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Sample records for expression signatures predict

  1. Predicting cellular growth from gene expression signatures.

    PubMed

    Airoldi, Edoardo M; Huttenhower, Curtis; Gresham, David; Lu, Charles; Caudy, Amy A; Dunham, Maitreya J; Broach, James R; Botstein, David; Troyanskaya, Olga G

    2009-01-01

    Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

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

    EPA Science Inventory

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

  3. 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

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

    EPA Science Inventory

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

  5. Towards Mechanism Classifiers: Expression-anchored Gene Ontology Signature Predicts Clinical Outcome in Lung Adenocarcinoma Patients

    PubMed Central

    Yang, Xinan; Li, Haiquan; Regan, Kelly; Li, Jianrong; Huang, Yong; Lussier, Yves A.

    2012-01-01

    We aim to provide clinically applicable, reproducible, mechanistic interpretations of gene expression changes that lack in gene overlap among predictive gene-signatures. Using a method we recently developed, Functional Analysis of Individual Microarray Expression (FAIME), we provide evidence that Gene Ontology-anchored signatures (GO-signatures) show reliable prognosis in lung cancer. In order to demonstrate the biological congruence and reproducibility of FAIME-derived mechanism classifiers, we chose a disease where gene expression classifiers signatures alone had failed to significantly stratify a larger collection of samples and that exhibited poor or no genetic overlap. For each patient in the two lung adenocarcinoma studies, personalized FAIME-profiles of GO biological processes are generated from genome-wide expression profiles. For both training studies, GO-signatures significantly associated to patient mortality were identified (Prediction Analysis for Microarrays; three-fold cross-validation). These two GO-signatures could effectively stratify patients from an independent validation cohort into sub-groups that show significant differences in disease-free survival (log-rank test P=0.019; P=0.001). Importantly, significant mechanism overlaps assessed by information-theory similarity were detected between the two GO-signatures (Fischer Exact Test p=0.001). Hence, together with machine learning technologies, FAIME could be utilized to develop an ontology-driven and expression-anchored prognostic signature that is personalized for an individual patient. PMID:23304380

  6. 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

  7. Renal Gene and Protein Expression Signatures for Prediction of Kidney Disease Progression

    PubMed Central

    Ju, Wenjun; Eichinger, Felix; Bitzer, Markus; Oh, Jun; McWeeney, Shannon; Berthier, Celine C.; Shedden, Kerby; Cohen, Clemens D.; Henger, Anna; Krick, Stefanie; Kopp, Jeffrey B.; Stoeckert, Christian J.; Dikman, Steven; Schröppel, Bernd; Thomas, David B.; Schlondorff, Detlef; Kretzler, Matthias; Böttinger, Erwin P.

    2009-01-01

    Although chronic kidney disease (CKD) is common, only a fraction of CKD patients progress to end-stage renal disease. Molecular predictors to stratify CKD populations according to their risk of progression remain undiscovered. Here we applied transcriptional profiling of kidneys from transforming growth factor-β1 transgenic (Tg) mice, characterized by heterogeneity of kidney disease progression, to identify 43 genes that discriminate kidneys by severity of glomerular apoptosis before the onset of tubulointerstitial fibrosis in 2-week-old animals. Among the genes examined, 19 showed significant correlation between mRNA expression in uninephrectomized left kidneys at 2 weeks of age and renal disease severity in right kidneys of Tg mice at 4 weeks of age. Gene expression profiles of human orthologs of the 43 genes in kidney biopsies were highly significantly related (R2 = 0.53; P < 0.001) to the estimated glomerular filtration rates in patients with CKD stages I to V, and discriminated groups of CKD stages I/II and III/IV/V with positive and negative predictive values of 0.8 and 0.83, respectively. Protein expression patterns for selected genes were successfully validated by immunohistochemistry in kidneys of Tg mice and kidney biopsies of patients with IgA nephropathy and CKD stages I to V, respectively. In conclusion, we developed novel mRNA and protein expression signatures that predict progressive renal fibrosis in mice and may be useful molecular predictors of CKD progression in humans. PMID:19465643

  8. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival.

    PubMed

    Miller, Lance D; Smeds, Johanna; George, Joshy; Vega, Vinsensius B; Vergara, Liza; Ploner, Alexander; Pawitan, Yudi; Hall, Per; Klaar, Sigrid; Liu, Edison T; Bergh, Jonas

    2005-09-20

    Perturbations of the p53 pathway are associated with more aggressive and therapeutically refractory tumors. However, molecular assessment of p53 status, by using sequence analysis and immunohistochemistry, are incomplete assessors of p53 functional effects. We posited that the transcriptional fingerprint is a more definitive downstream indicator of p53 function. Herein, we analyzed transcript profiles of 251 p53-sequenced primary breast tumors and identified a clinically embedded 32-gene expression signature that distinguishes p53-mutant and wild-type tumors of different histologies and outperforms sequence-based assessments of p53 in predicting prognosis and therapeutic response. Moreover, the p53 signature identified a subset of aggressive tumors absent of sequence mutations in p53 yet exhibiting expression characteristics consistent with p53 deficiency because of attenuated p53 transcript levels. Our results show the primary importance of p53 functional status in predicting clinical breast cancer behavior. PMID:16141321

  9. Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

    PubMed Central

    Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

    2012-01-01

    About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

  10. Prediction of In Vivo Radiation Dose Status in Radiotherapy Patients using Ex Vivo and In Vivo Gene Expression Signatures

    PubMed Central

    Paul, Sunirmal; Barker, Christopher A.; Turner, Helen C.; McLane, Amanda; Wolden, Suzanne L.; Amundson, Sally A.

    2011-01-01

    After a large-scale nuclear accident or an attack with an improvised nuclear device, rapid biodosimetry would be needed for triage. As a possible means to address this need, we previously defined a gene expression signature in human peripheral white blood cells irradiated ex vivo that predicts the level of radiation exposure with high accuracy. We now demonstrate this principle in vivo using blood from patients receiving total-body irradiation (TBI). Whole genome microarray analysis has identified genes responding significantly to in vivo radiation exposure in peripheral blood. A 3-nearest neighbor classifier built from the TBI patient data correctly predicted samples as exposed to 0, 1.25 or 3.75 Gy with 94% accuracy (P < 0.001) even when samples from healthy donor controls were included. The same samples were classified with 98% accuracy using a signature previously defined from ex vivo irradiation data. The samples could also be classified as exposed or not exposed with 100% accuracy. The demonstration that ex vivo irradiation is an appropriate model that can provide meaningful prediction of in vivo exposure levels, and that the signatures are robust across diverse disease states and independent sample sets, is an important advance in the application of gene expression for biodosimetry. PMID:21388269

  11. An expression based REST signature predicts patient survival and therapeutic response for glioblastoma multiforme

    PubMed Central

    Liang, Jianfeng; Meng, Qinghua; Zhao, Wanni; Tong, Pan; Li, Ping; Zhao, Yuanli; Zhao, Xiaodong; Li, Hua

    2016-01-01

    Proper regulation of neuronal gene expression is crucial for the development and differentiation of the central nervous system. The transcriptional repressor REST (repressor element-1 silencing transcription factor) is a key regulator in differentiation of pluripotent stem cells to neuronal progenitors and mature neurons. Dysregulated REST activity has been implicated in various diseases, among which the most deadly is glioblastoma multiforme (GBM). Here we have developed an expression-based REST signature (EXPREST), a device providing quantitative measurements of REST activity for GBM tumors. EXPREST robustly quantifies REST activity (REST score) using gene expression profiles in absence of clinic-pathologic assessments of REST. Molecular characterization of REST activity identified global alterations at the DNA, RNA, protein and microRNA levels, suggesting a widespread role of REST in GBM tumorigenesis. Although originally aimed to capture REST activity, REST score was found to be a prognostic factor for overall survival. Further, cell lines with enhanced REST activity was found to be more sensitive to IGF1R, VEGFR and ABL inhibitors. In contrast, cell lines with low REST score were more sensitive to cytotoxic drugs including Mitomycin, Camptothecin and Cisplatin. Together, our work suggests that therapeutic targeting of REST provides a promising opportunity for GBM treatment. PMID:27698411

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. MicroRNA expression signatures for the prediction of BRCA1/2 mutation-associated hereditary breast cancer in paraffin-embedded formalin-fixed breast tumors.

    PubMed

    Tanic, Miljana; Yanowski, Kira; Gómez-López, Gonzalo; Rodriguez-Pinilla, María Socorro; Marquez-Rodas, Iván; Osorio, Ana; Pisano, David G; Martinez-Delgado, Beatriz; Benítez, Javier

    2015-02-01

    Screening for germline mutations in breast cancer-associated genes BRCA1 and BRCA2 is indicated for patients with breast cancer from high-risk breast cancer families and influences both treatment options and clinical management. However, only 25% of selected patients test positive for BRCA1/2 mutation, indicating that additional diagnostic biomarkers are necessary. We analyzed 124 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients with hereditary (104) and sporadic (20) invasive breast cancer, divided into two series (A and B). Microarray expression profiling of 829 human miRNAs was performed on 76 samples (Series A), and bioinformatics tool Prophet was used to develop and test a microarray classifier. Samples were stratified into a training set (n = 38) for microarray classifier generation and a test set (n = 38) for signature validation. A 35-miRNA microarray classifier was generated for the prediction of BRCA1/2 mutation status with a reported 95% (95% CI = 0.88-1.0) and 92% (95% CI: 0.84-1.0) accuracy in the training and the test set, respectively. Differential expression of 12 miRNAs between BRCA1/2 mutation carriers versus noncarriers was validated by qPCR in an independent tumor series B (n = 48). Logistic regression model based on the expression of six miRNAs (miR-142-3p, miR-505*, miR-1248, miR-181a-2*, miR-25* and miR-340*) discriminated between tumors from BRCA1/2 mutation carriers and noncarriers with 92% (95% CI: 0.84-0.99) accuracy. In conclusion, we identified miRNA expression signatures predictive of BRCA1/2 mutation status in routinely available FFPE breast tumor samples, which may be useful to complement current patient selection criteria for gene testing by identifying individuals with high likelihood of being BRCA1/2 mutation carriers.

  19. 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

  20. The gene expression signatures of melanoma progression

    PubMed Central

    Haqq, Christopher; Nosrati, Mehdi; Sudilovsky, Daniel; Crothers, Julia; Khodabakhsh, Daniel; Pulliam, Brian L.; Federman, Scot; Miller, James R.; Allen, Robert E.; Singer, Mark I.; Leong, Stanley P. L.; Ljung, Britt-Marie; Sagebiel, Richard W.; Kashani-Sabet, Mohammed

    2005-01-01

    Because of the paucity of available tissue, little information has previously been available regarding the gene expression profiles of primary melanomas. To understand the molecular basis of melanoma progression, we compared the gene expression profiles of a series of nevi, primary melanomas, and melanoma metastases. We found that metastatic melanomas exhibit two dichotomous patterns of gene expression, which unexpectedly reflect gene expression differences already apparent in comparing laser-capture microdissected radial and vertical phases of a large primary melanoma. Unsupervised hierarchical clustering accurately separated nevi and primary melanomas. Multiclass significance analysis of microarrays comparing normal skin, nevi, primary melanomas, and the two types of metastatic melanoma identified 2,602 transcripts that significantly correlated with sample class. These results suggest that melanoma pathogenesis can be understood as a series of distinct molecular events. The gene expression signatures identified here provide the basis for developing new diagnostics and targeting therapies for patients with malignant melanoma. PMID:15833814

  1. 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

  2. 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

  3. A prognostic gene expression signature in infratentorial ependymoma.

    PubMed

    Wani, Khalida; Armstrong, Terri S; 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 R; Aldape, Ken

    2012-05-01

    Patients with ependymoma exhibit a wide range of clinical outcomes that are currently unexplained by clinical or histological factors. Little is known regarding molecular biomarkers that could predict clinical behavior. Since recent data suggest 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.

  4. Reactive oxygen species-associated molecular signature predicts survival in patients with sepsis.

    PubMed

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

    2016-06-01

    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

  5. 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.

  6. 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

  7. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    PubMed

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W K Alfred; Weinstein, John N

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  8. Identification of Common Prognostic Gene Expression Signatures with Biological Meanings from Microarray Gene Expression Datasets

    PubMed Central

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W. K. Alfred; Weinstein, John N.

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures. PMID:23029298

  9. 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

  10. 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

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. Evaluation of frozen tissue-derived prognostic gene expression signatures in FFPE colorectal cancer samples

    PubMed Central

    Zhu, Jing; Deane, Natasha G.; Lewis, Keeli B.; Padmanabhan, Chandrasekhar; Washington, M. Kay; Ciombor, Kristen K.; Timmers, Cynthia; Goldberg, Richard M.; Beauchamp, R. Daniel; Chen, Xi

    2016-01-01

    Defining molecular features that can predict the recurrence of colorectal cancer (CRC) for stage II-III patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed, Paraffin-Embedded (FFPE). NanoString nCounter® and Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) are the two platforms marketed for high-throughput gene expression profiling for FFPE samples. In this study, to evaluate the gene expression of frozen tissue-derived prognostic signatures in FFPE CRC samples, we evaluated the expression of 516 genes from published frozen tissue-derived prognostic signatures in 42 FFPE CRC samples measured by both platforms. Based on HTA platform-derived data, we identified both gene (99 individual genes, FDR < 0.05) and gene set (four of the six reported multi-gene signatures with sufficient information for evaluation, P < 0.05) expression differences associated with survival outcomes. Using nCounter platform-derived data, one of the six multi-gene signatures (P < 0.05) but no individual gene was associated with survival outcomes. Our study indicated that sufficiently high quality RNA could be obtained from FFPE tumor tissues to detect frozen tissue-derived prognostic gene expression signatures for CRC patients. PMID:27623752

  16. Evaluation of frozen tissue-derived prognostic gene expression signatures in FFPE colorectal cancer samples.

    PubMed

    Zhu, Jing; Deane, Natasha G; Lewis, Keeli B; Padmanabhan, Chandrasekhar; Washington, M Kay; Ciombor, Kristen K; Timmers, Cynthia; Goldberg, Richard M; Beauchamp, R Daniel; Chen, Xi

    2016-01-01

    Defining molecular features that can predict the recurrence of colorectal cancer (CRC) for stage II-III patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed, Paraffin-Embedded (FFPE). NanoString nCounter® and Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) are the two platforms marketed for high-throughput gene expression profiling for FFPE samples. In this study, to evaluate the gene expression of frozen tissue-derived prognostic signatures in FFPE CRC samples, we evaluated the expression of 516 genes from published frozen tissue-derived prognostic signatures in 42 FFPE CRC samples measured by both platforms. Based on HTA platform-derived data, we identified both gene (99 individual genes, FDR < 0.05) and gene set (four of the six reported multi-gene signatures with sufficient information for evaluation, P < 0.05) expression differences associated with survival outcomes. Using nCounter platform-derived data, one of the six multi-gene signatures (P < 0.05) but no individual gene was associated with survival outcomes. Our study indicated that sufficiently high quality RNA could be obtained from FFPE tumor tissues to detect frozen tissue-derived prognostic gene expression signatures for CRC patients. PMID:27623752

  17. Classification of Benign and Malignant Thyroid Nodules Using a Combined Clinical Information and Gene Expression Signatures

    PubMed Central

    Gu, Jianlei; Du, Jing; Wang, Lin; Gu, Shengli; Cheng, Juan; Yang, Jun; Lu, Hui

    2016-01-01

    Background A key challenge in thyroid carcinoma is preoperatively diagnosing malignant thyroid nodules. A novel diagnostic test that measures the expression of a 3-gene signature (DPP4, SCG5 and CA12) has demonstrated promise in thyroid carcinoma assessment. However, more reliable prediction methods combining clinical features with genomic signatures with high accuracy, good stability and low cost are needed. Methodology/Principal Findings 25 clinical information were recorded in 771 patients. Feature selection and validation were conducted using random forest. Thyroid samples and clinical data were obtained from 142 patients at two different hospitals, and expression of the 3-gene signature was measured using quantitative PCR. The predictive abilities of three models (based on the selected clinical variables, the gene expression profile, and integrated gene expression and clinical information) were compared. Seven clinical characteristics were selected based on a training set (539 patients) and tested in three test sets, yielding predictive accuracies of 82.3% (n = 232), 81.4% (n = 70), and 81.9% (n = 72). The predictive sensitivity, specificity, and accuracy were 72.3%, 80.5% and 76.8% for the model based on the gene expression signature, 66.2%, 81.8% and 74.6% for the model based on the clinical data, and 83.1%, 84.4% and 83.8% for the combined model in a 10-fold cross-validation (n = 142). Conclusions These findings reveal that the integrated model, which combines clinical data with the 3-gene signature, is superior to models based on gene expression or clinical data alone. The integrated model appears to be a reliable tool for the preoperative diagnosis of thyroid tumors. PMID:27776138

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. A Six-Gene Signature Predicts Survival of Patients with Localized Pancreatic Ductal Adenocarcinoma

    PubMed Central

    Stratford, Jeran K.; Bentrem, David J.; Anderson, Judy M.; Fan, Cheng; Volmar, Keith A.; Marron, J. S.; Routh, Elizabeth D.; Caskey, Laura S.; Samuel, Jonathan C.; Der, Channing J.; Thorne, Leigh B.; Calvo, Benjamin F.; Kim, Hong Jin; Talamonti, Mark S.; Iacobuzio-Donahue, Christine A.; Hollingsworth, Michael A.; Perou, Charles M.; Yeh, Jen Jen

    2010-01-01

    Background Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease. For patients with localized PDAC, surgery is the best option, but with a median survival of less than 2 years and a difficult and prolonged postoperative course for most, there is an urgent need to better identify patients who have the most aggressive disease. Methods and Findings We analyzed the gene expression profiles of primary tumors from patients with localized compared to metastatic disease and identified a six-gene signature associated with metastatic disease. We evaluated the prognostic potential of this signature in a training set of 34 patients with localized and resected PDAC and selected a cut-point associated with outcome using X-tile. We then applied this cut-point to an independent test set of 67 patients with localized and resected PDAC and found that our signature was independently predictive of survival and superior to established clinical prognostic factors such as grade, tumor size, and nodal status, with a hazard ratio of 4.1 (95% confidence interval [CI] 1.7–10.0). Patients defined to be high-risk patients by the six-gene signature had a 1-year survival rate of 55% compared to 91% in the low-risk group. Conclusions Our six-gene signature may be used to better stage PDAC patients and assist in the difficult treatment decisions of surgery and to select patients whose tumor biology may benefit most from neoadjuvant therapy. The use of this six-gene signature should be investigated in prospective patient cohorts, and if confirmed, in future PDAC clinical trials, its potential as a biomarker should be investigated. Genes in this signature, or the pathways that they fall into, may represent new therapeutic targets. Please see later in the article for the Editors' Summary PMID:20644708

  4. Signature Product Code for Predicting Protein-Protein Interactions

    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

  5. 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.

  6. 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

  7. Integrative analysis of lung development-cancer expression associations reveals the roles of signatures with inverse expression patterns.

    PubMed

    Zhang, Chunlong; Li, Chunquan; Xu, Yanjun; Feng, Li; Shang, Desi; Yang, Xinmiao; Han, Junwei; Sun, Zeguo; Li, Yixue; Li, Xia

    2015-05-01

    Recent studies have focused on exploring the associations between organ development and malignant tumors; however, the clinical relevance of the development signatures was inadequately addressed in lung cancer. In this study, we explored the associations between lung development and lung cancer progression by analyzing a total of two development and seven cancer datasets. We identified representative expression patterns (continuously up- and down-regulated) from development and cancer profiles, and inverse pattern associations were observed at both the gene and functional levels. Furthermore, we dissected the biological processes dominating the associations, and found that proliferation and immunity were respectively involved in the two inverse development-cancer expression patterns. Through sub-pathway analysis of the signatures with inverse expression patterns, we finally identified a 13-gene risk signature from the cell cycle sub-pathway, and evaluated its predictive performance for lung cancer patient clinical outcome using independent cohorts. Our findings indicated that the integrative analysis of development and cancer expression patterns provided a framework for identifying effective molecular signatures for clinical utility.

  8. 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

  9. Irma 5.2 multi-sensor signature prediction model

    NASA Astrophysics Data System (ADS)

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

    2007-04-01

    The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the validation test results of the Irma passive models and discuss the new features in Irma 5.2.

  10. Irma 5.2 multi-sensor signature prediction model

    NASA Astrophysics Data System (ADS)

    Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Pau, John

    2008-04-01

    The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/RW) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after extensive verification and validation of an upgraded and reengineered ladar channel. The reengineering effort then shifted focus to the Irma passive channel. Field measurements for the validation effort include both polarized and unpolarized data collection. Irma 5.2 was released in 2007 with a reengineered passive channel. This paper summarizes the capabilities of Irma and the progress toward Irma 5.3, which includes a reengineered radar channel.

  11. Ion channel gene expression predicts survival in glioma patients.

    PubMed

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

    2015-08-03

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

  12. 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

  13. Relapse-related long non-coding RNA signature to improve prognosis prediction of lung adenocarcinoma

    PubMed Central

    Zhao, Hengqiang; Wang, Zhenzhen; Shi, Hongbo; Cheng, Liang; Sun, Jie

    2016-01-01

    Increasing evidence has highlighted the important roles of dysregulated long non-coding RNA (lncRNA) expression in tumorigenesis, tumor progression and metastasis. However, lncRNA expression patterns and their prognostic value for tumor relapse in lung adenocarcinoma (LUAD) patients have not been systematically elucidated. In this study, we evaluated lncRNA expression profiles by repurposing the publicly available microarray expression profiles from a large cohort of LUAD patients and identified specific lncRNA signature closely associated with tumor relapse in LUAD from significantly altered lncRNAs using the weighted voting algorithm and cross-validation strategy, which was able to discriminate between relapsed and non-relapsed LUAD patients with sensitivity of 90.9% and specificity of 81.8%. From the discovery dataset, we developed a risk score model represented by the nine relapse-related lncRNAs for prognosis prediction, which classified patients into high-risk and low-risk subgroups with significantly different recurrence-free survival (HR=45.728, 95% CI=6.241-335.1; p=1.69e-04). The prognostic value of this relapse-related lncRNA signature was confirmed in the testing dataset and other two independent datasets. Multivariable Cox regression analysis and stratified analysis showed that the relapse-related lncRNA signature was independent of other clinical variables. Integrative in silico functional analysis suggested that these nine relapse-related lncRNAs revealed biological relevance to disease relapse, such as cell cycle, DNA repair and damage and cell death. Our study demonstrated that the relapse-related lncRNA signature may not only help to identify LUAD patients at high risk of relapse benefiting from adjuvant therapy but also could provide novel insights into the understanding of molecular mechanism of recurrent disease. PMID:27105492

  14. A novel gene expression signature for bone metastasis in breast carcinomas.

    PubMed

    Savci-Heijink, C Dilara; Halfwerk, Hans; Koster, Jan; van de Vijver, Marc J

    2016-04-01

    Metastatic cancer remains the leading cause of death for patients with breast cancer. To understand the mechanisms underlying the development of distant metastases to specific sites is therefore important and of potential clinical value. From 157 primary breast tumours of the patients with known metastatic disease, gene expression profiling data were generated and correlated to metastatic behaviour including site-specific metastasis, metastasis pattern and survival outcomes. We analysed gene expression signatures specifically associated with the development of bone metastases. As a validation cohort, we used a published dataset of 376 breast carcinomas for which gene expression data and site-specific metastasis information were available. 80.5 % of luminal-type tumours developed bone metastasis as opposed to 41.7 % of basal and 55.6 % of HER2-like tumours. A novel 15-gene signature identified 82.4 % of the tumours with bone metastasis, 85.2 % of the tumours which had bone metastasis as first site of metastasis and 100 % of the ones with bone metastasis only (p 9.99e-09), in the training set. In the independent dataset, 81.2 % of the positive tested tumours had known metastatic disease to the bone (p 4.28e-10). This 15-gene signature showed much better correlation with the development of bone metastases than previously identified signatures and was predictive in both ER-positive as well as in ER-negative tumours. Multivariate analyses revealed that together with the molecular subtype, our 15-gene expression signature was significantly correlated to bone metastasis status (p <0.001, 95 % CI 3.86-48.02 in the training set; p 0.001, 95 % CI 1.54-5.00 in the independent set). The 15 genes, APOPEC3B, ATL2, BBS1, C6orf61, C6orf167, MMS22L, KCNS1, MFAP3L, NIP7, NUP155, PALM2, PH-4, PGD5, SFT2D2 and STEAP3, encoded mainly membrane-bound molecules with molecular function of protein binding. The expression levels of the up-regulated genes (NAT1, BBS1 and PH-4) were

  15. 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

  16. 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

  17. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

    NASA Astrophysics Data System (ADS)

    Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M. R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D.; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'Ayan, Avi

    2016-09-01

    Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

  18. Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

    PubMed Central

    Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.; Fernandez, Nicolas F.; Gundersen, Gregory W.; Rouillard, Andrew D.; Jenkins, Sherry L.; Feldmann, Axel S.; Hu, Kevin S.; McDermott, Michael G.; Duan, Qiaonan; Clark, Neil R.; Jones, Matthew R.; Kou, Yan; Goff, Troy; Woodland, Holly; Amaral, Fabio M R.; Szeto, Gregory L.; Fuchs, Oliver; Schüssler-Fiorenza Rose, Sophia M.; Sharma, Shvetank; Schwartz, Uwe; Bausela, Xabier Bengoetxea; Szymkiewicz, Maciej; Maroulis, Vasileios; Salykin, Anton; Barra, Carolina M.; Kruth, Candice D.; Bongio, Nicholas J.; Mathur, Vaibhav; Todoric, Radmila D; Rubin, Udi E.; Malatras, Apostolos; Fulp, Carl T.; Galindo, John A.; Motiejunaite, Ruta; Jüschke, Christoph; Dishuck, Philip C.; Lahl, Katharina; Jafari, Mohieddin; Aibar, Sara; Zaravinos, Apostolos; Steenhuizen, Linda H.; Allison, Lindsey R.; Gamallo, Pablo; de Andres Segura, Fernando; Dae Devlin, Tyler; Pérez-García, Vicente; Ma'ayan, Avi

    2016-01-01

    Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization. PMID:27667448

  19. Human-associated microbial signatures: examining their predictive value.

    PubMed

    Knights, Dan; Parfrey, Laura Wegener; Zaneveld, Jesse; Lozupone, Catherine; Knight, Rob

    2011-10-20

    Host-associated microbial communities are unique to individuals, affect host health, and correlate with disease states. Although advanced technologies capture detailed snapshots of microbial communities, high within- and between-subject variation hampers discovery of microbial signatures in diagnostic or forensic settings. We suggest turning to machine learning and discuss key directions toward harnessing human-associated microbial signatures.

  20. Gene expression signatures of primary and metastatic uterine leiomyosarcoma

    PubMed Central

    Davidson, Ben; Abeler, Vera Maria; Førsund, Mette; Holth, Arild; Yang, Yanqin; Kobayashi, Yusuke; Chen, Lily; Kristensen, Gunnar B.; Shih, Ie-Ming; Wang, Tian-Li

    2013-01-01

    Leiomyosarcoma (LMS) is the most common uterine sarcoma. Although the disease is relatively rare, it is responsible for considerable mortality due to frequent metastasis and chemoresistance. The molecular events related to LMS metastasis are unknown to date. The present study compared the global gene expression patterns of primary uterine LMS and LMS metastases. Gene expression profiles of 13 primary and 15 metastatic uterine LMS were analyzed using the HumanRef-8 BeadChip from Illumina. Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry. To identify differently expressed genes between primary and metastatic tumors, we performed one-way ANOVA with Benjamini-Hochberg correction. This lead to identification of 203 unique probes that were significantly differentially expressed in the two tumor groups by greater than 1.58-fold with p-value <0.01%, of which 94 and 109 were overexpressed in primary and metastatic LMS, respectively. Genes overexpressed in primary uterine LMS included OSTN, NLGN4X, NLGN1, SLITRK4, MASP1, XRN2, ASS1, RORB, HRASLS and TSPAN7. Genes overexpressed in LMS metastases included TNNT1, FOLR3, TDO2, CRYM, GJA1, TSPAN10, THBS1, SGK1, SHMT1, EGR2 and AGT. Quantitative real-time PCR confirmed significant anatomic site-related differences in FOLR3, OSTN and NLGN4X levels, and immunohistochemistry showed significant differences in TDO2 expression. Gene expression profiling differentiates primary uterine LMS from LMS metastases. The molecular signatures unique to primary and metastatic LMS may aid in understanding tumor progression in this cancer and in providing a molecular basis for prognostic studies and therapeutic target discovery. PMID:24485798

  1. Gene Expression Signature in Adipose Tissue of Acromegaly Patients.

    PubMed

    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.

  2. 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

  3. 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

  4. 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

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

    NASA Astrophysics Data System (ADS)

    Almeida, S.; Le Vine, N.; McIntyre, N.; Wagener, T.; Buytaert, W.

    2015-06-01

    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 disinformative.

  6. 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.

  7. 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.

  8. 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

  9. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC.

  10. Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma.

    PubMed

    Zanaruddin, Sharifah Nurain Syed; Saleh, Amyza; Yang, Yi-Hsin; Hamid, Sharifah; Mustafa, Wan Mahadzir Wan; Khairul Bariah, A A N; Zain, Rosnah Binti; Lau, Shin Hin; Cheong, Sok Ching

    2013-03-01

    The presence of lymph node (LN) metastasis significantly affects the survival of patients with oral squamous cell carcinoma (OSCC). Successful detection and removal of positive LNs are crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the LNs, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis-positive LNs in the neck. We developed a molecular signature in the primary tumor that could predict LN metastasis in OSCC. A total of 211 cores from 55 individuals were included in the study. Eleven proteins were evaluated using immunohistochemical analysis in a tissue microarray. Of the 11 biomarkers evaluated using receiver operating curve analysis, epidermal growth factor receptor (EGFR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (HER-2/neu), laminin, gamma 2 (LAMC2), and ras homolog family member C (RHOC) were found to be significantly associated with the presence of LN metastasis. Unsupervised hierarchical clustering-demonstrated expression patterns of these 4 proteins could be used to differentiate specimens that have positive LN metastasis from those that are negative for LN metastasis. Collectively, EGFR, HER-2/neu, LAMC2, and RHOC have a specificity of 87.5% and a sensitivity of 70%, with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated that the LN signature could independently predict disease-specific survival (P = .036). The 4-protein LN signature validated in an independent set of samples strongly suggests that it could reliably distinguish patients with LN metastasis from those who were metastasis-free and therefore could be a prognostic tool for the management of patients with OSCC. PMID:23026198

  11. Comparative assessment of predictions in ungauged basins - Part 3: Runoff signatures in Austria

    NASA Astrophysics Data System (ADS)

    Viglione, A.; Parajka, J.; Rogger, M.; Salinas, J. L.; Laaha, G.; Sivapalan, M.; Blöschl, G.

    2013-01-01

    In a three-part paper we assess the performance of runoff predictions in ungauged basins in a comparative way. While Parajka et al. (2013) and Salinas et al. (2013) assess the regionalisation of hydrographs and hydrological extremes through a literature review, in this paper we assess prediction of a range of runoff signatures for a consistent dataset. Daily runoff time series are predicted for 213 catchments in Austria by a regionalised rainfall-runoff model and by Top-Kriging, a geostatistical interpolation method that accounts for the river network hierarchy. From the runoff timeseries, six runoff signatures are extracted: annual runoff, seasonal runoff, flow duration curves, low flows, high flows and runoff hydrograph. The predictive performance is assessed by the bias, error spread and proportion of unexplained spatial variance of statistical measures of these signatures in cross-validation mode. Results of the comparative assessment show that the geostatistical approach (Top-Kriging) generally outperforms the regionalised rainfall-runoff model. The predictive performance increases with catchment area for both methods and all signatures, while the dependence on climate characteristics is weaker. Annual and seasonal runoff can be predicted more accurately than all other signatures. The spatial variability of high flows is the most difficult to capture followed by the low flows. The relative predictive performance of the signatures depends on the selected performance measures. It is therefore essential to report performance in a consistent way by more than one performance measure.

  12. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

    PubMed

    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

  13. 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...

  14. Runoff signatures prediction in ungauged basins - a comparative assessment in Austria

    NASA Astrophysics Data System (ADS)

    Viglione, Alberto; Parajka, Juraj; Rogger, Magdalena; Salinas, Jose Luis; Laaha, Gregor; Sivapalan, Murugesu; Bloeschl, Guenter

    2013-04-01

    In this study we assess the prediction of a range of runoff signatures for a consistent dataset. Daily runoff time series are predicted for 213 catchments in Austria by a regionalised rainfall-runoff model and by Top-Kriging, a geostatistical interpolation method that accounts for the river network hierarchy. From the runoff timeseries, six runoff signatures are extracted: annual runoff, seasonal runoff, flow duration curves, low flows, high flows and runoff hydrograph. The predictive performance is assessed by the bias, error spread and proportion of unexplained spatial variance of statistical measures of these signatures in cross-validation mode. Results of the comparative assessment show that the geostatistical approach (Top-Kriging) generally outperforms the regionalised rainfall-runoff model. The predictive performance increases with catchment area for both methods and all signatures, while the dependence on climate characteristics is weaker. Annual and seasonal runoff can be predicted more accurately than all other signatures. The spatial variability of high flows is the most difficult to capture followed by the low flows. The relative predictive performance of the signatures depends on the selected performance measures. It is therefore essential to report performance in a consistent way by more than one performance measure.

  15. 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

  16. 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.

  17. Multiclass cancer diagnosis using tumor gene expression signatures

    DOE PAGES

    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

  18. 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.

  19. An Euler code prediction of near field to midfield sonic boom pressure signatures

    NASA Technical Reports Server (NTRS)

    Siclari, M. J.; Darden, C. M.

    1990-01-01

    A new approach is presented for computing sonic boom pressure signatures in the near field to midfield that utilizes a fully three-dimensional Euler finite volume code capable of analyzing complex geometries. Both linear and nonlinear sonic boom methodologies exist but for the most part rely primarily on equivalent area distributions for the prediction of far field pressure signatures. This is due to the absence of a flexible nonlinear methodology that can predict near field pressure signatures generated by three-dimensional aircraft geometries. It is the intention of the present study to present a nonlinear Euler method than can fill this gap and supply the needed near field signature data for many of the existing sonic boom codes.

  20. 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.

  1. Use of gene expression and pathway signatures to characterize the complexity of human melanoma.

    PubMed

    Freedman, Jennifer A; Tyler, Douglas S; Nevins, Joseph R; Augustine, Christina K

    2011-06-01

    A defining characteristic of most human cancers is heterogeneity, resulting from the somatic acquisition of a complex array of genetic and genomic alterations. Dissecting this heterogeneity is critical to developing an understanding of the underlying mechanisms of disease and to paving the way toward personalized treatments of the disease. We used gene expression data sets from the analysis of primary and metastatic melanomas to develop a molecular description of the heterogeneity that characterizes this disease. Unsupervised hierarchical clustering, gene set enrichment analyses, and pathway activity analyses were used to describe the genetic heterogeneity of melanomas. Patterns of gene expression that revealed two distinct classes of primary melanoma, two distinct classes of in-transit melanoma, and at least three subgroups of metastatic melanoma were identified. Expression signatures developed to predict the status of oncogenic signaling pathways were used to explore the biological basis underlying these differential patterns of expression. This analysis of activities revealed unique pathways that distinguished the primary and metastatic subgroups of melanoma. Distinct patterns of gene expression across primary, in-transit, and metastatic melanomas underline the genetic heterogeneity of this disease. This heterogeneity can be described in terms of deregulation of signaling pathways, thus increasing the knowledge of the biological features underlying individual melanomas and potentially directing therapeutic opportunities to individual patients with melanoma.

  2. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib

    PubMed Central

    Klammer, Martin; Dybowski, J. Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature — integrin β4 (ITGB4) — was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance. PMID:26083411

  3. Breast Cancer Biomarker Discovery in the Functional Genomic Age: A Systematic Review of 42 Gene Expression Signatures

    PubMed Central

    Abba, M.C; Lacunza, E; Butti, M; Aldaz, C.M

    2010-01-01

    In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules significantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identified meta-signature improves breast cancer patient stratification independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis. PMID:21082037

  4. Genomic signatures predict migration and spawning failure in wild Canadian salmon.

    PubMed

    Miller, Kristina M; Li, Shaorong; Kaukinen, Karia H; Ginther, Norma; Hammill, Edd; Curtis, Janelle M R; Patterson, David A; Sierocinski, Thomas; Donnison, Louise; Pavlidis, Paul; Hinch, Scott G; Hruska, Kimberly A; Cooke, Steven J; English, Karl K; Farrell, Anthony P

    2011-01-14

    Long-term population viability of Fraser River sockeye salmon (Oncorhynchus nerka) is threatened by unusually high levels of mortality as they swim to their spawning areas before they spawn. Functional genomic studies on biopsied gill tissue from tagged wild adults that were tracked through ocean and river environments revealed physiological profiles predictive of successful migration and spawning. We identified a common genomic profile that was correlated with survival in each study. In ocean-tagged fish, a mortality-related genomic signature was associated with a 13.5-fold greater chance of dying en route. In river-tagged fish, the same genomic signature was associated with a 50% increase in mortality before reaching the spawning grounds in one of three stocks tested. At the spawning grounds, the same signature was associated with 3.7-fold greater odds of dying without spawning. Functional analysis raises the possibility that the mortality-related signature reflects a viral infection.

  5. 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...

  6. 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

  7. Comparative assessment of predictions in ungauged basins - Part 3: Runoff signatures in Austria

    NASA Astrophysics Data System (ADS)

    Viglione, A.; Parajka, J.; Rogger, M.; Salinas, J. L.; Laaha, G.; Sivapalan, M.; Blöschl, G.

    2013-06-01

    This is the third of a three-part paper series through which we assess the performance of runoff predictions in ungauged basins in a comparative way. Whereas the two previous papers by Parajka et al. (2013) and Salinas et al. (2013) assess the regionalisation performance of hydrographs and hydrological extremes on the basis of a comprehensive literature review of thousands of case studies around the world, in this paper we jointly assess prediction performance of a range of runoff signatures for a consistent and rich dataset. Daily runoff time series are predicted for 213 catchments in Austria by a regionalised rainfall-runoff model and by Top-kriging, a geostatistical estimation method that accounts for the river network hierarchy. From the runoff time-series, six runoff signatures are extracted: annual runoff, seasonal runoff, flow duration curves, low flows, high flows and runoff hydrographs. The predictive performance is assessed in terms of the bias, error spread and proportion of unexplained spatial variance of statistical measures of these signatures in cross-validation (blind testing) mode. Results of the comparative assessment show that, in Austria, the predictive performance increases with catchment area for both methods and for most signatures, it tends to increase with elevation for the regionalised rainfall-runoff model, while the dependence on climate characteristics is weaker. Annual and seasonal runoff can be predicted more accurately than all other signatures. The spatial variability of high flows in ungauged basins is the most difficult to estimate followed by the low flows. It also turns out that in this data-rich study in Austria, the geostatistical approach (Top-kriging) generally outperforms the regionalised rainfall-runoff model.

  8. 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 ...

  9. 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.

  10. 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.

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

    PubMed

    Cui, Ang; Quon, Gerald; 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

  13. 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.

  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. 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

  16. 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

  17. Robust Prognostic Gene Expression Signatures in Bladder Cancer and Lung Adenocarcinoma Depend on Cell Cycle Related Genes

    PubMed Central

    Dancik, Garrett M.; Theodorescu, Dan

    2014-01-01

    Few prognostic biomarkers are approved for clinical use primarily because their initial performance cannot be repeated in independent datasets. We posited that robust biomarkers could be obtained by identifying deregulated biological processes shared among tumor types having a common etiology. We performed a gene set enrichment analysis in 20 publicly available gene expression datasets comprising 1968 patients having one of the three most common tobacco-related cancers (lung, bladder, head and neck) and identified cell cycle related genes as the most consistently prognostic class of biomarkers in bladder (BL) and lung adenocarcinoma (LUAD). We also found the prognostic value of 13 of 14 published BL and LUAD signatures were dependent on cell cycle related genes, supporting the importance of cell cycle related biomarkers for prognosis. Interestingly, no prognostic gene classes were identified in squamous cell lung carcinoma or head and neck squamous cell carcinoma. Next, a specific 31 gene cell cycle proliferation (CCP) signature, previously derived in prostate tumors was evaluated and found predictive of outcome in BL and LUAD cohorts in univariate and multivariate analyses. Specifically, CCP score significantly enhanced the predictive ability of multivariate models based on standard clinical variables for progression in BL patients and survival in LUAD patients in multiple cohorts. We then generated random CCP signatures of various sizes and found sets of 10–15 genes had robust performance in these BL and LUAD cohorts, a finding that was confirmed in an independent cohort. Our work characterizes the importance of cell cycle related genes in prognostic signatures for BL and LUAD patients and identifies a specific signature likely to survive additional validation. PMID:24465512

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Meta-analysis of age-related gene expression profiles identifies common signatures of aging

    PubMed Central

    de Magalhães, João Pedro; Curado, João; Church, George M.

    2009-01-01

    Motivation: Numerous microarray studies of aging have been conducted, yet given the noisy nature of gene expression changes with age, elucidating the transcriptional features of aging and how these relate to physiological, biochemical and pathological changes remains a critical problem. Results: We performed a meta-analysis of age-related gene expression profiles using 27 datasets from mice, rats and humans. Our results reveal several common signatures of aging, including 56 genes consistently overexpressed with age, the most significant of which was APOD, and 17 genes underexpressed with age. We characterized the biological processes associated with these signatures and found that age-related gene expression changes most notably involve an overexpression of inflammation and immune response genes and of genes associated with the lysosome. An underexpression of collagen genes and of genes associated with energy metabolism, particularly mitochondrial genes, as well as alterations in the expression of genes related to apoptosis, cell cycle and cellular senescence biomarkers, were also observed. By employing a new method that emphasizes sensitivity, our work further reveals previously unknown transcriptional changes with age in many genes, processes and functions. We suggest these molecular signatures reflect a combination of degenerative processes but also transcriptional responses to the process of aging. Overall, our results help to understand how transcriptional changes relate to the process of aging and could serve as targets for future studies. Availability: http://genomics.senescence.info/uarrays/signatures.html Contact: jp@senescence.info Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19189975

  3. 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

  4. 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

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

    PubMed

    Elbahesh, Husni; Schughart, Klaus

    2016-05-19

    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.

  6. Gene signatures of drug resistance predict patient survival in colorectal cancer

    PubMed Central

    Zheng, Y; Zhou, J; Tong, Y

    2015-01-01

    Different combinations of 5-fluorouracil (5-FU), oxaliplatin, irinotecan and other newly developed agents have been used to treat colorectal cancer. Despite the advent of new treatment regimens, the 5-year survival rate for metastatic colorectal cancer remains low (~10%). Knowing the drug sensitivity of a given tumor for a particular agent could significantly impact decision making and treatment planning. Biomarkers are proven to be successful in characterizing patients into different response groups. Using survival prediction analysis, we have identified three independent gene signatures, which are associated with sensitivity of colorectal cancer cells to 5-FU, oxaliplatin or irinotecan. On the basis of the three gene signatures, three score systems were developed to stratify patients from sensitive to resistance. These score systems exhibited robustness in stratify patients in two independent clinical studies. Patients with high scores in all three drugs exhibited the lowest survival. PMID:25179828

  7. Gene-expression signatures of Atlantic salmon’s plastic life cycle

    PubMed Central

    Aubin-Horth, Nadia; Letcher, Benjamin H.; Hofmann, Hans 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. PMID:19401203

  8. Effects Of Hydrothermal Alteration On Magnetic Properties And Magnetic Signatures - Implications For Predictive Magnetic Exploration Models

    NASA Astrophysics Data System (ADS)

    Clark, D.

    2012-12-01

    Magnetics is the most widely used geophysical method in hard rock exploration and magnetic surveys are an integral part of exploration programs for many types of mineral deposit, including porphyry Cu, intrusive-related gold, volcanic-hosted epithermal Au, IOCG, VMS, and Ni sulfide deposits. However, the magnetic signatures of ore deposits and their associated mineralized systems are extremely variable and exploration that is based simply on searching for signatures that resemble those of known deposits and systems is rarely successful. Predictive magnetic exploration models are based upon well-established geological models, combined with magnetic property measurements and geological information from well-studied deposits, and guided by magnetic petrological understanding of the processes that create, destroy and modify magnetic minerals in rocks. These models are designed to guide exploration by predicting magnetic signatures that are appropriate to specific geological settings, taking into account factors such as tectonic province; protolith composition; post-formation tilting/faulting/ burial/ exhumation and partial erosion; and metamorphism. Patterns of zoned hydrothermal alteration are important indicators of potentially mineralized systems and, if properly interpreted, can provided vectors to ore. Magnetic signatures associated with these patterns at a range of scales can provide valuable information on prospectivity and can guide drilling, provided they are correctly interpreted in geological terms. This presentation reviews effects of the important types of hydrothermal alteration on magnetic properties within mineralized systems, with particular reference to porphyry copper and IOCG deposits. For example, an unmodified gold-rich porphyry copper system, emplaced into mafic-intermediate volcanic host rocks (such as Bajo de la Alumbrera, Argentina) exhibits an inner potassic zone that is strongly mineralized and magnetite-rich, which is surrounded by an outer

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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

  14. Distinctive gene expression signatures in rheumatoid arthritis synovial tissue fibroblast cells: correlates with disease activity.

    PubMed

    Galligan, C L; Baig, E; Bykerk, V; Keystone, E C; Fish, E N

    2007-09-01

    Gene expression profiling of rheumatoid arthritis (RA) and osteoarthritis (OA) joint tissue samples provides a unique insight into the gene signatures involved in disease development and progression. Fibroblast-like synovial (FLS) cells were obtained from RA, OA and control trauma joint tissues (non-RA, non-OA) and RNA was analyzed by Affymetrix microarray. Thirty-four genes specific to RA and OA FLS cells were identified (P<0.05). HOXD10, HOXD11, HOXD13, CCL8 and LIM homeobox 2 were highly and exclusively expressed in RA and CLU, sarcoglycan-gamma, GPR64, POU3F3, peroxisome proliferative activated receptor-gamma and tripartite motif-containing 2 were expressed only in OA. The data also revealed expression heterogeneity for patients with the same disease. To address disease heterogeneity in RA FLS cells, we examined the effects of clinical disease parameters (Health Assessment Questionnaire (HAQ) score, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), rheumatoid factor (RF)) and drug therapies (methotrexate/prednisone) on RA FLS cell gene expression. Eight specific and unique correlations were identified: human leukocyte antigen (HLA)-DQA2 with HAQ score; Clec12A with RF; MAB21L2, SIAT7E, HAPLN1 and BAIAP2L1 with CRP level; RGMB and OSAP with ESR. Signature RA FLS cell gene expression profiles may provide insights into disease pathogenesis and have utility in diagnosis, prognosis and drug responsiveness. PMID:17568789

  15. 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

  16. Distinct microRNA expression signatures in human right atrial and ventricular myocardium.

    PubMed

    Zhang, Yangyang; Wang, Xiaowei; Xu, Xiaohan; Wang, Jun; Liu, Xiang; Chen, Yijiang

    2012-12-01

    Human atrial and ventricular myocardium has distinct structure and physiology. MicroRNAs (miRNAs) are the central players in the regulation of gene expression, participating in many physiological processes. A comprehensive knowledge of miRNA expression in the human heart is essential for the understanding of myocardial function. The aim of this study was to compare the miRNA signature in human right atrial and ventricular myocardium. Agilent human miRNA arrays were used to indicate the miRNA expression signatures of the right atrial (n = 8) and ventricular (n = 9) myocardium of healthy individuals. Quantitative reverse transcription-polymerase chain reactions (qRT-PCRs) were used to validate the array results. DIANA-mirPath was used to incorporate the miRNAs into pathways. MiRNA arrays showed that 169 miRNAs were expressed at different levels in human right atrial and ventricular myocardium. The unsupervised hierarchical clustering analysis based on the 169 dysregulated miRNAs showed that miRNA expression categorized two well-defined clusters that corresponded to human right atrial and ventricular myocardium. The qRT-PCR results correlated well with the microarray data. Bioinformatic analysis indicated the potential miRNA targets and molecular pathways. This study indicates that distinct miRNA expression signatures in human right atrial and ventricular myocardium. The findings provide a novel understanding of the molecular differences between human atrial and ventricular myocardium and may establish a framework for an anatomically detailed evaluation of cardiac function regulation.

  17. Predicted rotation signatures in MHD disc winds and comparison to DG Tau observations.

    NASA Astrophysics Data System (ADS)

    Pesenti, N.; Dougados, C.; Cabrit, S.; Ferreira, J.; Casse, F.; Garcia, P.; O'Brien, D.

    2004-03-01

    Motivated by the first detections of rotation signatures in the DG Tau jet (Bacciotti et al. \\cite{bacciotti2002}), we examine possible biases affecting the relation between detected rotation signatures and true azimuthal velocity for self-similar MHD disc winds, taking into account projection, convolution as well as excitation gradients effects. We find that computed velocity shifts are systematically smaller than the true underlying rotation curve. When outer slower streamlines dominate the emission, we predict observed shifts increasing with transverse distance to the jet axis, opposite to the true rotation profile. Determination of the full transverse rotation profile thus requires high angular resolution observations (<5 AU) on an object with dominant inner faster streamlines. Comparison of our predictions with HST/STIS observations of DG Tau clearly shows that self-similar, warm MHD disc wind models with λ = 13 and an outer radius of the disc ≃3 AU are able to reproduce detected velocity shifts, while cold disc wind models (λ > 50) are ruled out for the medium-velocity component in the DG Tau jet.

  18. 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

  19. 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

  20. 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

  1. 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

  2. Multivariate morphological brain signatures predict chronic abdominal pain patients from healthy control subjects

    PubMed Central

    Labus, Jennifer S.; Van Horn, John D.; Gupta, Arpana; Alaverdyan, Mher; Torgerson, Carinna; Ashe-McNalley, Cody; Irimia, Andrei; Hong, Jui-Yang; Naliboff, Bruce; Tillisch, Kirsten; Mayer, Emeran A.

    2015-01-01

    Irritable bowel syndrome (IBS) is the most common chronic visceral pain disorder. The pathophysiology of IBS is incompletely understood, however evidence strongly suggests dysregulation of the brain-gut axis. The aim of this study was to apply multivariate pattern analysis to identify an IBS-related morphometric brain signature which could serve as a central biological marker and provide new mechanistic insights into the pathophysiology of IBS. Parcellation of 165 cortical and subcortical regions was performed using Freesurfer and the Destrieux and Harvard-Oxford atlases. Volume, mean curvature, surface area and cortical thickness were calculated for each region. Sparse partial least squares-discriminant analysis was applied to develop a diagnostic model using a training set of 160 females (80 healthy controls, 80 IBS). Predictive accuracy was assessed in an age matched holdout test set of 52 females (26 health controls, 26 IBS). A two-component classification algorithm comprised of the morphometry of 1) primary somato-sensory and motor regions, and 2) multimodal network regions, explained 36% of the variance. Overall predictive accuracy of the classification algorithm was 70%. Small effect size associations were observed between the somatosensory and motor signature and non-gastrointestinal somatic symptoms. The findings demonstrate the predictive accuracy of a classification algorithm based solely on regional brain morphometry is not sufficient but they do provide support for the utility of multivariate pattern analysis for identifying meaningful neurobiological markers in IBS. Perspective This article presents the development, optimization, and testing of a classification algorithm for discriminating female IBS patients from healthy controls using only brain morphometry data. The results provide support for utility of multivariate pattern analysis for identifying meaningful neurobiological markers in IBS. PMID:25906347

  3. 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

  4. 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.

  5. The Bioinformatics Analysis of miRNAs Signatures Differentially Expressed in HER2(+) Versus HER2(−) Breast Cancers

    PubMed Central

    Nie, Weiwei; Jin, Lei; Wang, Yanru; Wang, Zexing

    2013-01-01

    Abstract Objective To identify the signatures of miRNAs differentially expressed in HER2(+) versus HER2(−) breast cancers that accurately predict the HER2 status of breast cancer, and to provide further insight into breast cancer therapy. Methods By the methods of literature search, aberrant expressed miRNAs were collected. By target prediction algorithm of TargetScan and PicTar and the data enrichment analysis, target gene sets of miRNAs differentially expressed in HER2(+) versus HER2(−) breast cancers were built. Then, using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database, the function modules of Gene Ontology categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) and BIOCARTA pathway, biological functions and signaling pathways that are probably regulated by miRNAs, were analyzed. Results We got five sets of miRNAs expressed in different HER2 status of breast cancers finally. The five sets of data contain 22; 32; 3; 38; and 62 miRNAs, respectively. After miRNAs target prediction and data enrichment, 5,734; 22,409; 1,142; 22,293; and 43,460 target genes of five miRNA sets were collected. Gene ontology analysis found these genes may be involved in transcription, protein transport, angiogenesis, and apoptosis. Moreover, certain KEGG and BIOCARTA signaling pathways related toHER2 status were found. Conclusion Using TargetScan and PicTar for data enrichment, and DAVID database, Gene Ontology categories, KEGG and BIOCARTA pathway for analysis of miRNAs different expression, we conducted a new method for biological interpretation of miRNA profiling data in HER2(+) versus HER2(−) breast cancers. It may improve understanding the regulatory roles of miRNAs in different molecular subtypes of breast cancers. Therefore, it is beneficial to improve the accuracy of experimental efforts to breast cancer and potential therapeutic targets. PMID:23009584

  6. 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

  7. 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

  8. Met-regulated expression signature defines a subset of human hepatocellular carcinomas with poor prognosis and aggressive phenotype

    PubMed Central

    Kaposi-Novak, Pal; Lee, Ju-Seog; Gòmez-Quiroz, Luis; Coulouarn, Cédric; Factor, Valentina M.; Thorgeirsson, Snorri S.

    2006-01-01

    Identification of specific gene expression signatures characteristic of oncogenic pathways is an important step toward molecular classification of human malignancies. Aberrant activation of the Met signaling pathway is frequently associated with tumor progression and metastasis. In this study, we defined the Met-dependent gene expression signature using global gene expression profiling of WT and Met-deficient primary mouse hepatocytes. Newly identified transcriptional targets of the Met pathway included genes involved in the regulation of oxidative stress responses as well as cell motility, cytoskeletal organization, and angiogenesis. To assess the importance of a Met-regulated gene expression signature, a comparative functional genomic approach was applied to 242 human hepatocellular carcinomas (HCCs) and 7 metastatic liver lesions. Cluster analysis revealed that a subset of human HCCs and all liver metastases shared the Met-induced expression signature. Furthermore, the presence of the Met signature showed significant correlation with increased vascular invasion rate and microvessel density as well as with decreased mean survival time of HCC patients. We conclude that the genetically defined gene expression signatures in combination with comparative functional genomics constitute an attractive paradigm for defining both the function of oncogenic pathways and the clinically relevant subgroups of human cancers. PMID:16710476

  9. 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

  10. EnzML: multi-label prediction of enzyme classes using InterPro signatures

    PubMed Central

    2012-01-01

    Background Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. Results We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC) annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein) for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. Conclusions InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values) using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN). PMID:22533924

  11. A common molecular signature in ASD gene expression: following Root 66 to autism

    PubMed Central

    Diaz-Beltran, L; Esteban, F J; Wall, D P

    2016-01-01

    Several gene expression experiments on autism spectrum disorders have been conducted using both blood and brain tissue. Individually, these studies have advanced our understanding of the molecular systems involved in the molecular pathology of autism and have formed the bases of ongoing work to build autism biomarkers. In this study, we conducted an integrated systems biology analysis of 9 independent gene expression experiments covering 657 autism, 9 mental retardation and developmental delay and 566 control samples to determine if a common signature exists and to test whether regulatory patterns in the brain relevant to autism can also be detected in blood. We constructed a matrix of differentially expressed genes from these experiments and used a Jaccard coefficient to create a gene-based phylogeny, validated by bootstrap. As expected, experiments and tissue types clustered together with high statistical confidence. However, we discovered a statistically significant subgrouping of 3 blood and 2 brain data sets from 3 different experiments rooted by a highly correlated regulatory pattern of 66 genes. This Root 66 appeared to be non-random and of potential etiologic relevance to autism, given their enriched roles in neurological processes key for normal brain growth and function, learning and memory, neurodegeneration, social behavior and cognition. Our results suggest that there is a detectable autism signature in the blood that may be a molecular echo of autism-related dysregulation in the brain. PMID:26731442

  12. Gene expression profiling identifies IRF4-associated molecular signatures in hematological malignancies.

    PubMed

    Wang, Ling; Yao, Zhi Q; Moorman, Jonathan P; Xu, Yanji; Ning, Shunbin

    2014-01-01

    The lymphocyte-specific transcription factor Interferon (IFN) Regulatory Factor 4 (IRF4) is implicated in certain types of lymphoid and myeloid malignancies. However, the molecular mechanisms underlying its interactions with these malignancies are largely unknown. In this study, we have first profiled molecular signatures associated with IRF4 expression in associated cancers, by analyzing existing gene expression profiling datasets. Our results show that IRF4 is overexpressed in melanoma, in addition to previously reported contexts including leukemia, myeloma, and lymphoma, and that IRF4 is associated with a unique gene expression pattern in each context. A pool of important genes involved in B-cell development, oncogenesis, cell cycle regulation, and cell death including BATF, LIMD1, CFLAR, PIM2, and CCND2 are common signatures associated with IRF4 in non-Hodgkin B cell lymphomas. We confirmed the correlation of IRF4 with LIMD1 and CFLAR in a panel of cell lines derived from lymphomas. Moreover, we profiled the IRF4 transcriptome in the context of EBV latent infection, and confirmed several genes including IFI27, IFI44, GBP1, and ARHGAP18, as well as CFLAR as novel targets for IRF4. These results provide valuable information for understanding the IRF4 regulatory network, and improve our knowledge of the unique roles of IRF4 in different hematological malignancies. PMID:25207815

  13. Identification of Aging-Associated Gene Expression Signatures That Precede Intestinal Tumorigenesis.

    PubMed

    Okuchi, Yoshihisa; Imajo, Masamichi; Mizuno, Rei; Kamioka, Yuji; Miyoshi, Hiroyuki; Taketo, Makoto Mark; Nagayama, Satoshi; Sakai, Yoshiharu; Matsuda, Michiyuki

    2016-01-01

    Aging-associated alterations of cellular functions have been implicated in various disorders including cancers. Due to difficulties in identifying aging cells in living tissues, most studies have focused on aging-associated changes in whole tissues or certain cell pools. Thus, it remains unclear what kinds of alterations accumulate in each cell during aging. While analyzing several mouse lines expressing fluorescent proteins (FPs), we found that expression of FPs is gradually silenced in the intestinal epithelium during aging in units of single crypt composed of clonal stem cell progeny. The cells with low FP expression retained the wild-type Apc allele and the tissues composed of them did not exhibit any histological abnormality. Notably, the silencing of FPs was also observed in intestinal adenomas and the surrounding normal mucosae of Apc-mutant mice, and mediated by DNA methylation of the upstream promoter. Our genome-wide analysis then showed that the silencing of FPs reflects specific gene expression alterations during aging, and that these alterations occur in not only mouse adenomas but also human sporadic and hereditary (familial adenomatous polyposis) adenomas. Importantly, pharmacological inhibition of DNA methylation, which suppresses adenoma development in Apc-mutant mice, reverted the aging-associated silencing of FPs and gene expression alterations. These results identify aging-associated gene expression signatures that are heterogeneously induced by DNA methylation and precede intestinal tumorigenesis triggered by Apc inactivation, and suggest that pharmacological inhibition of the signature genes could be a novel strategy for the prevention and treatment of intestinal tumors. PMID:27589228

  14. Identification of Aging-Associated Gene Expression Signatures That Precede Intestinal Tumorigenesis

    PubMed Central

    Okuchi, Yoshihisa; Imajo, Masamichi; Mizuno, Rei; Kamioka, Yuji; Miyoshi, Hiroyuki; Taketo, Makoto Mark; Nagayama, Satoshi; Sakai, Yoshiharu; Matsuda, Michiyuki

    2016-01-01

    Aging-associated alterations of cellular functions have been implicated in various disorders including cancers. Due to difficulties in identifying aging cells in living tissues, most studies have focused on aging-associated changes in whole tissues or certain cell pools. Thus, it remains unclear what kinds of alterations accumulate in each cell during aging. While analyzing several mouse lines expressing fluorescent proteins (FPs), we found that expression of FPs is gradually silenced in the intestinal epithelium during aging in units of single crypt composed of clonal stem cell progeny. The cells with low FP expression retained the wild-type Apc allele and the tissues composed of them did not exhibit any histological abnormality. Notably, the silencing of FPs was also observed in intestinal adenomas and the surrounding normal mucosae of Apc-mutant mice, and mediated by DNA methylation of the upstream promoter. Our genome-wide analysis then showed that the silencing of FPs reflects specific gene expression alterations during aging, and that these alterations occur in not only mouse adenomas but also human sporadic and hereditary (familial adenomatous polyposis) adenomas. Importantly, pharmacological inhibition of DNA methylation, which suppresses adenoma development in Apc-mutant mice, reverted the aging-associated silencing of FPs and gene expression alterations. These results identify aging-associated gene expression signatures that are heterogeneously induced by DNA methylation and precede intestinal tumorigenesis triggered by Apc inactivation, and suggest that pharmacological inhibition of the signature genes could be a novel strategy for the prevention and treatment of intestinal tumors. PMID:27589228

  15. Next generation sequencing-based expression profiling identifies signatures from benign stromal proliferations that define stromal components of breast cancer

    PubMed Central

    2013-01-01

    Introduction Multiple studies have shown that the tumor microenvironment (TME) of carcinomas can play an important role in the initiation, progression, and metastasis of cancer. Here we test the hypothesis that specific benign fibrous soft tissue tumor gene expression profiles may represent distinct stromal fibroblastic reaction types that occur in different breast cancers. The discovered stromal profiles could classify breast cancer based on the type of stromal reaction patterns in the TME. Methods Next generation sequencing-based gene expression profiling (3SEQ) was performed on formalin fixed, paraffin embedded (FFPE) samples of 10 types of fibrous soft tissue tumors. We determined the extent to which these signatures could identify distinct subsets of breast cancers in four publicly available breast cancer datasets. Results A total of 53 fibrous tumors were sequenced by 3SEQ with an average of 29 million reads per sample. Both the gene signatures derived from elastofibroma (EF) and fibroma of tendon sheath (FOTS) demonstrated robust outcome results for survival in the four breast cancer datasets. The breast cancers positive for the EF signature (20-33% of the cohort) demonstrated significantly better outcome for survival. In contrast, the FOTS signature-positive breast cancers (11-35% of the cohort) had a worse outcome. Conclusions We defined and validated two new stromal signatures in breast cancer (EF and FOTS), which are significantly associated with prognosis. Our group has previously identified novel cancer stromal gene expression signatures associated with outcome differences in breast cancer by gene expression profiling of three soft tissue tumors, desmoid-type fibromatosis (DTF), solitary fibrous tumor (SFT), and tenosynovial giant cell tumor (TGCT/CSF1), as surrogates for stromal expression patterns. By combining the stromal signatures of EF and FOTS, with our previously identified DTF and TGCT/CSF1 signatures we can now characterize clinically

  16. Diagnostic and prognostic gene expression signatures in 177 soft tissue sarcomas: hypoxia-induced transcription profile signifies metastatic potential

    PubMed Central

    Francis, Princy; Namløs, Heidi Maria; Müller, Christoph; Edén, Patrik; Fernebro, Josefin; Berner, Jeanne-Marie; Bjerkehagen, Bodil; Åkerman, Måns; Bendahl, Pär-Ola; Isinger, Anna; Rydholm, Anders; Myklebost, Ola; Nilbert, Mef

    2007-01-01

    Background Soft tissue sarcoma (STS) diagnosis is challenging because of a multitude of histopathological subtypes, different genetic characteristics, and frequent intratumoral pleomorphism. One-third of STS metastasize and current risk-stratification is suboptimal, therefore, novel diagnostic and prognostic markers would be clinically valuable. We assessed the diagnostic and prognostic value of array-based gene expression profiles using 27 k cDNA microarrays in 177, mainly high-grade, STS of 13 histopathological subtypes. Results Unsupervised analysis resulted in two major clusters – one mainly containing STS characterized by type-specific genetic alterations and the other with a predominance of genetically complex and pleomorphic STS. Synovial sarcomas, myxoid/round-cell liposarcomas, and gastrointestinal stromal tumors clustered tightly within the former cluster and discriminatory signatures for these were characterized by developmental genes from the EGFR, FGFR, Wnt, Notch, Hedgehog, RAR and KIT signaling pathways. The more pleomorphic STS subtypes, e.g. leiomyosarcoma, malignant fibrous histiocytoma/undifferentiated pleomorphic sarcoma and dedifferentiated/pleomorphic liposarcoma, were part of the latter cluster and were characterized by relatively heterogeneous profiles, although subclusters herein were identified. A prognostic signature partly characterized by hypoxia-related genes was identified among 89 genetically complex pleomorphic primary STS and could, in a multivariate analysis including established prognostic markers, independently predict the risk of metastasis with a hazard ratio of 2.2 (P = 0.04). Conclusion Diagnostic gene expression profiles linking signaling pathways to the different STS subtypes were demonstrated and a hypoxia-induced metastatic profile was identified in the pleomorphic, high-grade STS. These findings verify diagnostic utility and application of expression data for improved selection of high-risk STS patients. PMID:17359542

  17. MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.

    PubMed

    Vazquez, Miguel; Nogales-Cadenas, Ruben; Arroyo, Javier; Botías, Pedro; García, Raul; Carazo, Jose M; Tirado, Francisco; Pascual-Montano, Alberto; Carmona-Saez, Pedro

    2010-07-01

    The enormous amount of data available in public gene expression repositories such as Gene Expression Omnibus (GEO) offers an inestimable resource to explore gene expression programs across several organisms and conditions. This information can be used to discover experiments that induce similar or opposite gene expression patterns to a given query, which in turn may lead to the discovery of new relationships among diseases, drugs or pathways, as well as the generation of new hypotheses. In this work, we present MARQ, a web-based application that allows researchers to compare a query set of genes, e.g. a set of over- and under-expressed genes, against a signature database built from GEO datasets for different organisms and platforms. MARQ offers an easy-to-use and integrated environment to mine GEO, in order to identify conditions that induce similar or opposite gene expression patterns to a given experimental condition. MARQ also includes additional functionalities for the exploration of the results, including a meta-analysis pipeline to find genes that are differentially expressed across different experiments. The application is freely available at http://marq.dacya.ucm.es.

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

    PubMed Central

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

    2016-01-01

    Background Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods An open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS− populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS− patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS−). There was one complete response (GS−) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS− and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162. PMID:27502712

  19. 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

  20. A Snapshot of the Expression Signature of Androgen Receptor Splicing Variants and Their Distinctive Transcriptional Activities

    PubMed Central

    Hu, Rong; Isaacs, William B.; Luo, Jun

    2012-01-01

    BACKGROUND The diversity and complexity of the human androgen receptor (AR) splicing variants are well appreciated but not fully understood. The goal of this study is to generate a comprehensive expression signature of AR variants in castration-resistant prostate cancer (CRPC), and to address the relative importance of the individual variants in conferring the castration-resistant phenotype. METHODS A modified RNA amplification method, termed selective linear amplification of sense RNA, was developed to amplify all AR transcripts containing AR exon 3 in CRPC specimens, which were profiled using tiling expression microarrays. Coding sequences for the AR variants were cloned into expression vectors and assessed for their transcriptional activities. Quantitative RT-PCR was used to determine their in vivo expression patterns in an expanded set of clinical specimens. RESULTS In addition to expression peaks in AR intron 3, a novel AR exon, termed exon 9, was discovered. Exon 9 was spliced into multiple novel AR variants. Different AR splicing variants were functionally distinctive, with some demonstrating constitutive activity while others were conditionally active. Conditionally active AR-Vs may activate AR signaling depending on the cellular context. Importantly, AR variant functions did not appear to depend on the full-length AR. CONCLUSIONS This study provided the first unbiased snapshot of the AR variant signature consisting of multiple AR variants with distinctive functional properties, directly in CRPC specimens. Study findings suggest that the aggregate function of multiple AR variants may confer a castration-resistant phenotype independent of the full-length AR. PMID:21446008

  1. 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

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

    PubMed

    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.

  3. Molecular signatures and the study of gene expression profiles in inflammatory heart diseases.

    PubMed

    Ruppert, V; Maisch, B

    2012-09-01

    Myocarditis, a common heart disease pathologically defined as an inflammatory reaction of the myocardium, is most frequently caused by infectious agents, including viruses and bacteria, and may develop in later stages into dilated cardiomyopathy (DCM). Several studies have identified inflammatory components engaged in the transition from acute myocarditis to chronic DCM, and there is growing evidence that myocarditis and DCM are closely related. Novel technological advances in genomic screening have gained insight into molecular and cellular mechanisms involved the pathogenesis of inflammatory heart disease and, in particular, in the development of systolic dysfunction resulting from DCM. Detection of differential gene expression profiles have become valid tools in the study of inflammatory heart disease. Molecular signatures are defined as individual sets of genes, mRNA transcripts, proteins, genetic variations or other variables, which can be used as markers for a particular phenotype. These signatures may be useful for clinical diagnosis or risk assessment and, in addition, may help to identify molecules not previously known to be involved in the pathogenesis of these disease conditions. Microarray analyses have dramatically refined our knowledge about tissue-specific gene expression patterns, simply by being able to study thousands of genes simultaneously in a single experiment. In the field of cardiovascular research, microarrays are increasingly used in the study of end-stage cardiomyopathies, such as DCM, that ultimately lead to symptoms of heart failure. By means of microarray analysis, a set of differentially expressed genes can be detected, among them are transcripts coding for sarcomeric and extracellular matrix proteins, stress response and inflammatory proteins as well as transcription factors and translational regulators. Expression profiling may be particularly helpful to improve the differential diagnosis of heart failure and enable novel insight

  4. 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.

  5. 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

  6. 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

  7. Metastasis signatures: genes regulating tumor-microenvironment interactions predict metastatic behavior.

    PubMed

    Albini, Adriana; Mirisola, Valentina; Pfeffer, Ulrich

    2008-03-01

    The possibility of predicting clinical outcome of cancer patients through the analysis of gene expression profiles in the primary tumor is a kind of ideological revolution as the multistep carcinogenesis model postulates that the proportion of cells within the primary tumor that actually acquire metastasis driving mutation(s) is small; too small to leave its imprint on the gene expression profile. The data collected to date have brought a new paradigm to reality in the metastasis field: metastasis must at least in part rely on mutations and/or gene regulation events present in the majority of cells which constitute the primary tumor mass. By analyses of differential expression of primary tumors versus metastases or by functional analyses of putative metastasis genes in experimental metastasis, many metastasis-associated gene expression events have been identified that correlate with the development of metastases. Among genes "favoring" metastasis, we find many molecules that are expressed not by the tumor cell itself but by the cells of the microenvironment, as well as genes over-expressed in the primary tumor that have a principle role in mediating tumor-host interactions. Here we review these concepts and advance hypotheses on how gene expression of the primary tumor and the microenvironment can favor the spread of the metastasis seeds and how this knowledge can provide tools to secondary prevention.

  8. Identification of a novel flow-mediated gene expression signature in patients with bicuspid aortic valve.

    PubMed

    Maleki, Shohreh; Björck, Hanna M; Folkersen, Lasse; Nilsson, Roland; Renner, Johan; Caidahl, Kenneth; Franco-Cereceda, Anders; Länne, Toste; Eriksson, Per

    2013-01-01

    Individuals with bicuspid aortic valve (BAV) are at significantly higher risk of developing serious aortic complications than individuals with tricuspid aortic valves (TAV). Studies have indicated an altered aortic blood flow in patients with BAV; however, the extent to which altered flow influences the pathological state of BAV aorta is unclear. In the present study, we dissected flow-mediated aortic gene expression in patients undergoing elective open heart surgery. A large collection of public microarray data sets were firstly screened for consistent co-expression with five well-characterized flow-regulated genes (query genes). Genes with co-expression probability of >0.5 were selected and further analysed in expression profiles (127 arrays) from ascending aorta of BAV and TAV patients. Forty-four genes satisfied two filtering criteria: a significant correlation with one or more of the query genes (R > 0.40) and differential expression between patients with BAV and TAV. No gene fulfilled the criteria in mammary artery (88 arrays), an artery not in direct contact with the valve. Fifty-five percent of the genes significantly altered between BAV and TAV patients showed differential expression between two identified flow regions in the rat aorta. A large proportion of the identified genes were related to angiogenesis and/or wound healing, with pro-angiogenesis genes downregulated and inhibitory genes upregulated in patients with BAV. Moreover, differential expression of ZFP36, GRP116 and PKD2 was confirmed using immunohistochemistry. Implementing a new strategy, we have demonstrated an angiostatic gene expression signature in patients with BAV, indicating impaired wound healing in these patients, potentially involved in BAV-associated aortopathy. PMID:22903503

  9. Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from breast carcinoma in effusions.

    PubMed

    Davidson, Ben; Stavnes, Helene Tuft; Holth, Arild; Chen, Xu; Yang, Yanqin; Shih, Ie-Ming; Wang, Tian-Li

    2011-03-01

    Ovarian/primary peritoneal carcinoma and breast carcinoma are the gynaecological cancers that most frequently involve the serosal cavities.With the objective of improving on the limited diagnostic panel currently available for the differential diagnosis of these two malignancies,as well as to define tumour-specific biological targets, we compared their global gene expression patterns. Gene expression profiles of 10 serous ovarian/peritoneal and eight ductal breast carcinoma effusions were analysed using the HumanRef-8 BeadChip from Illumina.Differentially expressed candidate genes were validated using quantitative real-time PCR and immunohistochemistry. Unsupervised hierarchical clustering using all 54,675 genes in the array separated ovarian from breast carcinoma samples. We identified 288 unique probes that were significantly differentially expressed in the two cancers by greater than 3.5-fold, of which 81 and 207 were overexpressed in breast and ovarian/peritoneal carcinoma, respectively. SAM analysis identified 1078 differentially expressed probes with false discovery rate less than 0.05. Genes overexpressed in breast carcinoma included TFF1, TFF3, FOXA1, CA12, GATA3, SDC1, PITX1, TH, EHFD1, EFEMP1, TOB1 and KLF2. Genes overexpressed in ovarian/peritoneal carcinoma included SPON1, RBP1, MFGE8, TM4SF12, MMP7, KLK5/6/7, FOLR1/3,PAX8, APOL2 and NRCAM. The differential expression of 14 genes was validated by quantitative real-time PCR, and differences in 5 gene products were confirmed by immunohistochemistry. Expression profiling distinguishes ovarian/peritoneal carcinoma from breast carcinoma and identifies genes that are differentially expressed in these two tumour types. The molecular signatures unique to these cancers may facilitate their differential diagnosis and may provide a molecular basis for therapeutic target discovery.

  10. 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.

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

    PubMed

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

    2015-05-01

    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.

  12. 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

  13. 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

  14. 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.

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

    PubMed

    Staege, Martin Sebastian

    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

  16. 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

  17. 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

  18. The conformational signature of arrestin3 predicts its trafficking and signaling functions

    PubMed Central

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

    2016-01-01

    Arrestins are cytosolic proteins that regulate G protein-coupled receptor (GPCR) desensitization, internalization, trafficking, and signaling1,2. Arrestin recruitment uncouples GPCRs from heterotrimeric G proteins, and targets them for internalization via clathrin-coated pits3,4. Arrestins also function as ligand-regulated scaffolds that recruit multiple non-G protein effectors into GPCR-based ‘signalsomes’5,6. While the dominant function(s) of arrestins vary between receptors, the mechanism whereby different GPCRs specify divergent arrestin functions is not understood. Using a panel of intramolecular FlAsH-BRET reporters7 to monitor conformational changes in arrestin3, we show here that GPCRs impose distinctive arrestin ‘conformational signatures’ that reflect the stability of the receptor-arrestin complex and role of arrestin3 in activating or dampening downstream signaling 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 arrestin3 conformation. Our findings demonstrate that information about ligand-receptor conformation is encoded within the population average arrestin3 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 ligands8,9 and in identifying factors that dictate arrestin conformation and function. PMID:27007854

  19. 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.

  20. 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

  1. Gene expression signature of non-involved lung tissue associated with survival in lung adenocarcinoma patients.

    PubMed

    Galvan, Antonella; Frullanti, Elisa; Anderlini, Marco; Manenti, Giacomo; Noci, Sara; Dugo, Matteo; Ambrogi, Federico; De Cecco, Loris; Spinelli, Roberta; Piazza, Rocco; Pirola, Alessandra; Gambacorti-Passerini, Carlo; Incarbone, Matteo; Alloisio, Marco; Tosi, Davide; Nosotti, Mario; Santambrogio, Luigi; Pastorino, Ugo; Dragani, Tommaso A

    2013-12-01

    Lung adenocarcinoma patients of similar clinical stage and undergoing the same treatments often have marked interindividual variations in prognosis. These clinical discrepancies may be due to the genetic background modulating an individual's predisposition to fighting cancer. Herein, we hypothesized that the lung microenvironment, as reflected by its expression profile, may affect lung adenocarcinoma patients' survival. The transcriptome of non-involved lung tissue, excised from a discovery series of 204 lung adenocarcinoma patients, was evaluated using whole-genome expression microarrays (with probes corresponding to 28 688 well-annotated coding sequences). Genes associated with survival status at 60 months were identified by Cox regression analysis (adjusted for gender, age and clinical stage) and retested in a validation series of 78 additional cases. RNA-Seq analysis from non-involved lung tissue of 12 patients was performed to characterize the different isoforms of candidate genes. Ten genes for which the loge-transformed hazard ratios expressed the same direction of effect in the discovery (P < 1.0 × 10(-3)) and validation series comprised the gene expression signature associated with survival: CNTNAP1, PKNOX1, FAM156A, FRMD8, GALNTL1, TXNDC12, SNTB1, PPP3R1, SNX10 and SERPINH1. RNA sequencing highlighted the complex expression pattern of these genes in non-involved lung tissue from different patients and permitted the detection of a read-through gene fusion between PPP3R1 and the flanking gene (CNRIP1) as well as a novel isoform of CNTNAP1. Our findings support the hypothesis that individual genetic characteristics, evidenced by the expression pattern of non-involved tissue, influence the outcome of lung adenocarcinoma patients. PMID:23978379

  2. 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

  3. 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

  4. Aging-dependent alterations in gene expression and a mitochondrial signature of responsiveness to human influenza vaccination.

    PubMed

    Thakar, Juilee; Mohanty, Subhasis; West, A Phillip; Joshi, Samit R; Ueda, Ikuyo; Wilson, Jean; Meng, Hailong; Blevins, Tamara P; Tsang, Sui; Trentalange, Mark; Siconolfi, Barbara; Park, Koonam; Gill, Thomas M; Belshe, Robert B; Kaech, Susan M; Shadel, Gerald S; Kleinstein, Steven H; Shaw, Albert C

    2015-01-01

    To elucidate gene expression pathways underlying age-associated impairment in influenza vaccine response, we screened young (age 21-30) and older (age≥65) adults receiving influenza vaccine in two consecutive seasons and identified those with strong or absent response to vaccine, including a subset of older adults meeting criteria for frailty. PBMCs obtained prior to vaccination (Day 0) and at day 2 or 4, day 7 and day 28 post-vaccine were subjected to gene expression microarray analysis. We defined a response signature and also detected induction of a type I interferon response at day 2 and a plasma cell signature at day 7 post-vaccine in young responders. The response signature was dysregulated in older adults, with the plasma cell signature induced at day 2, and was never induced in frail subjects (who were all non-responders). We also identified a mitochondrial signature in young vaccine responders containing genes mediating mitochondrial biogenesis and oxidative phosphorylation that was consistent in two different vaccine seasons and verified by analyses of mitochondrial content and protein expression. These results represent the first genome-wide transcriptional profiling analysis of age-associated dynamics following influenza vaccination, and implicate changes in mitochondrial biogenesis and function as a critical factor in human vaccine responsiveness.

  5. Discriminative local subspaces in gene expression data for effective gene function prediction

    PubMed Central

    Gutiérrez, Rodrigo A.; Soto, Alvaro

    2012-01-01

    Motivation: Massive amounts of genome-wide gene expression data have become available, motivating the development of computational approaches that leverage this information to predict gene function. Among successful approaches, supervised machine learning methods, such as Support Vector Machines (SVMs), have shown superior prediction accuracy. However, these methods lack the simple biological intuition provided by co-expression networks (CNs), limiting their practical usefulness. Results: In this work, we present Discriminative Local Subspaces (DLS), a novel method that combines supervised machine learning and co-expression techniques with the goal of systematically predict genes involved in specific biological processes of interest. Unlike traditional CNs, DLS uses the knowledge available in Gene Ontology (GO) to generate informative training sets that guide the discovery of expression signatures: expression patterns that are discriminative for genes involved in the biological process of interest. By linking genes co-expressed with these signatures, DLS is able to construct a discriminative CN that links both, known and previously uncharacterized genes, for the selected biological process. This article focuses on the algorithm behind DLS and shows its predictive power using an Arabidopsis thaliana dataset and a representative set of 101 GO terms from the Biological Process Ontology. Our results show that DLS has a superior average accuracy than both SVMs and CNs. Thus, DLS is able to provide the prediction accuracy of supervised learning methods while maintaining the intuitive understanding of CNs. Availability: A MATLAB® implementation of DLS is available at http://virtualplant.bio.puc.cl/cgi-bin/Lab/tools.cgi Contact: tfpuelma@uc.cl Supplementary Information: Supplementary data are available at http://bioinformatics.mpimp-golm.mpg.de/. PMID:22820203

  6. 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.

  7. 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

  8. 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

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

    PubMed

    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:27445811

  10. 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

  11. 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.

  12. 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

  13. 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

  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. Inflammation, adenoma and cancer: objective classification of colon biopsy specimens with gene expression signature.

    PubMed

    Galamb, Orsolya; Györffy, Balázs; Sipos, Ferenc; Spisák, Sándor; Németh, Anna Mária; Miheller, Pál; Tulassay, Zsolt; Dinya, Elek; Molnár, Béla

    2008-01-01

    Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples), colorectal carcinomas (CRC) (15) and inflammatory bowel diseases (IBD) (14). Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIValpha1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2). Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  16. 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

  17. 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. PMID:27600246

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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

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

    PubMed

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

    2015-10-16

    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.

  6. Genomic Signatures in Breast Cancer: Limitations of Available Predictive Data and the Importance of Prognosis.

    PubMed

    Esteva, Francisco J

    2015-06-01

    Several biomarkers and gene mutations in breast cancer have been shown to be predictive, in that they determine which treatments a patient should receive. Ideally, predictive markers would be available that could determine the most appropriate treatment plan based on a patient’s biology. This goal is becoming a reality in some treatment settings and cancer types, with the increasing use of targeted therapies directed against specific molecular abnormalities. Immunohistochemistry (IHC) testing is in standard use for guiding breast cancer therapy. Testing for the estrogen receptor (ER) and progesterone receptor (PR) guides the use of endocrine therapy, and human epidermal growth factor receptor 2 (HER2) testing guides the use of HER2-targeted therapies. Although IHC provides some discrimination among breast cancer subsets and helps identify appropriate therapy, more information can be gained through gene expression analyses. Contemporary multianalyte assays have demonstrated greater precision and reproducibility than seen with IHC-based assays. The most important contribution of multigene assays is the identification of women with ER/PR-positive, HER2-negative, early-stage breast cancer who are at low risk of recurrence and therefore will likely do well with endocrine therapy alone. These patients can be safely spared from the cytotoxic effects of chemotherapy.

  7. Determination of death thresholds and identification of terahertz (THz)-specific gene expression signatures

    NASA Astrophysics Data System (ADS)

    Wilmink, Gerald J.; Ibey, Bennett L.; Roth, Caleb L.; Vincelette, Rebecca L.; Rivest, Benjamin D.; Horn, Christopher B.; Bernhard, Joshua; Roberson, Dawnlee; Roach, William P.

    2010-02-01

    In recent years, numerous security, military, and medical applications have been developed which use Terahertz (THz) radiation. These developments have heightened concerns in regards to the potential health risks that are associated with this type of radiation. To determine the cellular and molecular effects caused by THz radiation, we exposed several human cell lines to high-power THz radiation, and then we determined death thresholds and gene expression profiles. Necrotic and apoptotic death thresholds were determined for Jurkat cells using an optically-pumped molecular gas THz source (υ = 2.52 THz, H = 227 mW/cm2), MTT viability assays, and flow cytometric techniques. In addition, we used confocal microscopic techniques to demarcate lethal spatial regions in a monolayer of dermal fibroblasts exposed to THz radiation. Then, to determine if cells exhibit a THz-specific gene expression signature, we exposed dermal fibroblasts to THz radiation and analyzed their transcriptional response using microarray gene chips. We found that 60% of the Jurkat cells survived the 30-minute THz exposure, whereas only 20% survived the 40-minute exposure. The flow data confirmed these results and provided evidence that THz-induced cell death was mediated using both nectrotic and apoptotic processes. The preliminary microscopy studies provided convincing evidence warranting future efforts using these techniques. Lastly, we found that dermal fibroblasts up-regulated several genes when exposed to THz radiation. Overall, these results provide evidence for the cellular and molecular effects associated with THz radiation, and we speculate that the identified up-regulated genes may serve as excellent candidate biomarkers for THz exposures.

  8. 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

  9. A gene expression signature shared by human mature oocytes and embryonic stem cells

    PubMed Central

    Assou, Said; Cerecedo, Doris; Tondeur, Sylvie; Pantesco, Véronique; Hovatta, Outi; Klein, Bernard; Hamamah, Samir; De Vos, John

    2009-01-01

    Background The first week of human pre-embryo development is characterized by the induction of totipotency and then pluripotency. The understanding of this delicate process will have far reaching implication for in vitro fertilization and regenerative medicine. Human mature MII oocytes and embryonic stem (ES) cells are both able to achieve the feat of cell reprogramming towards pluripotency, either by somatic cell nuclear transfer or by cell fusion, respectively. Comparison of the transcriptome of these two cell types may highlight genes that are involved in pluripotency initiation. Results Based on a microarray compendium of 205 samples, we compared the gene expression profile of mature MII oocytes and human ES cells (hESC) to that of somatic tissues. We identified a common oocyte/hESC gene expression profile, which included a strong cell cycle signature, genes associated with pluripotency such as LIN28 and TDGF1, a large chromatin remodelling network (TOP2A, DNMT3B, JARID2, SMARCA5, CBX1, CBX5), 18 different zinc finger transcription factors, including ZNF84, and several still poorly annotated genes such as KLHL7, MRS2, or the Selenophosphate synthetase 1 (SEPHS1). Interestingly, a large set of genes was also found to code for proteins involved in the ubiquitination and proteasome pathway. Upon hESC differentiation into embryoid bodies, the transcription of this pathway declined. In vitro, we observed a selective sensitivity of hESC to the inhibition of the activity of the proteasome. Conclusion These results shed light on the gene networks that are concurrently overexpressed by the two human cell types with somatic cell reprogramming properties. PMID:19128516

  10. Graph based fusion of miRNA and mRNA expression data improves clinical outcome prediction in prostate cancer

    PubMed Central

    2011-01-01

    Background One of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification. With the increasing number of microarray studies collecting mRNA and miRNA from the same patient cohort there is a need for statistical methods to integrate or fuse both kinds of data into one prediction model in order to find a combined signature that improves the prediction. Results Here, we propose a new method to fuse miRNA and mRNA data into one prediction model. Since miRNAs are known regulators of mRNAs we used the correlations between them as well as the target prediction information to build a bipartite graph representing the relations between miRNAs and mRNAs. This graph was used to guide the feature selection in order to improve the prediction. The method is illustrated on a prostate cancer data set comprising 98 patient samples with miRNA and mRNA expression data. The biochemical relapse was used as clinical endpoint. It could be shown that the bipartite graph in combination with both data sets could improve prediction performance as well as the stability of the feature selection. Conclusions Fusion of mRNA and miRNA expression data into one prediction model improves clinical outcome prediction in terms of prediction error and stable feature selection. The R source code of the proposed method is available in the supplement. PMID:22188670

  11. 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 ...

  12. 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 ...

  13. Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes

    PubMed Central

    Levy, Hara; Wang, Xujing; Kaldunski, Mary; Jia, Shuang; Kramer, Joanna; Pavletich, Scott J.; Reske, Melissa; Gessel, Trevor; Yassai, Maryam; Quasney, Michael W.; Dahmer, Mary K.; Gorski, Jack; Hessner, Martin J.

    2014-01-01

    The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding therapeutic decisions, and monitoring interventions. We previously demonstrated that plasma samples from recent-onset Type 1 diabetes (RO T1D) patients induce a proinflammatory transcriptional signature in freshly drawn peripheral blood mononuclear cells (PBMCs) relative to that of unrelated healthy controls (HC). Here, using cryopreserved PBMC, we analyzed larger RO T1D and HC cohorts, examined T1D progression in pre-onset samples, and compared the RO T1D signature to those associated with three disorders characterized by airway infection and inflammation. The RO T1D signature, consisting of interleukin-1 cytokine family members, chemokines involved in immunocyte chemotaxis, immune receptors, and signaling molecules, was detected during early pre-diabetes and found to resolve post-onset. The signatures associated with cystic fibrosis patients chronically infected with Pseudomonas aeruginosa, patients with confirmed bacterial pneumonia, and subjects with H1N1 influenza all reflected immunological activation, yet each were distinct from one another and negatively correlated with that of T1D. This study highlights the remarkable capacity of cells to serve as biosensors capable of sensitively and comprehensively differentiating immunological states. PMID:22972474

  14. Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin-binding transcription activators (CAMTAs) to produce specific gene expression responses.

    PubMed

    Liu, Junli; Whalley, Helen J; Knight, Marc R

    2015-10-01

    Experimental data show that Arabidopsis thaliana is able to decode different calcium signatures to produce specific gene expression responses. It is also known that calmodulin-binding transcription activators (CAMTAs) have calmodulin (CaM)-binding domains. Therefore, the gene expression responses regulated by CAMTAs respond to calcium signals. However, little is known about how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. A dynamic model of Ca(2+) -CaM-CAMTA binding and gene expression responses is developed following thermodynamic and kinetic principles. The model is parameterized using experimental data. Then it is used to analyse how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. Modelling analysis reveals that: calcium signals in the form of cytosolic calcium concentration elevations are nonlinearly amplified by binding of Ca(2+) , CaM and CAMTAs; amplification of Ca(2+) signals enables calcium signatures to be decoded to give specific CAMTA-regulated gene expression responses; gene expression responses to a calcium signature depend upon its history and accumulate all the information during the lifetime of the calcium signature. Information flow from calcium signatures to CAMTA-regulated gene expression responses has been established by combining experimental data with mathematical modelling.

  15. Combining modelling and experimental approaches to explain how calcium signatures are decoded by calmodulin-binding transcription activators (CAMTAs) to produce specific gene expression responses.

    PubMed

    Liu, Junli; Whalley, Helen J; Knight, Marc R

    2015-10-01

    Experimental data show that Arabidopsis thaliana is able to decode different calcium signatures to produce specific gene expression responses. It is also known that calmodulin-binding transcription activators (CAMTAs) have calmodulin (CaM)-binding domains. Therefore, the gene expression responses regulated by CAMTAs respond to calcium signals. However, little is known about how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. A dynamic model of Ca(2+) -CaM-CAMTA binding and gene expression responses is developed following thermodynamic and kinetic principles. The model is parameterized using experimental data. Then it is used to analyse how different calcium signatures are decoded by CAMTAs to produce specific gene expression responses. Modelling analysis reveals that: calcium signals in the form of cytosolic calcium concentration elevations are nonlinearly amplified by binding of Ca(2+) , CaM and CAMTAs; amplification of Ca(2+) signals enables calcium signatures to be decoded to give specific CAMTA-regulated gene expression responses; gene expression responses to a calcium signature depend upon its history and accumulate all the information during the lifetime of the calcium signature. Information flow from calcium signatures to CAMTA-regulated gene expression responses has been established by combining experimental data with mathematical modelling. PMID:25917109

  16. Network Signatures of Survival in Glioblastoma Multiforme

    PubMed Central

    Patel, Vishal N.; Gokulrangan, Giridharan; Chowdhury, Salim A.; Chen, Yanwen; Sloan, Andrew E.; Koyutürk, Mehmet; Barnholtz-Sloan, Jill; Chance, Mark R.

    2013-01-01

    To determine a molecular basis for prognostic differences in glioblastoma multiforme (GBM), we employed a combinatorial network analysis framework to exhaustively search for molecular patterns in protein-protein interaction (PPI) networks. We identified a dysregulated molecular signature distinguishing short-term (survival<225 days) from long-term (survival>635 days) survivors of GBM using whole genome expression data from The Cancer Genome Atlas (TCGA). A 50-gene subnetwork signature achieved 80% prediction accuracy when tested against an independent gene expression dataset. Functional annotations for the subnetwork signature included “protein kinase cascade,” “IκB kinase/NFκB cascade,” and “regulation of programmed cell death” – all of which were not significant in signatures of existing subtypes. Finally, we used label-free proteomics to examine how our subnetwork signature predicted protein level expression differences in an independent GBM cohort of 16 patients. We found that the genes discovered using network biology had a higher probability of dysregulated protein expression than either genes exhibiting individual differential expression or genes derived from known GBM subtypes. In particular, the long-term survivor subtype was characterized by increased protein expression of DNM1 and MAPK1 and decreased expression of HSPA9, PSMD3, and CANX. Overall, we demonstrate that the combinatorial analysis of gene expression data constrained by PPIs outlines an approach for the discovery of robust and translatable molecular signatures in GBM. PMID:24068912

  17. Predicting environmental chemical factors associated with disease-related gene expression data

    PubMed Central

    2010-01-01

    Background Many common diseases arise from an interaction between environmental and genetic factors. Our knowledge regarding environment and gene interactions is growing, but frameworks to build an association between gene-environment interactions and disease using preexisting, publicly available data has been lacking. Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease. Methods We integrated publicly available disease-specific gene expression microarray data and curated chemical-gene interaction data to systematically predict environmental chemicals associated with disease. We derived chemical-gene signatures for 1,338 chemical/environmental chemicals from the Comparative Toxicogenomics Database (CTD). We associated these chemical-gene signatures with differentially expressed genes from datasets found in the Gene Expression Omnibus (GEO) through an enrichment test. Results We were able to verify our analytic method by accurately identifying chemicals applied to samples and cell lines. Furthermore, we were able to predict known and novel environmental associations with prostate, lung, and breast cancers, such as estradiol and bisphenol A. Conclusions We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature. PMID:20459635

  18. 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

  19. 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

  20. Diagnostic value of blood gene expression signatures in active tuberculosis in Thais: a pilot study.

    PubMed

    Satproedprai, N; Wichukchinda, N; Suphankong, S; Inunchot, W; Kuntima, T; Kumpeerasart, S; Wattanapokayakit, S; Nedsuwan, S; Yanai, H; Higuchi, K; Harada, N; Mahasirimongkol, S

    2015-06-01

    Tuberculosis (TB) is a major global health problem. Routine laboratory tests or newly developed molecular detection are limited to the quality of sputum sample. Here we selected genes specific to TB by a minimum redundancy-maximum relevancy package using publicly available microarray data and determine level of selected genes in blood collected from a Thai TB cohort of 40 active TB patients, 38 healthy controls and 18 previous TB patients using quantitative real-time PCR. FCGR1A, FCGR1B variant 1, FCGR1B variant 2, APOL1, GBP5, PSTPIP2, STAT1, KCNJ15, MAFB and KAZN had significantly higher expression level in active TB individuals as compared with healthy controls and previous TB cases (P<0.01). A mathematical method was applied to calculate TB predictive score, which contains the level of expression of seven genes and this score can identify active TB cases with 82.5% sensitivity and 100% specificity as compared with conventional culture confirmation. In addition, TB predictive scores in active TB patients were reduced to normal after completion of standard short-course therapy, which was mostly in concordant with the disease outcome. These finding suggested that blood gene expression measurement and TB Sick Score could have potential value in terms of diagnosis of TB and anti-TB treatment monitoring.

  1. Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer

    PubMed Central

    Yang, Xinan; Regan, Kelly; Huang, Yong; Zhang, Qingbei; Li, Jianrong; Seiwert, Tanguy Y.; Cohen, Ezra E. W.; Xing, H. Rosie; Lussier, Yves A.

    2012-01-01

    Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p<0.001) is more significant than the gene overlap (genes:4%). These Oncogenic FAIME Features of HNSCC can accurately discriminate tumors from control tissues in two additional HNSCC datasets (n = 35 and 91, F-accuracy = 100% and 97%, empirical p<0.001, area under the receiver operating characteristic curves = 99% and 92%), and stratify recurrence-free survival in patients from two independent studies (p = 0.0018 and p = 0.032, log-rank). Previous approaches depending on group assignment of individual samples before selecting features or learning a classifier are limited by design to

  2. Small RNA cloning and sequencing strategy affects host and viral microRNA expression signatures.

    PubMed

    Stik, Grégoire; Muylkens, Benoît; Coupeau, Damien; Laurent, Sylvie; Dambrine, Ginette; Messmer, Mélanie; Chane-Woon-Ming, Béatrice; Pfeffer, Sébastien; Rasschaert, Denis

    2014-07-10

    The establishment of the microRNA (miRNA) expression signatures is the basic element to investigate the role played by these regulatory molecules in the biology of an organism. Marek's disease virus 1 (MDV-1) is an avian herpesvirus that naturally infects chicken and induces T cells lymphomas. During latency, MDV-1, like other herpesviruses, expresses a limited subset of transcripts. These include three miRNA clusters. Several studies identified the expression of virus and host encoded miRNAs from MDV-1 infected cell cultures and chickens. But a high discrepancy was observed when miRNA cloning frequencies obtained from different cloning and sequencing protocols were compared. Thus, we analyzed the effect of small RNA library preparation and sequencing on the miRNA frequencies obtained from the same RNA samples collected during MDV-1 infection of chicken at different steps of the oncoviral pathogenesis. Qualitative and quantitative variations were found in the data, depending on the strategy used. One of the mature miRNA derived from the latency-associated-transcript (LAT), mdv1-miR-M7-5p, showed the highest variation. Its cloning frequency was 50% of the viral miRNA counts when a small scale sequencing approach was used. Its frequency was 100 times less abundant when determined through the deep sequencing approach. Northern blot analysis showed a better correlation with the miRNA frequencies found by the small scale sequencing approach. By analyzing the cellular miRNA repertoire, we also found a gap between the two sequencing approaches. Collectively, our study indicates that next-generation sequencing data considered alone are limited for assessing the absolute copy number of transcripts. Thus, the quantification of small RNA should be addressed by compiling data obtained by using different techniques such as microarrays, qRT-PCR and NB analysis in support of high throughput sequencing data. These observations should be considered when miRNA variations are studied

  3. Leptin, BMI, and a Metabolic Gene Expression Signature Associated with Clinical Outcome to VEGF Inhibition in Colorectal Cancer.

    PubMed

    Pommier, Aurélien J C; Farren, Matthew; Patel, Bhavika; Wappett, Mark; Michopoulos, Filippos; Smith, Neil R; Kendrew, Jane; Frith, Jeremy; Huby, Russell; Eberlein, Catherine; Campbell, Hayley; Womack, Christopher; Smith, Paul D; Robertson, Jane; Morgan, Shethah; Critchlow, Susan E; Barry, Simon T

    2016-01-12

    VEGF (vascular endothelial growth factor) signaling inhibitors are widely used in different cancer types; however, patient selection remains a challenge. Analyses of samples from a phase III clinical trial in metastatic colorectal cancer testing chemotherapy versus chemotherapy with the small molecule VEGF receptors inhibitor cediranib identified circulating leptin levels, BMI, and a tumor metabolic and angiogenic gene expression signature associated with improved clinical outcome in patients treated with cediranib. Patients with a glycolytic and hypoxic/angiogenic profile were associated with increased benefit from cediranib, whereas patients with a high lipogenic, oxidative phosphorylation and serine biosynthesis signature did not gain benefit. These findings translated to pre-clinical tumor xenograft models where the same metabolic gene expression profiles were associated with in vivo sensitivity to cediranib as monotherapy. These findings suggest a link between patient physiology, tumor biology, and response to antiangiogenics, which may guide patient selection for VEGF therapy in the future. PMID:26626460

  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. miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients

    PubMed Central

    Zadran, Sohila; Remacle, F.; Levine, R. D.

    2013-01-01

    Toward identifying a cancer-specific gene signature we applied surprisal analysis to the RNAs expression behavior for a large cohort of breast, lung, ovarian, and prostate carcinoma patients. We characterize the cancer phenotypic state as a shared response of a set of mRNA or microRNAs (miRNAs) in cancer patients versus noncancer controls. The resulting signature is robust with respect to individual patient variability and distinguishes with high fidelity between cancer and noncancer patients. The mRNAs and miRNAs that are implicated in the signature are correlated and are known to contribute to the regulation of cancer-signaling pathways. The miRNA and mRNA networks are common to the noncancer and cancer patients, but the disease modulates the strength of the connectivities. Furthermore, we experimentally assessed the cancer-specific signatures as possible therapeutic targets. Specifically we restructured a single dominant connectivity in the cancer-specific gene network in vitro. We find a deflection from the cancer phenotype, significantly reducing cancer cell proliferation and altering cancer cellular physiology. Our approach is grounded in thermodynamics augmented by information theory. The thermodynamic reasoning is demonstrated to ensure that the derived signature is bias-free and shows that the most significant redistribution of free energy occurs in programming a system between the noncancer and cancer states. This paper introduces a platform that can elucidate miRNA and mRNA behavior on a systems level and provides a comprehensive systematic view of both the energetics of the expression levels of RNAs and of their changes during tumorigenicity. PMID:24101511

  6. Precise predictions for top-quark-plus-missing-energy signatures at the LHC.

    PubMed

    Boughezal, Radja; Schulze, Markus

    2013-05-10

    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.

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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

  13. Expanded Non-human Primate Tregs Exhibit A Unique Gene Expression Signature and Potently Downregulate Allo-immune Responses

    PubMed Central

    Anderson, Alan; Martens, Christine; Hendrix, Rose; Stempora, Linda; Miller, Wes; Hamby, Kelly; Russell, Maria; Strobert, Elizabeth; Blazar, Bruce R.; Pearson, Thomas C.; Larsen, Christian P.; Kean, Leslie S.

    2009-01-01

    We have established two complementary strategies for purifying naturally occurring regulatory T cells (Tregs) from rhesus macaques in quantities which would be sufficient for use as an in vivo cellular therapeutic. The first identified Tregs based on their being CD4+/CD25bright. The second incorporated CD127, and purified Tregs based on their expression of CD4 and CD25 and their low expression of CD127. Using these purification strategies, we were able to purify as many as 1×106 Tregs from 120cc of peripheral blood. Culture of these cells with anti-CD3, anti-CD28 and IL-2 over 21 days yielded as much as 450-fold expansion, ultimately producing as many as 4.7×108 Tregs. Expanded Treg cultures potently inhibited alloimmune proliferation as measured by a CFSE-MLR assay even at a 1:100 ratio with responder T cells. Furthermore, both responder-specific and third-party Tregs downregulated alloproliferation similarly. Both freshly isolated and cultured Tregs had gene expression signatures distinguishable from concurrently isolated bulk CD4+ T cell populations, as measured by single-plex RT-PCR and gene array. Moreover, an overlapping yet distinct gene expression signature seen in freshly isolated compared to expanded Tregs identifies a subset of Treg genes likely to be functionally significant. PMID:18801023

  14. 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.

  15. 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

  16. 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

  17. 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

  18. Abnormal energy regulation in early life: childhood gene expression may predict subsequent chronic mountain sickness

    PubMed Central

    Huicho, Luis; Xing, Guoqiang; Qualls, Clifford; Rivera-Ch, María; Gamboa, Jorge L; Verma, Ajay; Appenzeller, Otto

    2008-01-01

    Background Life at altitude depends on adaptation to ambient hypoxia. In the Andes, susceptibility to chronic mountain sickness (CMS), a clinical condition that occurs to native highlanders or to sea level natives with prolonged residence at high altitude, remains poorly understood. We hypothesized that hypoxia-associated gene expression in children of men with CMS might identify markers that predict the development of CMS in adults. We assessed distinct patterns of gene expression of hypoxia-responsive genes in children of highland Andean men, with and without CMS. Methods We compared molecular signatures in children of highland (HA) men with CMS (n = 10), without CMS (n = 10) and in sea level (SL) children (n = 20). Haemoglobin, haematocrit, and oxygen saturation were measured. Gene expression in white cells was assessed at HA and then, in the same subjects, within one hour of arrival at sea level. Results HA children showed higher expression levels of genes regulated by HIF (hypoxia inducible factor) and lower levels of those involved in glycolysis and in the tricarboxilic acid (TCA) cycle. Pyruvate dehydrogenase kinase 1(PDK1) and HIF prolyl hydroxylase 3 (HPH3) mRNA expressions were lowest in children of CMS fathers at altitude. At sea level the pattern of gene expression in the 3 children's groups was indistinguishable. Conclusion The molecular signatures of children of CMS patients show impaired adaptation to hypoxia. At altitude children of CMS fathers had defective coupling between glycolysis and mitochondria TCA cycle, which may be a key mechanism/biomarker for adult CMS. Early biologic markers of disease susceptibility in Andeans might impact health services and social planning. PMID:18954447

  19. 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

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

    PubMed

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

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

  1. Updates on fuze and SAR modes in RF channel for Irma 5.2 signature prediction model

    NASA Astrophysics Data System (ADS)

    Willis, Carla; Coker, Charles; Thai, Bea; Aboutalib, Omar; Pau, John

    2009-05-01

    The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/RWGG) to facilitate the research and development of advanced weapon seekers Irma began as a high-resolution, physics-based infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and a passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after extensive verification and validation of an upgraded and reengineered ladar channel. In 2007, version 5.2 was released with a reengineered passive channel. The current Irma development effort is focused on the reengineering of the radar channel with an expected release of Irma 5.3 in 2009. This paper reports on two of the radar modes expected to be supported in the radar channel: the fuze mode and the spotlight synthetic aperture radar (SAR) mode.

  2. 76 FR 62000 - Express Mail Domestic Postage Refund Policy and Waiver of Signature

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-06

    ... * * * * * 110 Express Mail 113 Prices and Eligibility * * * * * 4.0 Service Features of Express Mail 4.1 General... Cards * * * * * 210 Express Mail 213 Prices and Eligibility * * * * * 4.0 Service Features of Express... Custom Designed service. * * * * * 300 Commercial Flats * * * * * 310 Express Mail 313 Prices...

  3. 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...

  4. 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

  5. Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

    PubMed Central

    2011-01-01

    Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management. PMID:21787441

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

    PubMed Central

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

    2016-01-01

    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

  7. 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

  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. Intraindividual genome expression analysis reveals a specific molecular signature of psoriasis and eczema.

    PubMed

    Quaranta, Maria; Knapp, Bettina; Garzorz, Natalie; Mattii, Martina; Pullabhatla, Venu; Pennino, Davide; Andres, Christian; Traidl-Hoffmann, Claudia; Cavani, Andrea; Theis, Fabian J; Ring, Johannes; Schmidt-Weber, Carsten B; Eyerich, Stefanie; Eyerich, Kilian

    2014-07-01

    Previous attempts to gain insight into the pathogenesis of psoriasis and eczema by comparing their molecular signatures were hampered by the high interindividual variability of those complex diseases. In patients affected by both psoriasis and nonatopic or atopic eczema simultaneously (n = 24), an intraindividual comparison of the molecular signatures of psoriasis and eczema identified genes and signaling pathways regulated in common and exclusive for each disease across all patients. Psoriasis-specific genes were important regulators of glucose and lipid metabolism, epidermal differentiation, as well as immune mediators of T helper 17 (TH17) responses, interleukin-10 (IL-10) family cytokines, and IL-36. Genes in eczema related to epidermal barrier, reduced innate immunity, increased IL-6, and a TH2 signature. Within eczema subtypes, a mutually exclusive regulation of epidermal differentiation genes was observed. Furthermore, only contact eczema was driven by inflammasome activation, apoptosis, and cellular adhesion. On the basis of this comprehensive picture of the pathogenesis of psoriasis and eczema, a disease classifier consisting of NOS2 and CCL27 was created. In an independent cohort of eczema (n = 28) and psoriasis patients (n = 25), respectively, this classifier diagnosed all patients correctly and also identified initially misdiagnosed or clinically undifferentiated patients.

  10. Transcriptional Signatures Related to Glucose and Lipid Metabolism Predict Treatment Response to the Tumor Necrosis Factor Antagonist Infliximab in Patients with Treatment-Resistant Depression

    PubMed Central

    Mehta, Divya; Raison, Charles L.; Woolwine, Bobbi J.; Haroon, Ebrahim; Binder, Elisabeth B.; Miller, Andrew H.; Felger, Jennifer C.

    2013-01-01

    The tumor necrosis factor (TNF) antagonist infliximab was recently found to reduce depressive symptoms in patients with increased baseline inflammation as reflected by a plasma C-reactive protein concentration >5mg/L. To further explore predictors and targets of response to infliximab, differential gene expression was examined in peripheral blood mononuclear cells from infliximab responders (n=13) versus non-responders (n=14) compared to placebo at baseline and 6hr, 24hr, and 2 weeks after the first infliximab infusion. Treatment response was defined as 50% reduction in depressive symptoms at any point during the 12-week trial. One-hundred-forty-eight gene transcripts were significantly associated (1.2 fold, adjusted p≤0.01) with response to infliximab and were distinct from placebo responders. Transcripts predictive of infliximab response were associated with gluconeogenesis and cholesterol transport, and were enriched in a network regulated by hepatocyte nuclear factor (HNF)4-alpha, a transcription factor involved in gluconeogenesis and cholesterol and lipid homeostasis. Of the 148 transcripts differentially expressed at baseline, 48% were significantly regulated over time in infliximab responders, including genes related to gluconeogenesis and the HNF4-alpha network, indicating that these predictive genes were responsive to infliximab. Responders also demonstrated inhibition of genes related to apoptosis through TNF signaling at 6hr and 24hr after infusion. Transcripts down-regulated in responders 2 weeks after infliximab were related to innate immune signaling and nuclear factor-kappa B. Thus, baseline transcriptional signatures reflective of alterations in glucose and lipid metabolism predicted antidepressant response to infliximab, and infliximab response involved regulation of metabolic genes and inhibition of genes related to innate immune activation. PMID:23624296

  11. 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

  12. Sorghum expressed sequence tags identify signature genes for drought, pathogenesis, and skotomorphogenesis from a milestone set of 16,801 unique transcripts.

    PubMed

    Pratt, Lee H; Liang, Chun; Shah, Manish; Sun, Feng; Wang, Haiming; Reid, St Patrick; Gingle, Alan R; Paterson, Andrew H; Wing, Rod; Dean, Ralph; Klein, Robert; Nguyen, Henry T; Ma, Hong-Mei; Zhao, Xin; Morishige, Daryl T; Mullet, John E; Cordonnier-Pratt, Marie-Michèle

    2005-10-01

    Improved knowledge of the sorghum transcriptome will enhance basic understanding of how plants respond to stresses and serve as a source of genes of value to agriculture. Toward this goal, Sorghum bicolor L. Moench cDNA libraries were prepared from light- and dark-grown seedlings, drought-stressed plants, Colletotrichum-infected seedlings and plants, ovaries, embryos, and immature panicles. Other libraries were prepared with meristems from Sorghum propinquum (Kunth) Hitchc. that had been photoperiodically induced to flower, and with rhizomes from S. propinquum and johnsongrass (Sorghum halepense L. Pers.). A total of 117,682 expressed sequence tags (ESTs) were obtained representing both 3' and 5' sequences from about half that number of cDNA clones. A total of 16,801 unique transcripts, representing tentative UniScripts (TUs), were identified from 55,783 3' ESTs. Of these TUs, 9,032 are represented by two or more ESTs. Collectively, these libraries were predicted to contain a total of approximately 31,000 TUs. Individual libraries, however, were predicted to contain no more than about 6,000 to 9,000, with the exception of light-grown seedlings, which yielded an estimate of close to 13,000. In addition, each library exhibits about the same level of complexity with respect to both the number of TUs preferentially expressed in that library and the frequency with which two or more ESTs is found in only that library. These results indicate that the sorghum genome is expressed in highly selective fashion in the individual organs and in response to the environmental conditions surveyed here. Close to 2,000 differentially expressed TUs were identified among the cDNA libraries examined, of which 775 were differentially expressed at a confidence level of 98%. From these 775 TUs, signature genes were identified defining drought, Colletotrichum infection, skotomorphogenesis (etiolation), ovary, immature panicle, and embryo.

  13. 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

  14. Proteomic signature of Temporomandibular Joint Disorders (TMD): Toward diagnostically predictive biomarkers

    PubMed Central

    Demerjian, Garabed Gary; Sims, Anothony Benjamin; Stack, Brendan Curran

    2011-01-01

    The temporomandibular joint (TMJ) articulates the mandible with the maxilla. Temporomandibular joint disorders (TMD) are dysfunctions of this joint, which range from acute to chronic inflammation, trauma and dislocations, developmental anomalies and neoplasia. TMD manifest as signs and symptoms that involve the surrounding muscles, ligaments, bones, synovial capsule, connective tissue, teeth and innervations proximal and distal to this joint. TMD induce proximal and distal, chronic and acute, dull or intense pain and discomfort, muscle spasm, clicking/popping sounds upon opening and closing of the mouth, and chewing or speaking difficulties. The trigeminal cranial nerve V, and its branches provide the primary sensory innervation to the TMJ. Our clinical work suggests that the auriculotemporal (AT) nerve, a branch of the mandibular nerve, the largest of the three divisions of the trigeminal nerve, plays a critical role in TMD sequelae. The AT nerve provides the somatosensory fibers that supply the joint, the middle ear, and the temporal region. By projecting fibers toward the otic ganglion, the AT nerve establishes an important bridge to the sympathetic system. As it courses posteriorly to the condylar head of the TMJ, compression, injury or irritation of the AT nerve can lead to significant neurologic and neuro-muscular disorders, including Tourette's syndrome,Torticolli, gait or balance disorders and Parkinson’s disease. Here, we propose that a proteomic signature of TMD can be obtained by assessing certain biomarkers in local (e.g., synovial fluid at the joint) and distal body fluids (e.g., saliva, cerebrospinal fluid), which can aid TMD diagnosis and prognosis. PMID:21364835

  15. 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

  16. 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...

  17. 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...

  18. 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...

  19. Embryo quality predictive models based on cumulus cells gene expression

    PubMed Central

    Burnik Papler, T; Verdenik, I; Fon Tacer, K; Vrtačnik Bokal, E

    2016-01-01

    Abstract Since the introduction of in vitro fertilization (IVF) in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC) have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR)] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC) for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice. PMID:27785402

  20. A gene expression signature associated with “K-Ras addiction” reveals regulators of EMT and tumor cell survival

    PubMed Central

    Singh, Anurag; Greninger, Patricia; Rhodes, Daniel; Koopman, Louise; Violette, Sheila; Bardeesy, Nabeel; Settleman, Jeff

    2009-01-01

    SUMMARY K-Ras mutations occur frequently in epithelial cancers. Using shRNAs to deplete K-Ras in lung and pancreatic cancer cell lines harboring K-Ras mutations, two classes were identified—lines that do or do not require K-Ras to maintain viability. Comparing these two classes of cancer cells revealed a gene expression signature in K-Ras-dependent cells, associated with a well-differentiated epithelial phenotype, which was also seen in primary tumors. Several of these genes encode pharmacologically tractable proteins, such as Syk and Ron kinases and integrin beta6, depletion of which induces epithelial-mesenchymal transformation (EMT) and apoptosis specifically in K-Ras-dependent cells. These findings indicate that epithelial differentiation and tumor cell viability are associated, and that EMT regulators in “K-Ras-addicted” cancers represent candidate therapeutic targets. SIGNIFICANCE K-Ras is the most frequently mutated oncogene in solid tumors and when aberrantly activated, is a potent tumor initiator. However, the identification of the critical effectors of K-Ras-mediated tumorigenesis and the development of clinically effective therapeutic strategies in this setting remain challenging. We have found that cancer cell lines harboring K-Ras mutations can be broadly classified into K-Ras-dependent and K-Ras-independent groups. By establishing a gene expression signature that can distinguish these two groups, we identified genes that are specifically up-regulated in K-Ras-dependent cells and are required for their viability. Therefore, the K-Ras dependency signature has revealed several potential therapeutic targets in a subset of otherwise pharmacologically intractable human cancers. PMID:19477428

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

    PubMed

    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

    2013-04-01

    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 3Mb 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.

  2. 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

  3. 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

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

    PubMed

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

    2007-07-01

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

  5. Peripheral Blood Mononuclear Cell Gene Expression Profiles Predict Poor Outcome in Idiopathic Pulmonary Fibrosis

    PubMed Central

    Herazo-Maya, Jose D.; Noth, Imre; Duncan, Steven R.; Kim, SungHwan; Ma, Shwu-Fan; Tseng, George C.; Feingold, Eleanor; Juan-Guardela, Brenda M.; Richards, Thomas J.; Lussier, Yves; Huang, Yong; Vij, Rekha; Lindell, Kathleen O.; Xue, Jianmin; Gibson, Kevin F.; Shapiro, Steven D.; Garcia, Joe G. N.; Kaminski, Naftali

    2014-01-01

    We aimed to identify peripheral blood mononuclear cell (PBMC) gene expression profiles predictive of poor outcomes in idiopathic pulmonary fibrosis (IPF) by performing microarray experiments of PBMCs in discovery and replication cohorts of IPF patients. Microarray analyses identified 52 genes associated with transplant-free survival (TFS) in the discovery cohort. Clustering the microarray samples of the replication cohort using the 52-gene outcome-predictive signature distinguished two patient groups with significant differences in TFS. We studied the pathways associated with TFS in each independent microarray cohort and identified decreased expression of “The costimulatory signal during T cell activation” Biocarta pathway and, in particular, the genes CD28, ICOS, LCK, and ITK, results confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A proportional hazards model, including the qRT-PCR expression of CD28, ICOS, LCK, and ITK along with patient’s age, gender, and percent predicted forced vital capacity (FVC%), demonstrated an area under the receiver operating characteristic curve of 78.5% at 2.4 months for death and lung transplant prediction in the replication cohort. To evaluate the potential cellular source of CD28, ICOS, LCK, and ITK expression, we analyzed and found significant correlation of these genes with the PBMC percentage of CD4+CD28+ T cells in the replication cohort. Our results suggest that CD28, ICOS, LCK, and ITK are potential outcome biomarkers in IPF and should be further evaluated for patient prioritization for lung transplantation and stratification in drug studies. PMID:24089408

  6. 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

  7. Abnormal gene expression profile reveals the common key signatures associated with clear cell renal cell carcinoma: a meta-analysis.

    PubMed

    Zhang, H J; Sun, Z Q; Qian, W Q; Sheng, L

    2015-01-01

    The aims of this study were to identify the common gene signatures of clear cell renal cell carcinoma (CCRCC), and to expand the respective protein-protein interaction networks associated with CCRCC regulation. For the latter, we utilized multiple gene expression data sets from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), with which we could analyze the aberrant gene expression patterns at the transcriptome level that distinguish cancer from normal samples. We obtained the GSE781 and GSE6344 clear cell renal cell carcinoma gene expression datasets from GEO, which contained a total of 37 cancer and 37 normal samples. Subsequent R language analysis allowed identification of the differentially expressed genes. The genes that exhibited significant up or downregulation in cancers were entered into the Database for Annotation, Visualization, and Integrated Discovery to perform analysis of gene functional annotations, resulting in the generation of two protein-protein interaction networks that included the most significantly up or downregulated genes in CCRCC. These allowed us to identify the key factor genes, which could potentially be utilized to separate cancer versus normal samples. The differentially regulated genes are also highly likely to be functionally important regulatory factors in renal cell carcinoma: cell functions showing enrichment of these genes include amine biosynthetic and vitamin metabolic processes, ion binding, extracellular transport function, and regulation of biosynthesis. Together, the results from our study offer further reason to pursue diagnosis and therapy of CCRCC at the molecular level. PMID:25867368

  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. 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

  10. Evaluation and Integration of Genetic Signature for Prediction Risk of Nasopharyngeal Carcinoma in Southern China

    PubMed Central

    Winkler, Cheryl A.; Li, Ji; Guan, Li; Tang, Minzhong; Liao, Jian; Deng, Hong; de Thé, Guy; Zeng, Yi; O'Brien, Stephen J.

    2014-01-01

    Genetic factors, as well as environmental factors, play a role in development of nasopharyngeal carcinoma (NPC). A number of single nucleotide polymorphisms (SNPs) have been reported to be associated with NPC. To confirm these genetic associations with NPC, two independent case-control studies from Southern China comprising 1166 NPC cases and 2340 controls were conducted. Seven SNPs in ITGA9 at 3p21.3 and 9 SNPs within the 6p21.3 HLA region were genotyped. To explore the potential clinical application of these genetic markers in NPC, we further evaluate the predictive/diagnostic role of significant SNPs by calculating the area under the curve (AUC). Results. The reported associations between ITGA9 variants and NPC were not replicated. Multiple loci of GABBR1, HLA-F, HLA-A, and HCG9 were statistically significant in both cohorts (Pcombined range from 5.96 × 10−17 to 0.02). We show for the first time that these factors influence NPC development independent of environmental risk factors. This study also indicated that the SNP alone cannot serve as a predictive/diagnostic marker for NPC. Integrating the most significant SNP with IgA antibodies status to EBV, which is presently used as screening/diagnostic marker for NPC in Chinese populations, did not improve the AUC estimate for diagnosis of NPC. PMID:25180181

  11. The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil

    PubMed Central

    2011-01-01

    Background Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase). The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH), which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP) and iodoacetate (IA), and the anti-metabolite, 5-fluorouracil (5-FU). Methods The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. Results We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Conclusions Overall, we suggest that the determination of the bioenergetic

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. Gene expression profiling of CD34+ cells identifies a molecular signature of chronic myeloid leukemia blast crisis.

    PubMed

    Zheng, C; Li, L; Haak, M; Brors, B; Frank, O; Giehl, M; Fabarius, A; Schatz, M; Weisser, A; Lorentz, C; Gretz, N; Hehlmann, R; Hochhaus, A; Seifarth, W

    2006-06-01

    Despite recent success in the treatment of early-stage disease, blastic phase (BP) of chronic myeloid leukemia (CML) that is characterized by rapid expansion of therapy-refractory and differentiation-arrested blasts, remains a therapeutic challenge. The development of resistance upon continuous administration of imatinib mesylate is associated with poor prognosis pointing to the need for alternative therapeutic strategies and a better understanding of the molecular mechanisms underlying disease progression. To identify transcriptional signatures that may explain pathological characteristics and aggressive behavior of BP blasts, we performed comparative gene expression profiling on CD34+ Ph+ cells purified from patients with untreated newly diagnosed chronic phase CML (CP, n=11) and from patients in BP (n=9) using Affymetrix oligonucleotide arrays. Supervised microarray data analysis revealed 114 differentially expressed genes (P<10(-4)), 34 genes displaying more than two-fold transcriptional changes when comparing CP and BP groups. While 24 of these genes were downregulated, 10 genes, especially suppressor of cytokine signalling 2 (SOCS2), CAMPATH-1 antigen (CD52), and four human leukocyte antigen-related genes were strongly overexpressed in BP. Expression of selected genes was validated by real-time-polymerase chain reaction and flow cytometry. Our data suggest the existence of a common gene expression profile of CML-BP and provide new insight into the molecular phenotype of blasts associated with disease progression and high malignancy. PMID:16617318

  17. 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

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

    PubMed

    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

    2015-08-28

    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.

  19. 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

  20. A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms.

    PubMed

    Plank, Michael; Wuttke, Daniel; van Dam, Sipko; Clarke, Susan A; de Magalhães, João Pedro

    2012-04-01

    Caloric restriction, a reduction in calorie intake without malnutrition, retards age-related degeneration and extends lifespan in several organisms. CR induces multiple changes, yet its underlying mechanisms remain poorly understood. In this work, we first performed a meta-analysis of microarray CR studies in mammals and identified genes and processes robustly altered due to CR. Our results reveal a complex array of CR-induced changes and we re-identified several genes and processes previously associated with CR, such as growth hormone signalling, lipid metabolism and immune response. Moreover, our results highlight novel associations with CR, such as retinol metabolism and copper ion detoxification, as well as hint of a strong effect of CR on circadian rhythms that in turn may contribute to metabolic changes. Analyses of our signatures by integrating co-expression data, information on genetic mutants, and transcription factor binding site analysis revealed candidate regulators of transcriptional modules in CR. Our results hint at a transcriptional module involved in sterol metabolism regulated by Srebf1. A putative regulatory role of Ppara was also identified. Overall, our conserved molecular signatures of CR provide a comprehensive picture of CR-induced changes and help understand its regulatory mechanisms.

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

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-02

    ... published a Federal Register proposed rule (76 FR 62000-62002) inviting comments on revisions to the... Prices and Eligibility * * * * * 4.0 Service Features of Express Mail 4.1 General [Revise the text of 4.1... Cards * * * * * 210 Express Mail 213 Prices and Eligibility * * * * * 4.0 Service Features of...

  2. 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

  3. Predicting polarization signatures for double-detonation and delayed-detonation models of Type Ia supernovae

    NASA Astrophysics Data System (ADS)

    Bulla, M.; Sim, S. A.; Kromer, M.; Seitenzahl, I. R.; Fink, M.; Ciaraldi-Schoolmann, F.; Röpke, F. K.; Hillebrandt, W.; Pakmor, R.; Ruiter, A. J.; Taubenberger, S.

    2016-10-01

    Calculations of synthetic spectropolarimetry are one means to test multidimensional explosion models for Type Ia supernovae. In a recent paper, we demonstrated that the violent merger of a 1.1 and 0.9 M⊙ white dwarf binary system is too asymmetric to explain the low polarization levels commonly observed in normal Type Ia supernovae. Here, we present polarization simulations for two alternative scenarios: the sub-Chandrasekhar mass double-detonation and the Chandrasekhar mass delayed-detonation model. Specifically, we study a 2D double-detonation model and a 3D delayed-detonation model, and calculate polarization spectra for multiple observer orientations in both cases. We find modest polarization levels (<1 per cent) for both explosion models. Polarization in the continuum peaks at ˜0.1-0.3 per cent and decreases after maximum light, in excellent agreement with spectropolarimetric data of normal Type Ia supernovae. Higher degrees of polarization are found across individual spectral lines. In particular, the synthetic Si II λ6355 profiles are polarized at levels that match remarkably well the values observed in normal Type Ia supernovae, while the low degrees of polarization predicted across the O I λ7774 region are consistent with the non-detection of this feature in current data. We conclude that our models can reproduce many of the characteristics of both flux and polarization spectra for well-studied Type Ia supernovae, such as SN 2001el and SN 2012fr. However, the two models considered here cannot account for the unusually high level of polarization observed in extreme cases such as SN 2004dt.

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

    PubMed

    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.

  5. High expression of DEK predicts poor prognosis of gastric adenocarcinoma

    PubMed Central

    2014-01-01

    Background DEK, as an oncoprotein, plays an important role in cancer development and progression. This study aimed to investigate the clinicopathological significance of DEK overexpression in patients with gastric cancer. Materials and methods The expression of DEK protein was evaluated by immunohistochemical (IHC) staining of 172 gastric cancer samples with complete clinicopathological features, and the correlation between DEK expression and clinicopathological features was examined. Survival rates were also calculated using the Kaplan-Meier method in gastric cancer patients with complete survival data. Results DEK protein showed a strictly nuclear staining pattern in gastric cancers with IHC and immunofluorescence. The strongly positive rate of DEK protein was 60.5% (104/172) in gastric cancers, which was significantly higher than that in either gastric dysplasia (19.4%, 7/36) or adjacent normal mucosa (0%, 0/27). DEK expression in gastric cancer correlated to tumor size, differentiation, clinical stage, disease-free survival, and overall survival rates. Further analysis showed that patients with early-stage gastric cancer and high DEK expression had shorter disease-free survival and overall survival duration than those with low DEK expression. Conclusion High level of DEK protein expression predicts the poor prognosis of patients with gastric cancer. DEK expression might be potentially used as an independent effective biomarker for prognostic evaluation of gastric cancers. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5050145571193097 PMID:24650035

  6. Prognostic Importance of MN1 Transcript Levels, and Biologic Insights From MN1-Associated Gene and MicroRNA Expression Signatures in Cytogenetically Normal Acute Myeloid Leukemia: A Cancer and Leukemia Group B Study

    PubMed Central

    Langer, Christian; Marcucci, Guido; Holland, Kelsi B.; Radmacher, Michael D.; Maharry, Kati; Paschka, Peter; Whitman, Susan P.; Mrózek, Krzysztof; Baldus, Claudia D.; Vij, Ravi; Powell, Bayard L.; Carroll, Andrew J.; Kolitz, Jonathan E.; Caligiuri, Michael A.; Larson, Richard A.; Bloomfield, Clara D.

    2009-01-01

    Purpose To determine the prognostic importance of the meningioma 1 (MN1) gene expression levels in the context of other predictive molecular markers, and to derive MN1 associated gene– and microRNA–expression profiles in cytogenetically normal acute myeloid leukemia (CN-AML). Patients and Methods MN1 expression was measured in 119 untreated primary CN-AML adults younger than 60 years by real-time reverse-transcriptase polymerase chain reaction. Patients were also tested for FLT3, NPM1, CEBPA, and WT1 mutations, MLL partial tandem duplications, and BAALC and ERG expression. Gene- and microRNA-expression profiles were attained by performing genome-wide microarray assays. Patients were intensively treated on two first-line Cancer and Leukemia Group B clinical trials. Results Higher MN1 expression associated with NPM1 wild-type (P < .001), increased BAALC expression (P = .004), and less extramedullary involvement (P = .01). In multivariable analyses, higher MN1 expression associated with a lower complete remission rate (P = .005) after adjustment for WBC; shorter disease-free survival (P = .01) after adjustment for WT1 mutations, FLT3 internal tandem duplications (FLT3-ITD), and high ERG expression; and shorter survival (P = .04) after adjustment for WT1 and NPM1 mutations, FLT3-ITD, and WBC. Gene- and microRNA-expression profiles suggested that high MN1 expressers share features with high BAALC expressers and patients with wild-type NPM1. Higher MN1 expression also appears to be associated with genes and microRNAs that are active in aberrant macrophage/monocytoid function and differentiation. Conclusion MN1 expression independently predicts outcome in CN-AML patients. The MN1 gene- and microRNA-expression signatures suggest biologic features that could be exploited as therapeutic targets. PMID:19451432

  7. 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

  8. 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

  9. Expression of a retinoic acid signature in circulating CD34 cells from coronary artery disease patients

    PubMed Central

    2010-01-01

    Background Circulating CD34+ progenitor cells have the potential to differentiate into a variety of cells, including endothelial cells. Knowledge is still scarce about the transcriptional programs used by CD34+ cells from peripheral blood, and how these are affected in coronary artery disease (CAD) patients. Results We performed a whole genome transcriptome analysis of CD34+ cells, CD4+ T cells, CD14+ monocytes, and macrophages from 12 patients with CAD and 11 matched controls. CD34+ cells, compared to other mononuclear cells from the same individuals, showed high levels of KRAB box transcription factors, known to be involved in gene silencing. This correlated with high expression levels in CD34+ cells for the progenitor markers HOXA5 and HOXA9, which are known to control expression of KRAB factor genes. The comparison of expression profiles of CD34+ cells from CAD patients and controls revealed a less naïve phenotype in patients' CD34+ cells, with increased expression of genes from the Mitogen Activated Kinase network and a lowered expression of a panel of histone genes, reaching levels comparable to that in more differentiated circulating cells. Furthermore, we observed a reduced expression of several genes involved in CXCR4-signaling and migration to SDF1/CXCL12. Conclusions The altered gene expression profile of CD34+ cells in CAD patients was related to activation/differentiation by a retinoic acid-induced differentiation program. These results suggest that circulating CD34+ cells in CAD patients are programmed by retinoic acid, leading to a reduced capacity to migrate to ischemic tissues. PMID:20565948

  10. Biomarker discovery to improve prediction of breast cancer survival: using gene expression profiling, meta-analysis, and tissue validation

    PubMed Central

    Meng, Liwei; Xu, Yingchun; Xu, Chaoyang; Zhang, Wei

    2016-01-01

    Purpose Breast cancer is the leading cause of cancer death worldwide in women. The molecular mechanism for human breast cancer is unknown. Gene microarray has been widely used in breast cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis survival. So far, the valuable multigene signatures in clinical practice are unclear, and the biological importance of individual genes is difficult to detect, as the described signatures virtually do not overlap. Early prognosis of this disease, breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS), is vital in breast surgery. Methods Thus, this study reports gene expression profiling in large breast cancer cohorts from Gene Expression Omnibus, including GSE29044 (N=138) and GSE10780 (N=185) test series and four independent validation series GSE21653 (N=266), GSE20685 (N=327), GSE26971 (N=276), and GSE12776 (N=204). Significantly differentially expressed genes in human breast IDC and breast DCIS were detected by transcriptome microarray analysis. Results We created a set of three genes (MAMDC2, TSHZ2, and CLDN11) that were significantly correlated with disease-free survival of breast cancer patients using a univariate Cox regression model (significance level P<0.01) in a meta-analysis. Based on the risk score of the three genes, the test series patients could be separated into low-risk and high-risk groups with significantly different survival times. This signature was validated in the other three cohorts. The prognostic value of this three-gene signature was confirmed in the internal validation series and another four independent breast cancer data sets. The prognostic impact of one of the three genes, CLDN11, was confirmed by immunohistochemistry. CLDN11 was significantly overexpressed in human breast IDC as compared with normal breast tissues and breast DCIS. Conclusion Using novel gene expression profiling together with a meta-analysis validation

  11. HOXA1 drives melanoma tumor growth and metastasis and elicits an invasion gene expression signature that prognosticates clinical outcome

    PubMed Central

    Wardwell-Ozgo, Joanna; Dogruluk, Turgut; Gifford, Armel; Zhang, Yiqun; Heffernan, Timothy P.; van Doorn, Remco; Creighton, Chad J.; Chin, Lynda; Scott, Kenneth L.

    2014-01-01

    Metastatic melanoma is a highly lethal disease notorious for its aggressive clinical course and eventual resistance to existing therapies. Currently we possess a limited understanding of the genetic events driving melanoma progression, and much effort is focused on identifying pro-metastatic aberrations or perturbed signaling networks that constitute new therapeutic targets. In this study, we validate and assess the mechanism by which homeobox transcription factor A1 (HOXA1), a pro-invasion oncogene previously identified in a metastasis screen by our group, contributes to melanoma progression. Transcriptome and pathway profiling analyses of cells expressing HOXA1 reveals up-regulation of factors involved in diverse cytokine pathways that include the TGFβ signaling axis, which we further demonstrate to be required for HOXA1-mediated cell invasion in melanoma cells. Transcriptome profiling also shows HOXA1’s ability to potently down-regulate expression of microphthalmia-associated transcription factor (MITF) and other genes required for melanocyte differentiation, suggesting a mechanism by which HOXA1 expression de-differentiates cells into a pro-invasive cell state concomitant with TGFβ activation. Our analysis of publicly available datasets indicate that the HOXA1-induced gene signature successfully categorizes melanoma specimens based on their metastatic potential and, importantly, is capable of stratifying melanoma patient risk for metastasis based on expression in primary tumors. Together, these validation data and mechanistic insights suggest that patients whose primary tumors express HOXA1 are among a high-risk metastasis subgroup that should be considered for anti-TGFβ therapy in adjuvant settings. Moreover, further analysis of HOXA1 target genes in melanoma may reveal new pathways or targets amenable to therapeutic intervention. PMID:23435427

  12. HOXA1 drives melanoma tumor growth and metastasis and elicits an invasion gene expression signature that prognosticates clinical outcome.

    PubMed

    Wardwell-Ozgo, J; Dogruluk, T; Gifford, A; Zhang, Y; Heffernan, T P; van Doorn, R; Creighton, C J; Chin, L; Scott, K L

    2014-02-20

    Melanoma is a highly lethal malignancy notorious for its aggressive clinical course and eventual resistance to existing therapies. Currently, we possess a limited understanding of the genetic events driving melanoma progression, and much effort is focused on identifying pro-metastatic aberrations or perturbed signaling networks that constitute new therapeutic targets. In this study, we validate and assess the mechanism by which homeobox transcription factor A1 (HOXA1), a pro-invasion oncogene previously identified in a metastasis screen by our group, contributes to melanoma progression. Transcriptome and pathway profiling analyses of cells expressing HOXA1 reveals upregulation of factors involved in diverse cytokine pathways that include the transforming growth factor beta (TGFβ) signaling axis, which we further demonstrate to be required for HOXA1-mediated cell invasion in melanoma cells. Transcriptome profiling also shows HOXA1's ability to potently downregulate expression of microphthalmia-associated transcription factor (MITF) and other genes required for melanocyte differentiation, suggesting a mechanism by which HOXA1 expression de-differentiates cells into a pro-invasive cell state concomitant with TGFβ activation. Our analysis of publicly available data sets indicate that the HOXA1-induced gene signature successfully categorizes melanoma specimens based on their metastatic potential and, importantly, is capable of stratifying melanoma patient risk for metastasis based on expression in primary tumors. Together, these validation data and mechanistic insights suggest that patients whose primary tumors express HOXA1 are among a high-risk metastasis subgroup that should be considered for anti-TGFβ therapy in adjuvant settings. Moreover, further analysis of HOXA1 target genes in melanoma may reveal new pathways or targets amenable to therapeutic intervention. PMID:23435427

  13. 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

  14. 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

  15. Altered Gene Expression in Schizophrenia: Findings from Transcriptional Signatures in Fibroblasts and Blood

    PubMed Central

    Cattane, Nadia; Minelli, Alessandra; Milanesi, Elena; Maj, Carlo; Bignotti, Stefano; Bortolomasi, Marco; Chiavetto, Luisella Bocchio; Gennarelli, Massimo

    2015-01-01

    Background Whole-genome expression studies in the peripheral tissues of patients affected by schizophrenia (SCZ) can provide new insight into the molecular basis of the disorder and innovative biomarkers that may be of great utility in clinical practice. Recent evidence suggests that skin fibroblasts could represent a non-neural peripheral model useful for investigating molecular alterations in psychiatric disorders. Methods A microarray expression study was conducted comparing skin fibroblast transcriptomic profiles from 20 SCZ patients and 20 controls. All genes strongly differentially expressed were validated by real-time quantitative PCR (RT-qPCR) in fibroblasts and analyzed in a sample of peripheral blood cell (PBC) RNA from patients (n = 25) and controls (n = 22). To evaluate the specificity for SCZ, alterations in gene expression were tested in additional samples of fibroblasts and PBCs RNA from Major Depressive Disorder (MDD) (n = 16; n = 21, respectively) and Bipolar Disorder (BD) patients (n = 15; n = 20, respectively). Results Six genes (JUN, HIST2H2BE, FOSB, FOS, EGR1, TCF4) were significantly upregulated in SCZ compared to control fibroblasts. In blood, an increase in expression levels was confirmed only for EGR1, whereas JUN was downregulated; no significant differences were observed for the other genes. EGR1 upregulation was specific for SCZ compared to MDD and BD. Conclusions Our study reports the upregulation of JUN, HIST2H2BE, FOSB, FOS, EGR1 and TCF4 in the fibroblasts of SCZ patients. A significant alteration in EGR1 expression is also present in SCZ PBCs compared to controls and to MDD and BD patients, suggesting that this gene could be a specific biomarker helpful in the differential diagnosis of major psychoses. PMID:25658856

  16. 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

  17. 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

  18. 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.

  19. Hantaviruses induce cell type- and viral species-specific host microRNA expression signatures.

    PubMed

    Shin, Ok Sarah; Kumar, Mukesh; Yanagihara, Richard; Song, Jin-Won

    2013-11-01

    The mechanisms of hantavirus-induced modulation of host cellular immunity remain poorly understood. Recently, microRNAs (miRNAs) have emerged as a class of essential regulators of host immune response genes. To ascertain if differential host miRNA expression toward representative hantavirus species correlated with immune response genes, miRNA expression profiles were analyzed in human endothelial cells, macrophages and epithelial cells infected with pathogenic and nonpathogenic rodent- and shrew-borne hantaviruses. Distinct miRNA expression profiles were observed in a cell type- and viral species-specific pattern. A subset of miRNAs, including miR-151-5p and miR-1973, were differentially expressed between Hantaan virus and Prospect Hill virus. Pathway analyses confirmed that the targets of selected miRNAs were associated with inflammatory responses and innate immune receptor-mediated signaling pathways. Our data suggest that differential immune responses following hantavirus infection may be regulated in part by cellular miRNA through dysregulation of genes critical to the inflammatory process.

  20. 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

  1. 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…

  2. mCSM-AB: a web server for predicting antibody–antigen affinity changes upon mutation with graph-based signatures

    PubMed Central

    Pires, Douglas E.V.; Ascher, David B.

    2016-01-01

    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

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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

  9. Physical activity-associated gene expression signature in nonhuman primate motor cortex.

    PubMed

    Mitchell, Amanda C; Leak, Rehana K; Garbett, Krassimira; Zigmond, Michael J; Cameron, Judy L; Mirnics, Károly

    2012-03-01

    It has been established that weight gain and weight loss are heavily influenced by activity level. In this study, we hypothesized that the motor cortex exhibits a distinct physical activity-associated gene expression profile, which may underlie changes in weight associated with movement. Using DNA microarrays we profiled gene expression in the motor cortex of a group of 14 female rhesus monkeys (Macaca mulatta) with a wide range of stable physical activity levels. We found that neuronal growth factor signaling and nutrient sensing transcripts in the brain were highly correlated with physical activity. A follow-up of AKT3 expression changes (a gene at the apex of neuronal survival and nutrient sensing) revealed increased protein levels of total AKT, phosphorylated AKT, and forkhead box O3 (FOXO3), one of AKT's main downstream effectors. In addition, we successfully validated three other genes via quantitative polymerase chain reaction (qPCR) (cereblon (CRBN), origin recognition complex subunit 4-like, and pyruvate dehydrogenase 4 (PDK4)). We conclude that these genes are important in the physical activity-associated pathway in the motor cortex, and may be critical for physical activity-associated changes in body weight and neuroprotection.

  10. The influence of a gene expression signature on the diagnosis and recommended treatment of melanocytic tumors by dermatopathologists

    PubMed Central

    Cockerell, Clay J.; Tschen, Jaime; Evans, Brent; Bess, Emily; Kidd, John; Kolquist, Kathryn A.; Rock, Colleen; Clarke, Loren E.

    2016-01-01

    Abstract It is well documented that histopathologic examination is sometimes inadequate for accurate and reproducible diagnosis of certain melanocytic neoplasms. Recently, a 23-gene expression signature has been clinically validated as an adjunctive diagnostic test to differentiate benign nevi from malignant melanomas. This study aimed to quantify the impact of this test on diagnosis and treatment recommendations made by dermatopathologists. Diagnostically challenging melanocytic lesions encountered during routine dermatopathology practice were submitted for gene expression testing and received a melanoma diagnostic score (MDS). Submitting dermatopathologists completed a survey documenting pre-test diagnosis, level of diagnostic confidence, and recommendations for treatment. The survey was repeated after receiving the MDS. Changes between the pre- and post-test surveys were analyzed retrospectively. When the MDS was available as part of a comprehensive case evaluation in diagnostically challenging cases, definitive diagnoses were increased by 56.6% for cases that were initially indeterminate and changes in treatment recommendations occurred in 49.1% of cases. Treatment recommendations were changed to align with the test result in 76.6% of diagnostically challenging cases. The MDS impacts diagnosis and treatment recommendations by dermatopathologists confronted with diagnostically challenging melanocytic lesions. Increased data are needed in order to completely understand how use of the MDS will translate from dermatopathology to clinical practice. PMID:27749545

  11. 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.

  12. 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

  13. Gene expression array analyses predict increased proto-oncogene expression in MMTV induced mammary tumors.

    PubMed

    Popken-Harris, Pamela; Kirchhof, Nicole; Harrison, Ben; Harris, Lester F

    2006-08-01

    Exogenous infection by milk-borne mouse mammary tumor viruses (MMTV) typically induce mouse mammary tumors in genetically susceptible mice at a rate of 90-95% by 1 year of age. In contrast to other transforming retroviruses, MMTV acts as an insertional mutagen and under the influence of steroid hormones induces oncogenic transformation after insertion into the host genome. As these events correspond with increases in adjacent proto-oncogene transcription, we used expression array profiling to determine which commonly associated MMTV insertion site proto-oncogenes were transcriptionally active in MMTV induced mouse mammary tumors. To verify our gene expression array results we developed real-time quantitative RT-PCR assays for the common MMTV insertion site genes found in RIII/Sa mice (int-1/wnt-1, int-2/fgf-3, int-3/Notch 4, and fgf8/AIGF) as well as two genes that were consistently up regulated (CCND1, and MAT-8) and two genes that were consistently down regulated (FN1 and MAT-8) in the MMTV induced tumors as compared to normal mammary gland. Finally, each tumor was also examined histopathologically. Our expression array findings support a model whereby just one or a few common MMTV insertions into the host genome sets up a dominant cascade of events that leave a characteristic molecular signature.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Simultaneous gene expression signature of heart and peripheral blood mononuclear cells in astemizole-treated rats.

    PubMed

    Lee, Eun-Hee; Oh, Jung-Hwa; Park, Han-Jin; Kim, Do-Geun; Lee, Jong-Hwa; Kim, Choong-Yong; Kwon, Myung-Sang; Yoon, Seokjoo

    2010-08-01

    We investigated the effects of astemizole, a second-generation antihistamine, on the heart and peripheral blood mononuclear cells (PBMCs) and identified the early markers of its cardiotoxicity using gene expression profiling. Astemizole causes torsades de pointes, which is a type of ventricular tachycardia. We administered astemizole (dosage: 20, 60 mg/kg) to male Sprague-Dawley rats, using an oral gavage. Cardiac tissue and PBMCs were collected from the rats 4 h after treatment. Gene expression profiles were obtained using an Affymetrix GeneChip. The most deregulated genes were associated with energy metabolism pathways and calcium ion homeostasis in the heart of astemizole-treated rats. The most altered genes in the PBMCs were those involved in developmental processes and cardiotoxicity. Genes related to the response to oxidative stress, reactive oxygen species, heat shock proteins, hypoxia, immunity, and inflammation were also deregulated in the heart and PBMCs. These data provide further insight into the genetic pathways affected by astemizole. In addition, the simultaneously deregulated genes identified herein may be further studied. It will be interesting to find out whether single genes or certain sets of these genes could finally serve as biomarkers for cardiotoxicity of astemizole or other similar antihistamine drugs. PMID:20221588

  20. Gene expression signatures defining fundamental biological processes in pluripotent, early, and late differentiated embryonic stem cells.

    PubMed

    Gaspar, John Antonydas; Doss, Michael Xavier; Winkler, Johannes; Wagh, Vilas; Hescheler, Jürgen; Kolde, Raivo; Vilo, Jaak; Schulz, Herbert; Sachinidis, Agapios

    2012-09-01

    Investigating the molecular mechanisms controlling the in vivo developmental program postembryogenesis is challenging and time consuming. However, the developmental program can be partly recapitulated in vitro by the use of cultured embryonic stem cells (ESCs). Similar to the totipotent cells of the inner cell mass, gene expression and morphological changes in cultured ESCs occur hierarchically during their differentiation, with epiblast cells developing first, followed by germ layers and finally somatic cells. Combination of high throughput -omics technologies with murine ESCs offers an alternative approach for studying developmental processes toward organ-specific cell phenotypes. We have made an attempt to understand differentiation networks controlling embryogenesis in vivo using a time kinetic, by identifying molecules defining fundamental biological processes in the pluripotent state as well as in early and the late differentiation stages of ESCs. Our microarray data of the differentiation of the ESCs clearly demonstrate that the most critical early differentiation processes occur at days 2 and 3 of differentiation. Besides monitoring well-annotated markers pertinent to both self-renewal and potency (capacity to differentiate to different cell lineage), we have identified candidate molecules for relevant signaling pathways. These molecules can be further investigated in gain and loss-of-function studies to elucidate their role for pluripotency and differentiation. As an example, siRNA knockdown of MageB16, a gene highly expressed in the pluripotent state, has proven its influence in inducing differentiation when its function is repressed.

  1. 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

  2. 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

  3. Reduced Glucocorticoid Receptor Expression Predicts Bladder Tumor Recurrence and Progression

    PubMed Central

    Ishiguro, Hitoshi; Kawahara, Takashi; Zheng, Yichun; Netto, George J.; Miyamoto, Hiroshi

    2015-01-01

    Objectives To assess the levels of glucocorticoid receptor (GR) expression in bladder tumors because the status and its prognostic value remain largely unknown. Methods We immunohistochemically stained for GR in bladder tumor and matched non-neoplastic bladder tissue specimens. Results Overall, GR was positive in 129 (87%) of 149 urothelial tumors, which was significantly (P = .026) lower than in non-neoplastic urothelium (90 [96%] of 94). Forty-two (79%) of 53 low-grade tumors vs 45 (47%) of 96 high-grade carcinomas (P < .001) and 61 (73%) of 84 non–muscle-invasive (NMI) tumors vs 26 (40%) of 65 muscle-invasive (MI) carcinomas (P < .001) were moderately to strongly immunoreactive for GR. Kaplan-Meier and log-rank tests revealed that loss or weak positivity of GR significantly or marginally correlated with recurrence of NMI tumors (P = .025), progression of MI tumors (P = .082), and cancer-specific survival of MI tumors (P = .067). Multivariate analysis identified low GR expression as a strong predictor for recurrence of NMI tumors (P = .034). Conclusions GR expression was downregulated in bladder tumors compared with nonneoplastic bladder tumors and in high-grade/MI tumors compared with low-grade/NMI tumors. Decreased expression of GR, as an independent prognosticator, predicted recurrence of NMI tumors. These results support experimental evidence suggesting an inhibitory role of GR signals in bladder cancer outgrowth. PMID:25015855

  4. 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

  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. Prediction of toddlers' expressive language from maternal sensitivity and toddlers' anger expressions: a developmental perspective.

    PubMed

    Nozadi, Sara S; Spinrad, Tracy L; Eisenberg, Nancy; Bolnick, Rebecca; Eggum-Wilkens, Natalie D; Smith, Cynthia L; Gaertner, Bridget; Kupfer, Anne; Sallquist, Julie

    2013-12-01

    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.

  7. Gene expression signatures affected by alcohol-induced DNA methylomic deregulation in human embryonic stem cells

    PubMed Central

    Kim, Hyun-Sung; Hoang, Michael; Tu, Thanh G.; Elie, Omid; Lee, Connie; Vu, Catherine; Horvath, Steve; Spigelman, Igor; Kim, Yong

    2014-01-01

    Stem cells, especially human embryonic stem cells (hESCs), are useful models to study molecular mechanisms of human disorders that originate during gestation. Alcohol (ethanol, EtOH) consumption during pregnancy causes a variety of prenatal and postnatal disorders collectively referred to as fetal alcohol spectrum disorders (FASDs). To better understand the molecular events leading to FASDs, we performed a genome-wide analysis of EtOH's effects on the maintenance and differentiation of hESCs in culture. Gene Co-expression Network Analysis showed significant alterations in gene profiles of EtOH-treated differentiated or undifferentiated hESCs, particularly those associated with molecular pathways for metabolic processes, oxidative stress, and neuronal properties of stem cells. A genome-wide DNA methylome analysis revealed widespread EtOH-induced alterations with significant hypermethylation of many regions of chromosomes. Undifferentiated hESCs were more vulnerable to EtOH's effect than their differentiated counterparts, with methylation on the promoter regions of chromosomes 2, 16 and 18 in undifferentiated hESCs most affected by EtOH exposure. Combined transcriptomic and DNA methylomic analysis produced a list of differentiation-related genes dysregulated by EtOH-induced DNA methylation changes, which likely play a role in EtOH-induced decreases in hESC pluripotency. DNA sequence motif analysis of genes epigenetically altered by EtOH identified major motifs representing potential binding sites for transcription factors. These findings should help in deciphering the precise mechanisms of alcohol-induced teratogenesis. PMID:24751885

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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 ...

  13. 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

  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. Multiple Suboptimal Solutions for Prediction Rules in Gene Expression Data

    PubMed Central

    Komori, Osamu; Pritchard, Mari; Eguchi, Shinto

    2013-01-01

    This paper discusses mathematical and statistical aspects in analysis methods applied to microarray gene expressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray gene expression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence. PMID:23662163

  16. 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

  17. Proteomic analysis of acquired tamoxifen resistance in MCF-7 cells reveals expression signatures associated with enhanced migration

    PubMed Central

    2012-01-01

    Introduction Acquired tamoxifen resistance involves complex signaling events that are not yet fully understood. Successful therapeutic intervention to delay the onset of hormone resistance depends critically on mechanistic elucidation of viable molecular targets associated with hormone resistance. This study was undertaken to investigate the global proteomic alterations in a tamoxifen resistant MCF-7 breast cancer cell line obtained by long term treatment of the wild type MCF-7 cell line with 4-hydroxytamoxifen (4-OH Tam). Methods We cultured MCF-7 cells with 4-OH Tam over a period of 12 months to obtain the resistant cell line. A gel-free, quantitative proteomic method was used to identify and quantify the proteome of the resistant cell line. Nano-flow high-performance liquid chromatography coupled to high resolution Fourier transform mass spectrometry was used to analyze fractionated peptide mixtures that were isobarically labeled from the resistant and control cell lysates. Real time quantitative PCR and Western blots were used to verify selected proteomic changes. Lentiviral vector transduction was used to generate MCF-7 cells stably expressing S100P. Online pathway analysis was performed to assess proteomic signatures in tamoxifen resistance. Survival analysis was done to evaluate clinical relevance of altered proteomic expressions. Results Quantitative proteomic analysis revealed a wide breadth of signaling events during transition to acquired tamoxifen resistance. A total of 629 proteins were found significantly changed with 364 up-regulated and 265 down-regulated. Collectively, these changes demonstrated the suppressed state of estrogen receptor (ER) and ER-regulated genes, activated survival signaling and increased migratory capacity of the resistant cell line. The protein S100P was found to play a critical role in conferring tamoxifen resistance and enhanced cell motility. Conclusions Our data demonstrate that the adaptive changes in the proteome of

  18. Prediction of recurrence-free survival using a protein expression-based risk classifier for head and neck cancer.

    PubMed

    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

    2015-04-20

    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.

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

    PubMed

    Zhang, Wei; Zhong, Liang; 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

  20. miRNA signature identification of retinoblastoma and the correlations between differentially expressed miRNAs during retinoblastoma progression

    PubMed Central

    Yang, Yang

    2015-01-01

    Purpose Retinoblastoma (RB) is a common pediatric cancer. The study aimed to uncover the mechanisms of RB progression and identify novel therapeutic biomarkers. Methods The miRNA expression profile GSE7072, which includes three RB samples and three healthy retina samples, was used. After data normalization using the preprocessCore package, differentially expressed miRNAs (DE-miRs) were selected by the limma package. The targets of the DE-miRs were predicted based on two databases, followed by construction of the miRNA–target network. Pathway enrichment analysis was conducted for the targets of the DE-miRNAs using DAVID. The CTD database was used to predict RB-related genes, followed by clustering analysis using the pvclust package. The correlation network of DE-miRs was established. MiRNA expression was validated in another data set, GSE41321. Results In total, 24 DE-miRs were identified whose targets were correlated with the cell cycle pathway. Among them, hsa-miR-373, hsa-miR-125b, and hsa-miR-181a were highlighted in the miRNA–target regulatory network; 14 DE-miRs, including hsa-miR-373, hsa-miR-125b, hsa-miR-18a, hsa-miR-25, hsa-miR-20a, and hsa-let-7 (a, b, c), were shown to distinguish RB from healthy tissue. In addition, hsa-miR-25, hsa-miR-18a, and hsa-miR-20a shared the common target BCL2L11; hsa-let-7b and hsa-miR-125b targeted the genes CDC25A, CDK6, and LIN28A. Expression of three miRNAs in GSE41321 was consistent with that in GSE7072. Conclusions Several critical miRNAs were identified in RB progression. Hsa-miR-373 might regulate RB invasion and metastasis, hsa-miR-181a might involve in the CDKN1B-mediated cell cycle pathway, and hsa-miR-125b and hsa-let-7b might serve as tumor suppressors by coregulating CDK6, CDC25A, and LIN28A. The miRNAs hsa-miR-25, hsa-miR-18a, and hsa-miR-20a might exert their function by coregulating BCL2L1. PMID:26730174

  1. Gene signatures associated with mouse postnatal hindbrain neural stem cells and medulloblastoma cancer stem cells identify novel molecular mediators and predict human medulloblastoma molecular classification.

    PubMed

    Corno, Daniela; Daniela, Corno; Pala, Mauro; Cominelli, Manuela; Cipelletti, Barbara; Leto, Ketty; Croci, Laura; Barili, Valeria; Brandalise, Federico; Melzi, Raffaella; Di Gregorio, Alessandra; Sergi, Lucia Sergi; Politi, Letterio Salvatore; Piemonti, Lorenzo; Bulfone, Alessandro; Rossi, Paola; Rossi, Ferdinando; Consalez, Gian Giacomo; Poliani, Pietro Luigi; Galli, Rossella

    2012-06-01

    Medulloblastoma arises from mutations occurring in stem/progenitor cells located in restricted hindbrain territories. Here we report that the mouse postnatal ventricular zone lining the IV ventricle also harbors bona fide stem cells that, remarkably, share the same molecular profile with cerebellar white matter-derived neural stem cells (NSC). To identify novel molecular mediators involved in medulloblastomagenesis, we compared these distinct postnatal hindbrain-derived NSC populations, which are potentially tumor initiating, with murine compound Ptch/p53 mutant medulloblastoma cancer stem cells (CSC) that faithfully phenocopy the different variants of human medulloblastoma in vivo. Transcriptome analysis of both hindbrain NSCs and medulloblastoma CSCs resulted in the generation of well-defined gene signatures, each reminiscent of a specific human medulloblastoma molecular subclass. Most interestingly, medulloblastoma CSCs upregulated developmentally related genes, such as Ebfs, that were shown to be highly expressed in human medulloblastomas and play a pivotal role in experimental medullo-blastomagenesis. These data indicate that gene expression analysis of medulloblastoma CSCs holds great promise not only for understanding functional differences between distinct CSC populations but also for identifying meaningful signatures that might stratify medulloblastoma patients beyond histopathologic staging.

  2. A miRNA-based signature predicts development of disease recurrence in HER2 positive breast cancer after adjuvant trastuzumab-based treatment

    PubMed Central

    Du, F.; Yuan, P.; Zhao, Z. T.; Yang, Z.; Wang, T.; Zhao, J. D.; Luo, Y.; Ma, F.; Wang, J. Y.; Fan, Y.; Cai, R. G.; Zhang, P.; Li, Q.; Song, Y. M.; Xu, B. H.

    2016-01-01

    Approximately 20% of HER2 positive breast cancer develops disease recurrence after adjuvant trastuzumab treatment. This study aimed to develop a molecular prognostic model that can reliably stratify patients by risk of developing disease recurrence. Using miRNA microarrays, nine miRNAs that differentially expressed between the recurrent and non-recurrent patients were identified. Then, we validated the expression of these miRNAs using qRT-PCR in training set (n = 101), and generated a 2-miRNA (miR-4734 and miR-150-5p) based prognostic signature. The prognostic accuracy of this classifier was further confirmed in an internal testing set (n = 57), and an external independent testing set (n = 53). Besides, by comparing the ROC curves, we found the incorporation of this miRNA based classifier into TNM stage could improve the prognostic performance of TNM system. The results indicated the 2-miRNA based signature was a reliable prognostic biomarker for patients with HER2 positive breast cancer. PMID:27650797

  3. The Signature Sequence Region of the Human Drug Transporter Organic Anion Transporting Polypeptide 1B1 Is Important for Protein Surface Expression.

    PubMed

    Taylor-Wells, Jennina; Meredith, David

    2014-01-01

    The organic anion transporting polypeptides (OATPs) encompass a family of membrane transport proteins responsible for the uptake of xenobiotic compounds. Human organic anion transporting polypeptide 1B1 (OATP1B1) mediates the uptake of clinically relevant compounds such as statins and chemotherapeutic agents into hepatocytes, playing an important role in drug delivery and detoxification. The OATPs have a putative 12-transmembrane domain topology and a highly conserved signature sequence (human OATP1B1: DSRWVGAWWLNFL), spanning the extracellular loop 3/TM6 boundary. The presence of three conserved tryptophan residues at the TM interface suggests a structural role for the sequence. This was investigated by site-directed mutagenesis of selected amino acids within the sequence D251E, W254F, W258/259F, and N261A. Transport was measured using the substrate estrone-3-sulfate and surface expression detected by luminometry and confocal microscopy, facilitated by an extracellular FLAG epitope. Uptake of estrone-3-sulfate and the surface expression of D251E, W254F, and W258/259F were both significantly reduced from the wild type OATP1B1-FLAG in transfected HEK293T cells. Confocal microscopy revealed that protein was produced but was retained intracellularly. The uptake and expression of N261A were not significantly different. The reduction in surface expression and intracellular protein retention indicates a structural and/or membrane localization role for these signature sequence residues in the human drug transporter OATP1B1.

  4. Discriminating gene expression signature of radiation-induced thyroid tumors after either external exposure or internal contamination.

    PubMed

    Ory, Catherine; Ugolin, Nicolas; Schlumberger, Martin; Hofman, Paul; Chevillard, Sylvie

    2011-12-21

    Both external radiation exposure and internal radionuclide contamination are well known risk factors in the development of thyroid epithelial tumors. The identification of specific molecular markers deregulated in radiation-induced thyroid tumors is important for the etiological diagnosis since neither histological features nor genetic alterations can discriminate between sporadic and radiation-induced tumors. Identification of highly discriminating markers in radiation-induced tumors is challenging as it relies on the ability to identify marker deregulation which is associated with a cellular stress that occurred many years before in the thyroid cells. The existence of such a signature is still controversial, as it was not found in several studies while a highly discriminating signature was found in both post-radiotherapy and post-Chernobyl series in other studies. Overall, published studies searching for radiation-induced thyroid tumor specificities, using transcriptomic, proteomic and comparative genomic hybridization approaches, and bearing in mind the analytical constraints required to analyze such small series of tumors, suggest that such a molecular signature could be found. In comparison with sporadic tumors, we highlight molecular similarities and specificities in tumors occurring after high-dose external radiation exposure, such as radiotherapy, and in post-Chernobyl tumors that occurred after internal 131I contamination. We discuss the relevance of signature extrapolation from series of tumors developing after high and low doses in the identification of tumors induced at very low doses of radiation.

  5. 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

  6. 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

  7. 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

  8. 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

  9. Gene expression signatures as a therapeutic target for severe H7N9 influenza - what do we know so far?

    PubMed

    Morrison, Juliet; Katze, Michael G

    2015-04-01

    A novel H7N9 avian influenza A virus (IAV) emerged in China in early 2013 causing > 450 cases of respiratory illness and 175 deaths within a 20-month period. Though avian viruses infect humans infrequently, the lack of human immunity to these viruses raises the possibility of a pandemic if they were to acquire the ability to transmit efficiently. Despite the fact that IAV pathogenicity results from the cytopathic effects and tissue damage caused by both viral replication and an overly robust immune response, current IAV therapeutics only target the viral proteins. This has led to the emergence of drug resistance due to the high mutation rates of viruses. The growing obsolescence of our current influenza therapeutics underscores the need for alternative treatment strategies. One promising area of research is the use of drugs that target the host response to IAV infection. This article describes how gene expression profiling can be used to predict drugs that reverse the destructive effects of the host response to H7N9 and other pathogenic influenza viruses. PMID:25600759

  10. Basic Fibroblast Growth Factor-2/beta3 Integrin Expression Profile: Signature of Local Progression After Chemoradiotherapy for Patients With Locally Advanced Non-Small-Cell Lung Cancer

    SciTech Connect

    Massabeau, Carole; Rouquette, Isabelle; Lauwers-Cances, Valerie; Mazieres, Julien; Bachaud, Jean-Marc; Armand, Jean-Pierre; Delisle, Marie-Bernadette; Favre, Gilles; Toulas, Christine; Cohen-Jonathan-Moyal, Elizabeth

    2009-11-01

    Purpose: No biologic signature of chemoradiotherapy sensitivity has been reported for patients with locally advanced non-small-cell lung cancer (NSCLC). We have previously demonstrated that basic fibroblast growth factor (FGF-2) and alphavbeta3 integrin pathways control tumor radioresistance. We investigated whether the expression of the proteins involved in these pathways might be associated with the response to treatment and, therefore, the clinical outcome. Methods and Materials: FGF-2, beta3 integrin, angiopoietin-2, and syndecan-1 expression was studied using immunohistochemistry performed on biopsies obtained, before any treatment, from 65 patients exclusively treated with chemoradiotherapy for locally advanced NSCLC. The response to treatment was evaluated according to the Response Evaluation Criteria in Solid Tumors criteria using computed tomography at least 6 weeks after the end of the chemoradiotherapy. Local progression-free survival, metastasis-free survival, and disease-free survival were studied using the log-rank test and Cox proportional hazard analysis. Results: Among this NSCLC biopsy population, 43.7% overexpressed beta3 integrin (beta3{sup +}), 43% FGF-2 (FGF-2{sup +}), 41.5% syndecan-1, and 59.4% angiopoietin-2. Our results showed a strong association between FGF-2 and beta3 integrin expression (p = .001). The adjusted hazard ratio of local recurrence for FGF-2{sup +}/beta3{sup +} tumors compared with FGF-2{sup -}/beta3{sup -} tumors was 6.1 (95% confidence interval, 2.6-14.6, p = .005). However, the risk of local recurrence was not increased when tumors overexpressed beta3 integrin or FGF-2 alone. Moreover, the co-expression of these two proteins was marginally associated with the response to chemoradiotherapy and metastasis-free survival. Conclusion: The results of this study have identified the combined profile FGF-2/beta3 integrin expression as a signature of local control in patients treated with chemoradiotherapy for locally advanced

  11. Selective gene-expression profiling of migratory tumor cells in vivo predicts clinical outcome in breast cancer patients

    PubMed Central

    2012-01-01

    Introduction Metastasis of breast cancer is the main cause of death in patients. Previous genome-wide studies have identified gene-expression patterns correlated with cancer patient outcome. However, these were derived mostly from whole tissue without respect to cell heterogeneity. In reality, only a small subpopulation of invasive cells inside the primary tumor is responsible for escaping and initiating dissemination and metastasis. When whole tissue is used for molecular profiling, the expression pattern of these cells is masked by the majority of the noninvasive tumor cells. Therefore, little information is available about the crucial early steps of the metastatic cascade: migration, invasion, and entry of tumor cells into the systemic circulation. Methods In the past, we developed an in vivo invasion assay that can capture specifically the highly motile tumor cells in the act of migrating inside living tumors. Here, we used this assay in orthotopic xenografts of human MDA-MB-231 breast cancer cells to isolate selectively the migratory cell subpopulation of the primary tumor for gene-expression profiling. In this way, we derived a gene signature specific to breast cancer migration and invasion, which we call the Human Invasion Signature (HIS). Results Unsupervised analysis of the HIS shows that the most significant upregulated gene networks in the migratory breast tumor cells include genes regulating embryonic and tissue development, cellular movement, and DNA replication and repair. We confirmed that genes involved in these functions are upregulated in the migratory tumor cells with independent biological repeats. We also demonstrate that specific genes are functionally required for in vivo invasion and hematogenous dissemination in MDA-MB-231, as well as in patient-derived breast tumors. Finally, we used statistical analysis to show that the signature can significantly predict risk of breast cancer metastasis in large patient cohorts, independent of well

  12. 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

  13. 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

  14. 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

  15. 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

  16. SLocX: Predicting Subcellular Localization of Arabidopsis Proteins Leveraging Gene Expression Data

    PubMed Central

    Ryngajllo, Malgorzata; Childs, Liam; Lohse, Marc; Giorgi, Federico M.; Lude, Anja; Selbig, Joachim; Usadel, Björn

    2011-01-01

    Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mitochondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins

  17. Design and Multiseries Validation of a Web-Based Gene Expression Assay for Predicting Breast Cancer Recurrence and Patient Survival

    PubMed Central

    Van Laar, Ryan K.

    2011-01-01

    Gene expression analysis is a valuable tool for determining the risk of disease recurrence and overall survival of an individual patient with breast cancer. The purpose of this study was to create and validate a robust prognostic algorithm and implement it within an online analysis environment. Genomic and clinical data from 477 clinically diverse patients with breast cancer were analyzed with Cox regression models to identify genes associated with outcome, independent of standard prognostic factors. Percentile-ranked expression data were used to train a “metagene” algorithm to stratify patients as having a high or low risk of recurrence. The classifier was applied to 1016 patients from five independent series. The 200-gene algorithm stratifies patients into risk groups with statistically and clinically significant differences in recurrence-free and overall survival. Multivariate analysis revealed the classifier to be the strongest predictor of outcome in each validation series. In untreated node-negative patients, 88% sensitivity and 44% specificity for 10-year recurrence-free survival was observed, with positive and negative predictive values of 32% and 92%, respectively. High-risk patients appear to significantly benefit from systemic adjuvant therapy. A 200-gene prognosis signature has been developed and validated using genomic and clinical data representing a range of breast cancer clinicopathological subtypes. It is a strong independent predictor of patient outcome and is available for research use. PMID:21458382

  18. Design and multiseries validation of a web-based gene expression assay for predicting breast cancer recurrence and patient survival.

    PubMed

    Van Laar, Ryan K

    2011-05-01

    Gene expression analysis is a valuable tool for determining the risk of disease recurrence and overall survival of an individual patient with breast cancer. The purpose of this study was to create and validate a robust prognostic algorithm and implement it within an online analysis environment. Genomic and clinical data from 477 clinically diverse patients with breast cancer were analyzed with Cox regression models to identify genes associated with outcome, independent of standard prognostic factors. Percentile-ranked expression data were used to train a "metagene" algorithm to stratify patients as having a high or low risk of recurrence. The classifier was applied to 1016 patients from five independent series. The 200-gene algorithm stratifies patients into risk groups with statistically and clinically significant differences in recurrence-free and overall survival. Multivariate analysis revealed the classifier to be the strongest predictor of outcome in each validation series. In untreated node-negative patients, 88% sensitivity and 44% specificity for 10-year recurrence-free survival was observed, with positive and negative predictive values of 32% and 92%, respectively. High-risk patients appear to significantly benefit from systemic adjuvant therapy. A 200-gene prognosis signature has been developed and validated using genomic and clinical data representing a range of breast cancer clinicopathological subtypes. It is a strong independent predictor of patient outcome and is available for research use.

  19. A predictive role for noncancerous prostate cells: low connexin-26 expression in radical prostatectomy tissues predicts metastasis

    PubMed Central

    Bijnsdorp, I V; Rozendaal, L; van Moorselaar, R J A; Geldof, A A

    2012-01-01

    Background: It is important to identify markers that predict whether prostate cancer will metastasise. The adjacent noncancerous cells (influenced by the tumour cells) may also express potential markers. The objective of this study was to determine the influence of cancer cells on noncancerous cells and to assess the value of the cell-communication protein connexin-26 (Cx26) as a marker to predict the development of metastasis. Methods: The effect of conditioned medium (CM) from PrCa cells on in vitro noncancerous cell proliferation, migration and invasion and Cx26 expression was determined. Connexin-26 expression was investigated in prostatectomy tissues from 51 PrCa patients by immunohistochemistry and compared with various clinicopathological parameters. Results: Proliferation, migration and invasion of noncancerous cells were influenced by CM from the PrCa cell lines. Importantly, a clear relation was found between low Cx26 expression in the noncancerous tissue in prostatectomy sections and the risk of development of metastasis (P<0.0002). Kaplan–Meier analysis showed a relation between low Cx26 expression in noncancerous tissues and time to biochemical recurrence (P=0.0002). Conclusion: Measuring Cx26 expression in the adjacent noncancerous tissues (rather than cancer tissues) of prostatectomy sections could help to identify high-risk patients who may benefit from adjuvant therapy to decrease the risk of metastasis. PMID:23169284

  20. 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.

  1. 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

  2. MiRNA expression patterns predict survival in glioblastoma

    PubMed Central

    2011-01-01

    Background In order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed. Methods 35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo)therapy were included in this retrospective analysis. For microarray analysis the febit biochip "Geniom® Biochip MPEA homo-sapiens" was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed. Results It was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status. Conclusions At present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required. PMID:22074483

  3. 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.

  4. Characterization and predicted role of the microRNA expression profile in amnion from obese pregnant women.

    PubMed

    Nardelli, C; Iaffaldano, L; Ferrigno, M; Labruna, G; Maruotti, G M; Quaglia, F; Capobianco, V; Di Noto, R; Del Vecchio, L; Martinelli, P; Pastore, L; Sacchetti, L

    2014-03-01

    Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases. The mechanisms underlying this process are poorly understood, but probably include genetic, epigenetic alterations and changes in fetal nutrient supply. We have studied the microRNA (miRNA) expression profile in amnion from obese and control women at delivery to investigate if a specific miRNA signature is associated with obesity. The expression profile of 365 human miRNAs was evaluated with the TaqMan Array in amnion from 10 obese and 5 control (prepregnancy body mass index (BMI) >30 and <25 kg m(-2), respectively) women at delivery. Target genes and miRNA-regulated pathways were predicted by bioinformatics. Anthropometric and biochemical parameters were also measured in mothers and newborns. Seven miRNAs were expressed only in obese women (miR-422b, miR-219, miR-575, miR-523, miR-579, miR-618 and miR-659), whereas 13 miRNAs were expressed at a higher level and 12 miRNAs at a lower level in obese women than in controls. MicroRNAs significantly downregulated the neurotrophin, cancer/ErbB, mammalian target of rapamycin, insulin, adipocytokine, actin cytoskeleton and mitogen-activated protein kinase signaling pathways. In conclusion, we show that the miRNA profile is altered in amnion during obesity and hypothesize that this could affect pathways important for placental growth and function, thereby contributing to an increase in the newborn's risk of future metabolic diseases.

  5. Immunohistochemical Validation of Overexpressed Genes Identified by Global Expression Microarrays in Adrenocortical Carcinoma Reveals Potential Predictive and Prognostic Biomarkers

    PubMed Central

    Ip, Julian C.Y.; Pang, Tony C.Y.; Glover, Anthony R.; Soon, Patsy; Zhao, Jing Ting; Clarke, Stephen; Robinson, Bruce G.; Gill, Anthony J.

    2015-01-01

    Background. Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis. The aim of this study was to identify novel protein signatures that would predict clinical outcomes in a large cohort of patients with ACC based on data from previous gene expression microarray studies. Materials and Methods. A tissue microarray was generated from the paraffin tissue blocks of 61 patients with clinical outcomes data. Selected protein biomarkers based on previous gene expression microarray profiling studies were selected, and immunohistochemistry staining was performed. Staining patterns were correlated with clinical outcomes, and a multivariate analysis was undertaken to identify potential biomarkers of prognosis. Results. Median overall survival was 45 months, with a 5-year overall survival rate of 44%. Median disease-free survival was 58 months, with a 5-year disease-free survival rate of 44%. The proliferation marker Ki-67 and DNA topoisomerase TOP2A were associated with significantly poorer overall and disease-free survival. The results also showed strong correlation between the transcriptional repressor EZH2 and TOP2A expression, suggesting a novel role for EZH2 as an additional marker of prognosis. In contrast, increased expression of the BARD1 protein, with its ubiquitin ligase function, was associated with significantly improved overall and disease-free survival, which has yet to be documented for ACC. Conclusion. We present novel biomarkers that assist in determining prognosis for patients with ACC. Ki-67, TOP2A, and EZH2 were all significantly associated with poorer outcomes, whereas BARD1 was associated with improved overall survival. It is hoped that these biomarkers may help tailor additional therapy and be potential targets for directed therapy. PMID:25657202

  6. 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

  7. Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells

    PubMed Central

    Buick, Julie K.; Moffat, Ivy; Williams, Andrew; Swartz, Carol D.; Recio, Leslie; Hyduke, Daniel R.; Li, Heng‐Hong; Fornace, Albert J.; Aubrecht, Jiri

    2015-01-01

    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. Environ. Mol. Mutagen. 56:520–534, 2015. © 2015 The Authors. Environmental and Molecular Mutagenesis Published by Wiley Periodicals, Inc. PMID:25733247

  8. Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure

    PubMed Central

    Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia

    2014-01-01

    The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850

  9. 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

  10. MicroRNA Gene Expression Signature Driven by miR-9 Overexpression in Ovarian Clear Cell Carcinoma

    PubMed Central

    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

  11. Quantitative proteome profiling of human myoma and myometrium tissue reveals kinase expression signatures with potential for therapeutic intervention.

    PubMed

    Lemeer, Simone; Gholami, Amin Moghaddas; Wu, Zhixiang; Kuster, Bernhard

    2015-01-01

    Uterine leiomyomas are benign tumors affecting a large proportion of the female population. Despite the very high prevalence, the molecular basis for understanding the onset and development of the disease are still poorly understood. In this study, we profiled the proteomes and kinomes of leiomyoma as well as myometrium samples from patients to a depth of >7000 proteins including 200 kinases. Statistical analysis identified a number of molecular signatures distinguishing healthy from diseased tissue. Among these, nine kinases (ADCK4, CDK5, CSNK2B, DDR1, EPHB1, MAP2K2, PRKCB, PRKG1, and RPS6KA5) representing a number of cellular signaling pathways showed particularly strong discrimination potential. Preliminary statistical analysis by receiver operator characteristics plots revealed very good performance for individual kinases (area under the curve, AUC of 0.70-0.94) as well as binary combinations thereof (AUC 0.70-1.00) that might be used to assess the activity of signaling pathways in myomas. Of note, the receptor tyrosine kinase DDR1 holds future potential as a drug target owing to its strong links to collagen signaling and the excessive formation of extracellular matrix typical for leiomyomas in humans. PMID:25327614

  12. 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…

  13. 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

  14. 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

  15. Predicting genes expressed via −1 and +1 frameshifts

    PubMed Central

    Moon, Sanghoon; Byun, Yanga; Kim, Hong-Jin; Jeong, Sunjoo; Han, Kyungsook

    2004-01-01

    Computational identification of ribosomal frameshift sites in genomic sequences is difficult due to their diverse nature, yet it provides useful information for understanding the underlying mechanisms and discovering new genes. We have developed an algorithm that searches entire genomic or mRNA sequences for frameshifting sites, and implements the algorithm as a web-based program called FSFinder (Frameshift Signal Finder). The current version of FSFinder is capable of finding −1 frameshift sites on heptamer sequences X XXY YYZ, and +1 frameshift sites for two genes: protein chain release factor B (prfB) and ornithine decarboxylase antizyme (oaz). We tested FSFinder on ∼190 genomic and partial DNA sequences from a number of organisms and found that it predicted frameshift sites efficiently and with greater sensitivity and specificity than existing approaches. It has improved sensitivity because it considers many known components of a frameshifting cassette and searches these components on both + and − strands, and its specificity is increased because it focuses on overlapping regions of open reading frames and prioritizes candidate frameshift sites. FSFinder is useful for discovering unknown genes that utilize alternative decoding, as well as for analyzing frameshift sites. It is freely accessible at http://wilab.inha.ac.kr/FSFinder/. PMID:15371551

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. Prediction of microRNAs affecting mRNA expression during retinal development

    PubMed Central

    2010-01-01

    Background MicroRNAs (miRNAs) are small RNA molecules (~22 nucleotides) which have been shown to play an important role both in development and in maintenance of adult tissue. Conditional inactivation of miRNAs in the eye causes loss of visual function and progressive retinal degeneration. In addition to inhibiting translation, miRNAs can mediate degradation of targeted mRNAs. We have previously shown that candidate miRNAs affecting transcript levels in a tissue can be deduced from mRNA microarray expression profiles. The purpose of this study was to predict miRNAs which affect mRNA levels in developing and adult retinal tissue and to confirm their expression. Results Microarray expression data from ciliary epithelial retinal stem cells (CE-RSCs), developing and adult mouse retina were generated or downloaded from public repositories. Analysis of gene expression profiles detected the effects of multiple miRNAs in CE-RSCs and retina. The expression of 20 selected miRNAs was confirmed by RT-PCR and the cellular distribution of representative candidates analyzed by in situ hybridization. The expression levels of miRNAs correlated with the significance of their predicted effects upon mRNA expression. Highly expressed miRNAs included miR-124, miR-125a, miR-125b, miR-204 and miR-9. Over-expression of three miRNAs with significant predicted effects upon global mRNA levels resulted in a decrease in mRNA expression of five out of six individual predicted target genes assayed. Conclusions This study has detected the effect of miRNAs upon mRNA expression in immature and adult retinal tissue and cells. The validity of these observations is supported by the experimental confirmation of candidate miRNA expression and the regulation of predicted target genes following miRNA over-expression. Identified miRNAs are likely to be important in retinal development and function. Misregulation of these miRNAs might contribute to retinal degeneration and disease. Conversely, manipulation

  3. 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

  4. Optimizing heat shock protein expression induced by prostate cancer laser therapy through predictive computational models.

    PubMed

    Rylander, Marissa Nichole; Feng, Yusheng; Zhang, Yongjie; Bass, Jon; Jason Stafford, R; Volgin, Andrei; Hazle, John D; Diller, Kenneth R

    2006-01-01

    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.

  5. 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.

  6. Gene expression in normal-appearing tissue adjacent to prostate cancers are predictive of clinical outcome: evidence for a biologically meaningful field effect

    PubMed Central

    Magi-Galluzzi, Cristina; Maddala, Tara; Falzarano, Sara Moscovita; Cherbavaz, Diana B.; Zhang, Nan; Knezevic, Dejan; Febbo, Phillip G.; Lee, Mark; Lawrence, Hugh Jeffrey; Klein, Eric A.

    2016-01-01

    Purpose We evaluated gene expression in histologically normal-appearing tissue (NT) adjacent to prostate tumor in radical prostatectomy specimens, assessing for biological significance based on prediction of clinical recurrence (cR - metastatic disease or local recurrence). Results A total of 410 evaluable patients had paired tumor and NT. Fortysix genes, representing diverse biological pathways (androgen signaling, stromal response, stress response, cellular organization, proliferation, cell adhesion, and chromatin remodeling) were associated with cR in NT (FDR < 20%), of which 39 concordantly predicted cR in tumor (FDR < 20%). Overall GPS and its stromal response and androgen-signaling gene group components also significantly predicted time to cR in NT (RM-corrected HR/20 units = 1.25; 95% CI: 1.01-1.56; P = 0.024). Experimental Design Expression of 732 genes was measured by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) separately in tumor and adjacent NT specimens from 127 patients with and 374 without cR following radical prostatectomy for T1/T2 prostate cancer. A 17-gene expression signature (Genomic Prostate Score [GPS]), previously validated to predict aggressive prostate cancer when measured in tumor tissue, was also assessed using pre-specified genes and algorithms. Analysis used Cox proportional hazards models, Storey's false discovery rate (FDR) control, and regression to the mean (RM) correction. Conclusions Gene expression profiles, including GPS, from NT adjacent to tumor can predict prostate cancer outcome. These findings suggest that there is a biologically significant field effect in primary prostate cancer that is a marker for aggressive disease. PMID:27121323

  7. Cyclooxygenase-2 expression is associated with initiation of hepatocellular carcinoma, while prostaglandin receptor-1 expression predicts survival

    PubMed Central

    Yang, Hao-Jie; Jiang, Jing-Hang; Yang, Yu-Ting; Yang, Xiang-Di; Guo, Zhe; Qi, Ya-Peng; Zeng, Feng-Hua; Zhang, Ke-Lan; Chen, Neng-Zhi; Xiang, Bang-De; Li, Le-Qun

    2016-01-01

    AIM To determine whether cyclooxygenase-2 (COX-2) and prostaglandin E1 receptor (EP1) contribute to disease and whether they help predict prognosis. METHODS We retrospectively reviewed the records of 116 patients with hepatocellular carcinoma (HCC) who underwent surgery between 2008 and 2011 at our hospital. Expression of COX-2 and EP1 receptor was examined by immunohistochemistry of formalin-fixed, paraffin-embedded tissues using polyclonal antibodies. Possible associations between immunohistochemical scores and survival were determined. RESULTS Factors associated with poor overall survival (OS) were alpha-fetoprotein > 400 ng/mL, tumor size ≥ 5 cm, and high EP1 receptor expression, but not high COX-2 expression. Disease-free survival was not significantly different between patients with low or high levels of COX-2 or EP1. COX-2 immunoreactivity was significantly higher in well-differentiated HCC tissues (Edmondson grade I-II) than in poorly differentiated tissues (Edmondson grade III-IV) (P = 0.003). EP1 receptor immunoreactivity was significantly higher in poorly differentiated tissue than in well-differentiated tissue (P = 0.001). CONCLUSION COX-2 expression appears to be linked to early HCC events (initiation), while EP1 receptor expression may participate in tumor progression and predict survival.

  8. MicroRNA signatures predict dysregulated vitamin D receptor and calcium pathways status in limb girdle muscle dystrophies (LGMD) 2A/2B.

    PubMed

    Aguennouz, M; Lo Giudice, C; Licata, N; Rodolico, C; Musumeci, O; Fanin, M; Migliorato, A; Ragusa, M; Macaione, V; Di Giorgio, R M; Angelini, C; Toscano, A

    2016-08-01

    miRNA expression profile and predicted pathways involved in selected limb-girdle muscular dystrophy (LGMD)2A/2B patients were investigated. A total of 187 miRNAs were dysregulated in all patients, with six miRNAs showing opposite regulation in LGMD2A versus LGMD2B patients. Silico analysis evidence: (1) a cluster of the dysregulated miRNAs resulted primarily involved in inflammation and calcium metabolism, and (2) two genes predicted as controlled by calcium-assigned miRNAs (Vitamin D Receptor gene and Guanine Nucleotide Binding protein beta polypeptide 1gene) showed an evident upregulation in LGMD2B patients, in accordance with miRNA levels. Our data support alterations in calcium pathway status in LGMD 2A/B, suggesting myofibre calcium imbalance as a potential therapeutic target. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27558075

  9. 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.

  10. 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. PMID:27602102

  11. 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

  12. Emotional facial expressions differentially influence predictions and performance for face recognition.

    PubMed

    Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

    2013-01-01

    This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

  13. Emotional facial expressions differentially influence predictions and performance for face recognition.

    PubMed

    Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

    2013-01-01

    This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion. PMID:22712473

  14. 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

  15. PTCH1 expression at diagnosis predicts imatinib failure in chronic myeloid leukaemia patients in chronic phase.

    PubMed

    Alonso-Dominguez, Juan M; Grinfeld, Jacob; Alikian, Mary; Marin, David; Reid, Alistair; Daghistani, Mustafa; Hedgley, Corinne; O'Brien, Stephen; Clark, Richard E; Apperley, Jane; Foroni, Letizia; Gerrard, Gareth

    2015-01-01

    The tyrosine kinase inhibitor (TKI) imatinib has revolutionized the management of chronic myeloid leukaemia (CML). However, around 25% of patients fail to sustain an adequate response. We sought to identify gene-expression biomarkers that could be used to predict imatinib response. The expression of 29 genes, previously implicated in CML pathogenesis, were measured by TaqMan Low Density Array in 73 CML patient samples. Patients were divided into low and high expression for each gene and imatinib failure (IF), probability of achieving CCyR, progression free survival and CML related OS were compared by Kaplan-Meier and log-rank. Results were validated in a second cohort of 56 patients, with a further technical validation using custom gene-expression assays in a conventional RT-qPCR in a sub-cohort of 37 patients. Patients with low PTCH1 expression showed a worse clinical response for all variables in all cohorts. PTCH1 was the most significant predictor in the multivariate analysis compared with Sokal, age and EUTOS. PTCH1 expression assay showed the adequate sensitivity, specificity and predictive values to predict for IF. Given the different treatments available for CML, measuring PTCH1 expression at diagnosis may help establish who will benefit best from imatinib and who is better selected for second generation TKI. PMID:25250944

  16. 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

  17. 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.

  18. Utilization of gene expression signature for quality control of traditional Chinese medicine formula Si-Wu-Tang.

    PubMed

    Xie, Chen; Wang, Zhijun; Wang, Charles; Xu, Jun; Wen, Zhining; Wang, Haitian; Shi, Leming; Chow, Moses S S; Huang, Ying; Zuo, Zhong

    2013-07-01

    The current study utilized a combined pharmacokinetic and genomic approach to demonstrate the feasibility of a new quality control method by using a panel of special differentially expressed genes (DEGs) as unique fingerprint to serve as marker of in vivo bioactivity for a representative traditional Chinese medicine (TCM) formula, Si-Wu-Tang (SWT). The method involves firstly obtaining possible in vivo active components, i.e., the "absorbable" components from the permeate of the Caco-2 monolayer model to simulate oral administration of two specific SWT products (CU-SWT, J-SWT), their component single herbs (Angelicae, Chuanxiong, Paeoniae, and Rehmanniae), and a standard mixture of active compounds (ferulic acid, ligustilide, senkyunolide A). Then, these respective absorbable components were incubated with MCF-7 cells to determine the gene expression profile using microarray processing/analysis as well as real-time PCR. From the available DEGs identified following the incubation, the magnitude of change in DEGs by real-time PCR was found to be consistent with that by microarray. The designated DEGs from the CU-SWT permeate were found to be distinct from other 19 products. Furthermore, the changes in the DEGs resulting from MCF-7 cells treated by eight replicate extracts of CU-SWT on three separate days were consistent. These results demonstrated sufficient specificity and consistency of the DEG panel which could serve as a unique bioactive "fingerprint" for the designated SWT product. The present method for DEG determination may be applied to other TCM products and with further definitive study can potentially provide a unique method for quality control of TCM in the future.

  19. An Automated Bayesian Framework for Integrative Gene Expression Analysis and Predictive Medicine

    PubMed Central

    Parikh, Neena; Zollanvari, Amin; Alterovitz, Gil

    2012-01-01

    Motivation This work constructs a closed loop Bayesian Network framework for predictive medicine via integrative analysis of publicly available gene expression findings pertaining to various diseases. Results: An automated pipeline was successfully constructed. Integrative models were made based on gene expression data obtained from GEO experiments relating to four different diseases using Bayesian statistical methods. Many of these models demonstrated a high level of accuracy and predictive ability. The approach described in this paper can be applied to any complex disorder and can include any number and type of genome-scale studies. PMID:22779059

  20. Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences.

    PubMed

    Meng, Hongying; Bianchi-Berthouze, Nadia; Deng, Yangdong; Cheng, Jinkuang; Cosmas, John P

    2016-04-01

    Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalistic expressions. In this paper, a novel two-stage automatic system is proposed to continuously predict affective dimension values from facial expression videos. In the first stage, traditional regression methods are used to classify each individual video frame, while in the second stage, a time-delay neural network (TDNN) is proposed to model the temporal relationships between consecutive predictions. The two-stage approach separates the emotional state dynamics modeling from an individual emotional state prediction step based on input features. In doing so, the temporal information used by the TDNN is not biased by the high variability between features of consecutive frames and allows the network to more easily exploit the slow changing dynamics between emotional states. The system was fully tested and evaluated on three different facial expression video datasets. Our experimental results demonstrate that the use of a two-stage approach combined with the TDNN to take into account previously classified frames significantly improves the overall performance of continuous emotional state estimation in naturalistic facial expressions. The proposed approach has won the affect recognition sub-challenge of the Third International Audio/Visual Emotion Recognition Challenge. PMID:25910269

  1. An Integrated Analysis of MicroRNA and mRNA Expression Profiles to Identify RNA Expression Signatures in Lambskin Hair Follicles in Hu Sheep.

    PubMed

    Lv, Xiaoyang; Sun, Wei; Yin, Jinfeng; Ni, Rong; Su, Rui; Wang, Qingzeng; Gao, Wen; Bao, Jianjun; Yu, Jiarui; Wang, Lihong; Chen, Ling

    2016-01-01

    Wave patterns in lambskin hair follicles are an important factor determining the quality of sheep's wool. Hair follicles in lambskin from Hu sheep, a breed unique to China, have 3 types of waves, designated as large, medium, and small. The quality of wool from small wave follicles is excellent, while the quality of large waves is considered poor. Because no molecular and biological studies on hair follicles of these sheep have been conducted to date, the molecular mechanisms underlying the formation of different wave patterns is currently unknown. The aim of this article was to screen the candidate microRNAs (miRNA) and genes for the development of hair follicles in Hu sheep. Two-day-old Hu lambs were selected from full-sib individuals that showed large, medium, and small waves. Integrated analysis of microRNA and mRNA expression profiles employed high-throughout sequencing technology. Approximately 13, 24, and 18 differentially expressed miRNAs were found between small and large waves, small and medium waves, and medium and large waves, respectively. A total of 54, 190, and 81 differentially expressed genes were found between small and large waves, small and medium waves, and medium and large waves, respectively, by RNA sequencing (RNA-seq) analysis. Differentially expressed genes were classified using gene ontology and pathway analyses. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport, and were associated with MAPK and the Notch signaling pathway. Reverse transcription-polymerase chain reaction (RT-PCR) analyses of differentially-expressed miRNA and genes were consistent with sequencing results. Integrated analysis of miRNA and mRNA expression indicated that, compared to small waves, large waves included 4 downregulated miRNAs that had regulatory effects on 8 upregulated genes and 3 upregulated miRNAs, which in turn influenced 13 downregulated genes. Compared to small waves, medium

  2. An Integrated Analysis of MicroRNA and mRNA Expression Profiles to Identify RNA Expression Signatures in Lambskin Hair Follicles in Hu Sheep

    PubMed Central

    Lv, Xiaoyang; Sun, Wei; Yin, Jinfeng; Ni, Rong; Su, Rui; Wang, Qingzeng; Gao, Wen; Bao, Jianjun; Yu, Jiarui; Wang, Lihong; Chen, Ling

    2016-01-01

    Wave patterns in lambskin hair follicles are an important factor determining the quality of sheep’s wool. Hair follicles in lambskin from Hu sheep, a breed unique to China, have 3 types of waves, designated as large, medium, and small. The quality of wool from small wave follicles is excellent, while the quality of large waves is considered poor. Because no molecular and biological studies on hair follicles of these sheep have been conducted to date, the molecular mechanisms underlying the formation of different wave patterns is currently unknown. The aim of this article was to screen the candidate microRNAs (miRNA) and genes for the development of hair follicles in Hu sheep. Two-day-old Hu lambs were selected from full-sib individuals that showed large, medium, and small waves. Integrated analysis of microRNA and mRNA expression profiles employed high-throughout sequencing technology. Approximately 13, 24, and 18 differentially expressed miRNAs were found between small and large waves, small and medium waves, and medium and large waves, respectively. A total of 54, 190, and 81 differentially expressed genes were found between small and large waves, small and medium waves, and medium and large waves, respectively, by RNA sequencing (RNA-seq) analysis. Differentially expressed genes were classified using gene ontology and pathway analyses. They were found to be mainly involved in cell differentiation, proliferation, apoptosis, growth, immune response, and ion transport, and were associated with MAPK and the Notch signaling pathway. Reverse transcription-polymerase chain reaction (RT-PCR) analyses of differentially-expressed miRNA and genes were consistent with sequencing results. Integrated analysis of miRNA and mRNA expression indicated that, compared to small waves, large waves included 4 downregulated miRNAs that had regulatory effects on 8 upregulated genes and 3 upregulated miRNAs, which in turn influenced 13 downregulated genes. Compared to small waves

  3. Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells.

    PubMed

    Kim, Yong-Wan; Kim, Eun Young; Jeon, Doin; Liu, Juinn-Lin; Kim, Helena Suhyun; Choi, Jin Woo; Ahn, Woong Shick

    2014-01-01

    Paclitaxel (Taxol) resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs) have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to identify target genes of selected miRNAs. Kaplan-Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the downregulation of the two miRNAs was associated with better survival, perhaps increasing the sensitivity of cancer cells to Taxol. In the chemo-sensitive patient group, only miR-647 could be a prognosis marker. These miRNAs inhibit several interacting genes of p53 networks, especially in TUOS-3 and TUOS-4, and showed cell line-specific inhibition effects. Taken together, the data indicate that the three miRNAs are closely associated with Taxol resistance and potentially better prognosis factors. Our results suggest that these miRNAs were successfully and reliably identified and would be used in the

  4. Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells

    PubMed Central

    Kim, Yong-Wan; Kim, Eun Young; Jeon, Doin; Liu, Juinn-Lin; Kim, Helena Suhyun; Choi, Jin Woo; Ahn, Woong Shick

    2014-01-01

    Paclitaxel (Taxol) resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs) have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to identify target genes of selected miRNAs. Kaplan–Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the downregulation of the two miRNAs was associated with better survival, perhaps increasing the sensitivity of cancer cells to Taxol. In the chemo-sensitive patient group, only miR-647 could be a prognosis marker. These miRNAs inhibit several interacting genes of p53 networks, especially in TUOS-3 and TUOS-4, and showed cell line-specific inhibition effects. Taken together, the data indicate that the three miRNAs are closely associated with Taxol resistance and potentially better prognosis factors. Our results suggest that these miRNAs were successfully and reliably identified and would be used in the

  5. 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

  6. ABCG2 expression in colorectal adenocarcinomas may predict resistance to irinotecan

    PubMed Central

    Tuy, Hoang Dinh; Shiomi, Hisanori; Mukaisho, Ken Ichi; Naka, Shigeyuki; Shimizu, Tomoharu; Sonoda, Hiromichi; Mekata, Eiji; Endo, Yoshihiro; Kurumi, Yoshimasa; Sugihara, Hiroyuki; Tani, Masaji; Tani, Tohru

    2016-01-01

    Irinotecan is a key drug for patients with advanced and recurrent colorectal carcinoma. However, the efficacy of irinotecan is not sufficient; partly, as there is no useful marker to predict chemosensitivity to the drug. The aim of the present study was to evaluate whether the expression levels of adenosine triphosphate-binding cassette sub-family G (WHITE) member 2 (Junior blood group) (ABCG2) in primary colorectal tumors predict chemoresistance to irinotecan. Using the resected primary tumor specimens of 189 patients with colorectal cancer, the association between the immunohistochemical expression of ABCG2 protein and the results of the collagen gel droplet embedded culture drug sensitivity test, performed to evaluate the chemosensitivity to SN-38 (an active metabolite of irinotecan), was investigated. Among the 189 patients, 17 received irinotecan-based chemotherapy, and their responses and progression-free survival (PFS) were analyzed. The tumors of patients with increased ABCG2 expression accounted for 60% of the tumors examined, and were significantly more resistant to SN-38, compared with patients with low ABCG2 expression (P<0.001). In a multivariate logistic regression analysis, increased expression of ABCG2 protein was an independent and significant predictor of resistance to SN-38, increasing the risk of resistance by 12-fold. Increased expression of ABCG2 and a low sensitivity to SN-38 was significantly associated with resistance to irinotecan-based chemotherapy (P=0.01 and 0.028, respectively). The median PFS of patients with increased expression of ABCG2 was significantly shorter, compared with patients with low expression levels of ABCG2 (104 vs. 242 days; P=0.047). The increased immunohistochemical expression of ABCG2 in primary tumors may be a useful predictive biomarker of resistance to irinotecan-based chemotherapy for patients with recurrent or metastatic colorectal cancer.

  7. Osteopontin Modulates Inflammation, Mucin Production, and Gene Expression Signatures After Inhalation of Asbestos in a Murine Model of Fibrosis

    PubMed Central

    Sabo-Attwood, Tara; Ramos-Nino, Maria E.; Eugenia-Ariza, Maria; MacPherson, Maximilian B.; Butnor, Kelly J.; Vacek, Pamela C.; McGee, Sean P.; Clark, Jessica C.; Steele, Chad; Mossman, Brooke T.

    2011-01-01

    Inflammation and lung remodeling are hallmarks of asbestos-induced fibrosis, but the molecular mechanisms that control these events are unclear. Using laser capture microdissection (LCM) of distal bronchioles in a murine asbestos inhalation model, we show that osteopontin (OPN) is up-regulated by bronchiolar epithelial cells after chrysotile asbestos exposures. In contrast to OPN wild-type mice (OPN+/+) inhaling asbestos, OPN null mice (OPN−/−) exposed to asbestos showed less eosinophilia in bronchoalveolar lavage fluids, diminished lung inflammation, and decreased mucin production. Bronchoalveolar lavage fluid concentrations of inflammatory cytokines (IL-1β, IL-4, IL-6, IL-12 subunit p40, MIP1α, MIP1β, and eotaxin) also were significantly less in asbestos-exposed OPN−/− mice. Microarrays performed on lung tissues from asbestos-exposed OPN+/+ and OPN−/− mice showed that OPN modulated the expression of a number of genes (Col1a2, Timp1, Tnc, Eln, and Col3a1) linked to fibrosis via initiation and cross talk between IL-1β and epidermal growth factor receptor-related signaling pathways. Novel targets of OPN identified include genes involved in cell signaling, immune system/defense, extracellular matrix remodeling, and cell cycle regulation. Although it is unclear whether the present findings are specific to chrysotile asbestos or would be observed after inhalation of other fibers in general, these results highlight new potential mechanisms and therapeutic targets for asbestosis and other diseases (asthma, smoking-related interstitial lung diseases) linked to OPN overexpression. PMID:21514415

  8. Protein pheromone expression levels predict and respond to the formation of social dominance networks.

    PubMed

    Nelson, A C; Cunningham, C B; Ruff, J S; Potts, W K

    2015-06-01

    Communication signals are key regulators of social networks and are thought to be under selective pressure to honestly reflect social status, including dominance status. The odours of dominants and nondominants differentially influence behaviour, and identification of the specific pheromones associated with, and predictive of, dominance status is essential for understanding the mechanisms of network formation and maintenance. In mice, major urinary proteins (MUPs) are excreted in extraordinary large quantities and expression level has been hypothesized to provide an honest signal of dominance status. Here, we evaluate whether MUPs are associated with dominance in wild-derived mice by analysing expression levels before, during and after competition for reproductive resources over 3 days. During competition, dominant males have 24% greater urinary MUP expression than nondominants. The MUP darcin, a pheromone that stimulates female attraction, is predictive of dominance status: dominant males have higher darcin expression before competition. Dominants also have a higher ratio of darcin to other MUPs before and during competition. These differences appear transient, because there are no differences in MUPs or darcin after competition. We also find MUP expression is affected by sire dominance status: socially naive sons of dominant males have lower MUP expression, but this apparent repression is released during competition. A requisite condition for the evolution of communication signals is honesty, and we provide novel insight into pheromones and social networks by showing that MUP and darcin expression is a reliable signal of dominance status, a primary determinant of male fitness in many species.

  9. Prolonged expression of the BX1 signature enzyme is associated with a recombination hotspot in the benzoxazinoid gene cluster in Zea mays

    PubMed Central

    Zheng, Linlin; McMullen, Michael D.; Bauer, Eva; Schön, Chris-Carolin; Gierl, Alfons; Frey, Monika

    2015-01-01

    Benzoxazinoids represent preformed protective and allelopathic compounds. The main benzoxazinoid in maize (Zea mays L.) is 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA). DIMBOA confers resistance to herbivores and microbes. Protective concentrations are found predominantly in young plantlets. We made use of the genetic diversity present in the maize nested association mapping (NAM) panel to identify lines with significant benzoxazinoid concentrations at later developmental stages. At 24 d after imbibition (dai), only three lines, including Mo17, showed effective DIMBOA concentrations of 1.5mM or more; B73, by contrast, had low a DIMBOA content. Mapping studies based on Mo17 and B73 were performed to reveal mechanisms that influence the DIMBOA level in 24 dai plants. A major quantitative trait locus mapped to the Bx gene cluster located on the short arm of chromosome 4, which encodes the DIMBOA biosynthetic genes. Mo17 was distinguished from all other NAM lines by high transcriptional expression of the Bx1 gene at later developmental stages. Bx1 encodes the signature enzyme of the pathway. In Mo17×B73 hybrids at 24 dai, only the Mo17 Bx1 allele transcript was detected. A 3.9kb cis-element, termed DICE (distal cis-element), that is located in the Bx gene cluster approximately 140kb upstream of Bx1, was required for high Bx1 transcript levels during later developmental stages in Mo17. The DICE region was a hotspot of meiotic recombination. Genetic analysis revealed that high 24 dai DIMBOA concentrations were not strictly dependent on high Bx1 transcript levels. However, constitutive expression of Bx1 in transgenics increased DIMBOA levels at 24 dai, corroborating a correlation between DIMBOA content and Bx1 transcription. PMID:25969552

  10. Prolonged expression of the BX1 signature enzyme is associated with a recombination hotspot in the benzoxazinoid gene cluster in Zea mays.

    PubMed

    Zheng, Linlin; McMullen, Michael D; Bauer, Eva; Schön, Chris-Carolin; Gierl, Alfons; Frey, Monika

    2015-07-01

    Benzoxazinoids represent preformed protective and allelopathic compounds. The main benzoxazinoid in maize (Zea mays L.) is 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA). DIMBOA confers resistance to herbivores and microbes. Protective concentrations are found predominantly in young plantlets. We made use of the genetic diversity present in the maize nested association mapping (NAM) panel to identify lines with significant benzoxazinoid concentrations at later developmental stages. At 24 d after imbibition (dai), only three lines, including Mo17, showed effective DIMBOA concentrations of 1.5mM or more; B73, by contrast, had low a DIMBOA content. Mapping studies based on Mo17 and B73 were performed to reveal mechanisms that influence the DIMBOA level in 24 dai plants. A major quantitative trait locus mapped to the Bx gene cluster located on the short arm of chromosome 4, which encodes the DIMBOA biosynthetic genes. Mo17 was distinguished from all other NAM lines by high transcriptional expression of the Bx1 gene at later developmental stages. Bx1 encodes the signature enzyme of the pathway. In Mo17×B73 hybrids at 24 dai, only the Mo17 Bx1 allele transcript was detected. A 3.9kb cis-element, termed DICE (distal cis-element), that is located in the Bx gene cluster approximately 140 kb upstream of Bx1, was required for high Bx1 transcript levels during later developmental stages in Mo17. The DICE region was a hotspot of meiotic recombination. Genetic analysis revealed that high 24 dai DIMBOA concentrations were not strictly dependent on high Bx1 transcript levels. However, constitutive expression of Bx1 in transgenics increased DIMBOA levels at 24 dai, corroborating a correlation between DIMBOA content and Bx1 transcription.

  11. Explicit expression to predict the erosive burning rate of solid propellants

    NASA Technical Reports Server (NTRS)

    Wang, S.

    1986-01-01

    Using the theory of gas dynamics and heat transfer from a turbulent gas flow to the burning surface of propellant along a permeable wall, an explicit expression is derived to predict the burning rate of the solid propellant with crossflow. Results of the calculation have been compared with experimental data and proved to be correct.

  12. Expression of Estrogen-Related Gene Markers in Breast Cancer Tissue Predicts Aromatase Inhibitor Responsiveness

    PubMed Central

    Moy, Irene; Lin, Zhihong; Rademaker, Alfred W.; Reierstad, Scott; Khan, Seema A.; Bulun, Serdar E.

    2013-01-01

    Aromatase inhibitors (AIs) are the most effective class of drugs in the endocrine treatment of breast cancer, with an approximate 50% treatment response rate. Our objective was to determine whether intratumoral expression levels of estrogen-related genes are predictive of AI responsiveness in postmenopausal women with breast cancer. Primary breast carcinomas were obtained from 112 women who received AI therapy after failing adjuvant tamoxifen therapy and developing recurrent breast cancer. Tumor ERα and PR protein expression were analyzed by immunohistochemistry (IHC). Messenger RNA (mRNA) levels of 5 estrogen-related genes–AKR1C3, aromatase, ERα, and 2 estradiol/ERα target genes, BRCA1 and PR–were measured by real-time PCR. Tumor protein and mRNA levels were compared with breast cancer progression rates to determine predictive accuracy. Responsiveness to AI therapy–defined as the combined complete response, partial response, and stable disease rates for at least 6 months–was 51%; rates were 56% in ERα-IHC-positive and 14% in ERα-IHC-negative tumors. Levels of ERα, PR, or BRCA1 mRNA were independently predictive for responsiveness to AI. In cross-validated analyses, a combined measurement of tumor ERα and PR mRNA levels yielded a more superior specificity (36%) and identical sensitivity (96%) to the current clinical practice (ERα/PR-IHC). In patients with ERα/PR-IHC-negative tumors, analysis of mRNA expression revealed either non-significant trends or statistically significant positive predictive values for AI responsiveness. In conclusion, expression levels of estrogen-related mRNAs are predictive for AI responsiveness in postmenopausal women with breast cancer, and mRNA expression analysis may improve patient selection. PMID:24223121

  13. Signature protein of the PVC superphylum.

    PubMed

    Lagkouvardos, Ilias; Jehl, Marc-André; Rattei, Thomas; Horn, Matthias

    2014-01-01

    The phyla Planctomycetes, Verrucomicrobia, Chlamydiae, Lentisphaerae, and "Candidatus Omnitrophica (OP3)" comprise bacteria that share an ancestor but show highly diverse biological and ecological features. Together, they constitute the PVC superphylum. Using large-scale comparative genome sequence analysis, we identified a protein uniquely shared among all of the known members of the PVC superphylum. We provide evidence that this signature protein is expressed by representative members of the PVC superphylum. Its predicted structure, physicochemical characteristics, and overexpression in Escherichia coli and gel retardation assays with purified signature protein suggest a housekeeping function with unspecific DNA/RNA binding activity. Phylogenetic analysis demonstrated that the signature protein is a suitable phylogenetic marker for members of the PVC superphylum, and the screening of published metagenome data indicated the existence of additional PVC members. This study provides further evidence of a common evolutionary history of the PVC superphylum and presents a unique case in which a single protein serves as an evolutionary link among otherwise highly diverse members of major bacterial groups.

  14. Lower MGMT expression predicts better prognosis in proneural-like glioblastoma

    PubMed Central

    He, Zhi-Cheng; Ping, Yi-Fang; Xu, Sen-Lin; Lin, Yong; Yu, Shi-Cang; Kung, Hsiang-Fu; Bian, Xiu-Wu

    2015-01-01

    Objective: To investigate the expression and significance of MGMT in different molecular subtypes of glioblastoma (GBM), and to evaluate the important role of MGMT and P53 in predicting the prognosis of GBM patients. Methods: MGMT expression was detected by immunohistochemical staining in 72 cases of GBM which had been classified as three molecular subtypes. The relationship between MGMT and P53, an important molecule for identification of proneural-like GBM, were further analyzed. The association between MGMT and patients’ prognosis was analyzed with Kaplan-Meier method, which was further validated by the data from 513 cases of GBM in the TCGA database. Results: MGMT expression was lower in proneural-like subtype in 72 GBM cases (p < 0.001), and was negatively correlated with P53 (r=-0. 6203, p < 0.001). This results was also verified by a validation group of 87 GBM cases (r=-0. 2950, p < 0.001). Interestingly, low expression of MGMT predicted a better outcome in proneurallike subtype or P53 high-expression group (p < 0.05) but not in non-proneural-like subtype and P53 low-expression group. All of these results were verified by the data from TCGA database. Conclusion: MGMT can be used as an independent prognostic factor and plays an important role in molecular typing and diagnosis of GBM by combination with proneural-like subtype marker P53. PMID:26884942

  15. Combining gene mutation with gene expression data improves outcome prediction in myelodysplastic syndromes

    PubMed Central

    Gerstung, Moritz; Pellagatti, Andrea; Malcovati, Luca; Giagounidis, Aristoteles; Porta, Matteo G Della; Jädersten, Martin; Dolatshad, Hamid; Verma, Amit; Cross, Nicholas C. P.; Vyas, Paresh; Killick, Sally; Hellström-Lindberg, Eva; Cazzola, Mario; Papaemmanuil, Elli; Campbell, Peter J.; Boultwood, Jacqueline

    2015-01-01

    Cancer is a genetic disease, but two patients rarely have identical genotypes. Similarly, patients differ in their clinicopathological parameters, but how genotypic and phenotypic heterogeneity are interconnected is not well understood. Here we build statistical models to disentangle the effect of 12 recurrently mutated genes and 4 cytogenetic alterations on gene expression, diagnostic clinical variables and outcome in 124 patients with myelodysplastic syndromes. Overall, one or more genetic lesions correlate with expression levels of ~20% of all genes, explaining 20–65% of observed expression variability. Differential expression patterns vary between mutations and reflect the underlying biology, such as aberrant polycomb repression for ASXL1 and EZH2 mutations or perturbed gene dosage for copy-number changes. In predicting survival, genomic, transcriptomic and diagnostic clinical variables all have utility, with the largest contribution from the transcriptome. Similar observations are made on the TCGA acute myeloid leukaemia cohort, confirming the general trends reported here. PMID:25574665

  16. Valproate Treatment of Human Cord Blood CD4-positive Effector T Cells Confers on Them the Molecular Profile (MicroRNA Signature and FOXP3 Expression) of Natural Regulatory CD4-positive Cells through Inhibition of Histone Deacetylase*

    PubMed Central

    Fayyad-Kazan, Hussein; Rouas, Redouane; Merimi, Makram; El Zein, Nabil; Lewalle, Philippe; Jebbawi, Fadi; Mourtada, Mohamad; Badran, Hussein; Ezzeddine, Mohamad; Salaun, Bruno; Romero, Pedro; Burny, Arsène; Martiat, Philippe; Badran, Bassam

    2010-01-01

    Regulatory T cells (Tregs) play a key role in immune system homeostasis and tolerance to antigens, thereby preventing autoimmunity, and may be partly responsible for the lack of an appropriate immune response against tumor cells. Although not sufficient, a high expression of forkhead box P3 (FOXP3) is necessary for their suppressive function. Recent reports have shown that histones deacetylase inhibitors increased FOXP3 expression in T cells. We therefore decided to investigate in non-Tregs CD4-positive cells, the mechanisms by which an aspecific opening of the chromatin could lead to an increased FOXP3 expression. We focused on binding of potentially activating transcription factors to the promoter region of FOXP3 and on modifications in the five miRs constituting the Tregs signature. Valproate treatment induced binding of Ets-1 and Ets-2 to the FOXP3 promoter and acted positively on its expression, by increasing the acetylation of histone H4 lysines. Valproate treatment also induced the acquisition of the miRs Tregs signature. To elucidate whether the changes in the miRs expression could be due to the increased FOXP3 expression, we transduced these non-Tregs with a FOXP3 lentiviral expression vector, and found no changes in miRs expression. Therefore, the modification in their miRs expression profile is not due to an increased expression of FOXP3 but directly results from histones deacetylase inhibition. Rather, the increased FOXP3 expression results from the additive effects of Ets factors binding and the change in expression level of miR-21 and miR-31. We conclude that valproate treatment of human non-Tregs confers on them a molecular profile similar to that of their regulatory counterpart. PMID:20427269

  17. Using machine learning to predict gene expression and discover sequence motifs

    NASA Astrophysics Data System (ADS)

    Li, Xuejing

    Recently, large amounts of experimental data for complex biological systems have become available. We use tools and algorithms from machine learning to build data-driven predictive models. We first present a novel algorithm to discover gene sequence motifs associated with temporal expression patterns of genes. Our algorithm, which is based on partial least squares (PLS) regression, is able to directly model the flow of information, from gene sequence to gene expression, to learn cis regulatory motifs and characterize associated gene expression patterns. Our algorithm outperforms traditional computational methods e.g. clustering in motif discovery. We then present a study of extending a machine learning model for transcriptional regulation predictive of genetic regulatory response to Caenorhabditis elegans. We show meaningful results both in terms of prediction accuracy on the test experiments and biological information extracted from the regulatory program. The model discovers DNA binding sites ab initio. We also present a case study where we detect a signal of lineage-specific regulation. Finally we present a comparative study on learning predictive models for motif discovery, based on different boosting algorithms: Adaptive Boosting (AdaBoost), Linear Programming Boosting (LPBoost) and Totally Corrective Boosting (TotalBoost). We evaluate and compare the performance of the three boosting algorithms via both statistical and biological validation, for hypoxia response in Saccharomyces cerevisiae.

  18. Low thrombospondin 2 expression is predictive of low tumor regression after neoadjuvant chemoradiotherapy in rectal cancer

    PubMed Central

    Lin, Cheng-Yi; Lin, Ching-Yih; Chang, I-Wei; Sheu, Ming-Jen; Li, Chien-Feng; Lee, Sung-Wei; Lin, Li-Ching; Lee, Ying-En; He, Hong-Lin

    2015-01-01

    Background: Neoadjuvant concurrent chemoradiotherapy (CCRT) followed by surgery is the mainstay of treatment for locally advanced rectal cancer. Several heparin-binding associated proteins have been reported to play a critical role in cancer progression. However, the clinical relevancies of such proteins and their associations with CCRT response in rectal cancer have not yet to be fully elucidated. Methods: The analysis of a public transcriptome of rectal cancer indicated that thrombospondin 2 (THBS2) is a predictive factor for CCRT response. Immunohistochemical analyses were conducted to evaluate the expression of THBS2 in pretreatment biopsy specimens from rectal cancer patients without distant metastasis. Furthermore, the relationships between THBS2 expression and various clinicopathological factors or survival were analyzed. Results: Low expression of THBS2 was significantly associated with advanced pretreatment tumor (P<0.001) and nodal status (P=0.004), post-treatment tumor (P<0.001) and nodal status (P<0.001), increased vascular invasion (P=0.003), increased perineural invasion (P=0.023) and inferior tumor regression grade (P=0.015). In univariate analysis, low THBS2 expression predicted worse outcomes for disease-free survival, local recurrence-free survival and metastasis-free survival (all P<0.001). In multivariate analysis, low expression of THBS2 still served as a negative prognostic factor for disease-free survival (Hazard ratio=3.057, P=0.002) and metastasis-free survival (Hazard ratio=3.362, P=0.012). Conclusion: Low THBS2 expression was correlated with advanced disease status and low tumor regression after preoperative CCRT and that it acted as an independent negative prognostic factor in rectal cancer. THBS2 may represent a predictive biomarker for CCRT response in rectal cancer. PMID:26807188

  19. Early postnatal testosterone predicts sex-related differences in early expressive vocabulary.

    PubMed

    Kung, Karson T F; Browne, Wendy V; Constantinescu, Mihaela; Noorderhaven, Rebecca M; Hines, Melissa

    2016-06-01

    During the first few years of life, girls typically have a larger expressive vocabulary than boys. This sex difference is important since a small vocabulary may predict subsequent language difficulties, which are more prevalent in boys than girls. The masculinizing effects of early androgen exposure on neurobehavioral development are well-documented in nonhuman mammals. The present study conducted the first test of whether early postnatal testosterone concentrations influence sex differences in expressive vocabulary in toddlers. It was found that testosterone measured in saliva samples collected at 1-3 months of age, i.e., during the period called mini-puberty, negatively predicted parent-report expressive vocabulary size at 18-30 months of age in boys and in girls. Testosterone concentrations during mini-puberty also accounted for additional variance in expressive vocabulary after other predictors such as sex, child's age at vocabulary assessment, and paternal education, were taken into account. Furthermore, testosterone concentrations during mini-puberty mediated the sex difference in expressive vocabulary. These results suggest that testosterone during the early postnatal period contributes to early language development and neurobehavioral sexual differentiation in humans.

  20. Early postnatal testosterone predicts sex-related differences in early expressive vocabulary.

    PubMed

    Kung, Karson T F; Browne, Wendy V; Constantinescu, Mihaela; Noorderhaven, Rebecca M; Hines, Melissa

    2016-06-01

    During the first few years of life, girls typically have a larger expressive vocabulary than boys. This sex difference is important since a small vocabulary may predict subsequent language difficulties, which are more prevalent in boys than girls. The masculinizing effects of early androgen exposure on neurobehavioral development are well-documented in nonhuman mammals. The present study conducted the first test of whether early postnatal testosterone concentrations influence sex differences in expressive vocabulary in toddlers. It was found that testosterone measured in saliva samples collected at 1-3 months of age, i.e., during the period called mini-puberty, negatively predicted parent-report expressive vocabulary size at 18-30 months of age in boys and in girls. Testosterone concentrations during mini-puberty also accounted for additional variance in expressive vocabulary after other predictors such as sex, child's age at vocabulary assessment, and paternal education, were taken into account. Furthermore, testosterone concentrations during mini-puberty mediated the sex difference in expressive vocabulary. These results suggest that testosterone during the early postnatal period contributes to early language development and neurobehavioral sexual differentiation in humans. PMID:26970201

  1. Expression of KLF4 is a predictive marker for survival in pediatric Burkitt lymphoma.

    PubMed

    Valencia-Hipόlito, Alberto; Hernández-Atenógenes, Miriam; Vega, Gabriel G; Maldonado-Valenzuela, Altagracia; Ramon, Guillermo; Mayani, Héctor; Peña Alonso, Yolanda; Martinez-Maza, Otoniel; Méndez-Tenorio, Alfonso; Huerta-Yepez, Sara; Bonavida, Benjamin; Vega, Mario I

    2014-08-01

    Krüppel-like factor 4 (KLF4) is expressed in a variety of tissues with diverse physiological functions and activities. KLF4 can also function as a tumor suppressor or an oncogene, depending on the cellular context. Its role in hematological malignancies is controversial. This study examined the expression levels of KLF4 by immunohistochemistry in 73 pediatric non-Hodgkin lymphomas (NHLs) in a tissue microarray and also on several B-NHL cell lines. Elevated levels of KLF4 expression were detected in 66% of lymphoma cases and were more frequent in the Burkitt lymphoma (p = 0.05) subtype. There was a significant predictive power for outcome with low KLF4 expression, predicting a favorable overall survival compared to high levels. Multivariate analyses confirmed the association of KLF4 expression with unfavorable overall survival (p < 0.005). These findings were consistent with analyses in existing NHL microarray datasets. The present findings revealed that KLF4 is overexpressed in Burkitt pediatric lymphoma and is a potential biomarker for inferior overall survival. PMID:24067139

  2. Computational prediction of microRNAs from Toxoplasma gondii potentially regulating the hosts' gene expression.

    PubMed

    Saçar, Müşerref Duygu; Bağcı, Caner; Allmer, Jens

    2014-10-01

    MicroRNAs (miRNAs) were discovered two decades ago, yet there is still a great need for further studies elucidating their genesis and targeting in different phyla. Since experimental discovery and validation of miRNAs is difficult, computational predictions are indispensable and today most computational approaches employ machine learning. Toxoplasma gondii, a parasite residing within the cells of its hosts like human, uses miRNAs for its post-transcriptional gene regulation. It may also regulate its hosts' gene expression, which has been shown in brain cancer. Since previous studies have shown that overexpressed miRNAs within the host are causal for disease onset, we hypothesized that T. gondii could export miRNAs into its host cell. We computationally predicted all hairpins from the genome of T. gondii and used mouse and human models to filter possible candidates. These were then further compared to known miRNAs in human and rodents and their expression was examined for T. gondii grown in mouse and human hosts, respectively. We found that among the millions of potential hairpins in T. gondii, only a few thousand pass filtering using a human or mouse model and that even fewer of those are expressed. Since they are expressed and differentially expressed in rodents and human, we suggest that there is a chance that T. gondii may export miRNAs into its hosts for direct regulation.

  3. ZEB1 Expression in Endometrial Biopsy Predicts Lymph Node Metastases in Patient with Endometrial Cancer

    PubMed Central

    Feng, Gang; Wang, Xiangming; Cao, Xiaozhi; Shen, Lijuan; Zhu, Jiansheng

    2014-01-01

    Purpose. The purpose of this study was to analyze the expression of zinc-finger E-box-binding homeobox 1 (ZEB1) in endometrial biopsy and its correlation with preoperative characteristics, including lymph node metastases in patient with endometrial cancer. Methods. Using quantitative RT-PCR, ZEB1 expressions in endometrial biopsy from 452 patients were measured. The relationship between ZEB1 expression and preoperative characteristics was analyzed. Results. ZEB1 expressions were significantly associated with subtype, grade, myometrial invasion, and lymph node metastases. Lymph node metastases could be identified with a sensitivity of 57.8% at specificity of 74.1% by ZEB1 expression in endometrial biopsy. Based on combination of preoperative characteristics and ZEB1 expression, lymph node metastases could be identified with a sensitivity of 62.1% at specificity of 96.2% prior to hysterectomy. Conclusion. ZEB1 expression in endometrial biopsy could help physicians to better predict the lymph node metastasis in patients with endometrial cancer prior to hysterectomy. PMID:25544793

  4. TAK1-regulated expression of BIRC3 predicts resistance to preoperative chemoradiotherapy in oesophageal adenocarcinoma patients

    PubMed Central

    Piro, G; Giacopuzzi, S; Bencivenga, M; Carbone, C; Verlato, G; Frizziero, M; Zanotto, M; Mina, M M; Merz, V; Santoro, R; Zanoni, A; De Manzoni, G; Tortora, G; Melisi, D

    2015-01-01

    Background: About 20% of resectable oesophageal carcinoma is resistant to preoperative chemoradiotherapy. Here we hypothesised that the expression of the antiapoptotic gene Baculoviral inhibitor of apoptosis repeat containing (BIRC)3 induced by the transforming growth factor β activated kinase 1 (TAK1) might be responsible for the resistance to the proapoptotic effect of chemoradiotherapy in oesophageal carcinoma. Methods: TAK1 kinase activity was inhibited in FLO-1 and KYAE-1 oesophageal adenocarcinoma cells using (5Z)-7-oxozeaenol. The BIRC3 mRNA expression was measured by qRT–PCR in 65 pretreatment frozen biopsies from patients receiving preoperatively docetaxel, cisplatin, 5-fluorouracil, and concurrent radiotherapy. Receiver operator characteristic (ROC) analyses were performed to determine the performance of BIRC3 expression levels in distinguishing patients with sensitive or resistant carcinoma. Results: In vitro, (5Z)-7-oxozeaenol significantly reduced BIRC3 expression in FLO-1 and KYAE-1 cells. Exposure to chemotherapeutic agents or radiotherapy plus (5Z)-7-oxozeaenol resulted in a strong synergistic antiapoptotic effect. In patients, median expression of BIRC3 was significantly (P<0.0001) higher in adenocarcinoma than in the more sensitive squamous cell carcinoma subtype. The BIRC3 expression significantly discriminated patients with sensitive or resistant adenocarcinoma (AUC-ROC=0.7773 and 0.8074 by size-based pathological response or Mandard's tumour regression grade classifications, respectively). Conclusions: The BIRC3 expression might be a valid biomarker for predicting patients with oesophageal adenocarcinoma that could most likely benefit from preoperative chemoradiotherapy. PMID:26291056

  5. Predicting response and survival in chemotherapy-treated triple-negative breast cancer

    PubMed Central

    Prat, A; Lluch, A; Albanell, J; Barry, W T; Fan, C; Chacón, J I; Parker, J S; Calvo, L; Plazaola, A; Arcusa, A; Seguí-Palmer, M A; Burgues, O; Ribelles, N; Rodriguez-Lescure, A; Guerrero, A; Ruiz-Borrego, M; Munarriz, B; López, J A; Adamo, B; Cheang, M C U; Li, Y; Hu, Z; Gulley, M L; Vidal, M J; Pitcher, B N; Liu, M C; Citron, M L; Ellis, M J; Mardis, E; Vickery, T; Hudis, C A; Winer, E P; Carey, L A; Caballero, R; Carrasco, E; Martín, M; Perou, C M; Alba, E

    2014-01-01

    Background: In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC). Methods: Gene expression and clinical–pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated. Results: Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55–81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival. Conclusions: The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not. PMID:25101563

  6. Autophagy-related prognostic signature for breast cancer.

    PubMed

    Gu, Yunyan; Li, Pengfei; Peng, Fuduan; Zhang, Mengmeng; Zhang, Yuanyuan; Liang, Haihai; Zhao, Wenyuan; Qi, Lishuang; Wang, Hongwei; Wang, Chenguang; Guo, Zheng

    2016-03-01

    Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer.

  7. Distinct patterns of ALDH1A1 expression predict metastasis and poor outcome of colorectal carcinoma

    PubMed Central

    Xu, Sen-Lin; Zeng, Dong-Zu; Dong, Wei-Guo; Ding, Yan-Qing; Rao, Jun; Duan, Jiang-Jie; Liu, Qing; Yang, Jing; Zhan, Na; Liu, Ying; Hu, Qi-Ping; Zhang, Xia; Cui, You-Hong; Kung, Hsiang-Fu; Yu, Shi-Cang; Bian, Xiu-Wu

    2014-01-01

    Purpose: Aldehyde dehydrogenase 1A1 (ALDH1A1) has been proposed as a candidate biomarker for colorectal carcinoma (CRC). However, the heterogeneity of its expression makes it difficult to predict the outcome of CRC. The aim of this study was to evaluate the diagnostic and prognostic value of this molecule in CRC. Methods and Results: In this study, we examined ALDH1A1 expression by immunohistochemistry including 406 cases of primary CRC with corresponding adjacent mucosa, with confirmation of real-time PCR and Western blotting. We found that the expression patterns of ALDH1A1 were heterogeneous in the CRC and corresponding adjacent tissues. We defined the ratio of ALDH1A1 level in adjacent mucosa to that in tumor tissues as RA/C and found that the capabilities of tumor invasion and metastasis in the tumors with RA/C < 1 were significantly higher than those with RA/C ≥ 1. Follow-up data showed the worse prognoses in the CRC patients with RA/C < 1. For understanding the underlying mechanism, the localization of β-catenin was detected in the CRC tissues with different patterns of ALDH1A1 expression from 221 patients and β-catenin was found preferentially expressed in cell nuclei of the tumors with RA/C < 1 and ALDH1A1high expression of HT29 cell line, indicating that nuclear translocation of β-catenin might contribute to the increased potentials of invasion and metastasis. Conclusion: Our results indicate that RA/C is a novel biomarker to reflect the distinct expression patterns of ALDH1A1 for predicting metastasis and prognosis of CRC. PMID:25031716

  8. Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats

    NASA Astrophysics Data System (ADS)

    Chaudhury, Baishali; Zhou, Mu; Farhidzadeh, Hamidreza; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Weinfurtner, Robert J.; Drukteinis, Jennifer S.

    2016-03-01

    The use of Ki67% expression, a cell proliferation marker, as a predictive and prognostic factor has been widely studied in the literature. Yet its usefulness is limited due to inconsistent cut off scores for Ki67% expression, subjective differences in its assessment in various studies, and spatial variation in expression, which makes it difficult to reproduce as a reliable independent prognostic factor. Previous studies have shown that there are significant spatial variations in Ki67% expression, which may limit its clinical prognostic utility after core biopsy. These variations are most evident when examining the periphery of the tumor vs. the core. To date, prediction of Ki67% expression from quantitative image analysis of DCE-MRI is very limited. This work presents a novel computer aided diagnosis framework to use textural kinetics to (i) predict the ratio of periphery Ki67% expression to core Ki67% expression, and (ii) predict Ki67% expression from individual tumor habitats. The pilot cohort consists of T1 weighted fat saturated DCE-MR images from 17 patients. Support vector regression with a radial basis function was used for predicting the Ki67% expression and ratios. The initial results show that texture features from individual tumor habitats are more predictive of the Ki67% expression ratio and spatial Ki67% expression than features from the whole tumor. The Ki67% expression ratio could be predicted with a root mean square error (RMSE) of 1.67%. Quantitative image analysis of DCE-MRI using textural kinetic habitats, has the potential to be used as a non-invasive method for predicting Ki67 percentage and ratio, thus more accurately reporting high KI-67 expression for patient prognosis.

  9. The Role of Prion Protein Expression in Predicting Gastric Cancer Prognosis

    PubMed Central

    Tang, Zhaoqing; Ma, Ji; Zhang, Wei; Gong, Changguo; He, Jing; Wang, Ying; Yu, Guohua; Yuan, Chonggang; Wang, Xuefei; Sun, Yihong; Ma, Jiyan; Liu, Fenglin; Zhao, Yulan

    2016-01-01

    Previous reports indicated that prion protein (PrP) is involved in gastric cancer (GC) development and progression, but its role in GC prognosis has been poorly characterized. A total of 480 GC patients were recruited in this retrospective study. PrP expression in cancerous and non-cancerous gastric tissues was detected by using the tissue microarray and immunohistochemical staining techniques. Our results showed that the PrP expression in GC was significantly less frequent than that in the non-cancerous gastric tissue (44.4% vs 66.4%, P < 0.001). Cox regression analysis revealed that PrP expression was associated with TNM stage, survival status and survival time. GC patients with higher TNM stages (stages II, III and IV) had significantly lower PrP expression levels in tumors than those with lower TNM stages (stages 0 and I). Kaplan-Meier survival curves revealed that negative PrP expression was associated with poor overall survival (log-rank test: P < 0.001). The mean survival time for patients with negative PrP expression was significant lower than those with positive PrP expression (43.0±28.5m vs. 53.9±31.1m, P<0.001). In multivariate Cox hazard regression, PrP expression was an independent prognostic factor for GC survival, with a HR (hazard ratio) of 0.687 (95%CI:0.520-0.907, P=0.008). Our results revealed that negative PrP expression could independently predict worse outcome in GC and thereby could be used to guide the clinical practice. PMID:27313789

  10. CXCL10 mRNA expression predicts response to neoadjuvant chemoradiotherapy in rectal cancer patients.

    PubMed

    Li, Cong; Wang, Zhimin; Liu, Fangqi; Zhu, Ji; Yang, Li; Cai, Guoxiang; Zhang, Zhen; Huang, Wei; Cai, Sanjun; Xu, Ye

    2014-10-01

    Chemoradiotherapy has been commonly used as neoadjuvant therapy for rectal cancer to allow for less aggressive surgical approaches and to improve quality of life. In cancer, it has been reported that CXCL10 has an anti-tumor function. However, the association between CXCL10 and chemoradiosensitivity has not been fully investigated. We performed this study to investigate the relationship between CXCL10 expression and chemoradiosensitivity in rectal cancer patients. Ninety-five patients with rectal cancer who received neoadjuvant chemoradiotherapy (NCRT) were included. Clinical parameters were compared with the outcome of NCRT and CXCL10 messenger RNA (mRNA) expression between the pathological complete response (pCR) group and non-pathological complete response (npCR) group. CXCL10 mRNA and protein expressions between groups were analyzed using the Student's t test and chi-square test. The mean mRNA level of CXCL10 in the pCR group was significantly higher than that in the npCR group (p = 0.010). In the pCR group, 73.7 % of the patients had high CXCL10 mRNA expression, and 61.4 % of the patients in the npCR group had low CXCL10 mRNA expression. Subjects with high CXCL10 mRNA expression demonstrated a higher sensitivity to NCRT (p = 0.011). The receiver operating characteristic curve showed that the diagnostic performance of CXCL10 mRNA expression had an area under the curve of 0.720 (95 % confidence interval, 0.573-0.867). There were no differences between the pCR and npCR groups in CXCL10 protein expression (p > 0.05). High CXCL10 mRNA expression is associated with a better tumor response to NCRT in rectal cancer patients and may predict the outcome of NCRT in this malignancy.

  11. Expression Pattern Similarities Support the Prediction of Orthologs Retaining Common Functions after Gene Duplication Events.

    PubMed

    Das, Malay; Haberer, Georg; Panda, Arup; Das Laha, Shayani; Ghosh, Tapas Chandra; Schäffner, Anton R

    2016-08-01

    The identification of functionally equivalent, orthologous genes (functional orthologs) across genomes is necessary for accurate transfer of experimental knowledge from well-characterized organisms to others. This frequently relies on automated, coding sequence-based approaches such as OrthoMCL, Inparanoid, and KOG, which usually work well for one-to-one homologous states. However, this strategy does not reliably work for plants due to the occurrence of extensive gene/genome duplication. Frequently, for one query gene, multiple orthologous genes are predicted in the other genome, and it is not clear a priori from sequence comparison and similarity which one preserves the ancestral function. We have studied 11 organ-dependent and stress-induced gene expression patterns of 286 Arabidopsis lyrata duplicated gene groups and compared them with the respective Arabidopsis (Arabidopsis thaliana) genes to predict putative expressologs and nonexpressologs based on gene expression similarity. Promoter sequence divergence as an additional tool to substantiate functional orthology only partially overlapped with expressolog classification. By cloning eight A. lyrata homologs and complementing them in the respective four Arabidopsis loss-of-function mutants, we experimentally proved that predicted expressologs are indeed functional orthologs, while nonexpressologs or nonfunctionalized orthologs are not. Our study demonstrates that even a small set of gene expression data in addition to sequence homologies are instrumental in the assignment of functional orthologs in the presence of multiple orthologs. PMID:27303025

  12. c-Fos expression predicts long-term social memory retrieval in mice.

    PubMed

    Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

    2016-10-15

    The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures.

  13. c-Fos expression predicts long-term social memory retrieval in mice.

    PubMed

    Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

    2016-10-15

    The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures. PMID:27449201

  14. Predicting Variabilities in Cardiac Gene Expression with a Boolean Network Incorporating Uncertainty.

    PubMed

    Grieb, Melanie; Burkovski, Andre; Sträng, J Eric; Kraus, Johann M; Groß, Alexander; Palm, Günther; Kühl, Michael; Kestler, Hans A

    2015-01-01

    Gene interactions in cells can be represented by gene regulatory networks. A Boolean network models gene interactions according to rules where gene expression is represented by binary values (on / off or {1, 0}). In reality, however, the gene's state can have multiple values due to biological properties. Furthermore, the noisy nature of the experimental design results in uncertainty about a state of the gene. Here we present a new Boolean network paradigm to allow intermediate values on the interval [0, 1]. As in the Boolean network, fixed points or attractors of such a model correspond to biological phenotypes or states. We use our new extension of the Boolean network paradigm to model gene expression in first and second heart field lineages which are cardiac progenitor cell populations involved in early vertebrate heart development. By this we are able to predict additional biological phenotypes that the Boolean model alone is not able to identify without utilizing additional biological knowledge. The additional phenotypes predicted by the model were confirmed by published biological experiments. Furthermore, the new method predicts gene expression propensities for modelled but yet to be analyzed genes.

  15. Predicting Variabilities in Cardiac Gene Expression with a Boolean Network Incorporating Uncertainty

    PubMed Central

    Kraus, Johann M.; Groß, Alexander; Palm, Günther; Kühl, Michael; Kestler, Hans A.

    2015-01-01

    Gene interactions in cells can be represented by gene regulatory networks. A Boolean network models gene interactions according to rules where gene expression is represented by binary values (on / off or {1, 0}). In reality, however, the gene’s state can have multiple values due to biological properties. Furthermore, the noisy nature of the experimental design results in uncertainty about a state of the gene. Here we present a new Boolean network paradigm to allow intermediate values on the interval [0, 1]. As in the Boolean network, fixed points or attractors of such a model correspond to biological phenotypes or states. We use our new extension of the Boolean network paradigm to model gene expression in first and second heart field lineages which are cardiac progenitor cell populations involved in early vertebrate heart development. By this we are able to predict additional biological phenotypes that the Boolean model alone is not able to identify without utilizing additional biological knowledge. The additional phenotypes predicted by the model were confirmed by published biological experiments. Furthermore, the new method predicts gene expression propensities for modelled but yet to be analyzed genes. PMID:26207376

  16. Employing gene set top scoring pairs to identify deregulated pathway-signatures in dilated cardiomyopathy from integrated microarray gene expression data.

    PubMed

    Tan, Aik Choon

    2012-01-01

    It is well accepted that a set of genes must act in concert to drive various cellular processes. However, under different biological phenotypes, not all the members of a gene set will participate in a biological process. Hence, it is useful to construct a discriminative classifier by focusing on the core members (subset) of a highly informative gene set. Such analyses can reveal which of those subsets from the same gene set correspond to different biological phenotypes. In this study, we propose Gene Set Top Scoring Pairs (GSTSP) approach that exploits the simple yet powerful relative expression reversal concept at the gene set levels to achieve these goals. To illustrate the usefulness of GSTSP, we applied this method to five different human heart failure gene expression data sets. We take advantage of the direct data integration feature in the GSTSP approach to combine two data sets, identify a discriminative gene set from >190 predefined gene sets, and evaluate the predictive power of the GSTSP classifier derived from this informative gene set on three independent test sets (79.31% in test accuracy). The discriminative gene pairs identified in this study may provide new biological understanding on the disturbed pathways that are involved in the development of heart failure. GSTSP methodology is general in purpose and is applicable to a variety of phenotypic classification problems using gene expression data.

  17. Fine motor skill predicts expressive language in infant siblings of children with autism.

    PubMed

    LeBarton, Eve Sauer; Iverson, Jana M

    2013-11-01

    We investigated whether fine motor and expressive language skills are related in the later-born siblings of children with autism (heightened-risk, HR infants) who are at increased risk for language delays. We observed 34 HR infants longitudinally from 12 to 36 months. We used parent report and standardized observation measures to assess fine motor skill from 12 to 24 months in HR infants (Study 1) and its relation to later expressive vocabulary at 36 months in HR infants (Study 2). In Study 1, we also included 25 infants without a family history of autism to serve as a normative comparison group for a parent-report fine motor measure. We found that HR infants exhibited fine motor delays between 12 and 24 months and expressive vocabulary delays at 36 months. Further, fine motor skill significantly predicted expressive language at 36 months. Fine motor and expressive language skills are related early in development in HR infants, who, as a group, exhibit risk for delays in both. Our findings highlight the importance of considering fine motor skill in children at risk for language impairments and may have implications for early identification of expressive language difficulties.

  18. Prediction errors to emotional expressions: the roles of the amygdala in social referencing.

    PubMed

    Meffert, Harma; Brislin, Sarah J; White, Stuart F; Blair, James R

    2015-04-01

    Social referencing paradigms in humans and observational learning paradigms in animals suggest that emotional expressions are important for communicating valence. It has been proposed that these expressions initiate stimulus-reinforcement learning. Relatively little is known about the role of emotional expressions in reinforcement learning, particularly in the context of social referencing. In this study, we examined object valence learning in the context of a social referencing paradigm. Participants viewed objects and faces that turned toward the objects and displayed a fearful, happy or neutral reaction to them, while judging the gender of these faces. Notably, amygdala activation was larger when the expressions following an object were less expected. Moreover, when asked, participants were both more likely to want to approach, and showed stronger amygdala responses to, objects associated with happy relative to objects associated with fearful expressions. This suggests that the amygdala plays two roles in social referencing: (i) initiating learning regarding the valence of an object as a function of prediction errors to expressions displayed toward this object and (ii) orchestrating an emotional response to the object when value judgments are being made regarding this object.

  19. Prediction errors to emotional expressions: the roles of the amygdala in social referencing.