imatinib resistance in GIST specimens. Functionally, miR-125a-5p expression modulated imatinib sensitivity in GIST882 cells with a homozygous KIT mutation but not in GIST48 cells with double KIT mutations. Overexpression of miR-125a-5p suppressed PTPN18 expression, and silencing of PTPN18 expression increased cell viability in GIST882 cells upon imatinib treatment. PTPN18 protein levels were significantly lower in the imatinib-resistant GISTs and inversely correlated with miR-125a-5p. Furthermore, several microRNAs were significantly associated with metastasis, KIT mutational status and survival. Conclusions: Our findings highlight a novel functional role of miR-125a-5p on imatinib response through PTPN18 regulation in GIST. PMID:25349971

  4. Different Gene Expression Signatures in Children and Adults with Celiac Disease.

    PubMed

    Pascual, V; Medrano, L M; López-Palacios, N; Bodas, A; Dema, B; Fernández-Arquero, M; González-Pérez, B; Salazar, I; Núñez, C

    2016-01-01

    Celiac disease (CD) is developed after gluten ingestion in genetically susceptible individuals. It can appear at any time in life, but some differences are commonly observed between individuals with onset early in life or in adulthood. We aimed to investigate the molecular basis underlying those differences. We collected 19 duodenal biopsies of children and adults with CD and compared the expression of 38 selected genes between each other and with the observed in 13 non-CD controls matched by age. A Bayesian methodology was used to analyze the differences of gene expression between groups. We found seven genes with a similarly altered expression in children and adults with CD when compared to controls (C2orf74, CCR6, FASLG, JAK2, IL23A, TAGAP and UBE2L3). Differences were observed in 13 genes: six genes being altered only in adults (IL1RL1, CD28, STAT3, TMEM187, VAMP3 and ZFP36L1) and two only in children (TNFSF18 and ICOSLG); and four genes showing a significantly higher alteration in adults (CCR4, IL6, IL18RAP and PLEK) and one in children (C1orf106). This is the first extensive study comparing gene expression in children and adults with CD. Differences in the expression level of several genes were found between groups, being notorious the higher alteration observed in adults. Further research is needed to evaluate the possible genetic influence underlying these changes and the specific functional consequences of the reported differences. PMID:26859134

  5. Different Gene Expression Signatures in Children and Adults with Celiac Disease

    PubMed Central

    López-Palacios, N.; Bodas, A.; Dema, B.; Fernández-Arquero, M.; González-Pérez, B.; Salazar, I.; Núñez, C.

    2016-01-01

    Celiac disease (CD) is developed after gluten ingestion in genetically susceptible individuals. It can appear at any time in life, but some differences are commonly observed between individuals with onset early in life or in adulthood. We aimed to investigate the molecular basis underlying those differences. We collected 19 duodenal biopsies of children and adults with CD and compared the expression of 38 selected genes between each other and with the observed in 13 non-CD controls matched by age. A Bayesian methodology was used to analyze the differences of gene expression between groups. We found seven genes with a similarly altered expression in children and adults with CD when compared to controls (C2orf74, CCR6, FASLG, JAK2, IL23A, TAGAP and UBE2L3). Differences were observed in 13 genes: six genes being altered only in adults (IL1RL1, CD28, STAT3, TMEM187, VAMP3 and ZFP36L1) and two only in children (TNFSF18 and ICOSLG); and four genes showing a significantly higher alteration in adults (CCR4, IL6, IL18RAP and PLEK) and one in children (C1orf106). This is the first extensive study comparing gene expression in children and adults with CD. Differences in the expression level of several genes were found between groups, being notorious the higher alteration observed in adults. Further research is needed to evaluate the possible genetic influence underlying these changes and the specific functional consequences of the reported differences. PMID:26859134

  6. Gene expression signature of cerebellar hypoplasia in a mouse model of Down syndrome during postnatal development

    PubMed Central

    Laffaire, Julien; Rivals, Isabelle; Dauphinot, Luce; Pasteau, Fabien; Wehrle, Rosine; Larrat, Benoit; Vitalis, Tania; Moldrich, Randal X; Rossier, Jean; Sinkus, Ralph; Herault, Yann; Dusart, Isabelle; Potier, Marie-Claude

    2009-01-01

    Background Down syndrome is a chromosomal disorder caused by the presence of three copies of chromosome 21. The mechanisms by which this aneuploidy produces the complex and variable phenotype observed in people with Down syndrome are still under discussion. Recent studies have demonstrated an increased transcript level of the three-copy genes with some dosage compensation or amplification for a subset of them. The impact of this gene dosage effect on the whole transcriptome is still debated and longitudinal studies assessing the variability among samples, tissues and developmental stages are needed. Results We thus designed a large scale gene expression study in mice (the Ts1Cje Down syndrome mouse model) in which we could measure the effects of trisomy 21 on a large number of samples (74 in total) in a tissue that is affected in Down syndrome (the cerebellum) and where we could quantify the defect during postnatal development in order to correlate gene expression changes to the phenotype observed. Statistical analysis of microarray data revealed a major gene dosage effect: for the three-copy genes as well as for a 2 Mb segment from mouse chromosome 12 that we show for the first time as being deleted in the Ts1Cje mice. This gene dosage effect impacts moderately on the expression of euploid genes (2.4 to 7.5% differentially expressed). Only 13 genes were significantly dysregulated in Ts1Cje mice at all four postnatal development stages studied from birth to 10 days after birth, and among them are 6 three-copy genes. The decrease in granule cell proliferation demonstrated in newborn Ts1Cje cerebellum was correlated with a major gene dosage effect on the transcriptome in dissected cerebellar external granule cell layer. Conclusion High throughput gene expression analysis in the cerebellum of a large number of samples of Ts1Cje and euploid mice has revealed a prevailing gene dosage effect on triplicated genes. Moreover using an enriched cell population that is thought

  7. Protein Sialylation Regulates a Gene Expression Signature that Promotes Breast Cancer Cell Pathogenicity

    PubMed Central

    2016-01-01

    Many mechanisms have been proposed for how heightened aerobic glycolytic metabolism fuels cancer pathogenicity, but there are still many unexplored pathways. Here, we have performed metabolomic profiling to map glucose incorporation into metabolic pathways upon transformation of mammary epithelial cells by 11 commonly mutated human oncogenes. We show that transformation of mammary epithelial cells by oncogenic stimuli commonly shunts glucose-derived carbons into synthesis of sialic acid, a hexosamine pathway metabolite that is converted to CMP-sialic acid by cytidine monophosphate N-acetylneuraminic acid synthase (CMAS) as a precursor to glycoprotein and glycolipid sialylation. We show that CMAS knockdown leads to elevations in intracellular sialic acid levels, a depletion of cellular sialylation, and alterations in the expression of many cancer-relevant genes to impair breast cancer pathogenicity. Our study reveals the heretofore unrecognized role of sialic acid metabolism and protein sialylation in regulating the expression of genes that maintain breast cancer pathogenicity. PMID:27380425

  8. Protein Sialylation Regulates a Gene Expression Signature that Promotes Breast Cancer Cell Pathogenicity.

    PubMed

    Kohnz, Rebecca A; Roberts, Lindsay S; DeTomaso, David; Bideyan, Lara; Yan, Peter; Bandyopadhyay, Sourav; Goga, Andrei; Yosef, Nir; Nomura, Daniel K

    2016-08-19

    Many mechanisms have been proposed for how heightened aerobic glycolytic metabolism fuels cancer pathogenicity, but there are still many unexplored pathways. Here, we have performed metabolomic profiling to map glucose incorporation into metabolic pathways upon transformation of mammary epithelial cells by 11 commonly mutated human oncogenes. We show that transformation of mammary epithelial cells by oncogenic stimuli commonly shunts glucose-derived carbons into synthesis of sialic acid, a hexosamine pathway metabolite that is converted to CMP-sialic acid by cytidine monophosphate N-acetylneuraminic acid synthase (CMAS) as a precursor to glycoprotein and glycolipid sialylation. We show that CMAS knockdown leads to elevations in intracellular sialic acid levels, a depletion of cellular sialylation, and alterations in the expression of many cancer-relevant genes to impair breast cancer pathogenicity. Our study reveals the heretofore unrecognized role of sialic acid metabolism and protein sialylation in regulating the expression of genes that maintain breast cancer pathogenicity. PMID:27380425

  9. Heme-related gene expression signatures of meat intakes in lung cancer tissues

    PubMed Central

    Lam, Tram Kim; Rotunno, Melissa; Ryan, Brid M.; Pesatori, Angela C.; Bertazzi, Pier Alberto; Spitz, Margaret; Caporaso, Neil E.; Landi, Maria Teresa

    2014-01-01

    Lung cancer causes more deaths worldwide than any other cancer. In addition to cigarette smoking, dietary factors may contribute to lung carcinogenesis. Epidemiologic studies, including the Environment and Genetics in Lung cancer Etiology (EAGLE), have reported increased consumption of red/processed meats to be associated with higher risk of lung cancer. Heme-iron toxicity may link meat intake with cancer. We investigated this hypothesis in meat-related lung carcinogenesis using whole genome expression. We measured genome-wide expression (HG-U133A) in 49 tumor and 42 non-involved fresh frozen lung tissues of 64 adenocarcinoma EAGLE patients. We studied gene expression profiles by high-versus-low meat consumption, with and without adjustment by sex, age, and smoking. Threshold for significance was a False Discovery Rate (FDR) ≤0.15. We studied whether the identified genes played a role in heme-iron related processes by means of manually curated literature search and gene ontology-based pathway analysis. We found that gene expression of 232 annotated genes in tumor tissue significantly distinguished lung adenocarcinoma cases who consumed above/below the median intake of fresh red meats (FDR=0.12). Sixty-three (~28%) of the 232 identified genes (12 expected by chance, p-value<0.001) were involved in heme binding, absorption, transport, and Wnt signaling pathway (e.g., CYPs, TPO, HPX, HFE, SLCs, WNTs). We also identified several genes involved in lipid metabolism (e.g., NCR1, TNF, UCP3) and oxidative stress (e.g., TPO, SGK2, MTHFR) that may be indirectly related to heme-toxicity. The study’s results provide preliminary evidence that heme-iron toxicity might be one underlying mechanism linking fresh red meat intake and lung cancer. PMID:23681825

  10. Heme-related gene expression signatures of meat intakes in lung cancer tissues.

    PubMed

    Lam, Tram Kim; Rotunno, Melissa; Ryan, Brid M; Pesatori, Angela C; Bertazzi, Pier Alberto; Spitz, Margaret; Caporaso, Neil E; Landi, Maria Teresa

    2014-07-01

    Lung cancer causes more deaths worldwide than any other cancer. In addition to cigarette smoking, dietary factors may contribute to lung carcinogenesis. Epidemiologic studies, including the environment and genetics in lung cancer etiology (EAGLE), have reported increased consumption of red/processed meats to be associated with higher risk of lung cancer. Heme-iron toxicity may link meat intake with cancer. We investigated this hypothesis in meat-related lung carcinogenesis using whole genome expression. We measured genome-wide expression (HG-U133A) in 49 tumor and 42 non-involved fresh frozen lung tissues of 64 adenocarcinoma EAGLE patients. We studied gene expression profiles by high-versus-low meat consumption, with and without adjustment by sex, age, and smoking. Threshold for significance was a false discovery rate (FDR) ≤ 0.15. We studied whether the identified genes played a role in heme-iron related processes by means of manually curated literature search and gene ontology-based pathway analysis. We found that gene expression of 232 annotated genes in tumor tissue significantly distinguished lung adenocarcinoma cases who consumed above/below the median intake of fresh red meats (FDR = 0.12). Sixty-three (∼ 28%) of the 232 identified genes (12 expected by chance, P-value < 0.001) were involved in heme binding, absorption, transport, and Wnt signaling pathway (e.g., CYPs, TPO, HPX, HFE, SLCs, and WNTs). We also identified several genes involved in lipid metabolism (e.g., NCR1, TNF, and UCP3) and oxidative stress (e.g., TPO, SGK2, and MTHFR) that may be indirectly related to heme-toxicity. The study's results provide preliminary evidence that heme-iron toxicity might be one underlying mechanism linking fresh red meat intake and lung cancer. PMID:23681825

  11. Use of Gene Expression Biomarkers to Predict Suicidality.

    PubMed

    Simons, Ries

    2016-07-01

    Since the tragic accident of Germanwings flight 4U9525, there has been discussion about methods to identify and prevent suicidality in pilots. Neurogenetic scientists claim that biomarker tests for suicidality as part of healthcare assessments may lead to early identification of suicidal behavior. In this commentary the value of these gene expression biomarkers for aeromedical purposes is evaluated based on relevant literature. It is concluded that the currently identified biomarkers for suicidality need thorough validation before they can be used. The aeromedical examiner's most important tool is still an anamnesis, in which warning signs of suicidal behavior can be picked up. Simons R. Use of gene expression biomarkers to predict suicidality. Aerosp Med Hum Perform. 2016; 87(7):659-660. PMID:27503048

  12. Prediction of Toddlers’ Expressive Language From Maternal Sensitivity And Toddlers’ Anger Expressions: A Developmental Perspective

    PubMed Central

    Nozadi, Sara S; Spinrad, Tracy L; Eisenberg, Nancy; Bolnick, Rebecca; Eggum-Wilkens, Natalie. D; Smith, Cynthia L; Gaertner, Bridget; Kupfer, Anne; Sallquist, Julie

    2013-01-01

    Despite evidence for the importance of individual differences in expressive language during toddlerhood in predicting later literacy skills, few researchers have examined individual and contextual factors related to language abilities across the toddler years. Furthermore, a gap remains in the literature about the extent to which the relations of negative emotions and parenting to language skills may differ for girls and boys. The purpose of this longitudinal study was to investigate the associations among maternal sensitivity, children’s observed anger reactivity, and expressive language when children were 18 (T1; n = 247) and 30 (T2; n = 216) months. At each age, mothers reported on their toddlers’ expressive language, and mothers’ sensitive parenting behavior was observed during an unstructured free-play task. Toddlers’ anger expressions were observed during an emotion-eliciting task. Using path modeling, results showed few relations at T1. At T2, maternal sensitivity was negatively related to anger, and in turn, anger was associated with lower language skills. However, moderation analyses showed that these findings were significant for boys but not for girls. In addition, T1 maternal sensitivity and anger positively predicted expressive language longitudinally for both sexes. Findings suggest that the relations between maternal sensitivity, anger reactivity and expressive language may vary depending on the child’s developmental stage and sex. PMID:23911594

  13. Molecular subtypes of serous borderline ovarian tumor show distinct expression patterns of benign tumor and malignant tumor-associated signatures.

    PubMed

    Curry, Edward W J; Stronach, Euan A; Rama, Nona R; Wang, Yuepeng Y P; Gabra, Hani; El-Bahrawy, Mona A

    2014-03-01

    Borderline ovarian tumors show heterogeneity in clinical behavior. Most have excellent prognosis, although a small percentage show recurrence or progressive disease, usually to low-grade serous carcinoma. The aim of this study was to understand the molecular relationship between these entities and identify potential markers of tumor progression and therapeutic targets. We studied gene expression using Affymetrix HGU133plus2 GeneChip microarrays in 3 low-grade serous carcinomas, 13 serous borderline tumors and 8 serous cystadenomas. An independent data set of 18 serous borderline tumors and 3 low-grade serous carcinomas was used for validation. Unsupervised clustering revealed clear separation of benign and malignant tumors, whereas borderline tumors showed two distinct groups, one clustering with benign and the other with malignant tumors. The segregation into benign- and malignant-like borderline molecular subtypes was reproducible on applying the same analysis to an independent publicly available data set. We identified 50 genes that separate borderline tumors into their subgroups. Functional enrichment analysis of genes that separate borderline tumors to the two subgroups highlights a cell adhesion signature for the malignant-like subset, with Claudins particularly prominent. This is the first report of molecular subtypes of borderline tumors based on gene expression profiling. Our results provide the basis for identification of biomarkers for the malignant potential of borderline ovarian tumor and potential therapeutic targets for low-grade serous carcinoma. PMID:23948749

  14. Analysis of Post-Traumatic Brain Injury Gene Expression Signature Reveals Tubulins, Nfe2l2, Nfkb, Cd44, and S100a4 as Treatment Targets

    PubMed Central

    Lipponen, Anssi; Paananen, Jussi; Puhakka, Noora; Pitkänen, Asla

    2016-01-01

    We aimed to define the chronically altered gene expression signature of traumatic brain injury (TBI-sig) to discover novel treatments to reverse pathologic gene expression or reinforce the expression of recovery-related genes. Genome-wide RNA-sequencing was performed at 3 months post-TBI induced by lateral fluid-percussion injury in rats. We found 4964 regulated genes in the perilesional cortex and 1966 in the thalamus (FDR < 0.05). TBI-sig was used for a LINCS analysis which identified 11 compounds that showed a strong connectivity with the TBI-sig in neuronal cell lines. Of these, celecoxib and sirolimus were recently reported to have a disease-modifying effect in in vivo animal models of epilepsy. Other compounds revealed by the analysis were BRD-K91844626, BRD-A11009626, NO-ASA, BRD-K55260239, SDZ-NKT-343, STK-661558, BRD-K75971499, ionomycin, and desmethylclomipramine. Network analysis of overlapping genes revealed the effects on tubulins (Tubb2a, Tubb3, Tubb4b), Nfe2l2, S100a4, Cd44, and Nfkb2, all of which are linked to TBI-relevant outcomes, including epileptogenesis and tissue repair. Desmethylclomipramine modulated most of the gene targets considered favorable for TBI outcome. Our data demonstrate long-lasting transcriptomics changes after TBI. LINCS analysis predicted that these changes could be modulated by various compounds, some of which are already in clinical use but never tested in TBI. PMID:27530814

  15. Analysis of Post-Traumatic Brain Injury Gene Expression Signature Reveals Tubulins, Nfe2l2, Nfkb, Cd44, and S100a4 as Treatment Targets.

    PubMed

    Lipponen, Anssi; Paananen, Jussi; Puhakka, Noora; Pitkänen, Asla

    2016-01-01

    We aimed to define the chronically altered gene expression signature of traumatic brain injury (TBI-sig) to discover novel treatments to reverse pathologic gene expression or reinforce the expression of recovery-related genes. Genome-wide RNA-sequencing was performed at 3 months post-TBI induced by lateral fluid-percussion injury in rats. We found 4964 regulated genes in the perilesional cortex and 1966 in the thalamus (FDR < 0.05). TBI-sig was used for a LINCS analysis which identified 11 compounds that showed a strong connectivity with the TBI-sig in neuronal cell lines. Of these, celecoxib and sirolimus were recently reported to have a disease-modifying effect in in vivo animal models of epilepsy. Other compounds revealed by the analysis were BRD-K91844626, BRD-A11009626, NO-ASA, BRD-K55260239, SDZ-NKT-343, STK-661558, BRD-K75971499, ionomycin, and desmethylclomipramine. Network analysis of overlapping genes revealed the effects on tubulins (Tubb2a, Tubb3, Tubb4b), Nfe2l2, S100a4, Cd44, and Nfkb2, all of which are linked to TBI-relevant outcomes, including epileptogenesis and tissue repair. Desmethylclomipramine modulated most of the gene targets considered favorable for TBI outcome. Our data demonstrate long-lasting transcriptomics changes after TBI. LINCS analysis predicted that these changes could be modulated by various compounds, some of which are already in clinical use but never tested in TBI. PMID:27530814

  16. MiR-34a Expression Has an Effect for Lower Risk of Metastasis and Associates with Expression Patterns Predicting Clinical Outcome in Breast Cancer

    PubMed Central

    Heikkinen, Tuomas; Kaur, Sippy; Bartkova, Jirina; Jamshidi, Maral; Aittomäki, Kristiina; Heikkilä, Päivi; Bartek, Jiri; Blomqvist, Carl; Bützow, Ralf; Nevanlinna, Heli

    2011-01-01

    MiR-34a acts as a candidate tumour suppressor gene, and its expression is reduced in several cancer types. We aimed to study miR-34a expression in breast cancer and its correlation with tumour characteristics and clinical outcome, and regulatory links with other genes. We analysed miR-34a expression in 1,172 breast tumours on TMAs. 25% of the tumours showed high, 43% medium and 32% low expression of miR-34a. High miR-34a expression associated with poor prognostic factors for breast cancer: positive nodal status (p = 0.006), high tumour grade (p<0.0001), ER-negativity (p = 0.0002), HER2-positivity (p = 0.0002), high proliferation rate (p<0.0001), p53-positivity (p<0.0001), high cyclin E (p<0.0001) and γH2AX (p<0.0001). However, multivariate analysis adjusting for conventional prognostic factors indicated that high miR-34a expression in fact associated with a lower risk of recurrence or death from breast cancer (HR = 0.63, 95% CI = 0.41–0.96, p = 0.031). Gene expression analysis by differential miR-34a expression revealed an expression signature with an effect on both the 5-year and 10-year survival of the patients (p<0.001). Functional genomic analysis highlighted a novel regulatory role of the transcription factor MAZ, apart from the known control by p53, on the expression of miR-34a and a number of miR-34a targets. Our findings suggest that while miR-34a expression activation is a marker of aggressive breast tumour phenotype it exerts an independent effect for a lower risk of recurrence or death from breast cancer. We also present an expression signature of 190 genes associated with miR-34a expression. Our analysis for regulatory loops suggest that MAZ and p53 transcription factors co-operate in modulating miR-34a, as well as miR-34a targets involved in several cellular pathways. Taken together, these results suggest that the network of genes co-regulated with and targeted by miR-34a form a group of down-stream effectors that maybe of

  17. Gene expression profiling in Daphnia magna, part II: validation of a copper specific gene expression signature with effluent from two copper mines in California.

    PubMed

    Poynton, Helen C; Zuzow, Rick; Loguinov, Alexandre V; Perkins, Edward J; Vulpe, Chris D

    2008-08-15

    Genomic technologies show great potential for classifying disease states and toxicological impacts from exposure to chemicals into functional categories. In environmental monitoring, the ability to classify field samples and predict the pollutants present in these samples could contribute to monitoring efforts and the diagnosis of contaminated sites. Using gene expression analysis, we challenged our custom Daphnia magna cDNA microarray to determine the presence of a specific metal toxicant in blinded field samples collected from two copper mines in California. We compared the gene expression profiles from our field samples to previously established expression profiles for Cu, Cd, and Zn. The expression profiles from the Cu-containing field samples clustered with the laboratory-exposed Cu-specific gene expression profiles and included genes previously identified as copper biomarkers, verifying that gene expression analysis can predict environmental exposure to a specific pollutant. In addition, our study revealed that upstream field samples containing undetectable levels of Cu caused the differential expression of only a few genes, lending support for the concept of a no observed transcriptional effect level (NOTEL). If confirmed by further studies, the NOTEL may play an important role in discriminating polluted and nonpolluted sites in future monitoring efforts. PMID:18767696

  18. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.

    PubMed

    Lamb, Justin; Crawford, Emily D; Peck, David; Modell, Joshua W; Blat, Irene C; Wrobel, Matthew J; Lerner, Jim; Brunet, Jean-Philippe; Subramanian, Aravind; Ross, Kenneth N; Reich, Michael; Hieronymus, Haley; Wei, Guo; Armstrong, Scott A; Haggarty, Stephen J; Clemons, Paul A; Wei, Ru; Carr, Steven A; Lander, Eric S; Golub, Todd R

    2006-09-29

    To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project. PMID:17008526

  19. mCSM-AB: a web server for predicting antibody-antigen affinity changes upon mutation with graph-based signatures.

    PubMed

    Pires, Douglas E V; Ascher, David B

    2016-07-01

    Computational methods have traditionally struggled to predict the effect of mutations in antibody-antigen complexes on binding affinity. This has limited their usefulness during antibody engineering and development, and their ability to predict biologically relevant escape mutations. Here we present mCSM-AB, a user-friendly web server for accurately predicting antibody-antigen affinity changes upon mutation which relies on graph-based signatures. We show that mCSM-AB performs better than comparable methods that have been previously used for antibody engineering. mCSM-AB web server is available at http://structure.bioc.cam.ac.uk/mcsm_ab. PMID:27216816

  20. Towards a tolerance toolkit: Gene expression signatures enabling the emergence of resistant bacterial strains

    NASA Astrophysics Data System (ADS)

    Erickson, Keesha; Chatterjee, Anushree

    2014-03-01

    Microbial pathogens are able to rapidly acquire tolerance to chemical toxins. Developing next-generation antibiotics that impede the emergence of resistance will help avoid a world-wide health crisis. Conversely, the ability to induce rapid tolerance gains could lead to high-yielding strains for sustainable production of biofuels and commodity chemicals. Achieving these goals requires an understanding of the general mechanisms allowing microbes to become resistant to diverse toxins. We apply top-down and bottom-up methodologies to identify biological network changes leading to adaptation and tolerance. Using a top-down approach, we perform evolution experiments to isolate resistant strains, collect samples for transcriptomic and proteomic analysis, and use the omics data to inform mathematical gene regulatory models. Using a bottom-up approach, we build and test synthetic genetic devices that enable increased or decreased expression of selected genes. Unique patterns in gene expression are identified in cultures actively gaining resistance, especially in pathways known to be involved with stress response, efflux, and mutagenesis. Genes correlated with tolerance could potentially allow the design of resistance-free antibiotics or robust chemical production strains.

  1. Identification of a 251 Gene Expression Signature That Can Accurately Detect M. tuberculosis in Patients with and without HIV Co-Infection

    PubMed Central

    Dawany, Noor; Showe, Louise C.; Kossenkov, Andrew V.; Chang, Celia; Ive, Prudence; Conradie, Francesca; Stevens, Wendy; Sanne, Ian

    2014-01-01

    Background Co-infection with tuberculosis (TB) is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. Methods We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC) samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. Results Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%). Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9–94.7% accuracy; 69.2–90% sensitivity and 90.3–100% specificity). We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. Conclusions A 251-gene signature is described to (a) detect TB in the presence or absence of an HIV co-infection, and (b) assess response to treatment following anti-TB therapy. PMID:24587128

  2. Transcriptomic Signature of the SHATTERPROOF2 Expression Domain Reveals the Meristematic Nature of Arabidopsis Gynoecial Medial Domain.

    PubMed

    Villarino, Gonzalo H; Hu, Qiwen; Manrique, Silvia; Flores-Vergara, Miguel; Sehra, Bhupinder; Robles, Linda; Brumos, Javier; Stepanova, Anna N; Colombo, Lucia; Sundberg, Eva; Heber, Steffen; Franks, Robert G

    2016-05-01

    Plant meristems, like animal stem cell niches, maintain a pool of multipotent, undifferentiated cells that divide and differentiate to give rise to organs. In Arabidopsis (Arabidopsis thaliana), the carpel margin meristem is a vital meristematic structure that generates ovules from the medial domain of the gynoecium, the female floral reproductive structure. The molecular mechanisms that specify this meristematic region and regulate its organogenic potential are poorly understood. Here, we present a novel approach to analyze the transcriptional signature of the medial domain of the Arabidopsis gynoecium, highlighting the developmental stages that immediately proceed ovule initiation, the earliest stages of seed development. Using a floral synchronization system and a SHATTERPROOF2 (SHP2) domain-specific reporter, paired with FACS and RNA sequencing, we assayed the transcriptome of the gynoecial medial domain with temporal and spatial precision. This analysis reveals a set of genes that are differentially expressed within the SHP2 expression domain, including genes that have been shown previously to function during the development of medial domain-derived structures, including the ovules, thus validating our approach. Global analyses of the transcriptomic data set indicate a similarity of the pSHP2-expressing cell population to previously characterized meristematic domains, further supporting the meristematic nature of this gynoecial tissue. Our method identifies additional genes including novel isoforms, cis-natural antisense transcripts, and a previously unrecognized member of the REPRODUCTIVE MERISTEM family of transcriptional regulators that are potential novel regulators of medial domain development. This data set provides genome-wide transcriptional insight into the development of the carpel margin meristem in Arabidopsis. PMID:26983993

  3. Transcriptomic Signature of the SHATTERPROOF2 Expression Domain Reveals the Meristematic Nature of Arabidopsis Gynoecial Medial Domain1[OPEN

    PubMed Central

    Villarino, Gonzalo H.; Hu, Qiwen; Flores-Vergara, Miguel; Sehra, Bhupinder; Brumos, Javier; Stepanova, Anna N.; Sundberg, Eva; Heber, Steffen

    2016-01-01

    Plant meristems, like animal stem cell niches, maintain a pool of multipotent, undifferentiated cells that divide and differentiate to give rise to organs. In Arabidopsis (Arabidopsis thaliana), the carpel margin meristem is a vital meristematic structure that generates ovules from the medial domain of the gynoecium, the female floral reproductive structure. The molecular mechanisms that specify this meristematic region and regulate its organogenic potential are poorly understood. Here, we present a novel approach to analyze the transcriptional signature of the medial domain of the Arabidopsis gynoecium, highlighting the developmental stages that immediately proceed ovule initiation, the earliest stages of seed development. Using a floral synchronization system and a SHATTERPROOF2 (SHP2) domain-specific reporter, paired with FACS and RNA sequencing, we assayed the transcriptome of the gynoecial medial domain with temporal and spatial precision. This analysis reveals a set of genes that are differentially expressed within the SHP2 expression domain, including genes that have been shown previously to function during the development of medial domain-derived structures, including the ovules, thus validating our approach. Global analyses of the transcriptomic data set indicate a similarity of the pSHP2-expressing cell population to previously characterized meristematic domains, further supporting the meristematic nature of this gynoecial tissue. Our method identifies additional genes including novel isoforms, cis-natural antisense transcripts, and a previously unrecognized member of the REPRODUCTIVE MERISTEM family of transcriptional regulators that are potential novel regulators of medial domain development. This data set provides genome-wide transcriptional insight into the development of the carpel margin meristem in Arabidopsis. PMID:26983993

  4. Molecular signature of disease onset in granulin mutation carriers: a gene expression analysis study.

    PubMed

    Milanesi, Elena; Bonvicini, Cristian; Alberici, Antonella; Pilotto, Andrea; Cattane, Nadia; Premi, Enrico; Gazzina, Stefano; Archetti, Silvana; Gasparotti, Roberto; Cancelli, Vanessa; Gennarelli, Massimo; Padovani, Alessandro; Borroni, Barbara

    2013-07-01

    Mutations within Granulin (GRN) gene are causative of autosomal dominant frontotemporal lobar degeneration (FTLD). Though GRN mutations are inherited at birth, the disease onset usually occurs in the sixth decade of life. The objective of this study was to identify new genetic pathways linked to inherited GRN disease and involved in the shift from asymptomatic to symptomatic stages. Microarray gene expression analysis on leukocytes was carried out on 15 patients carrying GRN T272SfsX10 mutation, and their asymptomatic siblings with (n = 14) or without (n = 11) GRN mutation. The results were then validated by real-time polymerase chain reaction, and compared with those obtained in a cohort of FTLD without GRN mutation (n = 16). The association between candidate genes and damage of specific brain areas was investigated by voxel-based morphometry on magnetic resonance imaging scans (family-wise error-corrected). Leukocytes mRNA levels of TMEM40 and LY6G6F and other genes mainly involved in inflammation were significantly higher in patients carrying GRN mutations compared with asymptomatic carriers and other FTLD. The higher the levels of TMEM40 the greater is the damage of parietal lobule; the higher the LY6G6F gene expression the greater is the atrophy in superior frontal gyrus. Enhanced inflammation associated with the onset of GRN disease might be either related to disease pathogenetic mechanism leading to neurodegeneration or to a compensatory pathway that counteracts disease progression. The identification of specific molecular targets of GRN-FTLD disease is essential when considering future disease-modifying therapies. PMID:23419701

  5. Identification of Novel Cholesteatoma-Related Gene Expression Signatures Using Full-Genome Microarrays

    PubMed Central

    Klenke, Christin; Janowski, Sebastian; Borck, Daniela; Widera, Darius; Ebmeyer, Jörg; Kalinowski, Jörn; Leichtle, Anke; Hofestädt, Ralf; Upile, Tahwinder; Kaltschmidt, Christian; Kaltschmidt, Barbara; Sudhoff, Holger

    2012-01-01

    Background Cholesteatoma is a gradually expanding destructive epithelial lesion within the middle ear. It can cause extensive local tissue destruction in the temporal bone and can initially lead to the development of conductive hearing loss via ossicular erosion. As the disease progresses, sensorineural hearing loss, vertigo or facial palsy may occur. Cholesteatoma may promote the spread of infection through the tegmen of the middle ear and cause meningitis or intracranial infections with abscess formation. It must, therefore, be considered as a potentially life-threatening middle ear disease. Methods and Findings In this study, we investigated differentially expressed genes in human cholesteatomas in comparison to regular auditory canal skin using Whole Human Genome Microarrays containing 19,596 human genes. In addition to already described up-regulated mRNAs in cholesteatoma, such as MMP9, DEFB2 and KRT19, we identified 3558 new cholesteatoma-related transcripts. 811 genes appear to be significantly differentially up-regulated in cholesteatoma. 334 genes were down-regulated more than 2-fold. Significantly regulated genes with protein metabolism activity include matrix metalloproteinases as well as PI3, SERPINB3 and SERPINB4. Genes like SPP1, KRT6B, PRPH, SPRR1B and LAMC2 are known as genes with cell growth and/or maintenance activity. Transport activity genes and signal transduction genes are LCN2, GJB2 and CEACAM6. Three cell communication genes were identified; one CDH19 and two from the S100 family. Conclusions This study demonstrates that the expression profile of cholesteatoma is similar to a metastatic tumour and chronically inflamed tissue. Based on the investigated profiles we present novel protein-protein interaction and signal transduction networks, which include cholesteatoma-regulated transcripts and may be of great value for drug targeting and therapy development. PMID:23285167

  6. Signature gene expression profiles discriminate between isoniazid-, thiolactomycin-, and triclosan-treated Mycobacterium tuberculosis.

    PubMed

    Betts, Joanna C; McLaren, Alistair; Lennon, Mark G; Kelly, Fiona M; Lukey, Pauline T; Blakemore, Steve J; Duncan, Ken

    2003-09-01

    Genomic technologies have the potential to greatly increase the efficiency of the drug development process. As part of our tuberculosis drug discovery program, we used DNA microarray technology to profile drug-induced effects in Mycobacterium tuberculosis. Expression profiles of M. tuberculosis treated with compounds that inhibit key metabolic pathways are required as references for the assessment of novel antimycobacterial agents. We have studied the response of M. tuberculosis to treatment with the mycolic acid biosynthesis inhibitors isoniazid, thiolactomycin, and triclosan. Thiolactomycin targets the beta-ketoacyl-acyl carrier protein (ACP) synthases KasA and KasB, while triclosan inhibits the enoyl-ACP reductase InhA. However, controversy surrounds the precise mode of action of isoniazid, with both InhA and KasA having been proposed as the primary target. We have shown that although the global response profiles of isoniazid and thiolactomycin are more closely related to each other than to that of triclosan, there are differences that distinguish the mode of action of these two drugs. In addition, we have identified two groups of genes, possibly forming efflux and detoxification systems, through which M. tuberculosis may limit the effects of triclosan. We have developed a mathematical model, based on the expression of 21 genes, which is able to perfectly discriminate between isoniazid-, thiolactomycin-, or triclosan-treated M. tuberculosis. This model is likely to prove invaluable as a tool to improve the efficiency of our drug development programs by providing a means to rapidly confirm the mode of action of thiolactomycin analogues or novel InhA inhibitors as well as helping to translate enzyme activity into whole-cell activity. PMID:12936993

  7. Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders

    PubMed Central

    Connors, Brenda L.; Rende, Richard; Colton, Timothy J.

    2013-01-01

    There has been a surge of interest in examining the utility of methods for capturing individual differences in decision-making style. We illustrate the potential offered by Movement Pattern Analysis (MPA), an observational methodology that has been used in business and by the US Department of Defense to record body movements that provide predictive insight into individual differences in decision-making motivations and actions. Twelve military officers participated in an intensive 2-h interview that permitted detailed and fine-grained observation and coding of signature movements by trained practitioners using MPA. Three months later, these subjects completed four hypothetical decision-making tasks in which the amount of information sought out before coming to a decision, as well as the time spent on the tasks, were under the partial control of the subject. A composite MPA indicator of how a person allocates decision-making actions and motivations to balance both Assertion (exertion of tangible movement effort on the environment to make something occur) and Perspective (through movements that support shaping in the body to perceive and create a suitable viewpoint for action) was highly correlated with the total number of information draws and total response time—individuals high on Assertion reached for less information and had faster response times than those high on Perspective. Discussion focuses on the utility of using movement-based observational measures to capture individual differences in decision-making style and the implications for application in applied settings geared toward investigations of experienced leaders and world statesmen where individuality rules the day. PMID:24069012

  8. Comprehensive analysis of miRNA expression in T-cell subsets of rheumatoid arthritis patients reveals defined signatures of naive and memory Tregs

    PubMed Central

    Smigielska-Czepiel, K; van den Berg, A; Jellema, P; van der Lei, R J; Bijzet, J; Kluiver, J; Boots, A M H; Brouwer, E; Kroesen, B-J

    2014-01-01

    Disturbed expression of microRNAs (miRNAs) in regulatory T cells (Tregs) leads to development of autoimmunity in experimental mouse models. However, the miRNA expression signature characterizing Tregs of autoimmune diseases, such as rheumatoid arthritis (RA) has not been determined yet. In this study, we have used a microarray approach to comprehensively analyze miRNA expression signatures of both naive Tregs (CD4+CD45RO-CD25++) and memory Tregs (CD4+CD45RO+CD25+++), as well as conventional naive (CD4+CD45RO−CD25−) and memory (CD4+CD45RO+CD25−) T cells (Tconvs) derived from peripheral blood of RA patients and matched healthy controls. Differential expression of selected miRNAs was validated by TaqMan-based quantitative reverse transcription-PCR. We found a positive correlation between increased expression of miR-451 in T cells of RA patients and disease activity score (DAS28), erythrocyte sedimentation rate levels and serum levels of interleukin-6. Moreover, we found characteristic, disease- and treatment-independent, global miRNA expression signatures defining naive Tregs, memory Tregs, naive Tconvs and memory Tconvs. The analysis allowed us to define miRNAs characteristic for a general naive phenotype (for example, miR-92a) and a general memory phenotype (for example, miR-21, miR-155). Importantly, the analysis allowed us to define miRNAs that are specifically expressed in both naive and memory Tregs, defining as such miRNA signature characterizing the Treg phenotype (that is, miR-146a, miR-3162, miR-1202, miR-1246 and miR-4281). PMID:24401767

  9. Identification of Gene Expression Biomarkers for Predicting Radiation Exposure

    PubMed Central

    Lu, Tzu-Pin; Hsu, Yi-Yao; Lai, Liang-Chuan; Tsai, Mong-Hsun; Chuang, Eric Y.

    2014-01-01

    A need for more accurate and reliable radiation dosimetry has become increasingly important due to the possibility of a large-scale radiation emergency resulting from terrorism or nuclear accidents. Although traditional approaches provide accurate measurements, such methods usually require tedious effort and at least two days to complete. Therefore, we provide a new method for rapid prediction of radiation exposure. Eleven microarray datasets were classified into two groups based on their radiation doses and utilized as the training samples. For the two groups, Student's t-tests and resampling tests were used to identify biomarkers, and their gene expression ratios were used to develop a prediction model. The performance of the model was evaluated in four independent datasets, and Ingenuity pathway analysis was performed to characterize the associated biological functions. Our meta-analysis identified 29 biomarkers, showing approximately 90% and 80% accuracy in the training and validation samples. Furthermore, the 29 genes significantly participated in the regulation of cell cycle, and 19 of them are regulated by three well-known radiation-modulated transcription factors: TP53, FOXM1 and ERBB2. In conclusion, this study demonstrates a reliable method for identifying biomarkers across independent studies and high and reproducible prediction accuracy was demonstrated in both internal and external datasets. PMID:25189756

  10. Expression signature of lncRNAs and their potential roles in cardiac fibrosis of post-infarct mice.

    PubMed

    Qu, Xuefeng; Song, Xiaotong; Yuan, Wei; Shu, You; Wang, Yuying; Zhao, Xuyun; Gao, Ming; Lu, Renzhong; Luo, Shenjian; Zhao, Wei; Zhang, Yue; Sun, Lihua; Lu, Yanjie

    2016-07-01

    The present study aimed to investigate whether long non-coding RNAs (lncRNAs) are involved in cardiac fibrogenesis induced by myocardial infarction (MI). The differentially expressed lncRNAs and mRNAs in peri-infarct region of mice 4 weeks after MI were selected for bioinformatic analysis including gene ontology (GO) enrichment, pathway and network analysis. Left ventricular tissue levels of lncRNAs and mRNAs were compared between MI and sham control mice, using a false discovery rate (FDR) of <5%. Out of 55000 lncRNAs detected, 263 were significantly up-regulated and 282 down-regulated. Out of 23000 mRNAs detected, 142 were significantly up-regulated and 67 down-regulated. Among the differentially expressed lncRNAs, 53 were up-regulated by ≥2.0-fold change and 37 down-regulated by ≤0.5-fold change. Nine up-regulated and five down-regulated lncRNAs were randomly selected for quantitative real-time PCR (qRT-PCR) verification. GO and pathway analyses revealed 173 correlated lncRNA-mRNA pairs for 57 differentially expressed lncRNAs and 20 differentially expressed genes which are related to the development of cardiac fibrosis. We identified TGF-β3 as the top-ranked gene, a critical component of the transforming growth factor-β (TGF-β) and mitogen activated protein kinase (MAPK) signalling pathways in cardiac fibrosis. NONMMUT022554 was identified as the top-ranked lncRNA, positively correlated with six up-regulated genes, which are involved in the extracellular matrix (ECM)-receptor interactions and the phosphoinositid-3 kinase/protein kinase B (PI3K-Akt) signalling pathway. Our study has identified the expression signature of lncRNAs in cardiac fibrosis induced by MI and unravelled the possible involvement of the deregulated lncRNAs in cardiac fibrosis and the associated pathological processes. PMID:27129287

  11. Gene expression signature for angiogenic and nonangiogenic non-small-cell lung cancer.

    PubMed

    Hu, Jiangting; Bianchi, Fabrizio; Ferguson, Mary; Cesario, Alfredo; Margaritora, Stefano; Granone, Pierluigi; Goldstraw, Peter; Tetlow, Michelle; Ratcliffe, Cathy; Nicholson, Andrew G; Harris, Adrian; Gatter, Kevin; Pezzella, Francesco

    2005-02-10

    Angiogenesis is regarded as essential for tumour growth. However, we have demonstrated that some other aggressive non-small-cell lung carcinomas (n-SCLC) do not have angiogenesis. In this study, using cDNA microarray analysis, we demonstrate that angiogenic and nonangiogenic tumour types can be distinguished by their gene expression profiles. Tissue samples from 42 n-SCLC patients were obtained with consent. In all, 12 tumours were nonangiogenic and 30 angiogenic. The two groups were matched by age, sex, smoking and tumour stage. Total RNAs were extracted followed by microarray hybridization and image scan procedure. Data were analysed using GeneSpring 5.1 software. A total of 62 genes were found to be able to separate angiogenic from nonangiogenic tumours. Nonangiogenic tumours have higher levels of genes concerned with mitochondrial metabolism, mRNA transcription, protein synthesis and the cell cycle. Angiogenic tumours have higher levels of genes coding for membrane vesicles, integrins, remodelling, angiogenesis and apoptosis. These results further support our first finding that nonangiogenic lung tumours are fast-growing tumours filling the alveoli in the absence of vascular remodelling. We raise the hypothesis that in nonangiogenic tumours, hypoxia leads to a higher activation of the mitochondrial respiratory chain, which allows tumour growth without triggering angiogenesis. PMID:15592519

  12. A 7-gene signature of the recipient predicts the progression of fibrosis after liver transplantation for hepatitis C virus infection.

    PubMed

    do O, Nicole T; Eurich, Dennis; Schmitz, Petra; Schmeding, Maximilian; Heidenhain, Christoph; Bahra, Marcus; Trautwein, Christian; Neuhaus, Peter; Neumann, Ulf P; Wasmuth, Hermann E

    2012-03-01

    Fibrosis recurrence after liver transplantation (LT) for hepatitis C virus (HCV) is a universal event and strongly determines a patient's prognosis. The recipient risk factors for fibrosis recurrence are still poorly defined. Here we assess a genetic risk score as a predictor of fibrosis after LT. The cirrhosis risk score (CRS), which comprises allele variants in 7 genes (adaptor-related protein complex 3 S2, aquaporin 2, antizyme inhibitor 1, degenerative spermatocyte homolog 1 lipid desaturase, syntaxin binding protein 5-like, toll-like receptor 4, and transient receptor potential cation channel M5), was calculated for 137 patients who underwent LT for HCV infection and experienced HCV reinfection of the graft. The patients were stratified into 3 CRS categories: <0.5, 0.5 to 0.7, and >0.7. All patients underwent protocol biopsy after LT (median follow-up = 5 years), and liver fibrosis was assessed according to the Desmet and Scheuer score. The data were analyzed with univariate and multivariate analyses. The results showed that the highest CRS category was strongly associated with the presence of F2 or F3 fibrosis in protocol biopsy samples 1, 3, and 5 years after LT (P = 0.006, P = 0.001, and P = 0.02, respectively). Overall, 75.0% of the patients with a CRS > 0.7 developed at least F2 fibrosis, whereas 51.5% developed F3 fibrosis during follow-up. The predictive value of the CRS for fibrosis progression was independent of known clinical risk factors, including the age of the donor, the sex of the recipient, and the occurrence of acute rejection. A Kaplan-Meier analysis confirmed the prognostic value of the CRS with respect to the recurrence of severe liver fibrosis in HCV-infected patients after LT (log rank = 6.23, P = 0.03). In conclusion, the genetic signature of the recipient predicts the likelihood of severe liver fibrosis in the graft after HCV recurrence. The CRS might help with early clinical decision making (eg, the selection of patients for antiviral

  13. Spatio-Temporal Gene Expression Profiling during In Vivo Early Ovarian Folliculogenesis: Integrated Transcriptomic Study and Molecular Signature of Early Follicular Growth

    PubMed Central

    Bonnet, Agnes; Servin, Bertrand; Mulsant, Philippe; Mandon-Pepin, Beatrice

    2015-01-01

    Background The successful achievement of early ovarian folliculogenesis is important for fertility and reproductive life span. This complex biological process requires the appropriate expression of numerous genes at each developmental stage, in each follicular compartment. Relatively little is known at present about the molecular mechanisms that drive this process, and most gene expression studies have been performed in rodents and without considering the different follicular compartments. Results We used RNA-seq technology to explore the sheep transcriptome during early ovarian follicular development in the two main compartments: oocytes and granulosa cells. We documented the differential expression of 3,015 genes during this phase and described the gene expression dynamic specific to these compartments. We showed that important steps occurred during primary/secondary transition in sheep. We also described the in vivo molecular course of a number of pathways. In oocytes, these pathways documented the chronology of the acquisition of meiotic competence, migration and cellular organization, while in granulosa cells they concerned adhesion, the formation of cytoplasmic projections and steroid synthesis. This study proposes the involvement in this process of several members of the integrin and BMP families. The expression of genes such as Kruppel-like factor 9 (KLF9) and BMP binding endothelial regulator (BMPER) was highlighted for the first time during early follicular development, and their proteins were also predicted to be involved in gene regulation. Finally, we selected a data set of 24 biomarkers that enabled the discrimination of early follicular stages and thus offer a molecular signature of early follicular growth. This set of biomarkers includes known genes such as SPO11 meiotic protein covalently bound to DSB (SPO11), bone morphogenetic protein 15 (BMP15) and WEE1 homolog 2 (S. pombe)(WEE2) which play critical roles in follicular development but other

  14. Prediction of antibiotic resistance by gene expression profiles

    PubMed Central

    Suzuki, Shingo; Horinouchi, Takaaki; Furusawa, Chikara

    2014-01-01

    Although many mutations contributing to antibiotic resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype–genotype mapping for drug resistance, here we analyse phenotypic and genotypic changes of antibiotic-resistant Escherichia coli strains obtained by laboratory evolution. We demonstrate that the resistances can be quantitatively predicted by the expression changes of a small number of genes. Several candidate mutations contributing to the resistances are identified, while phenotype–genotype mapping is suggested to be complex and includes various mutations that cause similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances. PMID:25517437

  15. Expression genomics and drug development: towards predictive pharmacology.

    PubMed

    Liu, Edison T

    2005-02-01

    Expression genomics can be defined as the study of the dynamic transciptome and its regulatory elements. Technologies are available that can assess transcripts on a genome-wide scale over time and across many samples. This comprehensive and dynamic database is being used to decipher signalling pathways and to identify new biomarkers and targets. Biomarkers emerging from these studies have prognostic potential and can be used to predict therapeutic outcome. The multiplex nature of this approach not only telescopes the time to discovery, but also allows for detection of complex interactions. Taken together, these capabilities, if carefully used, can speed drug development, enhance the identification of potent drug combinations and identify patient populations that will benefit from these new drugs. PMID:15814022

  16. Gene Expression Profiles of Peripheral Blood Mononuclear Cells Reveal Transcriptional Signatures as Novel Biomarkers for Cardiac Remodeling in Rats with Aldosteronism and Hypertensive Heart Disease

    PubMed Central

    Gerling, Ivan C.; Ahokas, Robert A.; Kamalov, German; Zhao, Wenyuan; Bhattacharya, Syamal K.; Sun, Yao; Weber, Karl T.

    2013-01-01

    Objectives In searching for a noninvasive surrogate tissue having mimicry with the prooxidant/-proinflammatory hypertensive heart disease (HHD) phenotype, we turned to peripheral blood mononuclear cells (PBMC). We tested whether iterations in [Ca2+]i, [Zn2+]i and oxidative stress in cardiomyocytes and PBMC would complement each other eliciting similar shifts in gene expression profiles in these tissues demonstrable during preclinical (wk 1) and pathologic (wk 4) stages of aldosterone/salt treatment (ALDOST). Background Inappropriate neurohormonal activation contributes to pathologic remodeling of myocardium in HHD associated with aldosteronism. In rats receiving chronic ALDOST, evidence of reparative fibrosis replacing necrotic cardiomyocytes and coronary vasculopathy appears at wk 4 associated with the induction of oxidative stress by mitochondria that overwhelms endogenous, largely Zn2+-based, antioxidant defenses. Biomarker-guided prediction of risk prior to the appearance of cardiac pathology would prove invaluable. Methods In PBMC and cardiomyocytes, quantitation of cytoplasmic free Ca2+ and Zn2+, H2O2 and 8-iosprostane levels, as well as isolation of RNA and gene expression, together with statistical and clustering analyses, and confirmation of genes by in situ hybridization and RT-PCR, were performed. Results Compared to controls, at wk 1 and 4 ALDOST, we found comparable: increments in [Ca2+]i, [Zn2+]i and 8-isoprotane coupled to increased H2O2 production in cardiac mitochondria and PBMC, together with the common networks of expression profiles dominated by genes involved in oxidative stress, inflammation and repair. These included three central Ingenuity pathway-linked genes: p38MAPK, a stress-responsive protein; NFκB, a redox-sensitive transcription factor and a proinflammatory cascade it regulates; and TGF-β1, a fibrogenic cytokine involved in tissue repair. Conclusions Significant overlapping demonstrated in the molecular mimicry of PBMC and

  17. Novel gene expression model for outcome prediction in paediatric medulloblastoma.

    PubMed

    Zakrzewska, Magdalena; Grešner, Sylwia M; Zakrzewski, Krzysztof; Zalewska-Szewczyk, Beata; Liberski, Pawel P

    2013-10-01

    Medulloblastoma is the most frequent type of embryonal tumour in the paediatric population. The disease progression in patients with this tumour may be connected with the presence of stem/tumour-initiating cells, but the precise source and characteristics of such cells is still a subject of debate. Thus, we tried to analyse biomarkers for which a connection with the presence of stem/tumour-initiating cells was suggested. We evaluated the transcriptional level of the ATOH1, FUT4, NGFR, OTX1, OTX2, PROM1 and SOX1 genes in 48 samples of medulloblastoma and analysed their usefulness in the prediction of disease outcome. The analyses showed a strong correlation of PROM1, ATOH1 and OTX1 gene expression levels with the outcome (p ≤ 0.2). On the basis of the multivariate Cox regression analysis, we propose a three-gene model predicting risk of the disease, calculated as follows: RS(risk score) =( 0:81 x PROM1) + (0:18 x OTX1) + (0:02 x ATOH1). Survival analysis revealed a better outcome among standard-risk patients, with a 5-year survival rate of 65 %, compared to the 40 % rate observed among high-risk patients. The most promising advantage of such molecular analysis consists in the identification of molecular markers influencing clinical behaviour, which may in turn be useful in therapy optimization. PMID:23649504

  18. Development of a computer technique for the prediction of transport aircraft flight profile sonic boom signatures. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Coen, Peter G.

    1991-01-01

    A new computer technique for the analysis of transport aircraft sonic boom signature characteristics was developed. This new technique, based on linear theory methods, combines the previously separate equivalent area and F function development with a signature propagation method using a single geometry description. The new technique was implemented in a stand-alone computer program and was incorporated into an aircraft performance analysis program. Through these implementations, both configuration designers and performance analysts are given new capabilities to rapidly analyze an aircraft's sonic boom characteristics throughout the flight envelope.

  19. Meteor signature interpretation

    SciTech Connect

    Canavan, G.H.

    1997-01-01

    Meteor signatures contain information about the constituents of space debris and present potential false alarms to early warnings systems. Better models could both extract the maximum scientific information possible and reduce their danger. Accurate predictions can be produced by models of modest complexity, which can be inverted to predict the sizes, compositions, and trajectories of object from their signatures for most objects of interest and concern.

  20. Probing the ToxCastTM Chemical Library for Predictive Signatures of Developmental Toxicity - Poster at Teratology Society Annual Meeting

    EPA Science Inventory

    EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

  1. Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer

    PubMed Central

    Chauhan, S S; Kaur, J; Kumar, M; Matta, A; Srivastava, G; Alyass, A; Assi, J; Leong, I; MacMillan, C; Witterick, I; Colgan, T J; Shukla, N K; Thakar, A; Sharma, M C; Siu, K W M; Walfish, P G; Ralhan, R

    2015-01-01

    Loco-regional recurrence in 50% of oral squamous cell carcinoma (OSCC) patients poses major challenge for oncologists. Lack of biomarkers that can predict disease aggressiveness and recurrence risk makes the scenario more dismal. On the basis of our earlier global proteomic analyses we identified five differentially expressed proteins in OSCC. This study aimed to develop protein biomarkers-based prognostic risk prediction model for OSCC. Sub-cellular expression of five proteins, S100A7, heterogeneous nuclear ribonucleoproteinK (hnRNPK), prothymosin α (PTMA), 14-3-3ζ and 14-3-3σ was analyzed by immunohistochemistry in test set (282 Indian OSCCs and 209 normal tissues), correlated with clinic–pathological parameters and clinical outcome over 12 years to develop a risk model for prediction of recurrence-free survival. This risk classifier was externally validated in 135 Canadian OSCC and 96 normal tissues. Biomarker signature score based on PTMA, S100A7 and hnRNPK was associated with recurrence free survival of OSCC patients (hazard ratio=1.11; 95% confidence interval 1.08, 1.13, P<0.001, optimism-corrected c-statistic=0.69) independent of clinical parameters. Biomarker signature score stratified OSCC patients into high- and low-risk groups with significant difference for disease recurrence. The high-risk group had median survival 14 months, and 3-year survival rate of 30%, whereas low-risk group survival probability did not reach 50%, and had 3-year survival rate of 71%. As a powerful predictor of 3-year recurrence-free survival in OSCC patients, the newly developed biomarkers panel risk classifier will facilitate patient counseling for personalized treatment. PMID:25893634

  2. Expression profiling and prediction of distant metastases in head and neck squamous cell carcinoma

    PubMed Central

    Braakhuis, B J M; Senft, A; de Bree, R; de Vries, J; Ylstra, B; Cloos, J; Kuik, D J; Leemans, C R; Brakenhoff, R H

    2006-01-01

    Background For breast and prostate cancer, a gene expression signature of the tumour is associated with the development of distant metastases. Regarding head and neck squamous cell carcinoma (HNSCC), the only known risk factor is the presence of ⩾3 tumour‐positive lymph nodes. Aim To evaluate whether a HNSCC gene expression signature can discriminate between the patients with and without distant metastases. Methods Patients with HNSCC with and without distant metastases had >3 tumour‐positive lymph nodes, and did not differ with respect to other risk factors. Statistical analysis was carried out using Student's t test, as well as statistical analysis of microarrays (SAM), to assess the false discovery rate for each gene. These analyses were supplemented with a newly developed method that computed deviations from gaussian‐order statistics (DEGOS). To validate the platform, normal mucosa of the head and neck was included as control. Results 2963 genes were differently expressed between HNSCC and normal mucosa (t test; p<0.01). More rigorous statistical analysis with SAM confirmed the differential expression of most genes. The comparison of genes in HNSCC with and without metastases showed 150 differently expressed genes (t test; p<0.01), none of which, however, could be confirmed using SAM or DEGOS. Conclusions No evidence for a metastasis signature is found, and gene expression profiling of HNSCC has seemingly no value in determining the risk of developing distant metastases. The absence of such a signature can be understood when it is realised that, for HNSCC in contrast with breast cancer, the lymph nodes are a necessary in‐between station for haematogenous spread. PMID:16679350

  3. Identification and Validation of a Five MicroRNA Signature Predictive of Prostate Cancer Recurrence and Metastasis: A Cohort Study

    PubMed Central

    Nam, Robert K.; Amemiya, Yutaka; Benatar, Tania; Wallis, Christopher J.D.; Stojcic-Bendavid, Jessica; Bacopulos, Stephanie; Sherman, Christopher; Sugar, Linda; Naeim, Magda; Yang, Wenyi; Zhang, Aiguo; Klotz, Laurence H.; Narod, Steven A.; Seth, Arun

    2015-01-01

    Background: MicroRNA (miRNA) have been shown to be important in regulating gene expression in prostate cancer. We used next generation miRNA sequencing to conduct a whole miRNome analysis to identify miRNAs associated with prostate cancer metastasis. Methods: We conducted discovery and validation analyses of miRNAs among a total of 546 men who underwent surgery for prostate cancer using the development of metastasis as an endpoint. Genome wide analysis was conducted among the discovery group (n=31) to identify new miRNAs associated with prostate cancer metastasis. Selected miRNAs were then analyzed using qPCR on prostatectomy specimens from an independent cohort (n=515) to determine whether their expression could predict the development of metastasis after surgery. To examine the biology underlying these associations, we created prostate cancer cell lines which overexpressed miR-301a for in vitro and in vivo functional assays. Results: We identified 33 miRNAs associated with prostate cancer metastasis and selected a panel comprising miRs-301a, 652, 454, 223 and 139 which strongly predicted metastasis (AUC=95.3%, 95%C.I.:84%-99%). Among the validation cohort, the 15-year metastasis-free survival was 77.5% (95% C.I.:63.9%-86.4%) for patients with a high miRNA panel score and 98.8% (95% C.I.:94.9%-99.7%, p<0.0001 for difference) for those with a low score. After adjusting for grade, stage, and PSA, the hazard ratio for metastasis was 4.3 (95% C.I.: 1.7-11.1, p=0.002) for patients with a high miRNA panel score, compared to those with a low score. Prostate cancer cell lines overexpressing miR-301a had in significantly higher tumor growth and metastasis in a xenograft mouse model. Conclusions: A panel of miRNAs is associated with prostate cancer metastasis. These could be used as potential new prognostic factors in the surgical management of prostate cancer. PMID:26516365

  4. Detection of Tuberculosis in HIV-Infected and -Uninfected African Adults Using Whole Blood RNA Expression Signatures: A Case-Control Study

    PubMed Central

    Anderson, Suzanne T.; Bangani, Nonzwakazi; Banwell, Claire M.; Brent, Andrew J.; Crampin, Amelia C.; Dockrell, Hazel M.; Eley, Brian; Heyderman, Robert S.; Hibberd, Martin L.; Kern, Florian; Langford, Paul R.; Ling, Ling; Mendelson, Marc; Ottenhoff, Tom H.; Zgambo, Femia; Wilkinson, Robert J.; Coin, Lachlan J.; Levin, Michael

    2013-01-01

    Background A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Methods and Findings Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87–100]; specificity 90%, 95% CI [80–97]) and TB from OD (sensitivity 93%, 95% CI [83–100]; specificity 88%, 95% CI [74–97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85–100]; specificity 94%, 95% CI [84–100]) and OD patients (sensitivity 100%, 95% CI [100–100]; specificity 96%, 95% CI [93–100]). Limitations of our study include the use of

  5. An integrated model of clinical information and gene expression for prediction of survival in ovarian cancer patients.

    PubMed

    Yang, Rendong; Xiong, Jie; Deng, Defeng; Wang, Yiren; Liu, Hequn; Jiang, Guli; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

    2016-06-01

    Accumulating evidence shows that clinical factors alone are not adequate for predicting the survival of patients with ovarian cancer (OvCa), and many genes have been found to be associated with OvCa prognosis. The objective of this study was to develop a model that integrates clinical information and a gene signature to predict the survival durations of patients diagnosed with OvCa. We constructed mRNA and microRNA expression profiles and gathered the corresponding clinical data of 552 OvCa patients and 8 normal controls from The Cancer Genome Atlas. Using univariate Cox regression followed by a permutation test, elastic net-regulated Cox regression, and ridge regression, we generated a prognosis index consisting of 2 clinical variables, 7 protective mRNAs, 12 risky mRNAs, and 1 protective microRNA. The area under the curve of the receiver operating characteristic of the integrated clinical-and-gene model was 0.756, larger than that of the clinical-alone model (0.686) or the gene-alone model (0.703). OvCa patients in the high-risk group had a significantly shorter overall survival time compared with patients in the low-risk group (hazard ratio = 8.374, 95% confidence interval = 4.444-15.780, P = 4.90 × 10(-11), by the Wald test). The reliability of the gene signature was confirmed by a public external data set from the Gene Expression Omnibus. Our conclusions that we have identified an integrated clinical-and-gene model superior to the traditional clinical-alone model in ascertaining the survival prognosis of patients with OvCa. Our findings may prove valuable for improving the clinical management of OvCa. PMID:27059002

  6. Tissue microarrays characterise the clinical significance of a VEGF-A protein expression signature in gastrointestinal stromal tumours

    PubMed Central

    Salto-Tellez, M; Nga, M E; Han, H C; Wong, A S-C; Lee, C K; Anuar, D; Ng, S S; Ho, M; Wee, A; Chan, Y H; Soong, R

    2007-01-01

    A tissue microarray analysis of 22 proteins in gastrointestinal stromal tumours (GIST), followed by an unsupervised, hierarchical monothetic cluster statistical analysis of the results, allowed us to detect a vascular endothelial growth factor (VEGF) protein overexpression signature discriminator of prognosis in GIST, and discover novel VEGF-A DNA variants that may have functional significance. PMID:17299397

  7. Profile of differentially expressed intratumoral cytokines to predict the immune-polarizing side effects of tamoxifen in breast cancer treatment

    PubMed Central

    Li, Bailiang; Li, Yang; Wang, Xiao-Yu; Yan, Zi-Qiao; Liu, Huidi; Liu, Gui-Rong; Liu, Shu-Lin

    2015-01-01

    Factors within the tissue of breast cancer (BC) may shift the polarization of CD4+ T cells towards Th2 direction. This tendency can promote tumor development and be enhanced by the use of tamoxifen during the treatment. Thus, the patients with low levels of tumor-induced Th2 polarization prior to tamoxifen treatment may better endure the immune-polarizing side effects (IPSE) of tamoxifen and have better prognoses. Estimation of Th2 polarization status should help predict the IPSE among tamoxifen-treated patients and guide the use of tamoxifen among all BC patients before the tamoxifen therapy. Here, we report profiling of differentially expressed (DE) intratumoral cytokines as a signature to evaluate the IPSE of tamoxifen. The DE genes of intratumoral CD4+ T cells (CD4 DEGs) were identified by gene expression profiles of purified CD4+ T cells from BC patients and validated by profiling of cultured intratumoral CD4+ T cells. Functional enrichment analyses showed a directed Th2 polarization of intratumoral CD4+ T cells. To find the factors inducing the Th2 polarization of CD4+ T cells, we identified 995 common DE genes of bulk BC tissues (BC DEGs) by integrating five independent datasets. Five DE cytokines observed in bulk BC tissues with dysregulated receptors in the intratumoral CD4+ T cells were selected as the predictor of the IPSE of tamoxifen. The patients predicted to suffer low IPSE (low Th2 polarization) had a significantly lower distant relapse risk than the patients predicted to suffer high IPSE in independent datasets (n = 608; HR = 4.326, P = 0.000897; HR = 2.014, P = 0.0173; HR = 2.72, P = 0.04077). Patients predicted to suffer low IPSE would benefit from tamoxifen treatment (HR = 2.908, P = 0.03905). The DE intratumoral cytokines identified in this study may help predict the IPSE of tamoxifen and justify the use of tamoxifen in BC treatment. PMID:25973310

  8. MORPHOLOGICAL SIGNATURES AND GENOMIC CORRELATES IN GLIOBLASTOMA

    PubMed Central

    Cooper, Lee A.D.; Kong, Jun; Wang, Fusheng; Kurc, Tahsin; Moreno, Carlos S.; Brat, Daniel J.; Saltz, Joel H.

    2011-01-01

    Large multimodal datasets such as The Cancer Genome Atlas present an opportunity to perform correlative studies of tissue morphology and genomics to explore the morphological phenotypes associated with gene expression and genetic alterations. In this paper we present an investigation of Cancer Genome Atlas data that correlates morphology with recently discovered molecular subtypes of glioblastoma. Using image analysis to segment and extract features from millions of cells, we calculate high-dimensional morphological signatures to describe trends of nuclear morphology and cytoplasmic staining in whole-slide images. We illustrate the similarities between the analysis of these signatures and predictive studies of gene expression, both in terms of limited sample size and high-dimensionality. Our top-down analysis demonstrates the power of morphological signatures to predict clinically-relevant molecular tumor subtypes, with 85.4% recognition of the proneural subtype. A complementary bottom-up analysis shows that self-aggregating clusters have statistically significant associations with tumor subtype and reveals the existence of remarkable structure in the morphological signature space of glioblastomas. PMID:22183148

  9. Nonverbal Style of Emotional Expression: Prediction of Parenting Behavior.

    ERIC Educational Resources Information Center

    Diskin, Susan D.

    This research reports the development of a semantic differential for rating nonverbal style of expressiveness in a population of expectant mothers. Mothers' nonverbal features (facial expression, gestures, voice quality) were emphasized as uniquely valid indices of emotional attitudes towards parenthood and as the principal forms of interpersonal…

  10. Translation of disease associated gene signatures across tissues.

    PubMed

    Kasim, Adetayo; Shkedy, Ziv; Lin, Dan; Van Sanden, Suzy; Abrahantes, Josè Cortiñas; Göhlmann, Hinrich W H; Bijnens, Luc; Yekutieli, Dani; Camilleri, Michael; Aerssens, Jeroen; Talloen, Willem

    2015-01-01

    It has recently been shown that disease associated gene signatures can be identified by profiling tissue other than the disease related tissue. In this paper, we investigate gene signatures for Irritable Bowel Syndrome (IBS) using gene expression profiling of both disease related tissue (colon) and surrogate tissue (rectum). Gene specific joint ANOVA models were used to investigate differentially expressed genes between the IBS patients and the healthy controls taken into account both intra and inter tissue dependencies among expression levels of the same gene. Classification algorithms in combination with feature selection methods were used to investigate the predictive power of gene expression levels from the surrogate and the target tissues. We conclude based on the analyses that expression profiles of the colon and the rectum tissue could result in better predictive accuracy if the disease associated genes are known. PMID:26333264

  11. PBK/TOPK Expression Predicts Prognosis in Oral Cancer

    PubMed Central

    Chang, Chin-Fang; Chen, Sung-Lang; Sung, Wen-Wei; Hsieh, Ming-Ju; Hsu, Hui-Ting; Chen, Li-Hsin; Chen, Mu-Kuan; Ko, Jiunn-Liang; Chen, Chih-Jung; Chou, Ming-Chih

    2016-01-01

    Oral cancer is a common cancer with poor prognosis. We evaluated the expression of PBK/TOPK (PDZ-binding kinase/T-LAK cell-originated protein kinase) and its prognostic significance in oral cancer. PBK/TOPK expression was measured by immunohistochemical staining of samples from 287 patients with oral cancer. The association between PBK/TOPK expression and clinicopathological features was analyzed. The prognostic value of PBK/TOPK for overall survival was determined by Kaplan-Meier analysis and Cox proportional hazard models. A high PBK/TOPK expression level was correlated with long overall survival. The prognostic role of PBK/TOPK expression was significant in young patients (p < 0.05), patients with smoking habits (p < 0.05), and late stage disease (p < 0.05). Our results suggest that PBK/TOPK expression is enhanced in oral cancer. High PBK/TOPK expression, either alone or in subgroups according to clinicopathological features, may serve as a favorable prognostic marker for patients with oral cancer. PMID:27347940

  12. PBK/TOPK Expression Predicts Prognosis in Oral Cancer.

    PubMed

    Chang, Chin-Fang; Chen, Sung-Lang; Sung, Wen-Wei; Hsieh, Ming-Ju; Hsu, Hui-Ting; Chen, Li-Hsin; Chen, Mu-Kuan; Ko, Jiunn-Liang; Chen, Chih-Jung; Chou, Ming-Chih

    2016-01-01

    Oral cancer is a common cancer with poor prognosis. We evaluated the expression of PBK/TOPK (PDZ-binding kinase/T-LAK cell-originated protein kinase) and its prognostic significance in oral cancer. PBK/TOPK expression was measured by immunohistochemical staining of samples from 287 patients with oral cancer. The association between PBK/TOPK expression and clinicopathological features was analyzed. The prognostic value of PBK/TOPK for overall survival was determined by Kaplan-Meier analysis and Cox proportional hazard models. A high PBK/TOPK expression level was correlated with long overall survival. The prognostic role of PBK/TOPK expression was significant in young patients (p < 0.05), patients with smoking habits (p < 0.05), and late stage disease (p < 0.05). Our results suggest that PBK/TOPK expression is enhanced in oral cancer. High PBK/TOPK expression, either alone or in subgroups according to clinicopathological features, may serve as a favorable prognostic marker for patients with oral cancer. PMID:27347940

  13. Signature control

    NASA Astrophysics Data System (ADS)

    Pyati, Vittal P.

    The reduction of vehicle radar signature is accomplished by means of vehicle shaping, the use of microwave frequencies-absorbent materials, and either passive or active cancellation techniques; such techniques are also useful in the reduction of propulsion system-associated IR emissions. In some anticipated scenarios, the objective is not signature-reduction but signature control, for deception, via decoy vehicles that mimic the signature characteristics of actual weapons systems. As the stealthiness of airframes and missiles increases, their propulsion systems' exhaust plumes assume a more important role in detection by an adversary.

  14. Blood-based gene expression signatures of medication-free outpatients with major depressive disorder: integrative genome-wide and candidate gene analyses

    PubMed Central

    Hori, Hiroaki; Sasayama, Daimei; Teraishi, Toshiya; Yamamoto, Noriko; Nakamura, Seiji; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

    2016-01-01

    Several microarray-based studies have investigated gene expression profiles in major depressive disorder (MDD), yet with highly variable findings. We examined blood-based genome-wide expression signatures of MDD, focusing on molecular pathways and networks underlying differentially expressed genes (DEGs) and behaviours of hypothesis-driven, evidence-based candidate genes for depression. Agilent human whole-genome arrays were used to measure gene expression in 14 medication-free outpatients with MDD who were at least moderately ill and 14 healthy controls matched pairwise for age and sex. After filtering, we compared expression of entire probes between patients and controls and identified DEGs. The DEGs were evaluated by pathway and network analyses. For the candidate gene analysis, we utilized 169 previously prioritized genes and examined their case-control separation efficiency and correlational co-expression network in patients relative to controls. The 317 screened DEGs mapped to a significantly over-represented pathway, the “synaptic transmission” pathway. The protein-protein interaction network was also significantly enriched, in which a number of key molecules for depression were included. The co-expression network of candidate genes was markedly disrupted in patients. This study provided evidence for an altered molecular network along with several key molecules in MDD and confirmed that the candidate genes are worthwhile targets for depression research. PMID:26728011

  15. Expression analysis of mitotic spindle checkpoint genes in breast carcinoma: role of NDC80/HEC1 in early breast tumorigenicity, and a two-gene signature for aneuploidy

    PubMed Central

    2011-01-01

    Background Aneuploidy and chromosomal instability (CIN) are common abnormalities in human cancer. Alterations of the mitotic spindle checkpoint are likely to contribute to these phenotypes, but little is known about somatic alterations of mitotic spindle checkpoint genes in breast cancer. Methods To obtain further insight into the molecular mechanisms underlying aneuploidy in breast cancer, we used real-time quantitative RT-PCR to quantify the mRNA expression of 76 selected mitotic spindle checkpoint genes in a large panel of breast tumor samples. Results The expression of 49 (64.5%) of the 76 genes was significantly dysregulated in breast tumors compared to normal breast tissues: 40 genes were upregulated and 9 were downregulated. Most of these changes in gene expression during malignant transformation were observed in epithelial cells. Alterations of nine of these genes, and particularly NDC80, were also detected in benign breast tumors, indicating that they may be involved in pre-neoplastic processes. We also identified a two-gene expression signature (PLK1 + AURKA) which discriminated between DNA aneuploid and DNA diploid breast tumor samples. Interestingly, some DNA tetraploid tumor samples failed to cluster with DNA aneuploid breast tumors. Conclusion This study confirms the importance of previously characterized genes and identifies novel candidate genes that could be activated for aneuploidy to occur. Further functional analyses are required to clearly confirm the role of these new identified genes in the molecular mechanisms involved in breast cancer aneuploidy. The novel genes identified here, and/or the two-gene expression signature, might serve as diagnostic or prognostic markers and form the basis for novel therapeutic strategies. PMID:21352579

  16. Genetic signatures of heroin addiction

    PubMed Central

    Chen, Shaw-Ji; Liao, Ding-Lieh; Shen, Tsu-Wang; Yang, Hsin-Chou; Chen, Kuang-Chi; Chen, Chia-Hsiang

    2016-01-01

    Abstract Heroin addiction is a complex psychiatric disorder with a chronic course and a high relapse rate, which results from the interaction between genetic and environmental factors. Heroin addiction has a substantial heritability in its etiology; hence, identification of individuals with a high genetic propensity to heroin addiction may help prevent the occurrence and relapse of heroin addiction and its complications. The study aimed to identify a small set of genetic signatures that may reliably predict the individuals with a high genetic propensity to heroin addiction. We first measured the transcript level of 13 genes (RASA1, PRKCB, PDK1, JUN, CEBPG, CD74, CEBPB, AUTS2, ENO2, IMPDH2, HAT1, MBD1, and RGS3) in lymphoblastoid cell lines in a sample of 124 male heroin addicts and 124 male control subjects using real-time quantitative PCR. Seven genes (PRKCB, PDK1, JUN, CEBPG, CEBPB, ENO2, and HAT1) showed significant differential expression between the 2 groups. Further analysis using 3 statistical methods including logistic regression analysis, support vector machine learning analysis, and a computer software BIASLESS revealed that a set of 4 genes (JUN, CEBPB, PRKCB, ENO2, or CEBPG) could predict the diagnosis of heroin addiction with the accuracy rate around 85% in our dataset. Our findings support the idea that it is possible to identify genetic signatures of heroin addiction using a small set of expressed genes. However, the study can only be considered as a proof-of-concept study. As the establishment of lymphoblastoid cell line is a laborious and lengthy process, it would be more practical in clinical settings to identify genetic signatures for heroin addiction directly from peripheral blood cells in the future study. PMID:27495086

  17. Genetic signatures of heroin addiction.

    PubMed

    Chen, Shaw-Ji; Liao, Ding-Lieh; Shen, Tsu-Wang; Yang, Hsin-Chou; Chen, Kuang-Chi; Chen, Chia-Hsiang

    2016-08-01

    Heroin addiction is a complex psychiatric disorder with a chronic course and a high relapse rate, which results from the interaction between genetic and environmental factors. Heroin addiction has a substantial heritability in its etiology; hence, identification of individuals with a high genetic propensity to heroin addiction may help prevent the occurrence and relapse of heroin addiction and its complications. The study aimed to identify a small set of genetic signatures that may reliably predict the individuals with a high genetic propensity to heroin addiction. We first measured the transcript level of 13 genes (RASA1, PRKCB, PDK1, JUN, CEBPG, CD74, CEBPB, AUTS2, ENO2, IMPDH2, HAT1, MBD1, and RGS3) in lymphoblastoid cell lines in a sample of 124 male heroin addicts and 124 male control subjects using real-time quantitative PCR. Seven genes (PRKCB, PDK1, JUN, CEBPG, CEBPB, ENO2, and HAT1) showed significant differential expression between the 2 groups. Further analysis using 3 statistical methods including logistic regression analysis, support vector machine learning analysis, and a computer software BIASLESS revealed that a set of 4 genes (JUN, CEBPB, PRKCB, ENO2, or CEBPG) could predict the diagnosis of heroin addiction with the accuracy rate around 85% in our dataset. Our findings support the idea that it is possible to identify genetic signatures of heroin addiction using a small set of expressed genes. However, the study can only be considered as a proof-of-concept study. As the establishment of lymphoblastoid cell line is a laborious and lengthy process, it would be more practical in clinical settings to identify genetic signatures for heroin addiction directly from peripheral blood cells in the future study. PMID:27495086

  18. HST/STIS Lyman-α observations of the quiet M dwarf GJ 436. Predictions for the exospheric transit signature of the hot Neptune GJ 436b

    NASA Astrophysics Data System (ADS)

    Ehrenreich, D.; Lecavelier Des Etangs, A.; Delfosse, X.

    2011-05-01

    Lyman-α (Lyα) emission of neutral hydrogen (λ1215.67 Å) is the main contributor to the ultraviolet flux of low-mass stars such as M dwarfs. It is also the main light source used in studies of the evaporating upper atmospheres of transiting extrasolar planets with ultraviolet transmission spectroscopy. However, there are very few observations of the Lyα emissions of quiet M dwarfs, and none exist for those hosting exoplanets. Here, we present Lyα observations of the hot-Neptune host star GJ 436 with the Hubble Space Telescope Imaging Spectrograph (HST/STIS). We detect bright emission in the first resolved and high quality spectrum of a quiet M dwarf at Lyα. Using an energy diagram for exoplanets and an N-body particle simulation, this detection enables the possible exospheric signature of the hot Neptune to be estimated as a ~11% absorption in the Lyα stellar emission, for a typical mass-loss rate of 1010 g s-1. The atmosphere of the planet GJ 436b is found to be stable to evaporation, and should be readily observable with HST. We also derive a correlation between X-ray and Lyα emissions for M dwarfs. This correlation will be useful for predicting the evaporation signatures of planets transiting other quiet M dwarfs. Based on observations made with the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope (Cycle 17 program GO/DD 11817).

  19. 13CH3D kinetic isotope effects for methane oxidation by OH - predicting the "clumped" isotopic signature of atmospheric methane

    NASA Astrophysics Data System (ADS)

    Whitehill, A. R.; Joelsson, L. M. T.; Wang, D. T.; Johnson, M. S.; Ono, S.

    2015-12-01

    Methane is a significant long-lived greenhouse gas, but the tropospheric methane budget is not entirely constrained. "Clumped" isotopologues of methane, including 13CH3D, can provide additional constraints on the atmospheric methane cycle. Interpretation of these novel isotope tracers requires an understanding of the "clumped" isotopic signature of various methane sources, as well as the kinetic isotope effects of the methane sink reactions. We performed a series of photochemical experiments to measure the isotopic fractionation during the CH4+OH reaction. Experiments were carried out in a 100 L quartz photochemical reactor. Photolysis of ozone (O3) in the presence of water (H2O) was used to produce OH radicals. Experiments were performed in a helium bath gas. Fourier transform infrared spectroscopy (FTIR) was used to monitor reaction progress. At various intervals during the reaction, methane was sampled from the cell and analyzed for isotope ratios by tunable infrared laser direct absorption spectroscopy (TILDAS). By simultaneously measuring four different isotopologues of methane (12CH4,12CH3D, 13CH4, 13CH3D), we were able to constrain the kinetic isotope effects for 12CH3D, 13CH4, and the doubly-substitued isotopologue 13CH3D. These results are combined with published clumped isotope data from different methane sources to model the Δ13CH3D (i.e. deviation from "stochastic" distribution of isotopes) of tropospheric methane and its sensitivity to different sources. The Δ13CH3D value of tropospheric methane does not strongly depend upon isotope fractionation during the OH sink reaction. Rather, the Δ13CH3D value of tropospheric methane reflects a mixing of different source signatures. Due to nonlinearity in mixing of Δ13CH3D, the Δ13CH3D value of tropospheric methane will be larger than the weighted average of the Δ13CH3D value of the sources. A first order interpretation of variations in the Δ13CH3D value of tropospheric methane is that it reflects changes

  20. Relationship between Anger Expression and Stress in Predicting Depression.

    ERIC Educational Resources Information Center

    Clay, Daniel L.; And Others

    1993-01-01

    Examines the relationship between anger expression and stressful life events as predictors of depression among college students. Hierarchical multiple regression analyses indicated that anger directed inward and stressful life events were significant predictors of depression. Because these factors are independent and additive predictors,…

  1. Alexithymia, not autism, predicts poor recognition of emotional facial expressions.

    PubMed

    Cook, Richard; Brewer, Rebecca; Shah, Punit; Bird, Geoffrey

    2013-05-01

    Despite considerable research into whether face perception is impaired in autistic individuals, clear answers have proved elusive. In the present study, we sought to determine whether co-occurring alexithymia (characterized by difficulties interpreting emotional states) may be responsible for face-perception deficits previously attributed to autism. Two experiments were conducted using psychophysical procedures to determine the relative contributions of alexithymia and autism to identity and expression recognition. Experiment 1 showed that alexithymia correlates strongly with the precision of expression attributions, whereas autism severity was unrelated to expression-recognition ability. Experiment 2 confirmed that alexithymia is not associated with impaired ability to detect expression variation; instead, results suggested that alexithymia is associated with difficulties interpreting intact sensory descriptions. Neither alexithymia nor autism was associated with biased or imprecise identity attributions. These findings accord with the hypothesis that the emotional symptoms of autism are in fact due to co-occurring alexithymia and that existing diagnostic criteria may need to be revised. PMID:23528789

  2. Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer

    PubMed Central

    Pearlman, Alexander; Campbell, Christopher; Brooks, Eric; Genshaft, Alex; Shajahan, Shahin; Ittman, Michael; Bova, G. Steven; Melamed, Jonathan; Holcomb, Ilona; Schneider, Robert J.; Ostrer, Harry

    2014-01-01

    The transition of cancer from a localized tumor to a distant metastasis is not well understood for prostate and many other cancers, partly, because of the scarcity of tumor samples, especially metastases, from cancer patients with long-term clinical follow-up. To overcome this limitation, we developed a semi-supervised clustering method using the tumor genomic DNA copy number alterations to classify each patient into inferred clinical outcome groups of metastatic potential. Our data set was comprised of 294 primary tumors and 49 metastases from 5 independent cohorts of prostate cancer patients. The alterations were modeled based on Darwin's evolutionary selection theory and the genes overlapping these altered genomic regions were used to develop a metastatic potential score for a prostate cancer primary tumor. The function of the proteins encoded by some of the predictor genes promote escape from anoikis, a pathway of apoptosis, deregulated in metastases. We evaluated the metastatic potential score with other clinical predictors available at diagnosis using a Cox proportional hazards model and show our proposed score was the only significant predictor of metastasis free survival. The metastasis gene signature and associated score could be applied directly to copy number alteration profiles from patient biopsies positive for prostate cancer. PMID:25419216

  3. Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer.

    PubMed

    Pearlman, Alexander; Campbell, Christopher; Brooks, Eric; Genshaft, Alex; Shajahan, Shahin; Ittman, Michael; Bova, G Steven; Melamed, Jonathan; Holcomb, Ilona; Schneider, Robert J; Ostrer, Harry

    2012-01-01

    The transition of cancer from a localized tumor to a distant metastasis is not well understood for prostate and many other cancers, partly, because of the scarcity of tumor samples, especially metastases, from cancer patients with long-term clinical follow-up. To overcome this limitation, we developed a semi-supervised clustering method using the tumor genomic DNA copy number alterations to classify each patient into inferred clinical outcome groups of metastatic potential. Our data set was comprised of 294 primary tumors and 49 metastases from 5 independent cohorts of prostate cancer patients. The alterations were modeled based on Darwin's evolutionary selection theory and the genes overlapping these altered genomic regions were used to develop a metastatic potential score for a prostate cancer primary tumor. The function of the proteins encoded by some of the predictor genes promote escape from anoikis, a pathway of apoptosis, deregulated in metastases. We evaluated the metastatic potential score with other clinical predictors available at diagnosis using a Cox proportional hazards model and show our proposed score was the only significant predictor of metastasis free survival. The metastasis gene signature and associated score could be applied directly to copy number alteration profiles from patient biopsies positive for prostate cancer. PMID:25419216

  4. CD24 Expression May Play a Role as a Predictive Indicator and a Modulator of Cisplatin Treatment Response in Head and Neck Squamous Cellular Carcinoma

    PubMed Central

    Modur, Vishnu; Joshi, Pooja; Nie, Daotai; Robbins, K. Thomas; Khan, Aziz U.; Rao, Krishna

    2016-01-01

    Platinum-based therapy is most often used to treat advanced cases of head and neck cancers, but only a small fraction of the patient population responds to cisplatin, with a median survival time of less than a year. Although gene signatures and molecular etiology of head and neck cancers have been previously described, none of them are predictive indicators of cisplatin treatment response in particular. Therefore, currently, there is a lack of clinically employable predictive indicators of the disease beyond HPV status to specifically predict patients' response to platinum-based therapy. It beckons a substantial effort to look for predictive indicators of cisplatin treatment response. In this regard, CD24 expression level appears to be a significant molecular phenotype of cisplatin-resistant residual cells in laryngeal carcinoma lines. CD24 expression level directly affects cisplatin sensitivity and affects the expression of critical apoptotic, stem and drug resistance genes. A relatively small retrospective patient tumor analysis suggests that CD24 high tumors go on to show an unfavorable response to cisplatin treatment. Overall, based on the strength of further analysis, CD24 presents a strong rationale to be utilized as a predictive indicator to stratify head and neck cancer patients for platinum-based therapy. It also provides a rationale for using CD24 as a therapeutic adjuvant target along with standard cisplatin therapy. PMID:27276062

  5. Brief-exposure to preoperative bevacizumab reveals a TGF-β signature predictive of response in HER2-negative breast cancers.

    PubMed

    Varadan, Vinay; Kamalakaran, Sitharthan; Gilmore, Hannah; Banerjee, Nilanjana; Janevski, Angel; Miskimen, Kristy L S; Williams, Nicole; Basavanhalli, Ajay; Madabhushi, Anant; Lezon-Geyda, Kimberly; Bossuyt, Veerle; Lannin, Donald R; Abu-Khalaf, Maysa; Sikov, William; Dimitrova, Nevenka; Harris, Lyndsay N

    2016-02-01

    To best define biomarkers of response, and to shed insight on mechanism of action of certain clinically important agents for early breast cancer, we used a brief-exposure paradigm in the preoperative setting to study transcriptional changes in patient tumors that occur with one dose of therapy prior to combination chemotherapy. Tumor biopsies from breast cancer patients enrolled in two preoperative clinical trials were obtained at baseline and after one dose of bevacizumab (HER2-negative), trastuzumab (HER2-positive) or nab-paclitaxel, followed by treatment with combination chemo-biologic therapy. RNA-Sequencing based PAM50 subtyping at baseline of 46 HER2-negative patients revealed a strong association between the basal-like subtype and pathologic complete response (pCR) to chemotherapy plus bevacizumab (p ≤ 0.0027), but did not provide sufficient specificity to predict response. However, a single dose of bevacizumab resulted in down-regulation of a well-characterized TGF-β activity signature in every single breast tumor that achieved pCR (p ≤ 0.004). The TGF-β signature was confirmed to be a tumor-specific read-out of the canonical TGF-β pathway using pSMAD2 (p ≤ 0.04), with predictive power unique to brief-exposure to bevacizumab (p ≤ 0.016), but not trastuzumab or nab-paclitaxel. Down-regulation of TGF-β activity was associated with reduction in tumor hypoxia by transcription and protein levels, suggesting therapy-induced disruption of an autocrine-loop between tumor stroma and malignant cells. Modulation of the TGF-β pathway upon brief-exposure to bevacizumab may provide an early functional readout of pCR to preoperative anti-angiogenic therapy in HER2-negative breast cancer, thus providing additional avenues for exploration in both preclinical and clinical settings with these agents. PMID:26284485

  6. Prospective Validation Obtained in a Similar Group of Patients and with Similar High Throughput Biological Tests Failed to Confirm Signatures for Prediction of Response to Chemotherapy and Survival in Advanced NSCLC: A Prospective Study from the European Lung Cancer Working Party

    PubMed Central

    Berghmans, Thierry; Ameye, Lieveke; Lafitte, Jean-Jacques; Colinet, Benoît; Cortot, Alexis; CsToth, Ingrid; Holbrechts, Stéphane; Lecomte, Jacques; Mascaux, Céline; Meert, Anne-Pascale; Paesmans, Marianne; Richez, Michel; Scherpereel, Arnaud; Tulippe, Christian; Willems, Luc; Dernies, Tiffany; Leclercq, Nathalie; Sculier, Jean-Paul

    2014-01-01

    Aim: Cisplatin doublets are standard 1st line treatment for advanced non-small cell lung cancer (NSCLC), without accurate predictor for response and survival, but important toxicity. Our aims were to identify predictive (for response) and prognostic (for survival) biological signatures in patients with NSCLC using messenger RNAs (mRNA) and miRNA expression. Methods: Patients with pathologically proven untreated NSCLC, receiving 1st line cisplatin–vinorelbine and with an assessable lesion were eligible. A bronchial biopsy was lysed into Tripure Isolation Reagent on ice, snap frozen, and stored at −80°C. mRNA expression was analyzed using microarrays Agilent Technologies. miRNA expression was assessed using TaqMan Low Density Arrays (756 human miR panel, Applied Biosystems). Validation was performed by RT-PCR on the selected genes. Survival was measured from the registration date and response assessed by WHO criteria. Results: Biopsies for transcriptomic analyses were obtained from 60 consecutive patients. No statistically significant differences were observed according to the main clinical characteristics, response rate (43 vs. 41%) or survival (median 25 vs. 29 months) between derivation and validation sets. In the derivation set (n = 38 patients), two mRNA and one miRNA predictive signatures for response were obtained. One mRNA and one miRNA prognostic signatures were derived from the first set, allowing an adequate distinction of patients with good and poor overall and progression-free survivals. None of these signatures could be validated in the validation set (n = 22 patients). Conclusion: In this prospective study with advanced NSCLC treated with cisplatin–vinorelbine, we were able to derive with high throughput techniques predictive and prognostic signatures based on transcriptomic analyses. However, these results could not be reproduced in an independent validation set. The role of miRNA and mRNA as predictive or prognostic factors remains a

  7. Decreased Pattern Recognition Receptor Signaling, Interferon-Signature, and Bactericidal/Permeability-Increasing Protein Gene Expression in Cord Blood of Term Low Birth Weight Human Newborns

    PubMed Central

    Singh, Vikas Vikram; Chauhan, Sudhir Kumar; Rai, Richa; Kumar, Ashok; Singh, Shiva M.; Rai, Geeta

    2013-01-01

    Background Morbidity and mortality rates of low birth weight (LBW) newborns at term are higher than rates in normal birth weight (NBW) newborns. LBW newborns are at greater risk to acquire recurrent bacterial and viral infections during their first few weeks of life possibly as an outcome of compromised innate immune functions. As adaptive immunity is in a naive state, increased risk of infection of LBW as compared to NBW newborns may reflect impairments in innate immunity. Methodology To characterize the increased susceptibility to infections in LBW newborns we used microarray technology to identify differences in gene expression in LBW newborns (n = 8) compared to NBW newborns (n = 4) using cord blood. The results obtained from the microarray study were validated on a larger number of samples using real time RT-PCR (LBW = 22, NBW = 18) and western blotting (LBW = 12, NBW = 12). The Interferome database was used to identify interferon (IFN) signature genes and ingenuity pathway analysis identified canonical pathways and biological functions associated with the differentially expressed genes in LBW newborns. ELISAs for IFNs and bactericidal/permeability-increasing protein were performed in both LBW and NBW newborns and in adults (LBW = 18, NBW = 18, Adults  = 8). Principal Findings Upon microarray analysis, we identified 1,391 differentially expressed genes, of which, 1,065 genes were down-regulated and 326 genes were up-regulated in the LBW compared to NBW newborns. Of note, 70 IFN-signature genes were found to be significantly down-regulated in LBW compared to NBW newborns. Ingenuity pathway analysis revealed pattern recognition receptors signaling including Toll-Like Receptors (TLRs) -1, -5, and -8 genes and IFN signaling as the most significantly impacted pathways. Respiratory infectious diseases were the most significantly affected bio-functions in LBW newborns. Conclusion and Significance Diminished PRRs, IFN-signature, and

  8. Distinct microRNA expression signatures are associated with melanoma subtypes and are regulated by HIF1A

    PubMed Central

    Hwang, Hun-Way; Baxter, Laura L.; Loftus, Stacie K.; Cronin, Julia C.; Trivedi, Niraj S.; Borate, Bhavesh; Pavan, William J.

    2014-01-01

    Summary The complex genetic changes underlying metastatic melanoma need to be deciphered to develop new and effective therapeutics. Previously, genome-wide microarray analyses of human melanoma identified two reciprocal gene expression programs, including transcripts regulated by either transforming growth factor, beta 1 (TGFβ1) pathways or microphthalmia-associated transcription factor (MITF)/SRY-box containing gene 10 (SOX10) pathways. We extended this knowledge by discovering that melanoma cell lines with these two expression programs exhibit distinctive microRNA (miRNA) expression patterns. We also demonstrated that hypoxia-inducible factor 1 alpha (HIF1A) is increased in TGFβ1 pathway-expressing melanoma cells and that HIF1A upregulates miR-210, miR-218, miR-224, and miR-452. Reduced expression of these four miRNAs in TGFβ1 pathway-expressing melanoma cells arrests the cell cycle, while their overexpression in mouse melanoma cells increases the expression of the hypoxic response gene Bnip3. Taken together, these data suggest that HIF1A may regulate some of the gene expression and biological behavior of TGFβ1 pathway-expressing melanoma cells, in part via alterations in these four miRNAs. PMID:24767210

  9. MicroRNA Expression Profiling of Peripheral Blood Samples Predicts Resistance to First-line Sunitinib in Advanced Renal Cell Carcinoma Patients12

    PubMed Central

    Gámez-Pozo, Angelo; Antón-Aparicio, Luis M; Bayona, Cristina; Borrega, Pablo; Gallegos Sancho, María I; García-Domínguez, Rocío; de Portugal, Teresa; Ramos-Vázquez, Manuel; Pérez-Carrión, Ramón; Bolós, María V; Madero, Rosario; Sánchez-Navarro, Iker; Fresno Vara, Juan A; Arranz, Enrique Espinosa

    2012-01-01

    Anti-angiogenic therapy benefits many patients with advanced renal cell carcinoma (RCC), but there is still a need for predictive markers that help in selecting the best therapy for individual patients. MicroRNAs (miRNAs) regulate cancer cell behavior and may be attractive biomarkers for prognosis and prediction of response. Forty-four patients with RCC were recruited into this observational prospective study conducted in nine Spanish institutions. Peripheral blood samples were taken before initiation of therapy and 14 days later in patients receiving first-line therapy with sunitinib for advanced RCC. miRNA expression in peripheral blood was assessed using microarrays and L2 boosting was applied to filtered miRNA expression data. Several models predicting poor and prolonged response to sunitinib were constructed and evaluated by binary logistic regression. Blood samples from 38 patients and 287 miRNAs were evaluated. Twenty-eight miRNAs of the 287 were related to poor response and 23 of the 287 were related to prolonged response to sunitinib treatment. Predictive models identified populations with differences in the established end points. In the poor response group, median time to progression was 3.5 months and the overall survival was 8.5, whereas in the prolonged response group these values were 24 and 29.5 months, respectively. Ontology analyses pointed out to cancer-related pathways, such angiogenesis and apoptosis. miRNA expression signatures, measured in peripheral blood, may stratify patients with advanced RCC according to their response to first-line therapy with sunitinib, improving diagnostic accuracy. After proper validation, these signatures could be used to tailor therapy in this setting. PMID:23308047

  10. MicroRNA expression signature of oral squamous cell carcinoma: functional role of microRNA-26a/b in the modulation of novel cancer pathways

    PubMed Central

    Fukumoto, I; Hanazawa, T; Kinoshita, T; Kikkawa, N; Koshizuka, K; Goto, Y; Nishikawa, R; Chiyomaru, T; Enokida, H; Nakagawa, M; Okamoto, Y; Seki, N

    2015-01-01

    Background: MicroRNAs (miRNAs) have been shown to play major roles in carcinogenesis in a variety of cancers. The aim of this study was to determine the miRNA expression signature of oral squamous cell carcinoma (OSCC) and to investigate the functional roles of miR-26a and miR-26b in OSCC cells. Methods: An OSCC miRNA signature was constructed by PCR-based array methods. Functional studies of differentially expressed miRNAs were performed to investigate cell proliferation, migration, and invasion in OSCC cells. In silico database and genome-wide gene expression analyses were performed to identify molecular targets and pathways mediated by miR-26a/b. Results: miR-26a and miR-26b were significantly downregulated in OSCC. Restoration of both miR-26a and miR-26b in cancer cell lines revealed that these miRNAs significantly inhibited cancer cell migration and invasion. Our data demonstrated that the novel transmembrane TMEM184B gene was a direct target of miR-26a/b regulation. Silencing of TMEM184B inhibited cancer cell migration and invasion, and regulated the actin cytoskeleton-pathway related genes. Conclusions: Loss of tumour-suppressive miR-26a/b enhanced cancer cell migration and invasion in OSCC through direct regulation of TMEM184B. Our data describing pathways regulated by tumour-suppressive miR-26a/b provide new insights into the potential mechanisms of OSCC oncogenesis and metastasis. PMID:25668004

  11. High Content Imaging of Early Morphological Signatures Predicts Long Term Mineralization Capacity of Human Mesenchymal Stem Cells upon Osteogenic Induction.

    PubMed

    Marklein, Ross A; Lo Surdo, Jessica L; Bellayr, Ian H; Godil, Saniya A; Puri, Raj K; Bauer, Steven R

    2016-04-01

    Human bone marrow-derived multipotent mesenchymal stromal cells, often referred to as mesenchymal stem cells (MSCs), represent an attractive cell source for many regenerative medicine applications due to their potential for multi-lineage differentiation, immunomodulation, and paracrine factor secretion. A major complication for current MSC-based therapies is the lack of well-defined characterization methods that can robustly predict how they will perform in a particular in vitro or in vivo setting. Significant advances have been made with identifying molecular markers of MSC quality and potency using multivariate genomic and proteomic approaches, and more recently with advanced techniques incorporating high content imaging to assess high-dimensional single cell morphological data. We sought to expand upon current methods of high dimensional morphological analysis by investigating whether short term cell and nuclear morphological profiles of MSCs from multiple donors (at multiple passages) correlated with long term mineralization upon osteogenic induction. Using the combined power of automated high content imaging followed by automated image analysis, we demonstrated that MSC morphology after 3 days was highly correlated with 35 day mineralization and comparable to other methods of MSC osteogenesis assessment (such as alkaline phosphatase activity). We then expanded on this initial morphological characterization and identified morphological features that were highly predictive of mineralization capacities (>90% accuracy) of MSCs from additional donors and different manufacturing techniques using linear discriminant analysis. Together, this work thoroughly demonstrates the predictive power of MSC morphology for mineralization capacity and motivates further studies into MSC morphology as a predictive marker for additional in vitro and in vivo responses. Stem Cells 2016;34:935-947. PMID:26865267

  12. Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures

    PubMed Central

    Eipel, Monika; Mayer, Felix; Arent, Tanja; Ferreira, Marcelo R. P.; Birkhofer, Carina; Gerstenmaier, Uwe; Costa, Ivan G.; Ritz-Timme, Stefanie; Wagner, Wolfgang

    2016-01-01

    Aging is reflected by highly reproducible DNA methylation (DNAm) changes that open new perspectives for estimation of chronological age in legal medicine. DNA can be harvested non-invasively from cells at the inside of a person's cheek using buccal swabs – but these specimens resemble heterogeneous mixtures of buccal epithelial cells and leukocytes with different epigenetic makeup. In this study, we have trained an age predictor based on three age-associated CpG sites (associated with the genes PDE4C, ASPA, and ITGA2B) for swab samples to reach a mean absolute deviation (MAD) between predicted and chronological age of 4.3 years in a training set and of 7.03 years in a validation set. Subsequently, the composition of buccal epithelial cells versus leukocytes was estimated by two additional CpGs (associated with the genes CD6 and SERPINB5). Results of this “Buccal-Cell-Signature” correlated with cell counts in cytological stains (R2 = 0.94). Combination of cell type-specific and age-associated CpGs into one multivariate model enabled age predictions with MADs of 5.09 years and 5.12 years in two independent validation sets. Our results demonstrate that the cellular composition in buccal swab samples can be determined by DNAm at two cell type-specific CpGs to improve epigenetic age predictions. PMID:27249102

  13. WeGET: predicting new genes for molecular systems by weighted co-expression.

    PubMed

    Szklarczyk, Radek; Megchelenbrink, Wout; Cizek, Pavel; Ledent, Marie; Velemans, Gonny; Szklarczyk, Damian; Huynen, Martijn A

    2016-01-01

    We have developed the Weighted Gene Expression Tool and database (WeGET, http://weget.cmbi.umcn.nl) for the prediction of new genes of a molecular system by correlated gene expression. WeGET utilizes a compendium of 465 human and 560 murine gene expression datasets that have been collected from multiple tissues under a wide range of experimental conditions. It exploits this abundance of expression data by assigning a high weight to datasets in which the known genes of a molecular system are harmoniously up- and down-regulated. WeGET ranks new candidate genes by calculating their weighted co-expression with that system. A weighted rank is calculated for human genes and their mouse orthologs. Then, an integrated gene rank and p-value is computed using a rank-order statistic. We applied our method to predict novel genes that have a high degree of co-expression with Gene Ontology terms and pathways from KEGG and Reactome. For each query set we provide a list of predicted novel genes, computed weights for transcription datasets used and cell and tissue types that contributed to the final predictions. The performance for each query set is assessed by 10-fold cross-validation. Finally, users can use the WeGET to predict novel genes that co-express with a custom query set. PMID:26582928

  14. WeGET: predicting new genes for molecular systems by weighted co-expression

    PubMed Central

    Szklarczyk, Radek; Megchelenbrink, Wout; Cizek, Pavel; Ledent, Marie; Velemans, Gonny; Szklarczyk, Damian; Huynen, Martijn A.

    2016-01-01

    We have developed the Weighted Gene Expression Tool and database (WeGET, http://weget.cmbi.umcn.nl) for the prediction of new genes of a molecular system by correlated gene expression. WeGET utilizes a compendium of 465 human and 560 murine gene expression datasets that have been collected from multiple tissues under a wide range of experimental conditions. It exploits this abundance of expression data by assigning a high weight to datasets in which the known genes of a molecular system are harmoniously up- and down-regulated. WeGET ranks new candidate genes by calculating their weighted co-expression with that system. A weighted rank is calculated for human genes and their mouse orthologs. Then, an integrated gene rank and p-value is computed using a rank-order statistic. We applied our method to predict novel genes that have a high degree of co-expression with Gene Ontology terms and pathways from KEGG and Reactome. For each query set we provide a list of predicted novel genes, computed weights for transcription datasets used and cell and tissue types that contributed to the final predictions. The performance for each query set is assessed by 10-fold cross-validation. Finally, users can use the WeGET to predict novel genes that co-express with a custom query set. PMID:26582928

  15. Evaluation of prediction intervals for expressing uncertainties in groundwater flow model predictions

    USGS Publications Warehouse

    Christensen, S.; Cooley, R.L.

    1999-01-01

    We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.

  16. Prognostic value of blood mRNA expression signatures in castration-resistant prostate cancer: a prospective, two-stage study

    PubMed Central

    Olmos, David; Brewer, Daniel; Clark, Jeremy; Danila, Daniel C; Parker, Chris; Attard, Gerhardt; Fleisher, Martin; Reid, Alison H M; Castro, Elena; Sandhu, Shahneen K; Barwell, Lorraine; Oommen, Nikhil Babu; Carreira, Suzanne; Drake, Charles G; Jones, Robert; Cooper, Colin S; Scher, Howard I; de Bono, Johann S

    2016-01-01

    -resistant prostate cancer in other LPD subgroups (LPD1 overall survival 10.7 months [95% CI 4.1–17.2] vs non-LPD1 25.6 months [18.0–33.4]; p<0.0001). A nine-gene signature verified by qRT-PCR classified patients into this LPD1 subgroup with a very low percentage of misclassification (1.2%). The ten patients who were initially unclassifiable by the LPD analyses were subclassified by this signature. We confirmed the prognostic utility of this nine-gene signature in the validation castration-resistant prostate cancer cohort, where LPD1 membership was also associated with worse overall survival (LPD1 9.2 months [95% CI 2.1–16.4] vs non-LPD1 21.6 months [7.5–35.6]; p=0.001), and remained an independent prognostic factor in multivariable analyses for both cohorts. Interpretation Our results suggest that whole-blood gene profiling could identify gene-expression signatures that stratify patients with castration-resistant prostate cancer into distinct prognostic groups. Funding AstraZeneca, Experimental Cancer Medicine Centre, Prostate Cancer Charity, Prostate Cancer Foundation. PMID:23059046

  17. Mode-expansion method for predicting radar signature above rough ocean surfaces at low-grazing angle

    NASA Technical Reports Server (NTRS)

    Zhang, Y.

    2005-01-01

    The Mode-Expansion Method (MEM) is introduced to calculate the electromagnetic (EM) waves scattered by 2-D rough water surfaces at low-grazing angles. The Electric Field Integral Equation (EFIE) is used in defining the problem and is simplified by using the Impedance Boundary Condition (IBC). The surface currents are expressed as the sum of modes expanded as the Fourier series with incident wave as the dominant mode. It is shown that, by the MEM and for the geometry with transmitting and receiving waves at low-grazing angles, very few modes are needed in solving the forward scattering field with reasonable accuracy.

  18. Combining Expressed Vocational Choice and Measures of Career Development to Predict Future Occupational Field.

    ERIC Educational Resources Information Center

    Noeth, Richard J.

    A study was designed to test predictability of actual occupation from expressed vocational choice when combined separately with measures of career development. Subjects were 1,994 members of a national study of high school career development who were working more than half-time three years later (1976). Expressed vocational choice and measures of…

  19. A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells

    PubMed Central

    Williams, Andrew; Buick, Julie K.; Moffat, Ivy; Swartz, Carol D.; Recio, Leslie; Hyduke, Daniel R.; Li, Heng-Hong; Fornace, Albert J.; Aubrecht, Jiri; Yauk, Carole L.

    2015-01-01

    Genotoxicity testing is a critical component of chemical assessment. The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the DNA damage response pathways involved in response, is becoming more common. In companion papers previously published in Environmental and Molecular Mutagenesis, Li et al. (2015) [6] developed a dose optimization protocol that was based on evaluating expression changes in several well-characterized stress-response genes using quantitative real-time PCR in human lymphoblastoid TK6 cells in culture. This optimization approach was applied to the analysis of TK6 cells exposed to one of 14 genotoxic or 14 non-genotoxic agents, with sampling 4 h post-exposure. Microarray-based transcriptomic analyses were then used to develop a classifier for genotoxicity using the nearest shrunken centroids method. A panel of 65 genes was identified that could accurately classify toxicants as genotoxic or non-genotoxic. In Buick et al. (2015) [1], the utility of the biomarker for chemicals that require metabolic activation was evaluated. In this study, TK6 cells were exposed to increasing doses of four chemicals (two genotoxic that require metabolic activation and two non-genotoxic chemicals) in the presence of rat liver S9 to demonstrate that S9 does not impair the ability to classify genotoxicity using this genomic biomarker in TK6cells. PMID:26425668

  20. Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer

    PubMed Central

    Claus, Rainer; Weichenhan, Dieter; Jung, Klaus; Kitz, Julia; Grade, Marian; Wolff, Hendrik A.; Jo, Peter; Doyen, Jérôme; Gérard, Jean-Pierre; Johnsen, Steven A.; Plass, Christoph; Beißbarth, Tim; Ghadimi, Michael

    2014-01-01

    In locally advanced rectal cancer a preoperative predictive biomarker is necessary to adjust treatment specifically for those patients expected to suffer relapse. We applied whole genome methylation CpG island array analyses to an initial set of patients (n=11) to identify differentially methylated regions (DMRs) that separate a good from a bad prognosis group. Using a quantitative high-resolution approach, candidate DMRs were first validated in a set of 61 patients (test set) and then confirmed DMRs were further validated in additional independent patient cohorts (n=71, n=42). We identified twenty highly discriminative DMRs and validated them in the test set using the MassARRAY technique. Ten DMRs could be confirmed which allowed separation into prognosis groups (p=0.0207, HR=4.09). The classifier was validated in two additional cohorts (n=71, p=0.0345, HR=3.57 and n=42, p=0.0113, HR=3.78). Interestingly, six of the ten DMRs represented regions close to the transcriptional start sites of genes which are also marked by the Polycomb Repressor Complex component EZH2. In conclusion we present a classifier comprising 10 DMRs which predicts patient prognosis with a high degree of accuracy. These data may now help to discriminate between patients that may respond better to standard treatments from those that may require alternative modalities. PMID:25261372

  1. FOXP1 suppresses immune response signatures and MHC class II expression in activated B-cell-like diffuse large B-cell lymphomas.

    PubMed

    Brown, P J; Wong, K K; Felce, S L; Lyne, L; Spearman, H; Soilleux, E J; Pedersen, L M; Møller, M B; Green, T M; Gascoyne, D M; Banham, A H

    2016-03-01

    The FOXP1 (forkhead box P1) transcription factor is a marker of poor prognosis in diffuse large B-cell lymphoma (DLBCL). Here microarray analysis of FOXP1-silenced DLBCL cell lines identified differential regulation of immune response signatures and major histocompatibility complex class II (MHC II) genes as some of the most significant differences between germinal center B-cell (GCB)-like DLBCL with full-length FOXP1 protein expression versus activated B-cell (ABC)-like DLBCL expressing predominantly short FOXP1 isoforms. In an independent primary DLBCL microarray data set, multiple MHC II genes, including human leukocyte antigen DR alpha chain (HLA-DRA), were inversely correlated with FOXP1 transcript expression (P<0.05). FOXP1 knockdown in ABC-DLBCL cells led to increased cell-surface expression of HLA-DRA and CD74. In R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone)-treated DLBCL patients (n=150), reduced HLA-DRA (<90% frequency) expression correlated with inferior overall survival (P=0.0003) and progression-free survival (P=0.0012) and with non-GCB subtype stratified by the Hans, Choi or Visco-Young algorithms (all P<0.01). In non-GCB DLBCL cases with <90% HLA-DRA, there was an inverse correlation with the frequency (P=0.0456) and intensity (P=0.0349) of FOXP1 expression. We propose that FOXP1 represents a novel regulator of genes targeted by the class II MHC transactivator CIITA (MHC II and CD74) and therapeutically targeting the FOXP1 pathway may improve antigen presentation and immune surveillance in high-risk DLBCL patients. PMID:26500140

  2. FOXP1 suppresses immune response signatures and MHC class II expression in activated B-cell-like diffuse large B-cell lymphomas

    PubMed Central

    Brown, P J; Wong, K K; Felce, S L; Lyne, L; Spearman, H; Soilleux, E J; Pedersen, L M; Møller, M B; Green, T M; Gascoyne, D M; Banham, A H

    2016-01-01

    The FOXP1 (forkhead box P1) transcription factor is a marker of poor prognosis in diffuse large B-cell lymphoma (DLBCL). Here microarray analysis of FOXP1-silenced DLBCL cell lines identified differential regulation of immune response signatures and major histocompatibility complex class II (MHC II) genes as some of the most significant differences between germinal center B-cell (GCB)-like DLBCL with full-length FOXP1 protein expression versus activated B-cell (ABC)-like DLBCL expressing predominantly short FOXP1 isoforms. In an independent primary DLBCL microarray data set, multiple MHC II genes, including human leukocyte antigen DR alpha chain (HLA-DRA), were inversely correlated with FOXP1 transcript expression (P<0.05). FOXP1 knockdown in ABC-DLBCL cells led to increased cell-surface expression of HLA-DRA and CD74. In R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone)-treated DLBCL patients (n=150), reduced HLA-DRA (<90% frequency) expression correlated with inferior overall survival (P=0.0003) and progression-free survival (P=0.0012) and with non-GCB subtype stratified by the Hans, Choi or Visco–Young algorithms (all P<0.01). In non-GCB DLBCL cases with <90% HLA-DRA, there was an inverse correlation with the frequency (P=0.0456) and intensity (P=0.0349) of FOXP1 expression. We propose that FOXP1 represents a novel regulator of genes targeted by the class II MHC transactivator CIITA (MHC II and CD74) and therapeutically targeting the FOXP1 pathway may improve antigen presentation and immune surveillance in high-risk DLBCL patients. PMID:26500140

  3. High Expression of Suppressor of Cytokine Signaling-2 Predicts Poor Outcome in Pediatric Acute Myeloid Leukemia: A Report from the Children's Oncology Group

    PubMed Central

    Laszlo, George S.; Ries, Rhonda E.; Gudgeon, Chelsea J.; Harrington, Kimberly H.; Alonzo, Todd A.; Gerbing, Robert B.; Raimondi, Susana C.; Hirsch, Betsy A.; Gamis, Alan S.; Meshinchi, Soheil; Walter, Roland B.

    2015-01-01

    Deregulated cytokine signaling is a characteristic feature of acute myeloid leukemia (AML), and expression signatures of cytokines and chemokines have been identified as significant prognostic factor in this disease. Given this aberrant signaling, we hypothesized that expression of Suppressor of Cytokine Signaling-2 (SOCS2), a negative regulator of cytokine signaling, might be altered in AML and could provide predictive information. Among 188 participants of the Children's Oncology Group AAML03P1 trial, SOCS2 mRNA levels varied >6,000-fold. Higher (>median) SOCS2 expression was associated with inferior overall (60±10% vs. 75±9%, p=0.026) and event-free (44±10% vs. 59±10%, p=0.031) survival. However, these differences were accounted for by higher prevalence of high-risk and lower prevalence of low-risk disease among patients with higher SOCS2 expression, limiting the clinical utility of SOCS2 as predictive marker. It remains untested whether high SOCS2 expression identifies a subset of leukemias with deregulated cytokine signaling that could be amenable to therapeutic intervention. PMID:24559289

  4. MGMT Expression Predicts PARP-Mediated Resistance to Temozolomide.

    PubMed

    Erice, Oihane; Smith, Michael P; White, Rachel; Goicoechea, Ibai; Barriuso, Jorge; Jones, Chris; Margison, Geoffrey P; Acosta, Juan C; Wellbrock, Claudia; Arozarena, Imanol

    2015-05-01

    Melanoma and other solid cancers are frequently resistant to chemotherapies based on DNA alkylating agents such as dacarbazine and temozolomide. As a consequence, clinical responses are generally poor. Such resistance is partly due to the ability of cancer cells to use a variety of DNA repair enzymes to maintain cell viability. Particularly, the expression of MGMT has been linked to temozolomide resistance, but cotargeting MGMT has proven difficult due to dose-limiting toxicities. Here, we show that the MGMT-mediated resistance of cancer cells is profoundly dependent on the DNA repair enzyme PARP. Both in vitro and in vivo, we observe that MGMT-positive cancer cells strongly respond to the combination of temozolomide and PARP inhibitors (PARPi), whereas MGMT-deficient cells do not. In melanoma cells, temozolomide induced an antiproliferative senescent response, which was greatly enhanced by PARPi in MGMT-positive cells. In summary, we provide compelling evidence to suggest that the stratification of patients with cancer upon the MGMT status would enhance the success of combination treatments using temozolomide and PARPi. PMID:25777962

  5. Current smoking-specific gene expression signature in normal bronchial epithelium is enhanced in squamous cell lung cancer.

    PubMed

    Boelens, Mirjam C; van den Berg, Anke; Fehrmann, Rudolf S N; Geerlings, Marie; de Jong, Wouter K; te Meerman, Gerard J; Sietsma, Hannie; Timens, Wim; Postma, Dirkje S; Groen, Harry J M

    2009-06-01

    Cigarette smoking is the main risk factor for the development of squamous cell lung carcinoma (SCC). However, the smoking-related molecular changes in SCC have not been studied. Gene expression studies in both histologically normal bronchial epithelium and SCC epithelial samples identified genes differentially expressed between current and ex-smokers. Subsequently, expression levels of the smoking-related genes in normal bronchial epithelium were compared with those in SCC cells, since we hypothesized that the smoking-induced changes would be also deregulated in SCC. Gene expression profiles were generated using Agilent whole human genome microarrays on laser-microdissected normal bronchial epithelium and SCC samples. Expression levels of 246 genes, mainly related to oxidative stress response, were significantly different between normal bronchial epithelium of current and ex-smokers. Such a differential gene expression profile did not exist in SCC cells of smokers and ex-smokers. Interestingly, when comparing SCC and normal bronchial epithelium from ex-smokers, the vast majority of these 246 genes were also deregulated in SCC. When comparing SCC with normal epithelium from smokers, 22% of the up-regulated genes showed a similar high expression in SCC whereas 79% of the down-regulated genes were even further reduced in SCC as compared to current smokers. The down-regulated genes included several tumour suppressor genes, such as C9orf9, INHBB, LRIG1, SCGB3A1, SERPINI2, STEAP3 and ZMYND10. Thus, our study shows that the majority of genes up-regulated in normal bronchial epithelium of current smokers show similar high expression levels in SCC, while down-regulated genes are even further repressed in SCC. Our data indicate that smoking-related changes in normal bronchial epithelial cells persist in malignant transformed squamous cells. PMID:19334046

  6. MicroRNA Gene Expression Signature Driven by miR-9 Overexpression in Ovarian Clear Cell Carcinoma.

    PubMed

    Yanaihara, Nozomu; Noguchi, Yukiko; Saito, Misato; Takenaka, Masataka; Takakura, Satoshi; Yamada, Kyosuke; Okamoto, Aikou

    2016-01-01

    Previous studies have identified microRNA (miRNA) involvement in human cancers. This study aimed to elucidate potential clinical and biological associations of ovarian cancer-related miRNA gene expression profiles in high-grade serous carcinoma (HGSC) and ovarian clear cell carcinoma (OCCC). Accordingly, we investigated 27 patients with ovarian cancer (12 HGSC and 15 OCCC cases) using quantitative real-time reverse transcription polymerase chain reaction to determine the cancer-related miRNA expressions. Gene Cluster 3.0 was used for hierarchical clustering analysis, and differentially expressed miRNAs between HGSC and OCCC were identified by the class comparison analysis using BRB-ArrayTools. An unsupervised hierarchical clustering analysis identified two distinct miRNA expression clusters, with histological subtype-related significant differences in the associations between clusters and clinicopathological features. A comparison of miRNA expression in HGSCs and OCCCs identified five miRNAs (miR-132, miR-9, miR-126, miR-34a, and miR-21), with OCCCs demonstrating a statistically higher expression. Further investigation of the biological significance of miR-9 overexpression in OCCC revealed that miR-9 inhibition reduced the cell invasion ability and upregulated E-cadherin expression. Using a luciferase reporter assay, we further demonstrated the direct binding of miR-9 to E-cadherin. Global cancer-related miRNA expression analysis identified statistically unique profiles that could discriminate ovarian cancer histotypes. In OCCC, miR-9 overexpression may affect pathogenesis by targeting E-cadherin, thereby inducing an epithelial-mesenchymal transition. Therefore, miR-9 may be a promising therapeutic target strategy for OCCC. PMID:27612152

  7. Development of the first oligonucleotide microarray for global gene expression profiling in guinea pigs: defining the transcription signature of infectious diseases

    PubMed Central

    2012-01-01

    Background The Guinea pig (Cavia porcellus) is one of the most extensively used animal models to study infectious diseases. However, despite its tremendous contribution towards understanding the establishment, progression and control of a number of diseases in general and tuberculosis in particular, the lack of fully annotated guinea pig genome sequence as well as appropriate molecular reagents has severely hampered detailed genetic and immunological analysis in this animal model. Results By employing the cross-species hybridization technique, we have developed an oligonucleotide microarray with 44,000 features assembled from different mammalian species, which to the best of our knowledge is the first attempt to employ microarray to study the global gene expression profile in guinea pigs. To validate and demonstrate the merit of this microarray, we have studied, as an example, the expression profile of guinea pig lungs during the advanced phase of M. tuberculosis infection. A significant upregulation of 1344 genes and a marked down regulation of 1856 genes in the lungs identified a disease signature of pulmonary tuberculosis infection. Conclusion We report the development of first comprehensive microarray for studying the global gene expression profile in guinea pigs and validation of its usefulness with tuberculosis as a case study. An important gap in the area of infectious diseases has been addressed and a valuable molecular tool is provided to optimally harness the potential of guinea pig model to develop better vaccines and therapies against human diseases. PMID:23031549

  8. Gene expression signatures in motor neurone disease fibroblasts reveal dysregulation of metabolism, hypoxia-response and RNA processing functions

    PubMed Central

    Raman, R; Allen, S P; Goodall, E F; Kramer, S; Ponger, L-L; Heath, P R; Milo, M; Hollinger, H C; Walsh, T; Highley, J R; Olpin, S; McDermott, C J; Shaw, P J; Kirby, J

    2015-01-01

    Aims Amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS) are two syndromic variants within the motor neurone disease spectrum. As PLS and most ALS cases are sporadic (SALS), this limits the availability of cellular models for investigating pathogenic mechanisms and therapeutic targets. The aim of this study was to use gene expression profiling to evaluate fibroblasts as cellular models for SALS and PLS, to establish whether dysregulated biological processes recapitulate those seen in the central nervous system and to elucidate pathways that distinguish the clinically defined variants of SALS and PLS. Methods Microarray analysis was performed on fibroblast RNA and differentially expressed genes identified. Genes in enriched biological pathways were validated by quantitative PCR and functional assays performed to establish the effect of altered RNA levels on the cellular processes. Results Gene expression profiling demonstrated that whilst there were many differentially expressed genes in common between SALS and PLS fibroblasts, there were many more expressed specifically in the SALS fibroblasts, including those involved in RNA processing and the stress response. Functional analysis of the fibroblasts confirmed a significant decrease in miRNA production and a reduced response to hypoxia in SALS fibroblasts. Furthermore, metabolic gene changes seen in SALS, many of which were also evident in PLS fibroblasts, resulted in dysfunctional cellular respiration. Conclusions The data demonstrate that fibroblasts can act as cellular models for ALS and PLS, by establishing the transcriptional changes in known pathogenic pathways that confer subsequent functional effects and potentially highlight targets for therapeutic intervention. PMID:24750211

  9. The Bimodality Index: A Criterion for Discovering and Ranking Bimodal Signatures from Cancer Gene Expression Profiling Data

    PubMed Central

    Wang, Jing; Wen, Sijin; Symmans, W. Fraser; Pusztai, Lajos; Coombes, Kevin R.

    2009-01-01

    Motivation Identifying genes with bimodal expression patterns from large-scale expression profiling data is an important analytical task. Model-based clustering is popular for this purpose. That technique commonly uses the Bayesian information criterion (BIC) for model selection. In practice, however, BIC appears to be overly sensitive and may lead to the identification of bimodally expressed genes that are unreliable or not clinically useful. We propose using a novel criterion, the bimodality index, not only to identify but also to rank meaningful and reliable bimodal patterns. The bimodality index can be computed using either a mixture model-based algorithm or Markov chain Monte Carlo techniques. Results We carried out simulation studies and applied the method to real data from a cancer gene expression profiling study. Our findings suggest that BIC behaves like a lax cutoff based on the bimodality index, and that the bimodality index provides an objective measure to identify and rank meaningful and reliable bimodal patterns from large-scale gene expression datasets. R code to compute the bimodality index is included in the ClassDiscovery package of the Object-Oriented Microarray and Proteomic Analysis (OOMPA) suite available at the web site http;//bioinformatics.mdanderson.org/Software/OOMPA. PMID:19718451

  10. Elevated HMGA2 expression is associated with cancer aggressiveness and predicts poor outcome in breast cancer.

    PubMed

    Wu, Jingjing; Zhang, Shizhen; Shan, Jinlan; Hu, Zujian; Liu, Xiyong; Chen, Lirong; Ren, Xingchang; Yao, Lifang; Sheng, Hongqiang; Li, Ling; Ann, David; Yen, Yun; Wang, Jian; Wang, Xiaochen

    2016-07-01

    High mobility group AT-hook 2 (HMGA2) is involved in a wide spectrum of biological processes and is upregulated in several tumors. Here, we collected 273 breast cancer (BC) specimens as a training set and 310 specimens as a validation set to examine the expression of HMGA2 by immunohistochemical staining. It was found that HMGA2 expression was significantly positively correlated with advanced tumor grade and poor survival. Subgroup analysis indicated that high level of HMGA2 was significantly correlated with poor prognosis, especially in the subgroups of stage II-III, low pathological grade and non-triple negative breast cancer cases. Gene set enrichment analysis (GSEA) demonstrated a significant positive correlation between HMGA2 level and the gene expression signature of metaplastic and mesenchymal phenotype. Importantly, we also observed that ectopic expression of HMGA2 promoted the migration and invasion of breast cancer cells, and protected cancer cells against genotoxic stress from agents stimulating P53 (Ser15) phosphorylation. As a conclusion, expression of HMGA2 might indicate more advanced malignancy of breast cancer. Thus we believe HMGA2 could serve as a biomarker of poor prognosis and a novel target in treating BC tumors. PMID:27063096

  11. Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance.

    PubMed

    Jensen, Niels F; Stenvang, Jan; Beck, Mette K; Hanáková, Barbora; Belling, Kirstine C; Do, Khoa N; Viuff, Birgitte; Nygård, Sune B; Gupta, Ramneek; Rasmussen, Mads H; Tarpgaard, Line S; Hansen, Tine P; Budinská, Eva; Pfeiffer, Per; Bosman, Fred; Tejpar, Sabine; Roth, Arnaud; Delorenzi, Mauro; Andersen, Claus L; Rømer, Maria U; Brünner, Nils; Moreira, José M A

    2015-06-01

    Current standard treatments for metastatic colorectal cancer (CRC) are based on combination regimens with one of the two chemotherapeutic drugs, irinotecan or oxaliplatin. However, drug resistance frequently limits the clinical efficacy of these therapies. In order to gain new insights into mechanisms associated with chemoresistance, and departing from three distinct CRC cell models, we generated a panel of human colorectal cancer cell lines with acquired resistance to either oxaliplatin or irinotecan. We characterized the resistant cell line variants with regards to their drug resistance profile and transcriptome, and matched our results with datasets generated from relevant clinical material to derive putative resistance biomarkers. We found that the chemoresistant cell line variants had distinctive irinotecan- or oxaliplatin-specific resistance profiles, with non-reciprocal cross-resistance. Furthermore, we could identify several new, as well as some previously described, drug resistance-associated genes for each resistant cell line variant. Each chemoresistant cell line variant acquired a unique set of changes that may represent distinct functional subtypes of chemotherapy resistance. In addition, and given the potential implications for selection of subsequent treatment, we also performed an exploratory analysis, in relevant patient cohorts, of the predictive value of each of the specific genes identified in our cellular models. PMID:25759163

  12. Clinical value of integrated-signature miRNAs in colorectal cancer: miRNA expression profiling analysis and experimental validation

    PubMed Central

    Wang, YuQun; Song, Mei; Zhou, Wu; Tu, HongXiang; Lin, Zhuo

    2015-01-01

    MicroRNA (miRNA) expression profiling of colorectal cancer (CRC) are often inconsistent among different studies. To determine candidate miRNA biomarkers for CRC, we performed an integrative analysis of miRNA expression profiling compared CRC tissues and paired neighboring noncancerous colorectal tissues. Using robust rank aggregation method, we identified a miRNA set of 10 integrated-signature miRNAs. In addition, the qRT-PCR validation demonstrated that 9 miRNAs were consistent dysregulated with the integrative analysis in CRC tissues, 4 miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were up-regulated expression, and 5 miRNAs (miR-145-5p, miR-195-5p, miR-139-5p, miR-378a-5p and miR-143-3p) were down-regulated expression (all p < 0.05). Consistent with the initial analysis, 7 miRNAs were found to be significantly dysregulated in CRC tissues in TCGA data base, 4 miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were significantly up-regulated expression, and 3 miRNAs (miR-145-5p, miR-139-5p and miR-378a-5p) were significantly down-regulated expression in CRC tissues (all p < 0.001). Furthermore, miR-17-5p (p = 0.011) and miR-20a-5p (p = 0.003) were up-regulated expression in the III/IV tumor stage, miR-145-5p (p = 0.028) and miR-195-5p (p = 0.001) were significantly increased expression with microscopic vascular invasion in CRC tissues, miR-17-5p (p = 0.037) and miR-145-5p (p = 0.023) were significantly increased expression with lymphovascular invasion. Moreover, Cox regression analysis of CRC patients in TCGA data base showed miR-20a-5p was correlated with survival (hazard ratio: 1.875, 95%CI: 1.088–3.232, p = 0.024). Hence, the finding of current study provides a basic implication of these miRNAs for further clinical application in CRC. PMID:26462034

  13. A unique gene expression signature associated with serotonin 2C receptor RNA editing in the prefrontal cortex and altered in suicide

    PubMed Central

    Di Narzo, Antonio Fabio; Kozlenkov, Alexey; Roussos, Panos; Hao, Ke; Hurd, Yasmin; Lewis, David A.; Sibille, Etienne; Siever, Larry J.; Koonin, Eugene; Dracheva, Stella

    2014-01-01

    Editing of the pre-mRNA for the serotonin receptor 2C (5-HT2CR) by site-specific adenosine deamination (A-to-I pre-mRNA editing) substantially increases the functional plasticity of this key neurotransmitter receptor and is thought to contribute to homeostatic mechanisms in neurons. 5-HT2CR mRNA editing generates up to 24 different receptor isoforms. The extent of editing correlates with 5-HT2CR functional activity: more highly edited isoforms exhibit the least function. Altered 5-HT2CR editing has been reported in postmortem brains of suicide victims. We report a comparative analysis of the connections among 5-HT2CR editing, genome-wide gene expression and DNA methylation in suicide victims, individuals with major depressive disorder and non-psychiatric controls. The results confirm previous findings of an overrepresentation of highly edited mRNA variants (which encode hypoactive 5-HT2CR receptors) in the brains of suicide victims. A large set of genes for which the expression level is associated with editing was detected. This signature set of editing-associated genes is significantly enriched for genes that are involved in synaptic transmission, genes that are preferentially expressed in neurons, and genes whose expression is correlated with the level of DNA methylation. Notably, we report that the link between 5-HT2CR editing and gene expression is disrupted in suicide victims. The results suggest that the postulated homeostatic function of 5-HT2CR editing is dysregulated in individuals who committed suicide. PMID:24781207

  14. Identification of co-expressed gene signatures in mouse B1, marginal zone and B2 B-cell populations

    PubMed Central

    Mabbott, Neil A; Gray, David

    2014-01-01

    In mice, three major B-cell subsets have been identified with distinct functionalities: B1 B cells, marginal zone B cells and follicular B2 B cells. Here, we used the growing body of publicly available transcriptomics data to create an expression atlas of 84 gene expression microarray data sets of distinct mouse B-cell subsets. These data were subjected to network-based cluster analysis using BioLayout Express3D. Using this analysis tool, genes with related functions clustered together in discrete regions of the network graph and enabled the identification of transcriptional networks that underpinned the functional activity of distinct cell populations. Some gene clusters were expressed highly by most of the cell populations included in this analysis (such as those with activity related to house-keeping functions). Others contained genes with expression patterns specific to distinct B-cell subsets. While these clusters contained many genes typically associated with the activity of the cells they were specifically expressed in, many novel B-cell-subset-specific candidate genes were identified. A large number of uncharacterized genes were also represented in these B-cell lineage-specific clusters. Further analysis of the activities of these uncharacterized candidate genes will lead to the identification of novel B-cell lineage-specific transcription factors and regulators of B-cell function. We also analysed 36 microarray data sets from distinct human B-cell populations. These data showed that mouse and human germinal centre B cells shared similar transcriptional features, whereas mouse B1 B cells were distinct from proposed human B1 B cells. PMID:24032749

  15. Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells.

    PubMed

    Buick, Julie K; Moffat, Ivy; Williams, Andrew; Swartz, Carol D; Recio, Leslie; Hyduke, Daniel R; Li, Heng-Hong; Fornace, Albert J; Aubrecht, Jiri; Yauk, Carole L

    2015-07-01

    The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the molecular pathways involved in the response, is becoming more common. In a companion article, a genomic biomarker was developed in human TK6 cells to classify chemicals as genotoxic or nongenotoxic. Because TK6 cells are not metabolically competent, we set out to broaden the utility of the biomarker for use with chemicals requiring metabolic activation. Specifically, chemical exposures were conducted in the presence of rat liver S9. The ability of the biomarker to classify genotoxic (benzo[a]pyrene, BaP; aflatoxin B1, AFB1) and nongenotoxic (dexamethasone, DEX; phenobarbital, PB) agents correctly was evaluated. Cells were exposed to increasing chemical concentrations for 4 hr and collected 0 hr, 4 hr, and 20 hr postexposure. Relative survival, apoptosis, and micronucleus frequency were measured at 24 hr. Transcriptome profiles were measured with Agilent microarrays. Statistical modeling and bioinformatics tools were applied to classify each chemical using the genomic biomarker. BaP and AFB1 were correctly classified as genotoxic at the mid- and high concentrations at all three time points, whereas DEX was correctly classified as nongenotoxic at all concentrations and time points. The high concentration of PB was misclassified at 24 hr, suggesting that cytotoxicity at later time points may cause misclassification. The data suggest that the use of S9 does not impair the ability of the biomarker to classify genotoxicity in TK6 cells. Finally, we demonstrate that the biomarker is also able to accurately classify genotoxicity using a publicly available dataset derived from human HepaRG cells. PMID:25733247

  16. Low expression of PKCα and high expression of KRAS predict poor prognosis in patients with colorectal cancer

    PubMed Central

    Chen, Suxian; Wang, Yadi; Zhang, Yun; Wan, Yizeng

    2016-01-01

    The current study aimed to determine the association between protein kinase Cα (PKCα) and Kirsten rat sarcoma viral oncogene homolog (KRAS) expression and the response to folinic acid, 5-fluorouracil and oxaliplatin (FOLFOX regimen) in patients with colorectal cancer (CRC). The protein levels of PKCα and KRAS were analyzed by immunohistochemistry in tissue samples from patients with CRC and in non-cancerous tissues, including 152 cases of colorectal adenocarcinoma, 30 cases of colorectal adenoma and 20 normal colonic mucosa samples. The association between PKCα and KRAS expression and clinicopathological features was analyzed. The rates of positive PKCα protein expression in patients with poorly, moderately and well-differentiated adenocarcinoma were 16.7% (6/36), 40.0% (24/60), and 57.1% (32/56), respectively (P<0.013). The rate of positive KRAS expression in CRC patients was significantly higher than in patients with colon adenoma and normal colon mucosa (P<0.001). Expression levels of KRAS were associated with the degree of differentiation of CRC (P<0.001). Expression of PKCα was negatively correlated with KRAS expression in CRC tissues. The mean progression-free survival (PFS) times in patients with high and low expression of PKCα were 43.9 and 38.8 months, respectively (P<0.001). The mean PFS times were 38.5 and 45.5 months in patients with high and low expression of KRAS, respectively (P=0.001). In conclusion, low PKCα and high KRAS expression predicted relatively poor prognosis in patients with CRC.

  17. WDR5 Supports an N-Myc Transcriptional Complex That Drives a Protumorigenic Gene Expression Signature in Neuroblastoma.

    PubMed

    Sun, Yuting; Bell, Jessica L; Carter, Daniel; Gherardi, Samuele; Poulos, Rebecca C; Milazzo, Giorgio; Wong, Jason W H; Al-Awar, Rima; Tee, Andrew E; Liu, Pei Y; Liu, Bing; Atmadibrata, Bernard; Wong, Matthew; Trahair, Toby; Zhao, Quan; Shohet, Jason M; Haupt, Ygal; Schulte, Johannes H; Brown, Peter J; Arrowsmith, Cheryl H; Vedadi, Masoud; MacKenzie, Karen L; Hüttelmaier, Stefan; Perini, Giovanni; Marshall, Glenn M; Braithwaite, Antony; Liu, Tao

    2015-12-01

    MYCN gene amplification in neuroblastoma drives a gene expression program that correlates strongly with aggressive disease. Mechanistically, trimethylation of histone H3 lysine 4 (H3K4) at target gene promoters is a strict prerequisite for this transcriptional program to be enacted. WDR5 is a histone H3K4 presenter that has been found to have an essential role in H3K4 trimethylation. For this reason, in this study, we investigated the relationship between WDR5-mediated H3K4 trimethylation and N-Myc transcriptional programs in neuroblastoma cells. N-Myc upregulated WDR5 expression in neuroblastoma cells. Gene expression analysis revealed that WDR5 target genes included those with MYC-binding elements at promoters such as MDM2. We showed that WDR5 could form a protein complex at the MDM2 promoter with N-Myc, but not p53, leading to histone H3K4 trimethylation and activation of MDM2 transcription. RNAi-mediated attenuation of WDR5 upregulated expression of wild-type but not mutant p53, an effect associated with growth inhibition and apoptosis. Similarly, a small-molecule antagonist of WDR5 reduced N-Myc/WDR5 complex formation, N-Myc target gene expression, and cell growth in neuroblastoma cells. In MYCN-transgenic mice, WDR5 was overexpressed in precancerous ganglion and neuroblastoma cells compared with normal ganglion cells. Clinically, elevated levels of WDR5 in neuroblastoma specimens were an independent predictor of poor overall survival. Overall, our results identify WDR5 as a key cofactor for N-Myc-regulated transcriptional activation and tumorigenesis and as a novel therapeutic target for MYCN-amplified neuroblastomas. PMID:26471359

  18. Residual expression of reprogramming factors affects the transcriptional program and epigenetic signatures of induced pluripotent stem cells.

    PubMed

    Sommer, Cesar A; Christodoulou, Constantina; Gianotti-Sommer, Andreia; Shen, Steven S; Sailaja, Badi Sri; Hezroni, Hadas; Spira, Avrum; Meshorer, Eran; Kotton, Darrell N; Mostoslavsky, Gustavo

    2012-01-01

    Delivery of the transcription factors Oct4, Klf4, Sox2 and c-Myc via integrating viral vectors has been widely employed to generate induced pluripotent stem cell (iPSC) lines from both normal and disease-specific somatic tissues, providing an invaluable resource for medical research and drug development. Residual reprogramming transgene expression from integrated viruses nevertheless alters the biological properties of iPSCs and has been associated with a reduced developmental competence both in vivo and in vitro. We performed transcriptional profiling of mouse iPSC lines before and after excision of a polycistronic lentiviral reprogramming vector to systematically define the overall impact of persistent transgene expression on the molecular features of iPSCs. We demonstrate that residual expression of the Yamanaka factors prevents iPSCs from acquiring the transcriptional program exhibited by embryonic stem cells (ESCs) and that the expression profiles of iPSCs generated with and without c-Myc are indistinguishable. After vector excision, we find 36% of iPSC clones show normal methylation of the Gtl2 region, an imprinted locus that marks ESC-equivalent iPSC lines. Furthermore, we show that the reprogramming factor Klf4 binds to the promoter region of Gtl2. Regardless of Gtl2 methylation status, we find similar endodermal and hepatocyte differentiation potential comparing syngeneic Gtl2(ON) vs Gtl2(OFF) iPSC clones. Our findings provide new insights into the reprogramming process and emphasize the importance of generating iPSCs free of any residual transgene expression. PMID:23272148

  19. Behaviorally Activated mRNA Expression Profiles Produce Signatures of Learning and Enhanced Inhibition in Aged Rats with Preserved Memory

    PubMed Central

    Haberman, Rebecca P.; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela

    2013-01-01

    Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to

  20. Behaviorally activated mRNA expression profiles produce signatures of learning and enhanced inhibition in aged rats with preserved memory.

    PubMed

    Haberman, Rebecca P; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela

    2013-01-01

    Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to

  1. Mammary gland morphology and gene expression signature of weanling male and female rats following exposure to exogenous estradiol.

    PubMed

    Miousse, Isabelle R; Gomez-Acevedo, Horacio; Sharma, Neha; Vantrease, Jamie; Hennings, Leah; Shankar, Kartik; Cleves, Mario A; Badger, Thomas M; Ronis, Martin Jj

    2013-09-01

    In order to characterize the actions of xenoestrogens, it is essential to possess a solid portrait of the physiological effects of exogenous estradiol. We assessed effects of three doses of exogenous estradiol (E2) (0.1, 1.0 and 10 µg/kg/day) given between postnatal days 21 and 33 on the mammary gland morphology and gene expression profiles of male and female rats compared to vehicle-treated controls. The male mammary gland was more responsive to E2 treatment than in females, with 509 genes regulated >2-fold in a dose-dependent manner in males and only 174 in females. In males, E2 treatment significantly (P < 0.01) increased the number of terminal end buds (TEBs) and the expression of proliferating cell nuclear antigen (PCNA) protein (P < 0.05), both of which are indicators of proliferation. This change was linked to a significant increase (P < 0.05) in the expression of the gene encoding amphiregulin, which is known to induce TEB formation. There was also a dose-dependent increase (P < 0.001) in the estrogen-regulated gene encoding the progesterone receptor. In intact females, despite lack of changes in mammary morphology, we observed a dose-dependent increase (P < 0.05) in the expression of genes encoding three milk proteins: whey acidic protein, casein beta and casein kappa. There was a significant (P < 0.05) downregulation of both estrogen receptors in response to E2 treatment. These results suggest that mammary glands of male rats are very sensitive to exogenous E2 during development post-weaning. The dose-dependent increase observed in amphiregulin and progesterone receptor gene expression was linked to morphological changes and represents a reliable and sensitive tool to evaluate estrogenicity. In contrast, intact weanling female rats were less responsive. PMID:23925648

  2. Optimizing heat shock protein expression induced by prostate cancer laser therapy through predictive computational models

    NASA Astrophysics Data System (ADS)

    Rylander, Marissa N.; Feng, Yusheng; Zhang, Yongjie; Bass, Jon; Stafford, Roger J.; Hazle, John D.; Diller, Kenneth R.

    2006-07-01

    Thermal therapy efficacy can be diminished due to heat shock protein (HSP) induction in regions of a tumor where temperatures are insufficient to coagulate proteins. HSP expression enhances tumor cell viability and imparts resistance to chemotherapy and radiation treatments, which are generally employed in conjunction with hyperthermia. Therefore, an understanding of the thermally induced HSP expression within the targeted tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of the overall tissue response. A treatment planning computational model capable of predicting the temperature, HSP27 and HSP70 expression, and damage fraction distributions associated with laser heating in healthy prostate tissue and tumors is presented. Measured thermally induced HSP27 and HSP70 expression kinetics and injury data for normal and cancerous prostate cells and prostate tumors are employed to create the first HSP expression predictive model and formulate an Arrhenius damage model. The correlation coefficients between measured and model predicted temperature, HSP27, and HSP70 were 0.98, 0.99, and 0.99, respectively, confirming the accuracy of the model. Utilization of the treatment planning model in the design of prostate cancer thermal therapies can enable optimization of the treatment outcome by controlling HSP expression and injury.

  3. Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

    PubMed Central

    Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

    2015-01-01

    The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

  4. Expression of VEGF in Neonatal Urinary Obstruction: Does Expression of VEGF Predict Hydronephrosis?

    PubMed Central

    Magyar, Zsófia; Schönleber, Julianna; Romics, Miklós; Hruby, Ervin; Nagy, Bálint; Sulya, Bálint; Beke, Artúr; Harmath, Ágnes; Jeager, Judit; Rigó, János; Görbe, Éva

    2015-01-01

    Background In animal studies, the inhibition of VEGF activity results in high mortality and impaired renal and glomerular development. Mechanical stimuli, like mechanical stretch in respiratory and circulatory systems, results in an elevated expression of VEGF. In animal models, the experimental urinary obstruction is associated with stretching of tubular cells and activations of the renin-angiotensin system. This results in the upregulation of vascular endothelial growth factor (VEGF) and TNF-alfa. Material/Methods Tissue samples from urinary tract obstruction were collected and immunohistochemistry was performed in 14 patients (average age: 7.1±4.1 years). The control histology group consisted of ureteropelvic junction tissue from 10 fetuses after midtrimester artificial abortion. The fetuses did not have any failure at ultrasound screening and pathological examination. The mean gestational age was 20.6 weeks of gestation (±2.2SD). Expression of VEGF was detected with immunohistochemistry method. Results Expression of VEGF was found in varying intensity in the submucosa and subserosa layers, but only in the test tissue (placental tissue). The tissue of the patients with urinary obstruction and the tissue of the fetal ureteropelvic junction without urinary obstruction were negative for expression of VEGF. The repeated examination showed negative cells and no color staining. Conclusions The pressure due to congenital urogenital obstruction resulting in mechanical stress in cells did not increase the expression of VEGF in young children in our study. To find a correlation between urogenital tract obstruction and increased expression of VEGF, we need to perform more examinations because the connection may be of therapeutic significance. PMID:25951999

  5. Hormonally defined pancreatic and duodenal neuroendocrine tumors differ in their transcription factor signatures: expression of ISL1, PDX1, NGN3, and CDX2.

    PubMed

    Hermann, Gratiana; Konukiewitz, Björn; Schmitt, Anja; Perren, Aurel; Klöppel, Günter

    2011-08-01

    We recently identified the transcription factor (TF) islet 1 gene product (ISL1) as a marker for well-differentiated pancreatic neuroendocrine tumors (P-NETs). In order to better understand the expression of the four TFs, ISL1, pancreatico-duodenal homeobox 1 gene product (PDX1), neurogenin 3 gene product (NGN3), and CDX-2 homeobox gene product (CDX2), that mainly govern the development and differentiation of the pancreas and duodenum, we studied their expression in hormonally defined P-NETs and duodenal (D-) NETs. Thirty-six P-NETs and 14 D-NETs were immunostained with antibodies against the four pancreatic hormones, gastrin, serotonin, calcitonin, ISL1, PDX1, NGN3, and CDX2. The TF expression pattern of each case was correlated with the tumor's hormonal profile. Insulin-positive NETs expressed only ISL1 (10/10) and PDX1 (9/10). Glucagon-positive tumors expressed ISL1 (7/7) and were almost negative for the other TFs. Gastrin-positive NETs, whether of duodenal or pancreatic origin, frequently expressed PDX1 (17/18), ISL1 (14/18), and NGN3 (14/18). CDX2 was mainly found in the gastrin-positive P-NETs (5/8) and rarely in the D-NETs (1/10). Somatostatin-positive NETs, whether duodenal or pancreatic in origin, expressed ISL1 (9/9), PDX1 (3/9), and NGN3 (3/9). The remaining tumors showed labeling for ISL1 in addition to NGN3. There was no association between a particular TF pattern and NET features such as grade, size, location, presence of metastases, and functional activity. We conclude from our data that there is a correlation between TF expression patterns and certain hormonally defined P-NET and D-NET types, suggesting that most of the tumor types originate from embryologically determined precursor cells. The observed TF signatures do not allow us to distinguish P-NETs from D-NETs. PMID:21739268

  6. Quantitative immunohistochemical expression of c Kit in breast carcinomas is predictive of patients' outcome

    PubMed Central

    Charpin, C; Giusiano, S; Charfi, S; Secq, V; Carpentier, S; Andrac, L; Lavaut, M-N; Allasia, C; Bonnier, P; Garcia, S

    2009-01-01

    Background: c Kit (CD117) expression in tissues has been reported as a relevant target for specific therapy in some human malignancies, but has been poorly documented in breast carcinomas Methods: The prognostic significance of c Kit in a series of 924 breast carcinomas (mean follow-up, 79 months) was investigated using standardised high-throughput quantitative densitometry of immunohistochemical precipitates in tissue microarrays. Results: c Kit was expressed in 14.7% breast carcinomas (and in 42 out of 586 node-negative tumours). In univariate analysis, (log-rank test) the score of c Kit expression correlated with poor patient outcome P=0.02 and particularly in node-negative cases (P=0.002). In multivariate Cox analysis, c Kit was an indicator of metastasis independent of 25 other concomitantly evaluated markers of prognosis. Logistic regression showed that c Kit ranked 10 out of 25 (P=0.041), and was included in a 10-marker signature that allowed 79.2% of the patients to be correctly classified in the metastatic or metastasis-free categories independently of hormone receptors and HER-2 status. Interestingly, c Kit was also a significant predictor of metastasis in node-negative tumours (2 out of 25 ranking, P<0.0001) and included in a six-marker signature of prognosis, correctly classifying 88.6% of the patients (P<0.0001). Conclusion: We concluded that, as assessed by quantitative immunohistochemistry, c Kit is an independent prognostic indicator that could also potentially serve as a target for specific therapy in breast carcinomas. PMID:19513067

  7. Does verbal and gestural expression ability predict comprehension ability in cerebral palsy?

    PubMed

    Pueyo, Roser; Ariza, Mar; Narberhaus, Ana; Ballester-Plané, Júlia; Laporta-Hoyos, Olga; Junqué, Carme; Vendrell, Pere

    2013-04-01

    Some people with cerebral palsy have motor and associated impairments that may hinder verbal and gestural expression to various extents. This study explores whether the ability to produce verbal or gestural expressions may be related to the comprehension of verbal communications and gestures. The influence of severity of motor impairment, general cognitive performance, and age on comprehension ability was also explored. Forty people with cerebral palsy were assigned to different groups according to their verbal and gestural expression abilities. A neuropsychological assessment of comprehension abilities and general cognitive performance was carried out. Multiple linear regression analysis was applied to identify the possible influence of expression abilities on comprehension abilities and also to detect the possible contribution of severity of motor impairment, general cognitive performance, and age. Results indicate that verbal and gestural comprehension was mainly predicted by general cognitive performance. Severity of motor impairment and age did not contribute to predicting comprehension abilities. Only verbal grammar comprehension was significantly predicted by verbal expression ability. Verbal expression ability may be an important marker for cerebral palsy therapies. In non-ambulant patients with bilateral cerebral palsy, impaired gestural expression should not be taken as an indicator of impaired gestural comprehension. PMID:24032327

  8. Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy

    PubMed Central

    Johnson, Douglas B.; Estrada, Monica V.; Salgado, Roberto; Sanchez, Violeta; Doxie, Deon B.; Opalenik, Susan R.; Vilgelm, Anna E.; Feld, Emily; Johnson, Adam S.; Greenplate, Allison R.; Sanders, Melinda E.; Lovly, Christine M.; Frederick, Dennie T.; Kelley, Mark C.; Richmond, Ann; Irish, Jonathan M.; Shyr, Yu; Sullivan, Ryan J.; Puzanov, Igor; Sosman, Jeffrey A.; Balko, Justin M.

    2016-01-01

    Anti-PD-1 therapy yields objective clinical responses in 30–40% of advanced melanoma patients. Since most patients do not respond, predictive biomarkers to guide treatment selection are needed. We hypothesize that MHC-I/II expression is required for tumour antigen presentation and may predict anti-PD-1 therapy response. In this study, across 60 melanoma cell lines, we find bimodal expression patterns of MHC-II, while MHC-I expression was ubiquitous. A unique subset of melanomas are capable of expressing MHC-II under basal or IFNγ-stimulated conditions. Using pathway analysis, we show that MHC-II(+) cell lines demonstrate signatures of ‘PD-1 signalling', ‘allograft rejection' and ‘T-cell receptor signalling', among others. In two independent cohorts of anti-PD-1-treated melanoma patients, MHC-II positivity on tumour cells is associated with therapeutic response, progression-free and overall survival, as well as CD4+ and CD8+ tumour infiltrate. MHC-II+ tumours can be identified by melanoma-specific immunohistochemistry using commercially available antibodies for HLA-DR to improve anti-PD-1 patient selection. PMID:26822383

  9. Redox Protein Expression Predicts Radiotherapeutic Response in Early-Stage Invasive Breast Cancer Patients

    SciTech Connect

    Woolston, Caroline M.; Al-Attar, Ahmad; Storr, Sarah J.; Ellis, Ian O.; Morgan, David A.L.; Martin, Stewart G.

    2011-04-01

    Purpose: Early-stage invasive breast cancer patients have commonly undergone breast-conserving surgery and radiotherapy. In a large majority of these patients, the treatment is effective; however, a proportion will develop local recurrence. Deregulated redox systems provide cancer cells protection from increased oxidative stress, such as that induced by ionizing radiation. Therefore, the expression of redox proteins was examined in tumor specimens from this defined cohort to determine whether such expression could predict response. Methods and Materials: The nuclear and cytoplasmic expression of nine redox proteins (glutathione, glutathione reductase, glutaredoxin, glutathione peroxidase 1, 3, and 4, and glutathione S-transferase-{theta}, -{pi}, and -{alpha}) was assessed using conventional immunohistochemistry on a tissue microarray of 224 tumors. Results: A high cytoplasmic expression of glutathione S-transferase-{theta} significantly correlated with a greater risk of local recurrence (p = .008) and, when combined with a low nuclear expression (p = .009), became an independent predictive factor (p = .002) for local recurrence. High cytoplasmic expression of glutathione S-transferase-{theta} also correlated with a worse overall survival (p = .009). Low nuclear and cytoplasmic expression of glutathione peroxidase 3 (p = .002) correlated with a greater risk of local recurrence and was an independent predictive factor (p = .005). These proteins did not correlate with tumor grade, suggesting their function might be specific to the regulation of oxidative stress rather than alterations of tumor phenotype. Only nuclear (p = .005) and cytoplasmic (p = .001) expression of glutathione peroxidase 4 correlated with the tumor grade. Conclusions: Our results support the use of redox protein expression, namely glutathione S-transferase-{theta} and glutathione peroxidase 3, to predict the response to radiotherapy in early-stage breast cancer patients. If incorporated into

  10. Gene expression profiling of MYC-driven tumor signatures in porcine liver stem cells by transcriptome sequencing

    PubMed Central

    Aravalli, Rajagopal N; Talbot, Neil C; Steer, Clifford J

    2015-01-01

    AIM: To identify the genes induced and regulated by the MYC protein in generating tumors from liver stem cells. METHODS: In this study, we have used an immortal porcine liver stem cell line, PICM-19, to study the role of c-MYC in hepatocarcinogenesis. PICM-19 cells were converted into cancer cells (PICM-19-CSCs) by overexpressing human MYC. To identify MYC-driven differential gene expression, transcriptome sequencing was carried out by RNA sequencing, and genes identified by this method were validated using real-time PCR. In vivo tumorigenicity studies were then conducted by injecting PICM-19-CSCs into the flanks of immunodeficient mice. RESULTS: Our results showed that MYC-overexpressing PICM-19 stem cells formed tumors in immunodeficient mice demonstrating that a single oncogene was sufficient to convert them into cancer cells (PICM-19-CSCs). By using comparative bioinformatics analyses, we have determined that > 1000 genes were differentially expressed between PICM-19 and PICM-19-CSCs. Gene ontology analysis further showed that the MYC-induced, altered gene expression was primarily associated with various cellular processes, such as metabolism, cell adhesion, growth and proliferation, cell cycle, inflammation and tumorigenesis. Interestingly, six genes expressed by PICM-19 cells (CDO1, C22orf39, DKK2, ENPEP, GPX6, SRPX2) were completely silenced after MYC-induction in PICM-19-CSCs, suggesting that the absence of these genes may be critical for inducing tumorigenesis. CONCLUSION: MYC-driven genes may serve as promising candidates for the development of hepatocellular carcinoma therapeutics that would not have deleterious effects on other cell types in the liver. PMID:25717234

  11. Gene Expression Signatures from Three Genetically Separable Resistance Gene Signaling Pathways for Downy Mildew Resistance1[w

    PubMed Central

    Eulgem, Thomas; Weigman, Victor J.; Chang, Hur-Song; McDowell, John M.; Holub, Eric B.; Glazebrook, Jane; Zhu, Tong; Dangl, Jeffery L.

    2004-01-01

    Resistance gene-dependent disease resistance to pathogenic microorganisms is mediated by genetically separable regulatory pathways. Using the GeneChip Arabidopsis genome array, we compared the expression profiles of approximately 8,000 Arabidopsis genes following activation of three RPP genes directed against the pathogenic oomycete Peronospora parasitica. Judicious choice of P. parasitica isolates and loss of resistance plant mutants allowed us to compare the responses controlled by three genetically distinct resistance gene-mediated signaling pathways. We found that all three pathways can converge, leading to up-regulation of common sets of target genes. At least two temporal patterns of gene activation are triggered by two of the pathways examined. Many genes defined by their early and transient increases in expression encode proteins that execute defense biochemistry, while genes exhibiting a sustained or delayed expression increase predominantly encode putative signaling proteins. Previously defined and novel sequence motifs were found to be enriched in the promoters of genes coregulated by the local defense-signaling network. These putative promoter elements may operate downstream from signal convergence points. PMID:15181204

  12. Gene expression in human lupus: bone marrow differentiates active from inactive patients and displays apoptosis and granulopoiesis signatures

    PubMed Central

    Nakou, Magdalene; Knowlton, Nicholas; Frank, Mark B.; Bertsias, George; Osban, Jeanette; Sandel, Clayton E.; Papadaki, Eleni; Raptopoulou, Amalia; Sidiropoulos, Prodromos; Kritikos, Heraklis; Tassiulas, Ioannis; Centola, Michael; Boumpas, Dimitrios T.

    2009-01-01

    Objective The cells of the immune system originate from the bone marrow (BM), where many of them also mature. To better understand the aberrant immune response in systemic lupus erythematosus (SLE), we examined the BM in lupus patients using DNA microarrays and compared it to the peripheral blood (PB). Patients and Methods Bone marrow mononuclear cells (BMMCs) from 20 SLE patients (11 with active disease and 9 with inactive disease) and peripheral blood mononuclear cells (PBMCs) from 27 patients (16 active/ 11 inactive); BMMCs and PBMCs from 7 healthy individuals and 3 osteoarthritis patients served as controls. Samples were analyzed on genome-scale microarrays with 21,329 genes represented. Results We found 102 differentially expressed genes between patients’ and controls’ BMMCs (unpaired student t-test), involved in various biologic processes; 53 of them are involved in major networks including cell death, growth, signaling and proliferation. Comparative analysis between BM and PB of patients identified 88 genes differentially expressed; 61 out of 88 participate in cell growth and differentiation, cellular movement and morphology, immune response and other hematopoietic cell functions. Unsupervised clustering of highly expressed genes revealed two major SLE patient clusters (active and inactive) in BM, but not in PB. The upregulated genes in the bone marrow of active patients included genes involved in cell death and granulopoiesis. Conclusion Microarray analysis of the bone marrow differentiates active from inactive lupus patients and provides further evidence for the role of apoptosis and granulocytes in the pathogenesis of the disease. PMID:18975309

  13. Temporal Anomalies in Immunological Gene Expression in a Time Series of Wild Mice: Signature of an Epidemic?

    PubMed Central

    Friberg, Ida M.; Lowe, Ann; Ralli, Catriona; Bradley, Janette E.; Jackson, Joseph A.

    2011-01-01

    Although the ecological importance of coinfection is increasingly recognized, analyses of microbial pathogen dynamics in wildlife usually focus on an ad hoc subset of the species present due to technological limitations on detection. Here we demonstrate the use of expression profiles for immunological genes (pattern recognition receptors, cytokines and transcription factors) as a means to identify, without preconception, the likelihood of important acute microbial infections in wildlife. Using a wood mouse population in the UK as a model we identified significant temporal clusters of individuals with extreme expression of immunological mediators across multiple loci, typical of an acute microbial infection. These clusters were circumstantially associated with demographic perturbation in the summertime wood mouse population. Animals in one cluster also had significantly higher individual macroparasite burdens than contemporaries with “normal” expression patterns. If the extreme transcriptional profiles observed are induced by an infectious agent then this implicates macroparasites as a possible player in mediating individual susceptibility or resilience to infection. The form of survey described here, combined with next generation nucleic acids sequencing methods for the broad detection of microbial infectious agents in individuals with anomalous immunological transcriptional profiles, could be a powerful tool for revealing unrecognized, ecologically important infectious agents circulating in wildlife populations. PMID:21629775

  14. Integrated microRNA, gene expression and transcription factors signature in papillary thyroid cancer with lymph node metastasis

    PubMed Central

    Mohamad Yusof, Azliana; Abdullah Suhaimi, Shahrun Niza; Muhammad, Rohaizak; Jamal, Rahman

    2016-01-01

    Background. Papillary thyroid carcinoma (PTC) is the commonest thyroid malignancy originating from the follicle cells in the thyroid. Despite a good overall prognosis, certain high-risk cases as in those with lymph node metastasis (LNM) have progressive disease and poorer prognosis. MicroRNAs are a class of non-protein-coding, 19–24 nucleotides single-stranded RNAs which regulate gene expression and these molecules have been shown to play a role in LNM. The integrated analysis of miRNAs and gene expression profiles together with transcription factors (TFs) has been shown to improve the identification of functional miRNA-target gene-TF relationships, providing a more complete view of molecular events underlying metastasis process. Objectives. We reanalyzed The Cancer Genome Atlas (TCGA) datasets on PTC to identify differentially expressed miRNAs/genes in PTC patients with LNM-positive (LNM-P) versus lymph node negative (LNN) PTC patients and to investigate the miRNA-gene-TF regulatory circuit that regulate LNM in PTC. Results. PTC patients with LNM (PTC LNM-P) have a significantly shorter disease-free survival rate compared to PTC patients without LNM (PTC LNN) (Log-rank Mantel Cox test, p = 0.0049). We identified 181 significantly differentially expressed miRNAs in PTC LNM-P versus PTC LNN; 110 were upregulated and 71 were downregulated. The five topmost deregulated miRNAs were hsa-miR-146b, hsa-miR-375, hsa-miR-31, hsa-miR-7-2 and hsa-miR-204. In addition, 395 miRNAs were differentially expressed between PTC LNM-P and normal thyroid while 400 miRNAs were differentially expressed between PTC LNN and normal thyroid. We found four significant enrichment pathways potentially involved in metastasis to the lymph nodes, namely oxidative phosphorylation (OxPhos), cell adhesion molecules (CAMs), leukocyte transendothelial migration and cytokine–cytokine receptor interaction. OxPhos was the most significantly perturbed pathway (p = 4.70E−06) involving downregulation

  15. Integrated microRNA, gene expression and transcription factors signature in papillary thyroid cancer with lymph node metastasis.

    PubMed

    Ab Mutalib, Nurul-Syakima; Othman, Sri Noraima; Mohamad Yusof, Azliana; Abdullah Suhaimi, Shahrun Niza; Muhammad, Rohaizak; Jamal, Rahman

    2016-01-01

    Background. Papillary thyroid carcinoma (PTC) is the commonest thyroid malignancy originating from the follicle cells in the thyroid. Despite a good overall prognosis, certain high-risk cases as in those with lymph node metastasis (LNM) have progressive disease and poorer prognosis. MicroRNAs are a class of non-protein-coding, 19-24 nucleotides single-stranded RNAs which regulate gene expression and these molecules have been shown to play a role in LNM. The integrated analysis of miRNAs and gene expression profiles together with transcription factors (TFs) has been shown to improve the identification of functional miRNA-target gene-TF relationships, providing a more complete view of molecular events underlying metastasis process. Objectives. We reanalyzed The Cancer Genome Atlas (TCGA) datasets on PTC to identify differentially expressed miRNAs/genes in PTC patients with LNM-positive (LNM-P) versus lymph node negative (LNN) PTC patients and to investigate the miRNA-gene-TF regulatory circuit that regulate LNM in PTC. Results. PTC patients with LNM (PTC LNM-P) have a significantly shorter disease-free survival rate compared to PTC patients without LNM (PTC LNN) (Log-rank Mantel Cox test, p = 0.0049). We identified 181 significantly differentially expressed miRNAs in PTC LNM-P versus PTC LNN; 110 were upregulated and 71 were downregulated. The five topmost deregulated miRNAs were hsa-miR-146b, hsa-miR-375, hsa-miR-31, hsa-miR-7-2 and hsa-miR-204. In addition, 395 miRNAs were differentially expressed between PTC LNM-P and normal thyroid while 400 miRNAs were differentially expressed between PTC LNN and normal thyroid. We found four significant enrichment pathways potentially involved in metastasis to the lymph nodes, namely oxidative phosphorylation (OxPhos), cell adhesion molecules (CAMs), leukocyte transendothelial migration and cytokine-cytokine receptor interaction. OxPhos was the most significantly perturbed pathway (p = 4.70E-06) involving downregulation of 90

  16. Expression profiling of selected microRNA signatures in plasma and tissues of Saudi colorectal cancer patients by qPCR

    PubMed Central

    AL-SHEIKH, YAZEED A.; GHNEIM, HAZEM K.; SOFTA, KHALIL I.; AL-JOBRAN, ABDULRAHMAN A.; AL-OBEED, OMAR; MOHAMED, MANSOOR A.V.; ABDULLA, MAHA; ABOUL-SOUD, MOURAD A.M.

    2016-01-01

    MicroRNAs (miRNAs or miRs) have been advocated as potentially robust and highly stable biomarkers of diverse disease conditions including cancer. The primary aim of this study was two-fold: i) to profile the expression levels of selected mature miRNA signature genes, such as miR-145, miR-195, miR-29 and miR-92, in a paired-study design of 20 colorectal cancer (CRC) tissues from patients versus adjacent neoplasm-free mucosal tissues employing reverse transcription-quantitative polymerase chain reaction; and ii) to examine their expression level in the plasma of the same CRC patients in relation to the age-matched plasma of healthy controls. Statistically significant (P<0.01) increases in miR-29 (2.5) and miR-92 (2.6) were observed in CRC tissues compared with adjacent neoplasm-free mucosal tissues. Profiling of CRC plasma samples showed that the expression levels of circulating miR-29 and miR-92 were significantly higher (P<0.01) than in the age-matched normal plasma. By contrast, miR-145 and miR-195 exhibited significant (P<0.05) decreases in their mean expression levels in CRC tissue samples in relation to the normal tissues. The mean expression levels of miR-145 and miR-195 were significantly lower (P<0.05) in CRC plasma than the healthy controls. Distinct stage-dependent changes in the expression level of the four miRNA gene profiles were observed between stages II and IV plasma of CRC patients relative to the control plasma. Taken together, the results clearly reflect a similar trend for the four miRNA expression levels in tissue and plasma as well as the positive correlation in the levels of miRNAs in tissues and plasma. These findings may be useful to clarify the molecular mechanisms underlying colorectal carcinogenesis and to underscore the potential of the investigated miRNAs as novel early diagnostic biomarkers of CRC. PMID:26893751

  17. Attention to Faces Expressing Negative Emotion at 7 Months Predicts Attachment Security at 14 Months.

    PubMed

    Peltola, Mikko J; Forssman, Linda; Puura, Kaija; van IJzendoorn, Marinus H; Leppänen, Jukka M

    2015-01-01

    To investigate potential infant-related antecedents characterizing later attachment security, this study tested whether attention to facial expressions, assessed with an eye-tracking paradigm at 7 months of age (N = 73), predicted infant-mother attachment in the Strange Situation Procedure at 14 months. Attention to fearful faces at 7 months predicted attachment security, with a smaller attentional bias to fearful expressions associated with insecure attachment. Attachment disorganization in particular was linked to an absence of the age-typical attentional bias to fear. These data provide the first evidence linking infants' attentional bias to negative facial expressions with attachment formation and suggest reduced sensitivity to facial expressions of negative emotion as a testable trait that could link attachment disorganization with later behavioral outcomes. PMID:26011101

  18. A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons

    PubMed Central

    Tian, Tian; Salis, Howard M.

    2015-01-01

    Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. PMID:26117546

  19. Gene expression signature-based approach identifies a pro-resolving mechanism of action for histone deacetylase inhibitors

    PubMed Central

    Montero-Melendez, T; Dalli, J; Perretti, M

    2013-01-01

    Despite several therapies being currently available to treat inflammatory diseases, new drugs to treat chronic conditions with less side effects and lower production costs are still needed. An innovative approach to drug discovery, the Connectivity Map (CMap), shows how integrating genome-wide gene expression data of drugs and diseases can accelerate this process. Comparison of genome-wide gene expression data generated with annexin A1 (AnxA1) with the CMap revealed significant alignment with gene profiles elicited by histone deacetylase inhibitors (HDACIs), what made us to hypothesize that AnxA1 might mediate the anti-inflammatory actions of HDACIs. Addition of HDACIs (valproic acid, sodium butyrate and thricostatin A) to mouse macrophages caused externalization of AnxA1 with concomitant inhibition of cytokine gene expression and release, events that occurred independently as this inhibition was retained in AnxA1 null macrophages. In contrast, novel AnxA1-mediated functions for HDACIs could be unveiled, including promotion of neutrophil apoptosis and macrophage phagocytosis, both steps crucial for effective resolution of inflammation. In a model of acute resolving inflammation, administration of valproic acid and sodium butyrate to mice at the peak of disease accelerated resolution processes in wild type, but much more modestly in AnxA1 null mice. Deeper analyses revealed a role for endogenous AnxA1 in the induction of neutrophil death in vivo by HDACIs. In summary, interrogation of the CMap revealed an unexpected association between HDACIs and AnxA1 that translated in mechanistic findings with particular impact on the processes that regulate the resolution of inflammation. We propose non-genomic modulation of AnxA1 in immune cells as a novel mechanism of action for HDACIs, which may underlie their reported efficacy in models of chronic inflammatory pathologies. PMID:23222458

  20. Avian Resistance to Campylobacter jejuni Colonization Is Associated with an Intestinal Immunogene Expression Signature Identified by mRNA Sequencing

    PubMed Central

    Connell, Sarah; Meade, Kieran G.; Allan, Brenda; Lloyd, Andrew T.; Kenny, Elaine; Cormican, Paul; Morris, Derek W.; Bradley, Daniel G.; O'Farrelly, Cliona

    2012-01-01

    Campylobacter jejuni is the most common cause of human bacterial gastroenteritis and is associated with several post-infectious manifestations, including onset of the autoimmune neuropathy Guillain-Barré syndrome, causing significant morbidity and mortality. Poorly-cooked chicken meat is the most frequent source of infection as C. jejuni colonizes the avian intestine in a commensal relationship. However, not all chickens are equally colonized and resistance seems to be genetically determined. We hypothesize that differences in immune response may contribute to variation in colonization levels between susceptible and resistant birds. Using high-throughput sequencing in an avian infection model, we investigate gene expression associated with resistance or susceptibility to colonization of the gastrointestinal tract with C. jejuni and find that gut related immune mechanisms are critical for regulating colonization. Amongst a single population of 300 4-week old chickens, there was clear segregation in levels of C. jejuni colonization 48 hours post-exposure. RNAseq analysis of caecal tissue from 14 C. jejuni-susceptible and 14 C. jejuni-resistant birds generated over 363 million short mRNA sequences which were investigated to identify 219 differentially expressed genes. Significantly higher expression of genes involved in the innate immune response, cytokine signaling, B cell and T cell activation and immunoglobulin production, as well as the renin-angiotensin system was observed in resistant birds, suggesting an early active immune response to C. jejuni. Lower expression of these genes in colonized birds suggests suppression or inhibition of a clearing immune response thus facilitating commensal colonization and generating vectors for zoonotic transmission. This study describes biological processes regulating C. jejuni colonization of the avian intestine and gives insight into the differential immune mechanisms incited in response to commensal bacteria in general

  1. 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

  2. Gene expression signatures in CD34+-progenitor-derived dendritic cells exposed to the chemical contact allergen nickel sulfate

    SciTech Connect

    Schoeters, Elke . E-mail: elke.schoeters@vito.be; Nuijten, Jean-Marie; Heuvel, Rosette L. van den; Nelissen, Inge; Witters, Hilda; Schoeters, Greet E.R.; Tendeloo, Vigor F.I. van; Berneman, Zwi N.; Verheyen, Geert R.

    2006-10-01

    The detection of the sensitizing potential of chemicals is of great importance to industry. A promising in vitro alternative to the currently applied animal assays for sensitization testing makes use of dendritic cells (DCs) that have the capability to process and present antigens to naive T cells and induce their proliferation. Here, we studied changes in gene expression profiles after exposing DCs to the contact allergen nickel sulfate. CD34+-progenitor-derived DCs, initiated from 3 different donors, were exposed to 60 {mu}M nickel sulfate, during 0.5, 1, 3, 6, 12 and 24 h. cDNA microarrays were used to assess the transcriptional activity of about 11,000 genes. Significant changes in the expression of 283 genes were observed; 178 genes were up-regulated and 93 down-regulated. These genes were involved in metabolism, cell structure, immune response, transcription, signal transduction, transport, and apoptosis. No functional information was found for 74 genes. Real-time RT-PCR was used to confirm the microarray results of 12 genes. In addition, 3 DC maturation markers not present on the microarrays (DEC205, DC LAMP and CCR7) were analyzed using real-time RT-PCR and found to be up-regulated at several time points. Our data indicate that a broad range of biological processes is influenced by nickel. Some processes are clearly linked to the immune response and DC maturation, others may indicate a toxic effect of nickel.

  3. Low Expression of Mir-137 Predicts Poor Prognosis in Cutaneous Melanoma Patients

    PubMed Central

    Li, Nan

    2016-01-01

    Background The present study aimed to measure miR-137 expression in patients with cutaneous melanoma (CM) and to estimate the correlation of miR-137 expression and the prognosis of CM patients. Material/Methods The expression level of miR-137 was assayed by quantitative real-time PCR (qRT-PCR) and presented as mean ±SD. Chi-square was used to evaluate the relationship between miR-137 expression and clinical characteristics. We used a Kaplan-Meier survival curve to determine the overall survival rate of CM patients. Moreover, the correlation between miR-137 expression and the prognosis of CM patients was confirmed by Cox regression analysis. Results The relative expression of miR-137 in CM tissue was 1.59±0.43, while that in paired normal tissue was 2.41±0.54, which was significantly higher. Chi-square analysis showed statistical significance between miR-137 expression and clinical characteristics such as TNM stage, ulcer, and occurrence site (P<0.05). However, no association was found between miR-137 expression and age, sex, or family history (P>0.05). According to the survival curve outcome, patients with low miR-137 expression showed relatively higher mortality (P=0.000) and multivariate analysis verified that low expression of miR-137 predicted poor prognosis of CM patients (HR=8.531, 95% CI=2.950–24.668, P=0.000). C