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Sample records for expression signatures predict

  1. 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...

  2. 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

  3. 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...

  4. A composite gene expression signature optimizes prediction of colorectal cancer metastasis and outcome

    PubMed Central

    Schell, Michael J.; Yang, Mingli; Missiaglia, Edoardo; Delorenzi, Mauro; Soneson, Charlotte; Yue, Binglin; Nebozhyn, Michael V.; Loboda, Andrey; Bloom, Gregory; Yeatman, Timothy J

    2015-01-01

    Purpose We previously found that an epithelial-to-mesenchymal transition (EMT)-based gene expression signature was highly correlated to the first principal component (PC1) of 326 colorectal cancer (CRC) tumors and was prognostic. This study was designed to improve these signatures for better prediction of metastasis and outcome. Experimental Design 468 CRC tumors including all stages (I–IV) and metastatic lesions were used to develop a new prognostic score (ΔPC1.EMT) by subtracting the EMT signature score from its correlated PC1 signature score. The score was validated on six other independent datasets with total 3697 tumors. Results ΔPC1.EMT was found to be far more predictive of metastasis and outcome than its parent scores. It performed well in Stages I–III, amongst MSI subtypes, and across multiple mutation-based subclasses, demonstrating a refined capacity to predict distant metastatic potential in tumors even with a “good” prognosis. For example, in the PETACC-3 clinical trial dataset it predicted worse overall survival in an adjusted multivariable model for Stage III patients (HR by IQR=1.50, 95%CI=1.25–1.81, P=0.000016, N=644). The improved performance of ΔPC1.EMT was related to its propensity of identifying epithelial-like subpopulations as well as mesenchymal-like subpopulations. Biologically, the signature was correlated positively with RAS signaling but negatively with mitochondrial metabolism. ΔPC1.EMT was a “best of assessed” prognostic score when compared to ten other known prognostic signatures. Conclusion The study developed a prognostic signature score with a propensity of detecting non-EMT features, including epithelial cancer stem cell-related properties, thereby improving its potential to predict metastasis and poorer outcome in Stages I-III patients. PMID:26446941

  5. 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

  6. Long noncoding RNA expression signature to predict platinum-based chemotherapeutic sensitivity of ovarian cancer patients.

    PubMed

    Liu, Rong; Zeng, Ying; Zhou, Cheng-Fang; Wang, Ying; Li, Xi; Liu, Zhao-Qian; Chen, Xiao-Ping; Zhang, Wei; Zhou, Hong-Hao

    2017-12-01

    Dysregulated long noncoding RNAs (lncRNAs) are potential markers of several tumor prognoses. This study aimed to develop a lncRNA expression signature that can predict chemotherapeutic sensitivity for patients with advanced stage and high-grade serous ovarian cancer (HGS-OvCa) treated with platinum-based chemotherapy. The lncRNA expression profiles of 258 HGS-OvCa patients from The Cancer Genome Atlas were analyzed. Results revealed that an eight-lncRNA signature was significantly associated with chemosensitivity in the multivariate logistic regression model, which can accurately predict the chemosensitivity of patients [Area under curve (AUC) = 0.83]. The association of a chemosensitivity predictor with molecular subtypes indicated the excellent prognosis performance of this marker in differentiated, mesenchymal, and immunoreactive subtypes (AUC > 0.8). The significant correlation between ZFAS1 expression and chemosensitivity was confirmed in 233 HGS-OvCa patients from the Gene Expression Omnibus datasets (GSE9891, GSE63885, and GSE51373). In vitro experiments demonstrated that the ZFAS1 expression was upregulated by cisplatin in A2008, HeyA8, and HeyC2 cell lines. This finding suggested that ZFAS1 may participate in platinum resistance. Therefore, the evaluation of the eight-lncRNA signature may be clinically implicated in the selection of platinum-resistant HGS-OvCa patients. The role of ZFAS1 in platinum resistance should be further investigated.

  7. Predicting Autism Spectrum Disorder Using Blood-based Gene Expression Signatures and Machine Learning

    PubMed Central

    Oh, Dong Hoon; Kim, Il Bin; Kim, Seok Hyeon; Ahn, Dong Hyun

    2017-01-01

    Objective The aim of this study was to identify a transcriptomic signature that could be used to classify subjects with autism spectrum disorder (ASD) compared to controls on the basis of blood gene expression profiles. The gene expression profiles could ultimately be used as diagnostic biomarkers for ASD. Methods We used the published microarray data (GSE26415) from the Gene Expression Omnibus database, which included 21 young adults with ASD and 21 age- and sex-matched unaffected controls. Nineteen differentially expressed probes were identified from a training dataset (n=26, 13 ASD cases and 13 controls) using the limma package in R language (adjusted p value <0.05) and were further analyzed in a test dataset (n=16, 8 ASD cases and 8 controls) using machine learning algorithms. Results Hierarchical cluster analysis showed that subjects with ASD were relatively well-discriminated from controls. Based on the support vector machine and K-nearest neighbors analysis, validation of 19-DE probes with a test dataset resulted in an overall class prediction accuracy of 93.8% as well as a sensitivity and specificity of 100% and 87.5%, respectively. Conclusion The results of our exploratory study suggest that the gene expression profiles identified from the peripheral blood samples of young adults with ASD can be used to identify a biological signature for ASD. Further study using a larger cohort and more homogeneous datasets is required to improve the diagnostic accuracy. PMID:28138110

  8. A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections

    PubMed Central

    2012-01-01

    Background The complex balance between environmental and host factors is an important determinant of susceptibility to infection. Disturbances of this equilibrium may result in multifactorial diseases as illustrated by the summer mortality syndrome, a worldwide and complex phenomenon that affects the oysters, Crassostrea gigas. The summer mortality syndrome reveals a physiological intolerance making this oyster species susceptible to diseases. Exploration of genetic basis governing the oyster resistance or susceptibility to infections is thus a major goal for understanding field mortality events. In this context, we used high-throughput genomic approaches to identify genetic traits that may characterize inherent survival capacities in C. gigas. Results Using digital gene expression (DGE), we analyzed the transcriptomes of hemocytes (immunocompetent cells) of oysters able or not able to survive infections by Vibrio species shown to be involved in summer mortalities. Hemocytes were nonlethally collected from oysters before Vibrio experimental infection, and two DGE libraries were generated from individuals that survived or did not survive. Exploration of DGE data and microfluidic qPCR analyses at individual level showed an extraordinary polymorphism in gene expressions, but also a set of hemocyte-expressed genes whose basal mRNA levels discriminate oyster capacity to survive infections by the pathogenic V. splendidus LGP32. Finally, we identified a signature of 14 genes that predicted oyster survival capacity. Their expressions are likely driven by distinct transcriptional regulation processes associated or not associated to gene copy number variation (CNV). Conclusions We provide here for the first time in oyster a gene expression survival signature that represents a useful tool for understanding mortality events and for assessing genetic traits of interest for disease resistance selection programs. PMID:22708697

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

    PubMed Central

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

    2016-01-01

    Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment. PMID:27983725

  10. A gene expression signature that can predict green tea exposure and chemopreventive efficacy of lung cancer in mice.

    PubMed

    Lu, Yan; Yao, Ruisheng; Yan, Ying; Wang, Yian; Hara, Yukihiko; Lubet, Ronald A; You, Ming

    2006-02-15

    Green tea has been shown to be a potent chemopreventive agent against lung tumorigenesis in animal models. Previously, we found that treatment of A/J mice with either green tea (0.6% in water) or a defined green tea catechin extract (polyphenon E; 2.0 g/kg in diet) inhibited lung tumor tumorigenesis. Here, we described expression profiling of lung tissues derived from these studies to determine the gene expression signature that can predict the exposure and efficacy of green tea in mice. We first profiled global gene expressions in normal lungs versus lung tumors to determine genes which might be associated with the tumorigenic process (TUM genes). Gene expression in control tumors and green tea-treated tumors (either green tea or polyphenon E) were compared to determine those TUM genes whose expression levels in green tea-treated tumors returned to levels seen in normal lungs. We established a 17-gene expression profile specific for exposure to effective doses of either green tea or polyphenon E. This gene expression signature was altered both in normal lungs and lung adenomas when mice were exposed to green tea or polyphenon E. These experiments identified patterns of gene expressions that both offer clues for green tea's potential mechanisms of action and provide a molecular signature specific for green tea exposure.

  11. A Cell Type-Specific Expression Signature Predicts Haploinsufficient Autism-Susceptibility Genes.

    PubMed

    Zhang, Chaolin; Shen, Yufeng

    2017-02-01

    Recent studies have identified many genes with rare de novo mutations in autism, but a limited number of these have been conclusively established as disease-susceptibility genes due to the lack of recurrence and confounding background mutations. Such extreme genetic heterogeneity severely limits recurrence-based statistical power even in studies with a large sample size. Here, we use cell-type specific expression profiles to differentiate mutations in autism patients from those in unaffected siblings. We report a gene expression signature in different neuronal cell types shared by genes with likely gene-disrupting (LGD) mutations in autism cases. This signature reflects haploinsufficiency of risk genes enriched in transcriptional and post-transcriptional regulators, with the strongest positive associations with specific types of neurons in different brain regions, including cortical neurons, cerebellar granule cells, and striatal medium spiny neurons. When used to prioritize genes with a single LGD mutation in cases, a D-score derived from the signature achieved a precision of 40% as compared with the 15% baseline with a minimal loss in sensitivity. An ensemble model combining D-score with mutation intolerance metrics from Exome Aggregation Consortium further improved the precision to 60%, resulting in 117 high-priority candidates. These prioritized lists can facilitate identification of additional autism-susceptibility genes.

  12. No Specific Gene Expression Signature in Human Granulosa and Cumulus Cells for Prediction of Oocyte Fertilisation and Embryo Implantation

    PubMed Central

    Burnik Papler, Tanja; Vrtacnik Bokal, Eda; Lovrecic, Luca; Kopitar, Andreja Natasa; Maver, Ales

    2015-01-01

    In human IVF procedures objective and reliable biomarkers of oocyte and embryo quality are needed in order to increase the use of single embryo transfer (SET) and thus prevent multiple pregnancies. During folliculogenesis there is an intense bi-directional communication between oocyte and follicular cells. For this reason gene expression profile of follicular cells could be an important indicator and biomarker of oocyte and embryo quality. The objective of this study was to identify gene expression signature(s) in human granulosa (GC) and cumulus (CC) cells predictive of successful embryo implantation and oocyte fertilization. Forty-one patients were included in the study and individual GC and CC samples were collected; oocytes were cultivated separately, allowing a correlation with IVF outcome and elective SET was performed. Gene expression analysis was performed using microarrays, followed by a quantitative real-time PCR validation. After statistical analysis of microarray data, there were no significantly differentially expressed genes (FDR<0,05) between non-fertilized and fertilized oocytes and non-implanted and implanted embryos in either of the cell type. Furthermore, the results of quantitative real-time PCR were in consent with microarray data as there were no significant differences in gene expression of genes selected for validation. In conclusion, we did not find biomarkers for prediction of oocyte fertilization and embryo implantation in IVF procedures in the present study. PMID:25769026

  13. 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

  14. Gene expression signature for early prediction of late occurring pancytopenia in irradiated baboons.

    PubMed

    Port, Matthias; Hérodin, Francis; Valente, Marco; Drouet, Michel; Lamkowski, Andreas; Majewski, Matthäus; Abend, Michael

    2017-02-24

    Based on gene expression changes measured in the peripheral blood within the first 2 days after irradiation, we predicted a pancytopenia in a baboon model. Eighteen baboons were irradiated with 2.5 or 5 Gy. According to changes in blood cell counts, the surviving baboons (n = 17) exhibited a hematological acute radiation syndrome (HARS) either with or without a pancytopenia. We used a two stage study design where stage I was a whole genome screen (microarrays) for mRNA combined with a qRT-PCR platform for simultaneous detection of 667 miRNAs using a part of the samples. Candidate mRNAs and miRNAs differentially upregulated or downregulated (>2-fold, p < 0.05) during the first 2 days after irradiation were chosen for validation in stage II using the remaining samples and using throughout more sensitive qRT-PCR. We detected about twice as many upregulated (mean 2128) than downregulated genes (mean 789) in baboons developing an HARS either with or without a pancytopenia. From 51 candidate mRNAs altogether, 11 mRNAs were validated using qRT-PCR. These mRNAs showed only significant differences between HARS groups and H0, but not between HARS groups with and without pancytopenia. Six miRNA species (e.g., miR-574-3p, p = 0.009, ROC = 0.94) revealed significant gene expression differences between HARS groups with and without pancytopenia and are known to sensitize irradiated cells. Hence, in particular, the newly identified miRNA species for prediction of pancytopenia will support the medical management decision making.

  15. 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.

  16. Transcription factor regulation can be accurately predicted from the presence of target gene signatures in microarray gene expression data

    PubMed Central

    Essaghir, Ahmed; Toffalini, Federica; Knoops, Laurent; Kallin, Anders; van Helden, Jacques; Demoulin, Jean-Baptiste

    2010-01-01

    Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining. PMID:20215436

  17. 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.

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

    PubMed Central

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

    2015-01-01

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

  19. miRNA expression profiling of inflammatory breast cancer identifies a 5-miRNA signature predictive of breast tumor aggressiveness.

    PubMed

    Lerebours, Florence; Cizeron-Clairac, Geraldine; Susini, Aurelie; Vacher, Sophie; Mouret-Fourme, Emmanuelle; Belichard, Catherine; Brain, Etienne; Alberini, Jean-Louis; Spyratos, Frédérique; Lidereau, Rosette; Bieche, Ivan

    2013-10-01

    IBC (inflammatory breast cancer) is a rare but very aggressive form of breast cancer with a particular phenotype. The molecular mechanisms responsible for IBC remain largely unknown. In particular, genetic and epigenetic alterations specific to IBC remain to be identified. MicroRNAs, a class of small noncoding RNAs able to regulate gene expression, are deregulated in breast cancer and may therefore serve as tools for diagnosis and prediction. This study was designed to determine miRNA expression profiling (microRNAome) in IBC. Quantitative RT-PCR was used to determine expression levels of 804 miRNAs in a screening series of 12 IBC compared to 31 non-stage-matched non-IBC and 8 normal breast samples. The differentially expressed miRNAs were then validated in a series of 65 IBC and 95 non-IBC. From a set of 18 miRNAs of interest selected from the screening series, 13 were differentially expressed with statistical significance in the validation series of IBC compared to non-IBC. Among these, a 5-miRNA signature comprising miR-421, miR-486, miR-503, miR-720 and miR-1303 was shown to be predictive for IBC phenotype with an overall accuracy of 89%. Moreover, multivariate analysis showed that this signature was an independent predictor of poor Metastasis-Free Survival in non-IBC patients.

  20. Expression signature based on TP53 target genes doesn't predict response to TP53-MDM2 inhibitor in wild type TP53 tumors.

    PubMed

    Sonkin, Dmitriy

    2015-10-22

    A number of TP53-MDM2 inhibitors are currently under investigation as therapeutic agents in a variety of clinical trials in patients with TP53 wild type tumors. Not all wild type TP53 tumors are sensitive to such inhibitors. In an attempt to improve selection of patients with TP53 wild type tumors, an mRNA expression signature based on 13 TP53 transcriptional target genes was recently developed (Jeay et al. 2015). Careful reanalysis of TP53 status in the study validation data set of cancer cell lines considered to be TP53 wild type detected TP53 inactivating alterations in 23% of cell lines. The subsequent reanalysis of the remaining TP53 wild type cell lines clearly demonstrated that unfortunately the 13-gene signature cannot predict response to TP53-MDM2 inhibitor in TP53 wild type tumors.

  1. A reported 20-gene expression signature to predict lymph node-positive disease at radical cystectomy for muscle-invasive bladder cancer is clinically not applicable

    PubMed Central

    van Kessel, Kim E. M.; van de Werken, Harmen J. G.; Lurkin, Irene; Ziel – van der Made, Angelique C. J.; Zwarthoff, Ellen C.; Boormans, Joost L.

    2017-01-01

    Background Neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) provides a small but significant survival benefit. Nevertheless, controversies on applying NAC remain because the limited benefit must be weight against chemotherapy-related toxicity and the delay of definitive local treatment. Therefore, there is a clear clinical need for tools to guide treatment decisions on NAC in MIBC. Here, we aimed to validate a previously reported 20-gene expression signature that predicted lymph node-positive disease at radical cystectomy in clinically node-negative MIBC patients, which would be a justification for upfront chemotherapy. Methods We studied diagnostic transurethral resection of bladder tumors (dTURBT) of 150 MIBC patients (urothelial carcinoma) who were subsequently treated by radical cystectomy and pelvic lymph node dissection. RNA was isolated and the expression level of the 20 genes was determined on a qRT-PCR platform. Normalized Ct values were used to calculate a risk score to predict the presence of node-positive disease. The Cancer Genome Atlas (TCGA) RNA expression data was analyzed to subsequently validate the results. Results In a univariate regression analysis, none of the 20 genes significantly correlated with node-positive disease. The area under the curve of the risk score calculated by the 20-gene expression signature was 0.54 (95% Confidence Interval: 0.44-0.65) versus 0.67 for the model published by Smith et al. Node-negative patients had a significantly lower tumor grade at TURBT (p = 0.03), a lower pT stage (p<0.01) and less frequent lymphovascular invasion (13% versus 38%, p<0.01) at radical cystectomy than node-positive patients. In addition, in the TCGA data, none of the 20 genes was differentially expressed in node-negative versus node-positive patients. Conclusions We conclude that a 20-gene expression signature developed for nodal staging of MIBC at radical cystectomy could not be validated on a qRT-PCR platform in a

  2. 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

  3. Irma multisensor predictive signature model

    NASA Astrophysics Data System (ADS)

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

    1995-06-01

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

  4. 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.

  5. Irma multisensor predictive signature model

    NASA Astrophysics Data System (ADS)

    Watson, John S.; Wellfare, Michael R.; Chenault, David B.; Talele, Sunjay E.; Blume, Bradley T.; Richards, Mike; Prestwood, Lee

    1997-06-01

    Development of target acquisition and target recognition algorithms in highly cluttered backgrounds in a variety of battlefield conditions demands a flexible, high fidelity capability for synthetic image generation. Cost effective smart weapons research and testing also requires extensive scene generation capability. The Irma software package addresses this need through a first principles, phenomenology based scene generator that enhances research into new algorithms, novel sensors, and sensor fusion approaches. Irma was one of the first high resolution synthetic infrared target and background signature models developed for tactical air-to-surface weapon scenarios. Originally developed in 1980 by the Armament Directorate of the Air Force Wright Laboratory, the Irma model was used exclusively to generate IR scenes for smart weapons research and development. in 1987, Nichols Research Corporation took over the maintenance of Irma and has since added substantial capabilities. The development of Irma has culminated in a program that includes not only passive visible, IR, and millimeter wave (MMW) channels but also active MMW and ladar channels. Each of these channels is co-registered providing the capability to develop algorithms for multi-band sensor fusion concepts and associated algorithms. In this paper, the capabilities of the latest release of Irma, Irma 4.0, will be described. A brief description of the elements of the software that are common to all channels will be provided. Each channel will be described briefly including a summary of the phenomenological effects and the sensor effects modeled in the software. Examples of Irma multi- channel imagery will be presented.

  6. Determination of minimal transcriptional signatures of compounds for target prediction

    PubMed Central

    2012-01-01

    The identification of molecular target and mechanism of action of compounds is a key hurdle in drug discovery. Multiplexed techniques for bead-based expression profiling allow the measurement of transcriptional signatures of compound-treated cells in high-throughput mode. Such profiles can be used to gain insight into compounds' mode of action and the protein targets they are modulating. Through the proxy of target prediction from such gene signatures we explored important aspects of the use of transcriptional profiles to capture biological variability of perturbed cellular assays. We found that signatures derived from expression data and signatures derived from biological interaction networks performed equally well, and we showed that gene signatures can be optimised using a genetic algorithm. Gene signatures of approximately 128 genes seemed to be most generic, capturing a maximum of the perturbation inflicted on cells through compound treatment. Moreover, we found evidence for oxidative phosphorylation to be one of the most general ways to capture compound perturbation. PMID:22574917

  7. Digital gene expression signatures for maize development

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  8. Digital gene expression signatures for maize development.

    PubMed

    Eveland, Andrea L; Satoh-Nagasawa, Namiko; Goldshmidt, Alexander; Meyer, Sandra; Beatty, Mary; Sakai, Hajime; Ware, Doreen; Jackson, David

    2010-11-01

    Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect the determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression profiles using Illumina's high-throughput sequencing technology and the newly assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in axillary meristem determinacy. The RA3 gene encodes a trehalose-6-phosphate phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of digital gene expression libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20- to 21-nucleotide reads with frequencies spanning 4 orders of magnitude. Unique sequence tags were anchored to 3'-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of nonredundant signature tags to the maize genome, which associated with 37,117 gene models and unannotated regions of expression. In total, 66% of genes were detected by at least nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) in functional analyses of differentially expressed maize genes. Results from this study provide a basis for the analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

  9. Predictive chromatin signatures in the mammalian genome

    PubMed Central

    Hon, Gary C.; Hawkins, R. David; Ren, Bing

    2009-01-01

    The DNA sequence of an organism is a blueprint of life: it harbors not only the information about proteins and other molecules produced in each cell, but also instructions on when and where such molecules are made. Chromatin, the structure of histone and DNA that has co-evolved with eukaryotic genome, also contains information that indicates the function and activity of the underlying DNA sequences. Such information exists in the form of covalent modifications to the histone proteins that comprise the nucleosome. Thanks to the development of high throughput technologies such as DNA microarrays and next generation DNA sequencing, we have begun to associate the various combinations of chromatin modification patterns with functional sequences in the human genome. Here, we review the rapid progress from descriptive observations of histone modification profiles to highly predictive models enabling use of chromatin signatures to enumerate novel functional sequences in mammalian genomes that have escaped previous detection. PMID:19808796

  10. 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.

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

    PubMed Central

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

    2016-01-01

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

  12. Developing a Predictive Capability for Bioluminescence Signatures

    DTIC Science & Technology

    2011-09-30

    naval nighttime operations because the flow field associated with their motion stimulates naturally occurring plankton . In the littoral, the primary...sources of bioluminescence are dinoflagellates, common unicellular plankton that are also known to form red tides. Dinoflagellate bioluminescence is...bioluminescent signatures of some swimming fish are distinct enough to differentiate species; nocturnally foraging predators may use bioluminescent

  13. Molecular classification of prostate cancer using curated expression signatures.

    PubMed

    Markert, Elke K; Mizuno, Hideaki; Vazquez, Alexei; Levine, Arnold J

    2011-12-27

    High Gleason score is currently the best prognostic indicator for poor prognosis in prostate cancer. However, a significant number of patients with low Gleason scores develop aggressive disease as well. In an effort to understand molecular signatures associated with poor outcome in prostate cancer, we analyzed a microarray dataset characterizing 281 prostate cancers from a Swedish watchful-waiting cohort. Patients were classified on the basis of their mRNA microarray signature profiles indicating embryonic stem cell expression patterns (stemness), inactivation of the tumor suppressors p53 and PTEN, activation of several oncogenic pathways, and the TMPRSS2-ERG fusion. Unsupervised clustering identified a subset of tumors manifesting stem-like signatures together with p53 and PTEN inactivation, which had very poor survival outcome, a second group with intermediate survival outcome, characterized by the TMPRSS2-ERG fusion, and three groups with benign outcome. The stratification was validated on a second independent dataset of 150 tumor and metastatic samples from a clinical cohort at Memorial Sloan-Kettering Cancer Center. This classification is independent of Gleason score and therefore provides useful unique molecular profiles for prostate cancer prognosis, helping to predict poor outcome in patients with low or average Gleason scores.

  14. Predicting Electromagnetic Signatures of Gravitational Wave Sources

    NASA Astrophysics Data System (ADS)

    D'Orazio, Daniel John

    This dissertation investigates the signatures of electromagnetic radiation that may accompany two specific sources of gravitational radiation: the inspiral and merger of massive black hole binaries (MBHBs) in galactic nuclei, and the coalescence of black hole neutron star (BHNS) pairs. Part I considers the interaction of MBHBs, at sub-pc separations, with a circumbinary gas disk. Accretion rates onto the MBHB are calculated from two-dimensional hydrodynamical simulations as a function of the relative masses of the black holes. The results are applied to interpretation of the recent, sub-pc separation MBHB candidate in the nucleus of the periodically variable Quasar PG 1302-102. We advance an interpretation of the variability observed in PG 1302-102 as being caused by Doppler-boosted emission sourced by the orbital velocity of the smaller black hole in a MBHB with disparate relative masses. Part II considers BHNS binaries in which the black hole is large enough to swallow the neutron star whole before it is disrupted. As the pair nears merger, orbital motion of the black hole through the magnetosphere of the neutron star generates an electromotive force, a black-hole-battery, which, for the strongest neutron star magnetic field strengths, could power luminosities large enough to make the merging pair observable out to cosmic distances. Relativistic solutions for vacuum fields of a magnetic dipole near a horizon are given, and a mechanism for harnessing the power of the black-hole-battery is put forth in the form of a fireball emitting in hard X-rays to gamma-rays.

  15. Tamoxifen therapy benefit predictive signature coupled with prognostic signature of post-operative recurrent risk for early stage ER+ breast cancer.

    PubMed

    Cai, Hao; Li, Xiangyu; Li, Jing; Ao, Lu; Yan, Haidan; Tong, Mengsha; Guan, Qingzhou; Li, Mengyao; Guo, Zheng

    2015-12-29

    Two types of prognostic signatures for predicting recurrent risk of ER+ breast cancer patients have been developed: one type for patients accepting surgery only and another type for patients receiving post-operative tamoxifen therapy. However, the first type of signature cannot distinguish high-risk patients who cannot benefit from tamoxifen therapy, while the second type of signature cannot identify patients who will be at low risk of recurrence even if they accept surgery only. In this study, we proposed to develop two coupled signatures to solve these problems based on within-sample relative expression orderings (REOs) of gene pairs. Firstly, we identified a prognostic signature of post-operative recurrent risk using 544 samples of ER+ breast cancer patients accepting surgery only. Then, applying this drug-free signature to 840 samples of patients receiving post-operative tamoxifen therapy, we recognized 553 samples of patients who would have been at high risk of recurrence if they had accepted surgery only and used these samples to develop a tamoxifen therapy benefit predictive signature. The two coupled signatures were validated in independent data. The signatures developed in this study are robust against experimental batch effects and applicable at the individual levels, which can facilitate the clinical decision of tamoxifen therapy.

  16. Tamoxifen therapy benefit predictive signature coupled with prognostic signature of post-operative recurrent risk for early stage ER+ breast cancer

    PubMed Central

    Cai, Hao; Li, Xiangyu; Li, Jing; Ao, Lu; Yan, Haidan; Tong, Mengsha; Guan, Qingzhou; Li, Mengyao; Guo, Zheng

    2015-01-01

    Two types of prognostic signatures for predicting recurrent risk of ER+ breast cancer patients have been developed: one type for patients accepting surgery only and another type for patients receiving post-operative tamoxifen therapy. However, the first type of signature cannot distinguish high-risk patients who cannot benefit from tamoxifen therapy, while the second type of signature cannot identify patients who will be at low risk of recurrence even if they accept surgery only. In this study, we proposed to develop two coupled signatures to solve these problems based on within-sample relative expression orderings (REOs) of gene pairs. Firstly, we identified a prognostic signature of post-operative recurrent risk using 544 samples of ER+ breast cancer patients accepting surgery only. Then, applying this drug-free signature to 840 samples of patients receiving post-operative tamoxifen therapy, we recognized 553 samples of patients who would have been at high risk of recurrence if they had accepted surgery only and used these samples to develop a tamoxifen therapy benefit predictive signature. The two coupled signatures were validated in independent data. The signatures developed in this study are robust against experimental batch effects and applicable at the individual levels, which can facilitate the clinical decision of tamoxifen therapy. PMID:26527319

  17. Spatiotemporal Signatures of Lexical–Semantic Prediction

    PubMed Central

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

    2016-01-01

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

  18. Design of a multi-signature ensemble classifier predicting neuroblastoma patients' outcome

    PubMed Central

    2012-01-01

    Background Neuroblastoma is the most common pediatric solid tumor of the sympathetic nervous system. Development of improved predictive tools for patients stratification is a crucial requirement for neuroblastoma therapy. Several studies utilized gene expression-based signatures to stratify neuroblastoma patients and demonstrated a clear advantage of adding genomic analysis to risk assessment. There is little overlapping among signatures and merging their prognostic potential would be advantageous. Here, we describe a new strategy to merge published neuroblastoma related gene signatures into a single, highly accurate, Multi-Signature Ensemble (MuSE)-classifier of neuroblastoma (NB) patients outcome. Methods Gene expression profiles of 182 neuroblastoma tumors, subdivided into three independent datasets, were used in the various phases of development and validation of neuroblastoma NB-MuSE-classifier. Thirty three signatures were evaluated for patients' outcome prediction using 22 classification algorithms each and generating 726 classifiers and prediction results. The best-performing algorithm for each signature was selected, validated on an independent dataset and the 20 signatures performing with an accuracy > = 80% were retained. Results We combined the 20 predictions associated to the corresponding signatures through the selection of the best performing algorithm into a single outcome predictor. The best performance was obtained by the Decision Table algorithm that produced the NB-MuSE-classifier characterized by an external validation accuracy of 94%. Kaplan-Meier curves and log-rank test demonstrated that patients with good and poor outcome prediction by the NB-MuSE-classifier have a significantly different survival (p < 0.0001). Survival curves constructed on subgroups of patients divided on the bases of known prognostic marker suggested an excellent stratification of localized and stage 4s tumors but more data are needed to prove this point. Conclusions The

  19. Uncertainty of hydrological signatures predicted for ungauged basins

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  20. 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

  1. 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.

  2. 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.

  3. NF-κB gene signature predicts prostate cancer progression

    PubMed Central

    Jin, Renjie; Yi, Yajun; Yull, Fiona E.; Blackwell, Timothy S.; Clark, Peter E.; Koyama, Tatsuki; Smith, Joseph A.; Matusik, Robert J.

    2014-01-01

    In many prostate cancer (PCa) patients, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage PCa would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with PCa progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse PCa model when compared to Hi-Myc alone. Using the non-malignant NF-κB activated androgen depleted mouse prostate, a NF-κB Activated Recurrence Predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with PCa. This transgenic mouse model derived gene signature provides a useful and unique molecular profile for human PCa prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery. PMID:24686169

  4. Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach

    PubMed Central

    Sun, Yijun; Urquidi, Virginia

    2010-01-01

    Previous studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical breast cancer recurrence, however, many of these predictive models have been derived using simple computational algorithms and validated internally or using one-way validation on a single dataset. We have recently developed a new feature selection algorithm that overcomes some limitations inherent to high-dimensional data analysis. In this study, we applied this algorithm to two publicly available gene expression datasets obtained from over 400 patients with breast cancer to investigate whether we could derive more accurate prognostic signatures and reveal common predictive factors across independent datasets. We compared the performance of three advanced computational algorithms using a robust two-way validation method, where one dataset was used for training and to establish a prediction model that was then blindly tested on the other dataset. The experiment was then repeated in the reverse direction. Analyses identified prognostic signatures that while comprised of only 10–13 genes, significantly outperformed previously reported signatures for breast cancer evaluation. The cross-validation approach revealed CEGP1 and PRAME as major candidates for breast cancer biomarker development. PMID:19291396

  5. Genomic signatures of germline gene expression.

    PubMed

    McVicker, Graham; Green, Phil

    2010-11-01

    Transcribed regions in the human genome differ from adjacent intergenic regions in transposable element density, crossover rates, and asymmetric substitution and sequence composition patterns. We tested whether these differences reflect selection or are instead a byproduct of germline transcription, using publicly available gene expression data from a variety of germline and somatic tissues. Crossover rate shows a strong negative correlation with gene expression in meiotic tissues, suggesting that crossover is inhibited by transcription. Strand-biased composition (G+T content) and A → G versus T → C substitution asymmetry are both positively correlated with germline gene expression. We find no evidence for a strand bias in allele frequency data, implying that the substitution asymmetry reflects a mutation rather than a fixation bias. The density of transposable elements is positively correlated with germline expression, suggesting that such elements preferentially insert into regions that are actively transcribed. For each of the features examined, our analyses favor a nonselective explanation for the observed trends and point to the role of germline gene expression in shaping the mammalian genome.

  6. Shape Signatures: New Descriptors for Predicting Cardiotoxicity In Silico

    PubMed Central

    Chekmarev, Dmitriy S.; Kholodovych, Vladyslav; Balakin, Konstantin V.; Ivanenkov, Yan; Ekins, Sean; Welsh, William J.

    2009-01-01

    Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors (k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were assessed by applying them to a data set of compounds with varying affinity toward the 5-HT2B receptor as well as a set of human ether-a-go-go-related gene (hERG) potassium channel inhibitors. Our classification models for 5-HT2B represented the first attempt at global computational models for this receptor and exhibited average accuracies in the range of 73−83%. This level of performance is comparable to using commercially available molecular descriptors. The overall accuracy of the hERG Shape Signatures–SVM models was 69−73%, in line with other computational models published to date. Our data indicate that Shape Signatures descriptors can be used with SVM and Kohonen SOM and perform better in classification problems related to the analysis of highly clustered and heterogeneous property spaces. Such models may have utility for predicting the potential for cardiotoxicity in drug discovery mediated by the 5-HT2B receptor and hERG. PMID:18461975

  7. A gene expression signature for RSV: clinical implications and limitations.

    PubMed

    Openshaw, Peter J M

    2013-11-01

    Peter Openshaw discusses the challenges in advancing respiratory syncytial virus (RSV) treatments and the implications of a study by Mejias and colleagues using a newly identified gene signature for diagnosis and prediction of RSV severity. Please see later in the article for the Editors' Summary.

  8. Gene expression signatures in lymphoid tumours.

    PubMed

    Kees, Ursula R

    2004-04-01

    Lymphoid tumours comprise the acute and chronic leukaemias, the broad spectrum of lymphomas, including Hodgkin's disease, and multiple myeloma. The subdivision of the acute leukaemias according to the proliferating type of white blood cells has had a major impact on the care of these patients. More recently, specific chromosomal translocations have been used to identify patients who may benefit from more intensive therapies. The novel high-throughput genomic technologies, such as microarrays, provide new avenues for the molecular diagnosis of the haematological malignancies. Rapid advances in genome sequencing and gene expression profiling provide unprecedented opportunities to identify specific genes involved in complex biological processes, including tumorigenesis. The features of microarray technology and the variety of experimental approaches to elucidate lymphoid malignancies are discussed. Microarray technology has the potential to lead to more accurate prognostic assessment for patients and is expected to ultimately allow the clinician to select therapies optimally suited to each patient.

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

    PubMed

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

    2015-11-24

    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.

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

    PubMed

    Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

    2015-01-01

    The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  17. 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

  18. A gene expression signature of retinoblastoma loss-of-function is a predictive biomarker of resistance to palbociclib in breast cancer cell lines and is prognostic in patients with ER positive early breast cancer.

    PubMed

    Malorni, Luca; Piazza, Silvano; Ciani, Yari; Guarducci, Cristina; Bonechi, Martina; Biagioni, Chiara; Hart, Christopher D; Verardo, Roberto; Di Leo, Angelo; Migliaccio, Ilenia

    2016-09-13

    Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 - 3.2] p = 1.87e-08 and HR = 2.62 [1.9- 3.5] p = 8.6e-11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted.

  19. A gene expression signature of retinoblastoma loss-of-function is a predictive biomarker of resistance to palbociclib in breast cancer cell lines and is prognostic in patients with ER positive early breast cancer

    PubMed Central

    Malorni, Luca; Piazza, Silvano; Ciani, Yari; Guarducci, Cristina; Bonechi, Martina; Biagioni, Chiara; Hart, Christopher D.; Verardo, Roberto; Leo, Angelo Di; Migliaccio, Ilenia

    2016-01-01

    Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 − 3.2] p = 1.87e−08 and HR = 2.62 [1.9− 3.5] p = 8.6e−11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted. PMID:27634906

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  2. 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

  3. 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

  4. Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244).

    PubMed

    Dry, Jonathan R; Pavey, Sandra; Pratilas, Christine A; Harbron, Chris; Runswick, Sarah; Hodgson, Darren; Chresta, Christine; McCormack, Rose; Byrne, Natalie; Cockerill, Mark; Graham, Alexander; Beran, Garry; Cassidy, Andrew; Haggerty, Carolyn; Brown, Helen; Ellison, Gillian; Dering, Judy; Taylor, Barry S; Stark, Mitchell; Bonazzi, Vanessa; Ravishankar, Sugandha; Packer, Leisl; Xing, Feng; Solit, David B; Finn, Richard S; Rosen, Neal; Hayward, Nicholas K; French, Tim; Smith, Paul D

    2010-03-15

    Selumetinib (AZD6244, ARRY-142886) is a selective, non-ATP-competitive inhibitor of mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK)-1/2. The range of antitumor activity seen preclinically and in patients highlights the importance of identifying determinants of response to this drug. In large tumor cell panels of diverse lineage, we show that MEK inhibitor response does not have an absolute correlation with mutational or phospho-protein markers of BRAF/MEK, RAS, or phosphoinositide 3-kinase (PI3K) activity. We aimed to enhance predictivity by measuring pathway output through coregulated gene networks displaying differential mRNA expression exclusive to resistant cell subsets and correlated to mutational or dynamic pathway activity. We discovered an 18-gene signature enabling measurement of MEK functional output independent of tumor genotype. Where the MEK pathway is activated but the cells remain resistant to selumetinib, we identified a 13-gene signature that implicates the existence of compensatory signaling from RAS effectors other than PI3K. The ability of these signatures to stratify samples according to functional activation of MEK and/or selumetinib sensitivity was shown in multiple independent melanoma, colon, breast, and lung tumor cell lines and in xenograft models. Furthermore, we were able to measure these signatures in fixed archival melanoma tumor samples using a single RT-qPCR-based test and found intergene correlations and associations with genetic markers of pathway activity to be preserved. These signatures offer useful tools for the study of MEK biology and clinical application of MEK inhibitors, and the novel approaches taken may benefit other targeted therapies.

  5. 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.

  6. 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

  7. Specific molecular signatures predict decitabine response in chronic myelomonocytic leukemia.

    PubMed

    Meldi, Kristen; Qin, Tingting; Buchi, Francesca; Droin, Nathalie; Sotzen, Jason; Micol, Jean-Baptiste; Selimoglu-Buet, Dorothée; Masala, Erico; Allione, Bernardino; Gioia, Daniela; Poloni, Antonella; Lunghi, Monia; Solary, Eric; Abdel-Wahab, Omar; Santini, Valeria; Figueroa, Maria E

    2015-05-01

    Myelodysplastic syndromes and chronic myelomonocytic leukemia (CMML) are characterized by mutations in genes encoding epigenetic modifiers and aberrant DNA methylation. DNA methyltransferase inhibitors (DMTis) are used to treat these disorders, but response is highly variable, with few means to predict which patients will benefit. Here, we examined baseline differences in mutations, DNA methylation, and gene expression in 40 CMML patients who were responsive or resistant to decitabine (DAC) in order to develop a molecular means of predicting response at diagnosis. While somatic mutations did not differentiate responders from nonresponders, we identified 167 differentially methylated regions (DMRs) of DNA at baseline that distinguished responders from nonresponders using next-generation sequencing. These DMRs were primarily localized to nonpromoter regions and overlapped with distal regulatory enhancers. Using the methylation profiles, we developed an epigenetic classifier that accurately predicted DAC response at the time of diagnosis. Transcriptional analysis revealed differences in gene expression at diagnosis between responders and nonresponders. In responders, the upregulated genes included those that are associated with the cell cycle, potentially contributing to effective DAC incorporation. Treatment with CXCL4 and CXCL7, which were overexpressed in nonresponders, blocked DAC effects in isolated normal CD34+ and primary CMML cells, suggesting that their upregulation contributes to primary DAC resistance.

  8. 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

  9. 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.

  10. 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

  11. An 8-gene signature for prediction of prognosis and chemoresponse in non-small cell lung cancer

    PubMed Central

    Nguyen, Minh Nam; Matondo, Abel; Jo, Yong Hwa; Yoo, Ji Youn; Nguyen, Ngoc Ngo Yen; Yun, Hyeong Rok; Kim, Jieun; Akter, Salima; Kang, Insug; Ha, Joohun; Maeng, Chi Hoon; Kim, Si-Young; Lee, Ju-seog; Kim, Jayoung; Kim, Sung Soo

    2016-01-01

    Identification of a potential gene signature for improved diagnosis in non-small cell lung cancer (NSCLC) patient is necessary. Here, we aim to establish and validate the prognostic efficacy of a gene set that can predict prognosis and benefits of adjuvant chemotherapy (ACT) in NSCLC patients from various ethnicities. An 8-gene signature was calculated from the gene expression of 181 patients using univariate Cox proportional hazard regression analysis. The prognostic value of the signature was robustly validated in 1,477 patients from five microarray independent data sets and one RNA-seq data set. The 8-gene signature was identified as an independent predictor of patient survival in the presence of clinical parameters in univariate and multivariate analyses [hazard ratio (HR): 2.84, 95% confidence interval CI (1.74-4.65), p=3.06e-05, [HR] 2.62, 95% CI (1.51-4.53), p=0.001], respectively. Subset analysis demonstrated that the 8-gene signature could identify high-risk patients in stage II-III with improved survival from ACT [(HR) 1.47, 95% CI (1.01-2.14), p=0.044]. The 8-gene signature also stratified risk groups in EGFR-mutated and wild-type patients. In conclusion, the 8-gene signature is a strong and independent predictor that can significantly stratify patients into low- and high-risk groups. Our gene signature also has the potential to predict patients in stage II-III that are likely to benefit from ACT. PMID:27863408

  12. 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

  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. Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer

    DTIC Science & Technology

    2014-10-01

    Award Number: W81XWH-12-1-0521 TITLE: Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer PRINCIPAL...SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-12-1-0521 Identification of a Genomic Signature Predicting for Recurrence in Early-Stage...clinical annotation and accurate pathological review (228 recurrent and 364 non-recurrent), 2) established a specimen repository and clinical data

  15. A Signature of Circulating microRNAs Predicts the Susceptibility of Acute Mountain Sickness

    PubMed Central

    Liu, Bao; Huang, He; Wu, Gang; Xu, Gang; Sun, Bing-Da; Zhang, Er-Long; Chen, Jian; Gao, Yu-Qi

    2017-01-01

    Background: Acute mountain sickness (AMS) is a common disabling condition in individuals experiencing high altitudes, which may progress to life-threatening high altitude cerebral edema. Today, no established biomarkers are available for prediction the susceptibility of AMS. MicroRNAs emerge as promising sensitive and specific biomarkers for a variety of diseases. Thus, we sought to identify circulating microRNAs suitable for prediction the susceptible of AMS before exposure to high altitude. Methods: We enrolled 109 healthy man adults and collected blood samples before their exposure to high altitude. Then we took them to an elevation of 3648 m for 5 days. Circulating microRNAs expression was measured by microarray and quantitative reverse-transcription polymerase chain reaction (qRT-PCR). AMS was defined as Lake Louise score ≥3 and headache using Lake Louise Acute Mountain Sickness Scoring System. Results: A total of 31 microRNAs were differentially expressed between AMS and Non-AMS groups, 15 up-regulated and 16 down-regulated. Up-regulation of miR-369-3p, miR-449b-3p, miR-136-3p, and miR-4791 in patients with AMS compared with Non-AMS individuals were quantitatively confirmed using qRT-PCR (all, P < 0.001). With multiple logistic regression analysis, a unique signature encompassing miR-369-3p, miR-449b-3p, and miR-136-3p discriminate AMS from Non-AMS (area under the curve 0.986, 95%CI 0.970–1.000, P < 0.001, LR+: 14.21, LR–: 0.08). This signature yielded a 92.68% sensitivity and a 93.48% specificity for AMS vs. Non-AMS. Conclusion: The study here, for the first time, describes a signature of three circulating microRNAs as a robust biomarker to predict the susceptibility of AMS before exposure to high altitude. PMID:28228730

  16. A Signature of Circulating microRNAs Predicts the Susceptibility of Acute Mountain Sickness.

    PubMed

    Liu, Bao; Huang, He; Wu, Gang; Xu, Gang; Sun, Bing-Da; Zhang, Er-Long; Chen, Jian; Gao, Yu-Qi

    2017-01-01

    Background: Acute mountain sickness (AMS) is a common disabling condition in individuals experiencing high altitudes, which may progress to life-threatening high altitude cerebral edema. Today, no established biomarkers are available for prediction the susceptibility of AMS. MicroRNAs emerge as promising sensitive and specific biomarkers for a variety of diseases. Thus, we sought to identify circulating microRNAs suitable for prediction the susceptible of AMS before exposure to high altitude. Methods: We enrolled 109 healthy man adults and collected blood samples before their exposure to high altitude. Then we took them to an elevation of 3648 m for 5 days. Circulating microRNAs expression was measured by microarray and quantitative reverse-transcription polymerase chain reaction (qRT-PCR). AMS was defined as Lake Louise score ≥3 and headache using Lake Louise Acute Mountain Sickness Scoring System. Results: A total of 31 microRNAs were differentially expressed between AMS and Non-AMS groups, 15 up-regulated and 16 down-regulated. Up-regulation of miR-369-3p, miR-449b-3p, miR-136-3p, and miR-4791 in patients with AMS compared with Non-AMS individuals were quantitatively confirmed using qRT-PCR (all, P < 0.001). With multiple logistic regression analysis, a unique signature encompassing miR-369-3p, miR-449b-3p, and miR-136-3p discriminate AMS from Non-AMS (area under the curve 0.986, 95%CI 0.970-1.000, P < 0.001, LR+: 14.21, LR-: 0.08). This signature yielded a 92.68% sensitivity and a 93.48% specificity for AMS vs. Non-AMS. Conclusion: The study here, for the first time, describes a signature of three circulating microRNAs as a robust biomarker to predict the susceptibility of AMS before exposure to high altitude.

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

    PubMed

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

    2015-01-01

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

  18. Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis.

    PubMed

    Toonen, Erik J M; Gilissen, Christian; Franke, Barbara; Kievit, Wietske; Eijsbouts, Agnes M; den Broeder, Alfons A; van Reijmersdal, Simon V; Veltman, Joris A; Scheffer, Hans; Radstake, Timothy R D J; van Riel, Piet L C M; Barrera, Pilar; Coenen, Marieke J H

    2012-01-01

    So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response.

  19. Validation Study of Existing Gene Expression Signatures for Anti-TNF Treatment in Patients with Rheumatoid Arthritis

    PubMed Central

    Toonen, Erik J. M.; Gilissen, Christian; Franke, Barbara; Kievit, Wietske; Eijsbouts, Agnes M.; den Broeder, Alfons A.; van Reijmersdal, Simon V.; Veltman, Joris A.; Scheffer, Hans; Radstake, Timothy R. D. J.; van Riel, Piet L. C. M.; Barrera, Pilar; Coenen, Marieke J. H.

    2012-01-01

    So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response. PMID:22457743

  20. Using Protein Interaction Database and Support Vector Machines to Improve Gene Signatures for Prediction of Breast Cancer Recurrence

    PubMed Central

    Sehhati, Mohammad Reza; Dehnavi, Alireza Mehri; Rabbani, Hossein; Javanmard, Shaghayegh Haghjoo

    2013-01-01

    Numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. However, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. This inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due to their computational burden. In this study, an integrated approach with low computational cost was proposed for identifying a more predictive gene signature, for prediction of breast cancer recurrence. First, a small set of genes was primarily selected as signature by an appropriate filter feature selection (FFS) method. Then, a binary sub-class of protein-protein interaction (PPI) network was used to expand the primary set by adding adjacent proteins of each gene signature from the PPI-network. Subsequently, the support vector machine-based recursive feature elimination (SVMRFE) method was applied to the expression level of all the genes in the expanded set. Finally, the genes with the highest score by SVMRFE were selected as the new biomarkers. Accuracy of the final selected biomarkers was evaluated to classify four datasets on breast cancer patients, including 800 cases, into two cohorts of poor and good prognosis. The results of the five-fold cross validation test, using the support vector machine as a classifier, showed more than 13% improvement in the average accuracy, after modifying the primary selected signatures. Moreover, the method used in this study showed a lower computational cost compared to the other PPI-based methods. The proposed method demonstrated more robust and accurate biomarkers using the PPI network, at a low computational cost. This approach could be used as a supplementary procedure in microarray studies after applying various gene selection methods. PMID:24098862

  1. Using protein interaction database and support vector machines to improve gene signatures for prediction of breast cancer recurrence.

    PubMed

    Sehhati, Mohammad Reza; Dehnavi, Alireza Mehri; Rabbani, Hossein; Javanmard, Shaghayegh Haghjoo

    2013-04-01

    Numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. However, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. This inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due to their computational burden. In this study, an integrated approach with low computational cost was proposed for identifying a more predictive gene signature, for prediction of breast cancer recurrence. First, a small set of genes was primarily selected as signature by an appropriate filter feature selection (FFS) method. Then, a binary sub-class of protein-protein interaction (PPI) network was used to expand the primary set by adding adjacent proteins of each gene signature from the PPI-network. Subsequently, the support vector machine-based recursive feature elimination (SVMRFE) method was applied to the expression level of all the genes in the expanded set. Finally, the genes with the highest score by SVMRFE were selected as the new biomarkers. Accuracy of the final selected biomarkers was evaluated to classify four datasets on breast cancer patients, including 800 cases, into two cohorts of poor and good prognosis. The results of the five-fold cross validation test, using the support vector machine as a classifier, showed more than 13% improvement in the average accuracy, after modifying the primary selected signatures. Moreover, the method used in this study showed a lower computational cost compared to the other PPI-based methods. The proposed method demonstrated more robust and accurate biomarkers using the PPI network, at a low computational cost. This approach could be used as a supplementary procedure in microarray studies after applying various gene selection methods.

  2. Multiclass cancer diagnosis using tumor gene expression signatures

    DOE PAGES

    Ramaswamy, S.; Tamayo, P.; Rifkin, 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 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

  3. 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.

  4. 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.

  5. A miRNA-based signature detected in primary melanoma tissue predicts development of brain metastasis

    PubMed Central

    Hanniford, Doug; Zhong, Judy; Koetz, Lisa; Gaziel-Sovran, Avital; Lackaye, Daniel J.; Shang, Shulian; Pavlick, Anna; Shapiro, Richard; Berman, Russell; Darvishian, Farbod; Shao, Yongzhao; Osman, Iman; Hernando, Eva

    2015-01-01

    Purpose Brain metastasis is the major cause of mortality among melanoma patients. A molecular prognostic test that can reliably stratify patients at initial melanoma diagnosis by risk of developing brain metastasis may inform the clinical management of these patients. Experimental Design We performed a retrospective, cohort-based study analyzing genome-wide and targeted microRNA expression profiling of primary melanoma tumors of three patient cohorts (n= 92, n= 119, n= 45) with extensive clinical follow up. We used Cox regression analysis to establish a microRNA-based signature that improves the ability of the current clinicopathologic staging system to predict the development of brain metastasis. Results Our analyses identified a 4-microRNA (miR-150–5p, miR-15b-5p, miR-16–5p, and miR-374b-3p) prognostic signature that, in combination with stage, distinguished primary melanomas that metastasized to the brain from non-recurrent and non-brain-metastatic primary tumors (training cohort: C-index=81.4%, validation cohort: C-index=67.4%, independent cohort: C-index=76.9%). Corresponding Kaplan-Meier curves of high- vs. low-risk patients displayed a clear separation in brain-metastasis-free and overall survival (training: p<0.001, p<0.001, validation: p=0.033, p=0.007, independent: p=0.021, p=0.022, respectively). Finally, of the microRNA in the prognostic model, we found that the expression of a key lymphocyte miRNA, miR-150–5p, which is less abundant in primary melanomas metastatic to brain, correlated with presence of CD45+ tumor infiltrating lymphocytes. Conclusions A prognostic assay based on the described miRNA expression signature combined with the currently used staging criteria may improve accuracy of primary melanoma patient prognoses and aid clinical management of patients, including selection for adjuvant treatment or clinical trials of adjuvant therapies. PMID:26089374

  6. Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

    PubMed Central

    Welsh, Eric A.

    2017-01-01

    Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA) can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified. PMID:28265563

  7. Gene expression-based prognostic signatures in lung cancer: ready for clinical use?

    PubMed

    Subramanian, Jyothi; Simon, Richard

    2010-04-07

    A substantial number of studies have reported the development of gene expression-based prognostic signatures for lung cancer. The ultimate aim of such studies should be the development of well-validated clinically useful prognostic signatures that improve therapeutic decision making beyond current practice standards. We critically reviewed published studies reporting the development of gene expression-based prognostic signatures for non-small cell lung cancer to assess the progress made toward this objective. Studies published between January 1, 2002, and February 28, 2009, were identified through a PubMed search. Following hand-screening of abstracts of the identified articles, 16 were selected as relevant. Those publications were evaluated in detail for appropriateness of the study design, statistical validation of the prognostic signature on independent datasets, presentation of results in an unbiased manner, and demonstration of medical utility for the new signature beyond that obtained using existing treatment guidelines. Based on this review, we found little evidence that any of the reported gene expression signatures are ready for clinical application. We also found serious problems in the design and analysis of many of the studies. We suggest a set of guidelines to aid the design, analysis, and evaluation of prognostic signature studies. These guidelines emphasize the importance of focused study planning to address specific medically important questions and the use of unbiased analysis methods to evaluate whether the resulting signatures provide evidence of medical utility beyond standard of care-based prognostic factors.

  8. Predictive Outcomes for HER2-enriched Cancer Using Growth and Metastasis Signatures Driven By SPARC.

    PubMed

    Güttlein, Leandro N; Benedetti, Lorena G; Fresno, Cristóbal; Spallanzani, Raúl G; Mansilla, Sabrina F; Rotondaro, Cecilia; Raffo Iraolagoitia, Ximena L; Salvatierra, Edgardo; Bravo, Alicia I; Fernández, Elmer A; Gottifredi, Vanesa; Zwirner, Norberto W; Llera, Andrea S; Podhajcer, Osvaldo L

    2017-03-01

    Understanding the mechanism of metastatic dissemination is crucial for the rational design of novel therapeutics. The secreted protein acidic and rich in cysteine (SPARC) is a matricellular glycoprotein which has been extensively associated with human breast cancer aggressiveness although the underlying mechanisms are still unclear. Here, shRNA-mediated SPARC knockdown greatly reduced primary tumor growth and completely abolished lung colonization of murine 4T1 and LM3 breast malignant cells implanted in syngeneic BALB/c mice. A comprehensive study including global transcriptomic analysis followed by biological validations confirmed that SPARC induces primary tumor growth by enhancing cell cycle and by promoting a COX-2-mediated expansion of myeloid-derived suppressor cells (MDSC). The role of SPARC in metastasis involved a COX-2-independent enhancement of cell disengagement from the primary tumor and adherence to the lungs that fostered metastasis implantation. Interestingly, SPARC-driven gene expression signatures obtained from these murine models predicted the clinical outcome of patients with HER2-enriched breast cancer subtypes. In total, the results reveal that SPARC and its downstream effectors are attractive targets for antimetastatic therapies in breast cancer.Implications: These findings shed light on the prometastatic role of SPARC, a key protein expressed by breast cancer cells and surrounding stroma, with important consequences for disease outcome. Mol Cancer Res; 15(3); 304-16. ©2016 AACR.

  9. 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...

  10. Improved signature prediction through coupling of ShipIR and CFD

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

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

  11. 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

  12. HVPG signature: A prognostic and predictive tool in hepatocellular carcinoma

    PubMed Central

    Xiang, Yi; Chen, Jinjun; Zhao, Jianbo; Li, Jing; Qi, Fu-Zhen; Xu, Yong

    2016-01-01

    Hepatic venous pressure gradient (HVPG) measurement provides independent prognostic value in patients with cirrhosis, and the prognostic and predictive role of HVPG in hepatocellular carcinoma (HCC) also has been explored. The management of HCC is limited to the European Association for the Study of the Liver (EASL) and American Association for the Study of Liver Diseases (AASLD) guidelines that consider that HVPG≥10 mmHg to be a contraindication for hepatic resection (HR), otherwise other treatment modalities are recommended. Current studies show that a raised HVPG diagnosed directly or indirectly leads to a negative prognosis of patients with HCC and cirrhosis, but HVPG greater than 10 mmHg should not be regarded as an absolute contraindication for HR. Selecting direct or surrogate measurement of HVPG is still under debate. Only several studies reported the impact of HVPG in negative prognosis of HCC patients after liver transplantation (LT) and the value of HVPG in the prediction of HCC development, which need to be further validated. PMID:27566593

  13. 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 ...

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

    SciTech Connect

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

    1998-06-01

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

  15. MicroRNA Expression Signatures During Malignant Progression From Barrett's Esophagus.

    PubMed

    Bansal, Ajay; Gupta, Vijayalaxmi; Wang, Kenneth

    2016-06-01

    The rapid increase and poor survival of esophageal adenocarcinoma (EAC) have led to significant efforts to promote early detection. Given that the premalignant lesion of Barrett's esophagus (BE) is the major known risk factor for EAC, multiple investigators have studied biomarker signatures that can predict malignant progression of BE to EAC. MicroRNAs, a novel class of gene regulators, are small non-coding RNAs and have been associated with carcinogenesis. MicroRNAs are ideal biomarkers because of their remarkable stability in fixed tissues, a common method for collection of clinical specimens, and in blood either within exosomes or as microRNA-protein complexes. Multiple studies show potential of microRNAs as tissue and blood biomarkers for diagnosis and prognosis of EAC but the results need confirmation in prospective studies. Although head-to-head comparisons are lacking, microRNA panels require less genes than messenger RNA panels for diagnosis of EAC in BE. MicroRNA diagnostic panels will need to be compared for accuracy against global measures of genome instability that were recently shown to be good predictors of progression but require sophisticated analytic techniques. Early studies on blood microRNA panels are promising but have found microRNA markers to be inconsistent among studies. MicroRNA expression in blood is different between various microRNA sub-compartments such as exosomes and microRNA-protein complexes and could affect blood microRNA measurements. Further standardization is needed to yield consistent results. We have summarized the current understanding of the tissue and blood microRNA signatures that may predict the development and progression of EAC.

  16. 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.

  17. 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.

  18. A 4-miRNA signature predicts the therapeutic outcome of glioblastoma

    PubMed Central

    Niyazi, Maximilian; Pitea, Adriana; Mittelbronn, Michel; Steinbach, Joachim; Sticht, Carsten; Zehentmayr, Franz; Piehlmaier, Daniel; Zitzelsberger, Horst; Ganswindt, Ute; Rödel, Claus; Lauber, Kirsten; Belka, Claus; Unger, Kristian

    2016-01-01

    Multimodal therapy of glioblastoma (GBM) reveals inter-individual variability in terms of treatment outcome. Here, we examined whether a miRNA signature can be defined for the a priori identification of patients with particularly poor prognosis. FFPE sections from 36 GBM patients along with overall survival follow-up were collected retrospectively and subjected to miRNA signature identification from microarray data. A risk score based on the expression of the signature miRNAs and cox-proportional hazard coefficients was calculated for each patient followed by validation in a matched GBM subset of TCGA. Genes potentially regulated by the signature miRNAs were identified by a correlation approach followed by pathway analysis. A prognostic 4-miRNA signature, independent of MGMT promoter methylation, age, and sex, was identified and a risk score was assigned to each patient that allowed defining two groups significantly differing in prognosis (p-value: 0.0001, median survival: 10.6 months and 15.1 months, hazard ratio = 3.8). The signature was technically validated by qRT-PCR and independently validated in an age- and sex-matched subset of standard-of-care treated patients of the TCGA GBM cohort (n=58). Pathway analysis suggested tumorigenesis-associated processes such as immune response, extracellular matrix organization, axon guidance, signalling by NGF, GPCR and Wnt. Here, we describe the identification and independent validation of a 4-miRNA signature that allows stratification of GBM patients into different prognostic groups in combination with one defined threshold and set of coefficients that could be utilized as diagnostic tool to identify GBM patients for improved and/or alternative treatment approaches. PMID:27302927

  19. 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

  20. 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.

  1. 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

  2. Clinically Viable Gene Expression Assays with Potential for Predicting Benefit from MEK Inhibitors.

    PubMed

    Brant, Roz; Sharpe, Alan; Liptrot, Tom; Dry, Jonathan R; Harrington, Elizabeth A; Barrett, J Carl; Whalley, Nicky; Womack, Christopher; Smith, Paul; Hodgson, Darren R

    2017-03-15

    Purpose: To develop a clinically viable gene expression assay to measure RAS/RAF/MEK/ERK (RAS-ERK) pathway output suitable for hypothesis testing in non-small cell lung cancer (NSCLC) clinical studies.Experimental Design: A published MEK functional activation signature (MEK signature) that measures RAS-ERK functional output was optimized for NSCLC in silico NanoString assays were developed for the NSCLC optimized MEK signature and the 147-gene RAS signature. First, platform transfer from Affymetrix to NanoString, and signature modulation following treatment with KRAS siRNA and MEK inhibitor, were investigated in cell lines. Second, the association of the signatures with KRAS mutation status, dynamic range, technical reproducibility, and spatial and temporal variation was investigated in NSCLC formalin-fixed paraffin-embedded tissue (FFPET) samples.Results: We observed a strong cross-platform correlation and modulation of signatures in vitro Technical and biological replicates showed consistent signature scores that were robust to variation in input total RNA; conservation of scores between primary and metastatic tumor was statistically significant. There were statistically significant associations between high MEK (P = 0.028) and RAS (P = 0.003) signature scores and KRAS mutation in 50 NSCLC samples. The signatures identify overlapping but distinct candidate patient populations from each other and from KRAS mutation testing.Conclusions: We developed a technically and biologically robust NanoString gene expression assay of MEK pathway output, compatible with the quantities of FFPET routinely available. The gene signatures identified a different patient population for MEK inhibitor treatment compared with KRAS mutation testing. The predictive power of the MEK signature should be studied further in clinical trials. Clin Cancer Res; 23(6); 1471-80. ©2016 AACRSee related commentary by Xue and Lito, p. 1365.

  3. Characterising Cytokine Gene Expression Signatures in Patients with Severe Sepsis

    PubMed Central

    Grealy, Robert; White, Mary; Stordeur, Patrick; Kelleher, Dermot; Doherty, Derek G.; McManus, Ross; Ryan, Thomas

    2013-01-01

    Introduction. Severe sepsis in humans may be related to an underlying profound immune suppressive state. We investigated the link between gene expression of immune regulatory cytokines and the range of illness severity in patients with infection and severe sepsis. Methods. A prospective observational study included 54 ICU patients with severe sepsis, 53 patients with infection without organ failure, and 20 healthy controls. Gene expression in peripheral blood mononuclear cells (PBMC) was measured using real-time polymerase chain reaction. Results. Infection differed from health by decreased expression of the IL2, and IL23 and greater expression of IL10 and IL27. Severe sepsis differed from infection by having decreased IL7, IL23, IFNγ, and TNFα gene expression. An algorithm utilising mRNA copy number for TNFα, IFNγ, IL7, IL10, and IL23 accurately distinguished sepsis from severe sepsis with a receiver operator characteristic value of 0.88. Gene expression was similar with gram-positive and gram-negative infection and was similar following medical and surgical severe sepsis. Severity of organ failure was associated with serum IL6 protein levels but not with any index of cytokine gene expression in PBMCs. Conclusions. Immune regulatory cytokine gene expression in PBMC provides a robust method of modelling patients' response to infection. PMID:23935244

  4. Quantitative analysis of competition in posttranscriptional regulation reveals a novel signature in target expression variation.

    PubMed

    Klironomos, Filippos D; Berg, Johannes

    2013-02-19

    When small RNAs are loaded onto Argonaute proteins they can form the RNA-induced silencing complexes (RISCs), which mediate RNA interference (RNAi). RISC-formation is dependent on a shared pool of Argonaute proteins and RISC-loading factors, and is susceptible to competition among small RNAs. We present a mathematical model that aims to understand how small RNA competition for RISC-formation affects target gene repression. We discuss that small RNA activity is limited by RISC-formation, RISC-degradation, and the availability of Argonautes. We show that different competition conditions for RISC-loading result in different signatures of RNAi determined also by the amount of RISC-recycling taking place. In particular, we find that the small RNAs, although less efficient at RISC-formation, can perform in the low RISC-recycling range as well as their more effective counterparts. Additionally, we predict that under conditions of low RISC-loading efficiency and high RISC-recycling, the variation in target levels increases linearly with the target transcription rate. Furthermore, we show that RISC-recycling determines the effect that Argonaute scarcity conditions have on target expression variation. Our observations, taken together, offer a framework of predictions that can be used to infer from data the particular characteristics of underlying RNAi activity.

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

    PubMed Central

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

    2015-01-01

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

  6. A PRIM approach to predictive-signature development for patient stratification.

    PubMed

    Chen, Gong; Zhong, Hua; Belousov, Anton; Devanarayan, Viswanath

    2015-01-30

    Patients often respond differently to a treatment because of individual heterogeneity. Failures of clinical trials can be substantially reduced if, prior to an investigational treatment, patients are stratified into responders and nonresponders based on biological or demographic characteristics. These characteristics are captured by a predictive signature. In this paper, we propose a procedure to search for predictive signatures based on the approach of patient rule induction method. Specifically, we discuss selection of a proper objective function for the search, present its algorithm, and describe a resampling scheme that can enhance search performance. Through simulations, we characterize conditions under which the procedure works well. To demonstrate practical uses of the procedure, we apply it to two real-world data sets. We also compare the results with those obtained from a recent regression-based approach, Adaptive Index Models, and discuss their respective advantages. In this study, we focus on oncology applications with survival responses.

  7. 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.

  8. Identifying a gene expression signature of cluster headache in blood

    PubMed Central

    Eising, Else; Pelzer, Nadine; Vijfhuizen, Lisanne S.; Vries, Boukje de; Ferrari, Michel D.; ‘t Hoen, Peter A. C.; Terwindt, Gisela M.; van den Maagdenberg, Arn M. J. M.

    2017-01-01

    Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Gene expression data were analysed by gene and by module of co-expressed genes with particular attention to previously implicated disease pathways including hypocretin dysregulation. Only moderate gene expression differences were identified and no associations were found with previously reported pathogenic mechanisms. At the level of functional gene sets, associations were observed for genes involved in several brain-related mechanisms such as GABA receptor function and voltage-gated channels. In addition, genes and modules of co-expressed genes showed a role for intracellular signalling cascades, mitochondria and inflammation. Although larger study samples may be required to identify the full range of involved pathways, these results indicate a role for mitochondria, intracellular signalling and inflammation in cluster headache. PMID:28074859

  9. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma

    PubMed Central

    Coroller, Thibaud P.; Grossmann, Patrick; Hou, Ying; Rios Velazquez, Emmanuel; Leijenaar, Ralph T.H.; Hermann, Gretchen; Lambin, Philippe; Haibe-Kains, Benjamin; Mak, Raymond H.; Aerts, Hugo J.W.L.

    2015-01-01

    Background and Purpose Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. Material and Methods We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). Results Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI=0.55, p-value=2.77 × 10−5) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI=0.61, p-value=1.79 ×10−17). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset (p-value=1.56 × 10−11). Conclusions Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data. PMID:25746350

  10. Hyperspectral reflectance signature protocol for predicting subsurface bottom reflectance in water: in-situ and analytical methods

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Rotkiske, Tyler; Oney, Taylor

    2016-10-01

    In-situ measurement of bottom reflectance signatures and bottom features in water are used to test an analytical based irradiance model protocol. Comparisons between predicted and measured bottom reflectance signatures are obtained using measured hyperspectral remote sensing reflectance signatures, water depth and water column constituent concentrations. Analytical solutions and algorithms are used to generate synthetic signatures of different bottom types. The analytical methodology used to simulated bottom reflectance contains offset and bias that can be corrected using spectral window based corrections. Example results are demonstrated for application to coral species, submerged aquatic vegetation and a sand bottom type. Spectral windows are identified for predicting the above bottom types. Sensitivity analysis of predicted bottom reflectance signatures is conducted by varying water depth, chlorophyll, dissolved organic matter and total suspended mater concentrations. The protocol can be applied to shallow subsurface geospatial mapping using sensor based water surface reflectance based upon an analytical model solution derived from primitive radiative transfer theory.

  11. Identification of a RNA-Seq Based 8-Long Non-Coding RNA Signature Predicting Survival in Esophageal Cancer

    PubMed Central

    Fan, Qiaowei; Liu, Bingrong

    2016-01-01

    Background Accumulating evidence suggests the involvement of long non-coding RNAs (lncRNAs) as oncogenic or tumor suppressive regulators in the development of various cancers. In the present study, we aimed to identify a lncRNA signature based on RNA sequencing (RNA-seq) data to predict survival in esophageal cancer. Material/Methods The RNA-seq lncRNA expression data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs were screened out between esophageal cancer and normal tissues. Univariate and multivariate Cox regression analysis were performed to establish a lncRNA-related prognostic model. Receiver operating characteristic (ROC) analysis was conducted to test the sensitivity and specificity of the model. GO (gene ontology) functional and KEGG pathway enrichment analyses were performed for mRNAs co-expressed with the lncRNAs to explore the potential functions of the prognostic lncRNAs. Results A total of 265 differentially expressed lncRNAs were identified between esophageal cancer and normal tissues. After univariate and multivariate Cox regression analysis, eight lncRNAs (GS1-600G8.5, LINC00365, CTD-2357A8.3, RP11-705O24.1, LINC01554, RP1-90J4.1, RP11-327J17.1, and LINC00176) were finally screened out to establish a predictive model by which patients could be classified into high-risk and low-risk groups with significantly different overall survival. Further analysis indicated independent prognostic capability of the 8-lncRNA signature from other clinicopathological factors. ROC curve analysis demonstrated good performance of the 8-lncRNA signature. Functional enrichment analysis showed that the prognostic lncRNAs were mainly associated with esophageal cancer related biological processes such as regulation of glucose metabolic process and amino acid and lipids metabolism. Conclusions Our study developed a novel candidate model providing additional and more powerful prognostic information

  12. Predictability of Expressed Career Intent.

    ERIC Educational Resources Information Center

    Shenk, Faye

    An historical study of officer input from the various Air Force commissioning programs was initiated in 1963. The study was designed to determine the predictability of an Air Force officer's career decision and to evaluate relationships between career intent and demographic, environmental, and attitudinal factors. Career-intention information for…

  13. An Epigenetic Signature for Monoallelic Olfactory Receptor Expression

    PubMed Central

    Magklara, Angeliki; Yen, Angela; Colquitt, Bradley M.; Clowney, E. Josephine; Allen, William; Markenscoff-Papadimitriou, Eirene; Evans, Zoe A.; Kheradpour, Pouya; Mountoufaris, George; Carey, Catriona; Barnea, Gilad; Kellis, Manolis; Lomvardas, Stavros

    2011-01-01

    SUMMARY Constitutive heterochromatin is traditionally viewed as the static form of heterochromatin that silences pericentromeric and telomeric repeats in a cell cycle and differentiation independent manner. Here, we show that in the mouse olfactory epithelium, olfactory receptor (OR) genes are marked, in a highly dynamic fashion, with the molecular hallmarks of constitutive heterochromatin, H3K9me3 and H4K20me3. The cell-type and developmentally dependent deposition of these marks along the OR clusters is, most likely, reversed during the process of OR choice to allow for monogenic and monoallelic OR expression. In contrast to the current view of OR choice, our data suggest that OR silencing takes place before OR expression, indicating that it is not the product of an OR-elicited feedback signal. This suggests a new role for chromatin-mediated silencing as the molecular foundation upon which singular and stochastic selection can be applied. PMID:21529909

  14. Identification of a five B cell-associated gene prognostic and predictive signature for advanced glioma patients harboring immunosuppressive subtype preference

    PubMed Central

    Wang, Haoyuan; Song, Sonya Wei

    2016-01-01

    High grade gliomas contribute to most brain tumor mortality. A few studies reported that the immune system affected glioma development, and immune biomarkers helped understand the disease and formulate effective immunotherapy for patients. Currently, no B lymphocyte-based prognostic signature was reported in gliomas. By applying 78 B cell lineage-specific genes, we conducted a whole-genome gene expression analysis in 782 high grade gliomas derived from three independent datasets by Cox regression analysis and risk score method for signature identification, and then used Gene Ontology, Gene Set Enrichment Analysis, and other statistical methods for functional annotations of the signature-defined differences. We developed a five B cell-associated gene signature for prognosis of high grade glioma patients, which is independent of clinicopathological and genetic features. The signature identified high risk patients suitable for chemoradiotherapy, whereas low risk patients should rule out chemotherapy with radiotherapy only. We found that tumors of TCGA Mesenchymal subtype and wild type IDH1 were preferentially stratified to the high risk group, which bore strong immunosuppressive microenvironment, while tumors of TCGA Proneural subtype and mutated IDH1 were significantly accumulated to the low risk group, which exhibited less immunosuppressive state. The five B cell-associated gene signature predicts poor survival of high risk patients bearing strong immunosuppression and helps select optimal therapeutic regimens for glioma patients. PMID:27738332

  15. Gene Expression Signature-Based Screening Identifies New Broadly Effective Influenza A Antivirals

    PubMed Central

    Josset, Laurence; Textoris, Julien; Loriod, Béatrice; Ferraris, Olivier; Moules, Vincent; Lina, Bruno; N'Guyen, Catherine; Diaz, Jean-Jacques; Rosa-Calatrava, Manuel

    2010-01-01

    Classical antiviral therapies target viral proteins and are consequently subject to resistance. To counteract this limitation, alternative strategies have been developed that target cellular factors. We hypothesized that such an approach could also be useful to identify broad-spectrum antivirals. The influenza A virus was used as a model for its viral diversity and because of the need to develop therapies against unpredictable viruses as recently underlined by the H1N1 pandemic. We proposed to identify a gene-expression signature associated with infection by different influenza A virus subtypes which would allow the identification of potential antiviral drugs with a broad anti-influenza spectrum of activity. We analyzed the cellular gene expression response to infection with five different human and avian influenza A virus strains and identified 300 genes as differentially expressed between infected and non-infected samples. The most 20 dysregulated genes were used to screen the connectivity map, a database of drug-associated gene expression profiles. Candidate antivirals were then identified by their inverse correlation to the query signature. We hypothesized that such molecules would induce an unfavorable cellular environment for influenza virus replication. Eight potential antivirals including ribavirin were identified and their effects were tested in vitro on five influenza A strains. Six of the molecules inhibited influenza viral growth. The new pandemic H1N1 virus, which was not used to define the gene expression signature of infection, was inhibited by five out of the eight identified molecules, demonstrating that this strategy could contribute to identifying new broad anti-influenza agents acting on cellular gene expression. The identified infection signature genes, the expression of which are modified upon infection, could encode cellular proteins involved in the viral life cycle. This is the first study showing that gene expression-based screening can be

  16. 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

  17. Development of an experimental capability to validate infrared signature predictions of installed aircraft exhaust systems

    NASA Astrophysics Data System (ADS)

    Rooks, Steve; Fair, Martin L.; Smith, Anthony G.; Chettle, Nicholas

    2002-08-01

    As methods continue to develop for predicting infrared signatures for complex propulsion systems, the need to validate such methods and, indeed to gain confidence in new designs grows. Within Dstl, work to develop static engine test rigs has been carried out. These rigs allow aspects of infrared signature such as plume mixing, cavity emissions, surface impingement and subsequent treatment, obscuration and nozzle shaping to be studied. However, there is a growing need for data, which is more closely related to actual flight conditions. Full flight measurements are prohibitively expensive and often out of the question when a range of geometries are to be studied. Wind tunnel tests can also be difficult because of the quantity of power required for the free stream flow and the need to produce realistic hot gas. This paper describes the work that has been carried out to produce a cost effective free stream measurement capability, which makes use of existing static engine facilities. By bleeding engine compressor flows and exhaust flows, a reduced scale system has been created which allows the simulation of infrared propulsion issues at free stream Mach numbers of up to 0.5. The data obtained with this system has been used to validate the prediction methods for 3D-exhaust plume and afterbody infrared signature.

  18. A Circulating microRNA Signature Predicts Age-Based Development of Lymphoma

    PubMed Central

    Beheshti, Afshin; Vanderburg, Charles; McDonald, J. Tyson; Ramkumar, Charusheila; Kadungure, Tatenda; Zhang, Hong; Gartenhaus, Ronald B.; Evens, Andrew M.

    2017-01-01

    Extensive epidemiological data have demonstrated an exponential rise in the incidence of non-Hodgkin lymphoma (NHL) that is associated with increasing age. The molecular etiology of this remains largely unknown, which impacts the effectiveness of treatment for patients. We proposed that age-dependent circulating microRNA (miRNA) signatures in the host influence diffuse large B cell lymphoma (DLBCL) development. Our objective was to examine tumor development in an age-based DLBCL system using an inventive systems biology approach. We harnessed a novel murine model of spontaneous DLBCL initiation (Smurf2-deficient) at two age groups: 3 and 15 months old. All Smurf2-deficient mice develop visible DLBCL tumor starting at 15 months of age. Total miRNA was isolated from serum, bone marrow and spleen and were collected for all age groups for Smurf2-deficient mice and age-matched wild-type C57BL/6 mice. Using systems biology techniques, we identified a list of 10 circulating miRNAs being regulated in both the spleen and bone marrow that were present in DLBCL forming mice starting at 3 months of age that were not present in the control mice. Furthermore, this miRNA signature was found to occur circulating in the blood and it strongly impacted JUN and MYC oncogenic signaling. In addition, quantification of the miRNA signature was performed via Droplet Digital PCR technology. It was discovered that a key miRNA signature circulates throughout a host prior to the formation of a tumor starting at 3 months old, which becomes further modulated by age and yielded calculation of a ‘carcinogenic risk score’. This novel age-based circulating miRNA signature may potentially be leveraged as a DLBCL risk profile at a young age to predict future lymphoma development or disease progression as well as for potential innovative miRNA-based targeted therapeutic strategies in lymphoma. PMID:28107482

  19. Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus.

    PubMed

    Baechler, Emily C; Batliwalla, Franak M; Karypis, George; Gaffney, Patrick M; Ortmann, Ward A; Espe, Karl J; Shark, Katherine B; Grande, William J; Hughes, Karis M; Kapur, Vivek; Gregersen, Peter K; Behrens, Timothy W

    2003-03-04

    Systemic lupus erythematosus (SLE) is a complex, inflammatory autoimmune disease that affects multiple organ systems. We used global gene expression profiling of peripheral blood mononuclear cells to identify distinct patterns of gene expression that distinguish most SLE patients from healthy controls. Strikingly, about half of the patients studied showed dysregulated expression of genes in the IFN pathway. Furthermore, this IFN gene expression "signature" served as a marker for more severe disease involving the kidneys, hematopoetic cells, and/or the central nervous system. These results provide insights into the genetic pathways underlying SLE, and identify a subgroup of patients who may benefit from therapies targeting the IFN pathway.

  20. 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

  1. 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

  2. Expression profiling elucidates a molecular gene signature for pulmonary hypertension in sarcoidosis

    PubMed Central

    Singla, Sunit; Zhou, Tong; Javaid, Kamran; Abbasi, Taimur; Casanova, Nancy; Zhang, Wei; Ma, Shwu-Fan; Wade, Michael S.; Noth, Imre; Sweiss, Nadera J.; Garcia, Joe G. N.

    2016-01-01

    Abstract Pulmonary hypertension (PH), when it complicates sarcoidosis, carries a poor prognosis, in part because it is difficult to detect early in patients with worsening respiratory symptoms. Pathogenesis of sarcoidosis occurs via incompletely characterized mechanisms that are distinct from the mechanisms of pulmonary vascular remodeling well known to occur in conjunction with other chronic lung diseases. To address the need for a biomarker to aid in early detection as well as the gap in knowledge regarding the mechanisms of PH in sarcoidosis, we used genome-wide peripheral blood gene expression analysis and identified an 18-gene signature capable of distinguishing sarcoidosis patients with PH (n = 8), sarcoidosis patients without PH (n = 17), and healthy controls (n = 45). The discriminative accuracy of this 18-gene signature was 100% in separating sarcoidosis patients with PH from those without it. If validated in a large replicate cohort, this signature could potentially be used as a diagnostic molecular biomarker for sarcoidosis-associated PH. PMID:28090288

  3. A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients

    PubMed Central

    Afroz, Sumbul; Giddaluru, Jeevan; Vishwakarma, Sandeep; Naz, Saima; Khan, Aleem Ahmed; Khan, Nooruddin

    2017-01-01

    Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients’ (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including PLCG2, HLA-DOB, HLA-F, EIF4E2, and CYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA. PMID:28210261

  4. A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients.

    PubMed

    Afroz, Sumbul; Giddaluru, Jeevan; Vishwakarma, Sandeep; Naz, Saima; Khan, Aleem Ahmed; Khan, Nooruddin

    2017-01-01

    Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients' (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including PLCG2, HLA-DOB, HLA-F, EIF4E2, and CYFIP2, which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA.

  5. Bioinformatic identification of prognostic signature defined by copy number alteration and expression of CCNE1 in non-muscle invasive bladder cancer

    PubMed Central

    Song, Bic-Na; Kim, Seon-Kyu; Chu, In-Sun

    2017-01-01

    Non-muscle invasive bladder cancer (NMIBC) patients frequently fail to respond to treatment and experience disease progression because of their clinical and biological diversity. In this study, we identify a prognostic molecular signature for predicting the heterogeneity of NMIBC by using an integrative analysis of copy number and gene expression data. We analyzed the copy number and gene expression profiles of 404 patients with bladder cancer obtained from The Cancer Genome Atlas (TCGA) consortium. Of the 14 molecules with significant copy number alterations that were previously reported, 13 were significantly correlated with copy number and expression changes. Prognostic gene sets based on the 13 genes were developed, and their prognostic values were verified in three independent patient cohorts (n=501). Among them, a signature of CCNE1 and its coexpressed genes was significantly associated with disease progression and validated in the independent cohorts. The CCNE1 signature was an independent risk factor based on the result of a multivariate analysis (hazard ratio=6.849, 95% confidence interval=1.613–29.092, P=0.009). Finally, gene network and upstream regulator analyses revealed that NMIBC progression is potentially mediated by CCND1-CCNE1-SP1 pathways. The prognostic molecular signature defined by copy number and expression changes of CCNE1 suggests a novel diagnostic tool for predicting the likelihood of NMIBC progression. PMID:28082741

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

    PubMed Central

    Zhu, Bo; Zhang, Wenli; Jiang, Jiming

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  8. 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

  9. Protein Expression Signatures for Inhibition of Epidermal Growth Factor Receptor-mediated Signaling*

    PubMed Central

    Myers, Matthew V.; Manning, H. Charles; Coffey, Robert J.; Liebler, Daniel C.

    2012-01-01

    Analysis of cellular signaling networks typically involves targeted measurements of phosphorylated protein intermediates. However, phosphoproteomic analyses usually require affinity enrichment of phosphopeptides and can be complicated by artifactual changes in phosphorylation caused by uncontrolled preanalytical variables, particularly in the analysis of tissue specimens. We asked whether changes in protein expression, which are more stable and easily analyzed, could reflect network stimulation and inhibition. We employed this approach to analyze stimulation and inhibition of the epidermal growth factor receptor (EGFR) by EGF and selective EGFR inhibitors. Shotgun analysis of proteomes from proliferating A431 cells, EGF-stimulated cells, and cells co-treated with the EGFR inhibitors cetuximab or gefitinib identified groups of differentially expressed proteins. Comparisons of these protein groups identified 13 proteins whose EGF-induced expression changes were reversed by both EGFR inhibitors. Targeted multiple reaction monitoring analysis verified differential expression of 12 of these proteins, which comprise a candidate EGFR inhibition signature. We then tested these 12 proteins by multiple reaction monitoring analysis in three other models: 1) a comparison of DiFi (EGFR inhibitor-sensitive) and HCT116 (EGFR-insensitive) cell lines, 2) in formalin-fixed, paraffin-embedded mouse xenograft DiFi and HCT116 tumors, and 3) in tissue biopsies from a patient with the gastric hyperproliferative disorder Ménétrier's disease who was treated with cetuximab. Of the proteins in the candidate signature, a core group, including c-Jun, Jagged-1, and Claudin 4, were decreased by EGFR inhibitors in all three models. Although the goal of these studies was not to validate a clinically useful EGFR inhibition signature, the results confirm the hypothesis that clinically used EGFR inhibitors generate characteristic protein expression changes. This work further outlines a prototypical

  10. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

    PubMed Central

    Varshney, Arushi; Scott, Laura J.; Welch, Ryan P.; Erdos, Michael R.; Chines, Peter S.; Narisu, Narisu; Albanus, Ricardo D’O.; Orchard, Peter; Wolford, Brooke N.; Kursawe, Romy; Vadlamudi, Swarooparani; Cannon, Maren E.; Didion, John P.; Hensley, John; Kirilusha, Anthony; Bonnycastle, Lori L.; Taylor, D. Leland; Watanabe, Richard; Mohlke, Karen L.; Boehnke, Michael; Collins, Francis S.; Parker, Stephen C. J.; Stitzel, Michael L.

    2017-01-01

    Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition. PMID:28193859

  11. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes.

    PubMed

    Varshney, Arushi; Scott, Laura J; Welch, Ryan P; Erdos, Michael R; Chines, Peter S; Narisu, Narisu; Albanus, Ricardo D'O; Orchard, Peter; Wolford, Brooke N; Kursawe, Romy; Vadlamudi, Swarooparani; Cannon, Maren E; Didion, John P; Hensley, John; Kirilusha, Anthony; Bonnycastle, Lori L; Taylor, D Leland; Watanabe, Richard; Mohlke, Karen L; Boehnke, Michael; Collins, Francis S; Parker, Stephen C J; Stitzel, Michael L

    2017-02-28

    Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition.

  12. An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi

    PubMed Central

    Flake, Darl D.; Busam, Klaus; Cockerell, Clay; Helm, Klaus; McNiff, Jennifer; Reed, Jon; Tschen, Jaime; Kim, Jinah; Barnhill, Raymond; Elenitsas, Rosalie; Prieto, Victor G.; Nelson, Jonathan; Kimbrell, Hillary; Kolquist, Kathryn A.; Brown, Krystal L.; Warf, M. Bryan; Roa, Benjamin B.; Wenstrup, Richard J.

    2016-01-01

    BACKGROUND Recently, a 23‐gene signature was developed to produce a melanoma diagnostic score capable of differentiating malignant and benign melanocytic lesions. The primary objective of this study was to independently assess the ability of the gene signature to differentiate melanoma from benign nevi in clinically relevant lesions. METHODS A set of 1400 melanocytic lesions was selected from samples prospectively submitted for gene expression testing at a clinical laboratory. Each sample was tested and subjected to an independent histopathologic evaluation by 3 experienced dermatopathologists. A primary diagnosis (benign or malignant) was assigned to each sample, and diagnostic concordance among the 3 dermatopathologists was required for inclusion in analyses. The sensitivity and specificity of the score in differentiating benign and malignant melanocytic lesions were calculated to assess the association between the score and the pathologic diagnosis. RESULTS The gene expression signature differentiated benign nevi from malignant melanoma with a sensitivity of 91.5% and a specificity of 92.5%. CONCLUSIONS These results reflect the performance of the gene signature in a diverse array of samples encountered in routine clinical practice. Cancer 2017;123:617–628. © 2016 American Cancer Society. PMID:27768230

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

    PubMed Central

    2015-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  15. Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia

    PubMed Central

    Yan, Han; Wen, Lu; Tan, Dan; Xie, Pan; Pang, Feng-mei; Zhou, Hong-hao; Zhang, Wei; Liu, Zhao-qian; Tang, Jie; Li, Xi; Chen, Xiao-ping

    2017-01-01

    The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10−4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis. PMID:27903973

  16. A combined oncogenic pathway signature of BRAF, KRAS and PI3KCA mutation improves colorectal cancer classification and cetuximab treatment prediction

    PubMed Central

    Tian, Sun; Simon, Iris; Moreno, Victor; Roepman, Paul; Tabernero, Josep; Snel, Mireille; van't Veer, Laura; Salazar, Ramon; Bernards, Rene

    2013-01-01

    Objective To develop gene expression profiles that characterise KRAS-, BRAF- or PIK3CA-activated- tumours, and to explore whether these profiles might be helpful in predicting the response to the epidermal growth factor receptor (EGFR) pathway inhibitors better than mutation status alone. Design Fresh frozen tumour samples from 381 colorectal cancer (CRC) patients were collected and mutations in KRAS, BRAF and PIK3CA were assessed. Using microarray data, three individual oncogenic and a combined model were developed and validated in an independent set of 80 CRC patients, and in a dataset from metastatic CRC patients treated with cetuximab. Results 175 tumours (45.9%) harboured oncogenic mutations in KRAS (30.2%), BRAF (11.0%) and PIK3CA (11.5%). Activating mutation signatures for KRAS (75 genes), for BRAF (58 genes,) and for PIK3CA (49 genes) were developed. The development of a combined oncogenic pathway signature-classified tumours as ‘activated oncogenic’, or as ‘wildtype-like’ with a sensitivity of 90.3% and a specificity of 61.7%. The identified signature revealed other mechanisms that can activate ERK/MAPK pathway in KRAS, BRAF and PIK3CA wildtype patients. The combined signature is associated with response to cetuximab treatment in patients with metastatic CRC (HR 2.51, p<0.0009). Conclusion A combined oncogenic pathway signature allows the identification of patients with an active EGFR-signalling pathway that could benefit from downstream pathway inhibition. PMID:22798500

  17. 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.

  18. Epithelial cells captured from ductal carcinoma in situ reveal a gene expression signature associated with progression to invasive breast cancer

    PubMed Central

    Abuázar, Carolina Sens; de Toledo Osorio, Cynthia Aparecida Bueno; Pinilla, Mabel Gigliola; da Silva, Sabrina Daniela; Camargo, Anamaria Aranha; Silva, Wilson Araujo; e Ferreira, Elisa Napolitano; Brentani, Helena Paula; Carraro, Dirce Maria

    2016-01-01

    Breast cancer biomarkers that can precisely predict the risk of progression of non-invasive ductal carcinoma in situ (DCIS) lesions to invasive disease are lacking. The identification of molecular alterations that occur during the invasion process is crucial for the discovery of drivers of transition to invasive disease and, consequently, biomarkers with clinical utility. In this study, we explored differences in gene expression in mammary epithelial cells before and after the morphological manifestation of invasion, i.e., early and late stages, respectively. In the early stage, epithelial cells were captured from both pre-invasive lesions with distinct malignant potential [pure DCIS as well as the in situ component that co-exists with invasive breast carcinoma lesions (DCIS-IBC)]; in the late stage, epithelial cells were captured from the two distinct morphological components of the same sample (in situ and invasive components). Candidate genes were identified using cDNA microarray and rapid subtractive hybridization (RaSH) cDNA libraries and validated by RT-qPCR assay using new samples from each group. These analyses revealed 26 genes, including 20 from the early and 6 from the late stage. The expression profile based on the 20 genes, marked by a preferential decrease in expression level towards invasive phenotype, discriminated the majority of DCIS samples. Thus, this study revealed a gene expression signature with the potential to predict DCIS progression and, consequently, provides opportunities to tailor treatments for DCIS patients. PMID:27708222

  19. Evaluation of data discretization methods to derive platform independent isoform expression signatures for multi-class tumor subtyping

    PubMed Central

    2015-01-01

    Background Many supervised learning algorithms have been applied in deriving gene signatures for patient stratification from gene expression data. However, transferring the multi-gene signatures from one analytical platform to another without loss of classification accuracy is a major challenge. Here, we compared three unsupervised data discretization methods--Equal-width binning, Equal-frequency binning, and k-means clustering--in accurately classifying the four known subtypes of glioblastoma multiforme (GBM) when the classification algorithms were trained on the isoform-level gene expression profiles from exon-array platform and tested on the corresponding profiles from RNA-seq data. Results We applied an integrated machine learning framework that involves three sequential steps; feature selection, data discretization, and classification. For models trained and tested on exon-array data, the addition of data discretization step led to robust and accurate predictive models with fewer number of variables in the final models. For models trained on exon-array data and tested on RNA-seq data, the addition of data discretization step dramatically improved the classification accuracies with Equal-frequency binning showing the highest improvement with more than 90% accuracies for all the models with features chosen by Random Forest based feature selection. Overall, SVM classifier coupled with Equal-frequency binning achieved the best accuracy (> 95%). Without data discretization, however, only 73.6% accuracy was achieved at most. Conclusions The classification algorithms, trained and tested on data from the same platform, yielded similar accuracies in predicting the four GBM subgroups. However, when dealing with cross-platform data, from exon-array to RNA-seq, the classifiers yielded stable models with highest classification accuracies on data transformed by Equal frequency binning. The approach presented here is generally applicable to other cancer types for

  20. 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

  1. Computational analysis of expression of human embryonic stem cell-associated signatures in tumors

    PubMed Central

    2011-01-01

    Background The cancer stem cell model has been proposed based on the linkage between human embryonic stem cells and human cancer cells. However, the evidences supporting the cancer stem cell model remain to be collected. In this study, we extensively examined the expression of human embryonic stem cell-associated signatures including core genes, transcription factors, pathways and microRNAs in various cancers using the computational biology approach. Results We used the class comparison analysis and survival analysis algorithms to identify differentially expressed genes and their associated transcription factors, pathways and microRNAs among normal vs. tumor or good prognosis vs. poor prognosis phenotypes classes based on numerous human cancer gene expression data. We found that most of the human embryonic stem cell- associated signatures were frequently identified in the analysis, suggesting a strong linkage between human embryonic stem cells and cancer cells. Conclusions The present study revealed the close linkage between the human embryonic stem cell associated gene expression profiles and cancer-associated gene expression profiles, and therefore offered an indirect support for the cancer stem cell theory. However, many interest issues remain to be addressed further. PMID:22041030

  2. A gene expression signature for recent onset rheumatoid arthritis in peripheral blood mononuclear cells

    PubMed Central

    Olsen, N; Sokka, T; Seehorn, C; Kraft, B; Maas, K; Moore, J; Aune, T

    2004-01-01

    Background: In previous studies the presence of a distinct gene expression pattern has been shown in peripheral blood cells from patients with autoimmune disease. Objective: To determine whether other specific signatures might be used to identify subsets of these autoimmune diseases and whether gene expression patterns in early disease might identify pathogenetic factors. Methods: Peripheral blood mononuclear cells were acquired from patients with rheumatoid arthritis (RA) and analysed by microarrays containing over 4300 named human genes. Patients with RA for <2 years were compared with subjects with longstanding RA (average duration 10 years) and with patients with other immune or autoimmune diagnoses. Results: Cluster analyses permitted separation of the patients with early RA (ERA) from those with longstanding disease. Comparison with other patient groups suggested that the ERA signature showed some overlap with that seen in the normal immune response to viral antigen as well as with a subset of patients with systemic lupus erythematosus. Conclusions: The ERA signature may reflect, in part, a response to an unknown infectious agent. Furthermore, shared features with some lupus patients suggest that common aetiological factors and pathogenetic pathways may be involved in these two autoimmune disorders. PMID:15479887

  3. 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

  4. Predicting signatures of anisotropic resonance energy transfer in dye-functionalized nanoparticles.

    PubMed

    Gil, Gabriel; Corni, Stefano; Delgado, Alain; Bertoni, Andrea; Goldoni, Guido

    2016-11-13

    Resonance energy transfer (RET) is an inherently anisotropic process. Even the simplest, well-known Förster theory, based on the transition dipole-dipole coupling, implicitly incorporates the anisotropic character of RET. In this theoretical work, we study possible signatures of the fundamental anisotropic character of RET in hybrid nanomaterials composed of a semiconductor nanoparticle (NP) decorated with molecular dyes. In particular, by means of a realistic kinetic model, we show that the analysis of the dye photoluminescence difference for orthogonal input polarizations reveals the anisotropic character of the dye-NP RET which arises from the intrinsic anisotropy of the NP lattice. In a prototypical core/shell wurtzite CdSe/ZnS NP functionalized with cyanine dyes (Cy3B), this difference is predicted to be as large as 75% and it is strongly dependent in amplitude and sign on the dye-NP distance. We account for all the possible RET processes within the system, together with competing decay pathways in the separate segments. In addition, we show that the anisotropic signature of RET is persistent up to a large number of dyes per NP.

  5. Next-generation sequencing of microRNAs uncovers expression signatures in polarized macrophages.

    PubMed

    Cobos Jiménez, Viviana; Bradley, Edward J; Willemsen, Antonius M; van Kampen, Antoine H C; Baas, Frank; Kootstra, Neeltje A

    2014-02-01

    microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at a posttranscriptional level and play a crucial role in the development of cells of the immune system. Macrophages are essential for generating inflammatory reactions upon tissue damage and encountering of invading pathogens, yet modulation of their immune responses is critical for maintaining tissue homeostasis. Macrophages can present different phenotypes, depending on the cytokine environment they encounter in the affected tissues. In this study, we have identified expression signatures of miRNAs that are differentially regulated during maturation of monocytes and polarization of macrophages by cytokines. We present a comprehensive characterization of miRNA expression in human monocytes and M1, M2a, and M2c polarized macrophages, using next-generation sequencing. Furthermore, we show that miRNA expression signatures are closely related to the various immune functions of polarized macrophages and therefore are involved in shaping the diverse phenotypes of these cells. The miRNAs identified here serve as markers for identification of inflammatory macrophages involved in the development of immune responses. Our findings contribute to understanding the role of miRNAs in determining the macrophage function in healthy and diseased tissues.

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

    PubMed

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

    2015-07-13

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

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

    EPA Pesticide Factsheets

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

  8. 4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

    PubMed

    De Marchi, Tommaso; Liu, Ning Qing; Stingl, Cristoph; Timmermans, Mieke A; Smid, Marcel; Look, Maxime P; Tjoa, Mila; Braakman, Rene B H; Opdam, Mark; Linn, Sabine C; Sweep, Fred C G J; Span, Paul N; Kliffen, Mike; Luider, Theo M; Foekens, John A; Martens, John W M; Umar, Arzu

    2016-01-01

    Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast

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

    PubMed

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

    2013-03-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-01-05

    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.

  12. An immune-inflammation gene expression signature in prostate tumors of smokers

    PubMed Central

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

    2016-01-01

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

  13. Gene Expression Profiling Identifies IRF4-Associated Molecular Signatures in Hematological Malignancies

    PubMed Central

    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

  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. 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

  16. 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

  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. 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

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

    PubMed

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

    2016-08-01

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

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

    PubMed

    Zamani-Ahmadmahmudi, Mohamad

    2016-08-01

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

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

    PubMed Central

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

    2015-01-01

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

  2. 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.

  3. An atlas of human gene expression from massively parallel signature sequencing (MPSS)

    PubMed Central

    Jongeneel, C. Victor; Delorenzi, Mauro; Iseli, Christian; Zhou, Daixing; Haudenschild, Christian D.; Khrebtukova, Irina; Kuznetsov, Dmitry; Stevenson, Brian J.; Strausberg, Robert L.; Simpson, Andrew J.G.; Vasicek, Thomas J.

    2005-01-01

    We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com. PMID:15998913

  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. Effector CD4+ T cell expression signatures and immune-mediated disease associated genes.

    PubMed

    Zhang, Wei; Ferguson, John; Ng, Sok Meng; Hui, Ken; Goh, Gerald; Lin, Aiping; Esplugues, Enric; Flavell, Richard A; Abraham, Clara; Zhao, Hongyu; Cho, Judy H

    2012-01-01

    Genome-wide association studies (GWAS) in immune-mediated diseases have identified over 150 associated genomic loci. Many of these loci play a role in T cell responses, and regulation of T cell differentiation plays a critical role in immune-mediated diseases; however, the relationship between implicated disease loci and T cell differentiation is incompletely understood. To further address this relationship, we examined differential gene expression in naïve human CD4+ T cells, as well as in in vitro differentiated Th1, memory Th17-negative and Th17-enriched CD4+ T cells subsets using microarray and RNASeq. We observed a marked enrichment for increased expression in memory CD4+ compared to naïve CD4+ T cells of genes contained among immune-mediated disease loci. Within memory T cells, expression of disease-associated genes was typically increased in Th17-enriched compared to Th17-negative cells. Utilizing RNASeq and promoter methylation studies, we identified a differential regulation pattern for genes solely expressed in Th17 cells (IL17A and CCL20) compared to genes expressed in both Th17 and Th1 cells (IL23R and IL12RB2), where high levels of promoter methylation are correlated to near zero RNASeq levels for IL17A and CCL20. These findings have implications for human Th17 celI plasticity and for the regulation of Th17-Th1 expression signatures. Importantly, utilizing RNASeq we found an abundant isoform of IL23R terminating before the transmembrane domain that was enriched in Th17 cells. In addition to molecular resolution, we find that RNASeq provides significantly improved power to define differential gene expression and identify alternative gene variants relative to microarray analysis. The comprehensive integration of differential gene expression between cell subsets with disease-association signals, and functional pathways provides insight into disease pathogenesis.

  6. Genetic and epigenetic regulation and expression signatures of glutathione S-transferases in developing mouse liver.

    PubMed

    Cui, Julia Yue; Choudhuri, Supratim; Knight, Tamara R; Klaassen, Curtis D

    2010-07-01

    The hepatic glutathione S-transferases (Gsts) are critical phase II enzymes in protecting cellular macromolecules against electrophiles and oxidative stress. Little is known about the ontogeny of Gsts and the underlying regulatory mechanisms during liver development. Therefore, in this study, the ontogeny and the regulatory mechanisms of 19 known Gst isoforms were investigated in mouse liver from 2 days before birth to postnatal day 45. With the exception of Gstm5 and MGst2 that showed a progressive decline in postnatal messenger RNA (mRNA) expression, most other Gst isoforms showed a progressive increase in postnatal mRNA expression. Two-way hierarchical clustering revealed three distinct expression patterns of these Gsts isoforms: perinatal, adolescent, and adult enriched. The expression signatures of certain Gst isoforms showed positive association with the ontogeny of critical xenobiotic-sensing transcription factors, including aryl hydrocarbon receptor, pregnane X receptor (PXR), constitutive androstane receptor, peroxisome proliferator-activated receptor alpha, and NF-E2-related factor-2. Specifically, genome-wide chromatin immunoprecipitation coupled with the next generation sequencing technology (ChIP-Seq) revealed direct PXR-binding sites to the Gsta, Gstm, Gstt, and Gstp polycistron clusters as well as to the Mgst1 gene locus. Chromatin immunoprecipitation-on-chip analysis demonstrated that DNA methylation and histone H3K27-trimethylation (H3K27me3), two-gene expression-suppressing epigenetic marks, were consistently low around the Gstz1 gene locus. In contrast, enrichment of histone H3K4-dimethylation (H3K4me2), a hallmark for gene activation, increased 60% around the Gstz1 gene locus from prenatal to the young adult period. Regression analysis revealed a strong correlation between the enrichment of H3K4me2 and Gstz1 mRNA expression (r = 0.76). In conclusion, this study characterized three distinct ontogenic expression signatures of the 19 Gst isoforms

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

    PubMed Central

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

    2013-01-01

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

  8. 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

  9. Acoustic signature prediction of a combat vehicle using finite and boundary element methods

    NASA Astrophysics Data System (ADS)

    Wu, Zhen; Shalis, Edward

    1996-05-01

    The acoustic signature, i.e., the tonal peaks of the radiated noise spectrum, is important to the detectability and survivability of a ground combat vehicle. In the low frequency range below 200 Hz, the structure-borne noise radiation of the vehicle caused by excitation from its track and suspension, can be simulated by numerical models. The numerical simulation provides useful guidance to minimize the detectability through design modifications and countermeasures. A full vehicle finite-element structural model of the M1 Abrams tank was built with approximately 7,000 elements. The dynamic modal frequency response was computed using MSC/NASTRANTM with simulated force/moment input from the track and suspension. The output surface vibration velocities were then mapped on to an acoustic boundary-element model with coarser mesh of approximately 2,000 elements. The radiated far-field acoustic pressure was then computed on a 30 meter radius hemisphere using COMET/AcousticsTM. The numerical results were able to predict the unique fundamental tonal frequencies and some of their amplitudes for different vehicle speeds with reasonable correlation to the test data.

  10. 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.

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

    PubMed

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

    2013-09-01

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

  12. 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

  13. RNA Sequencing Reveals that Kaposi Sarcoma-Associated Herpesvirus Infection Mimics Hypoxia Gene Expression Signature

    PubMed Central

    Viollet, Coralie; Davis, David A.; Tekeste, Shewit S.; Reczko, Martin; Pezzella, Francesco; Ragoussis, Jiannis

    2017-01-01

    Kaposi sarcoma-associated herpesvirus (KSHV) causes several tumors and hyperproliferative disorders. Hypoxia and hypoxia-inducible factors (HIFs) activate latent and lytic KSHV genes, and several KSHV proteins increase the cellular levels of HIF. Here, we used RNA sequencing, qRT-PCR, Taqman assays, and pathway analysis to explore the miRNA and mRNA response of uninfected and KSHV-infected cells to hypoxia, to compare this with the genetic changes seen in chronic latent KSHV infection, and to explore the degree to which hypoxia and KSHV infection interact in modulating mRNA and miRNA expression. We found that the gene expression signatures for KSHV infection and hypoxia have a 34% overlap. Moreover, there were considerable similarities between the genes up-regulated by hypoxia in uninfected (SLK) and in KSHV-infected (SLKK) cells. hsa-miR-210, a HIF-target known to have pro-angiogenic and anti-apoptotic properties, was significantly up-regulated by both KSHV infection and hypoxia using Taqman assays. Interestingly, expression of KSHV-encoded miRNAs was not affected by hypoxia. These results demonstrate that KSHV harnesses a part of the hypoxic cellular response and that a substantial portion of hypoxia-induced changes in cellular gene expression are induced by KSHV infection. Therefore, targeting hypoxic pathways may be a useful way to develop therapeutic strategies for KSHV-related diseases. PMID:28046107

  14. RNA Sequencing Reveals that Kaposi Sarcoma-Associated Herpesvirus Infection Mimics Hypoxia Gene Expression Signature.

    PubMed

    Viollet, Coralie; Davis, David A; Tekeste, Shewit S; Reczko, Martin; Ziegelbauer, Joseph M; Pezzella, Francesco; Ragoussis, Jiannis; Yarchoan, Robert

    2017-01-01

    Kaposi sarcoma-associated herpesvirus (KSHV) causes several tumors and hyperproliferative disorders. Hypoxia and hypoxia-inducible factors (HIFs) activate latent and lytic KSHV genes, and several KSHV proteins increase the cellular levels of HIF. Here, we used RNA sequencing, qRT-PCR, Taqman assays, and pathway analysis to explore the miRNA and mRNA response of uninfected and KSHV-infected cells to hypoxia, to compare this with the genetic changes seen in chronic latent KSHV infection, and to explore the degree to which hypoxia and KSHV infection interact in modulating mRNA and miRNA expression. We found that the gene expression signatures for KSHV infection and hypoxia have a 34% overlap. Moreover, there were considerable similarities between the genes up-regulated by hypoxia in uninfected (SLK) and in KSHV-infected (SLKK) cells. hsa-miR-210, a HIF-target known to have pro-angiogenic and anti-apoptotic properties, was significantly up-regulated by both KSHV infection and hypoxia using Taqman assays. Interestingly, expression of KSHV-encoded miRNAs was not affected by hypoxia. These results demonstrate that KSHV harnesses a part of the hypoxic cellular response and that a substantial portion of hypoxia-induced changes in cellular gene expression are induced by KSHV infection. Therefore, targeting hypoxic pathways may be a useful way to develop therapeutic strategies for KSHV-related diseases.

  15. Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution

    PubMed Central

    Erickson, Keesha E.; Otoupal, Peter B.

    2017-01-01

    ABSTRACT Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment

  16. Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution.

    PubMed

    Erickson, Keesha E; Otoupal, Peter B; Chatterjee, Anushree

    2017-01-01

    Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress

  17. A three ion channel genes-based signature predicts prognosis of primary glioblastoma patients and reveals a chemotherapy sensitive subtype

    PubMed Central

    Liu, Xiu; Yan, Xiao-Yan; Wang, Wen; Wu, Fan; Liang, Ting-Yu; Yang, Fan; Hu, Hui-Min; Mao, Heng-Xu; Liu, Yan-Wei; Zhang, Shi-Zhong

    2016-01-01

    Increasing evidence suggests that ion channels not only regulate electric signaling in excitable cells but also play important roles in the development of brain tumor. However, the roles of ion channels in glioma remain controversial. In the present study, we systematically analyzed the expression patterns of ion channel genes in a cohort of Chinese patients with glioma using RNAseq expression profiling. First, a molecular signature comprising three ion channel genes (KCNN4, KCNB1 and KCNJ10) was identified using Univariate Cox regression and two-tailed student's t test conducted in overall survival (OS) and gene expression. We assigned a risk score based on three ion channel genes to each primary Glioblastoma multiforme (pGBM) patient. We demonstrated that pGBM patients who had a high risk of unfavorable outcome were sensitive to chemotherapy. Next, we screened the three ion genes-based signature in different molecular glioma subtypes. The signature showed a Mesenchymal subtype and wild-type IDH1 preference. Gene ontology (GO) analysis for the functional annotation of the signature showed that patients with high-risk scores tended to exhibit the increased expression of proteins associated with apoptosis, immune response, cell adhesion and motion and vasculature development. Gene Set Enrichment Analysis (GSEA) results showed that pathways associated with negative regulation of programmed cell death, cell proliferation and locomotory behavior were highly expressed in the high-risk group. These results suggest that ion channel gene expression could improve the subtype classification in gliomas at the molecular level. The findings in the present study have been validated in two independent cohorts. PMID:27713134

  18. 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

  19. Glycan-related gene expression signatures in breast cancer subtypes; relation to survival.

    PubMed

    Potapenko, Ivan O; Lüders, Torben; Russnes, Hege G; Helland, Åslaug; Sørlie, Therese; Kristensen, Vessela N; Nord, Silje; Lingjærde, Ole C; Børresen-Dale, Anne-Lise; Haakensen, Vilde D

    2015-04-01

    Alterations in glycan structures are early signs of malignancy and have recently been proposed to be in part a driving force behind malignant transformation. Here, we explore whether differences in expression of genes related to the process of glycosylation exist between breast carcinoma subtypes - and look for their association to clinical parameters. Five expression datasets of 454 invasive breast carcinomas, 31 ductal carcinomas in situ (DCIS), and 79 non-malignant breast tissue samples were analysed. Results were validated in 1960 breast carcinomas. 419 genes encoding glycosylation-related proteins were selected. The DCIS samples appeared expression-wise similar to carcinomas, showing altered gene expression related to glycosaminoglycans (GAGs) and N-glycans when compared to non-malignant samples. In-situ lesions with different aggressiveness potentials demonstrated changes in glycosaminoglycan sulfation and adhesion proteins. Subtype-specific expression patterns revealed down-regulation of genes encoding glycan-binding proteins in the luminal A and B subtypes. Clustering basal-like samples using a consensus list of genes differentially expressed across discovery datasets produced two clusters with significantly differing prognosis in the validation dataset. Finally, our analyses suggest that glycolipids may play an important role in carcinogenesis of breast tumors - as demonstrated by association of B3GNT5 and UGCG genes to patient survival. In conclusion, most glycan-specific changes occur early in the carcinogenic process. We have identified glycan-related alterations specific to breast cancer subtypes including a prognostic signature for two basal-like subgroups. Future research in this area may potentially lead to markers for better prognostication and treatment stratification of breast cancer patients.

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

    PubMed

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

    2015-10-06

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

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

    PubMed Central

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

    2012-01-01

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

  2. A host-based RT-PCR gene expression signature to identify acute respiratory viral infection.

    PubMed

    Zaas, Aimee K; Burke, Thomas; Chen, Minhua; McClain, Micah; Nicholson, Bradly; Veldman, Timothy; Tsalik, Ephraim L; Fowler, Vance; Rivers, Emanuel P; Otero, Ronny; Kingsmore, Stephen F; Voora, Deepak; Lucas, Joseph; Hero, Alfred O; Carin, Lawrence; Woods, Christopher W; Ginsburg, Geoffrey S

    2013-09-18

    Improved ways to diagnose acute respiratory viral infections could decrease inappropriate antibacterial use and serve as a vital triage mechanism in the event of a potential viral pandemic. Measurement of the host response to infection is an alternative to pathogen-based diagnostic testing and may improve diagnostic accuracy. We have developed a host-based assay with a reverse transcription polymerase chain reaction (RT-PCR) TaqMan low-density array (TLDA) platform for classifying respiratory viral infection. We developed the assay using two cohorts experimentally infected with influenza A H3N2/Wisconsin or influenza A H1N1/Brisbane, and validated the assay in a sample of adults presenting to the emergency department with fever (n = 102) and in healthy volunteers (n = 41). Peripheral blood RNA samples were obtained from individuals who underwent experimental viral challenge or who presented to the emergency department and had microbiologically proven viral respiratory infection or systemic bacterial infection. The selected gene set on the RT-PCR TLDA assay classified participants with experimentally induced influenza H3N2 and H1N1 infection with 100 and 87% accuracy, respectively. We validated this host gene expression signature in a cohort of 102 individuals arriving at the emergency department. The sensitivity of the RT-PCR test was 89% [95% confidence interval (CI), 72 to 98%], and the specificity was 94% (95% CI, 86 to 99%). These results show that RT-PCR-based detection of a host gene expression signature can classify individuals with respiratory viral infection and sets the stage for prospective evaluation of this diagnostic approach in a clinical setting.

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

    PubMed Central

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

    2015-01-01

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

  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. Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

    PubMed Central

    Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong

    2011-01-01

    Background Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. Methodology/Principal Findings Using microarray technology, we generated a gene expression profile of human gastric cancer–specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A) whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. Conclusions/Significance We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment. PMID:21931799

  6. Gene expression signatures in tree shrew choroid in response to three myopiagenic conditions

    PubMed Central

    He, Li; Frost, Michael R.; Siegwart, John T.; Norton, Thomas T.

    2014-01-01

    We examined gene expression in tree shrew choroid in response to three different myopiagenic conditions: minus lens (ML) wear, form deprivation (FD), and continuous darkness (DK). Four groups of tree shrews (n = 7 per group) were used. Starting 24 days after normal eye opening (days of visual experience [DVE]), the ML group wore a monocular −5 D lens for 2 days. The FD group wore a monocular translucent diffuser for 2 days. The DK group experienced continuous darkness binocularly for 11 days, starting at 17 DVE. An age-matched normal group was examined at 26 DVE. Quantitative PCR was used to measure the relative (treated eye vs. control eye) differences in mRNA levels in the choroid for 77 candidate genes. Small myopic changes were observed in the treated eyes (relative to the control eyes) of the ML group (−1.0 ± 0.2 D; mean ± SEM) and FD group (−1.9 ± 0.2 D). A larger myopia developed in the DK group (−4.4 ± 1.0 D) relative to Normal eyes (both groups, mean of right and left eyes). In the ML group, 28 genes showed significant differential mRNA expression; eighteen were down-regulated. A very similar pattern occurred in the FD group; twenty-seven of the same genes were similarly regulated, along with five additional genes. Fewer expression differences in the DK group were significant compared to normal or the control eyes of the ML and FD groups, but the pattern was similar to that of the ML and FD differential expression patterns. These data suggest that, at the level of the choroid, the gene expression signatures produced by “GO” emmetropization signals are highly similar despite the different visual conditions. PMID:25072854

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  8. SIGNATURES OF MRI-DRIVEN TURBULENCE IN PROTOPLANETARY DISKS: PREDICTIONS FOR ALMA OBSERVATIONS

    SciTech Connect

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

    2015-08-01

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

  9. 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

  10. Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

    PubMed

    Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

    2013-01-01

    A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal

  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. 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

  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.

  14. 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

  15. Gene-expression signature of tumor recurrence in patients with stage II and III colon cancer treated with 5'fluoruracil-based adjuvant chemotherapy.

    PubMed

    Giráldez, María Dolores; Lozano, Juan José; Cuatrecasas, Míriam; Alonso-Espinaco, Virginia; Maurel, Joan; Mármol, Maribel; Hörndler, Carlos; Ortego, Javier; Alonso, Vicente; Escudero, Pilar; Ramírez, Gina; Petry, Christoph; Lasalvia, Luis; Bohmann, Kerstin; Wirtz, Ralph; Mira, Aurea; Castells, Antoni

    2013-03-01

    Although receiving adjuvant chemotherapy after radical surgery, a disappointing proportion of patients with colorectal cancer will develop tumor recurrence. Probability of relapse is currently predicted from pathological staging, there being a need for additional markers to further select high-risk patients. This study was aimed to identify a gene-expression signature to predict tumor recurrence in patients with Stages II and III colon cancer treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy. Two-hundred and twenty-eight patients diagnosed with Stages II-III colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. RNA was extracted from formalin-fixed, paraffin-embedded tissue samples and expression of 27 selected candidate genes was analyzed by RT-qPCR. A tumor recurrence predicting model, including clinico-pathological variables and gene-expression profiling, was developed by Cox regression analysis and validated by bootstrapping. The regression analysis identified tumor stage and S100A2 and S100A10 gene expression as independently associated with tumor recurrence. The risk score derived from this model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95%CI, 1.71-4.39; p = 0.0001), which it was maintained when patients were stratified according to tumor stage. The algorithm was also able to distinguish two groups with different overall survival (HR, 2.68; 95%CI, 1.12-6.42; p = 0.03). Identification of a new gene-expression signature associated with a high probability of tumor recurrence in patients with Stages II and III colon cancer receiving adjuvant 5FU-based chemotherapy, and its combination in a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies.

  16. 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.

  17. A Two-Gene Signature, SKI and SLAMF1, Predicts Time-to-Treatment in Previously Untreated Patients with Chronic Lymphocytic Leukemia

    PubMed Central

    Schweighofer, Carmen D.; Coombes, Kevin R.; Barron, Lynn L.; Diao, Lixia; Newman, Rachel J.; Ferrajoli, Alessandra; O'Brien, Susan; Wierda, William G.; Luthra, Rajyalakshmi; Medeiros, L. Jeffrey; Keating, Michael J.; Abruzzo, Lynne V.

    2011-01-01

    We developed and validated a two-gene signature that predicts prognosis in previously-untreated chronic lymphocytic leukemia (CLL) patients. Using a 65 sample training set, from a cohort of 131 patients, we identified the best clinical models to predict time-to-treatment (TTT) and overall survival (OS). To identify individual genes or combinations in the training set with expression related to prognosis, we cross-validated univariate and multivariate models to predict TTT. We identified four gene sets (5, 6, 12, or 13 genes) to construct multivariate prognostic models. By optimizing each gene set on the training set, we constructed 11 models to predict the time from diagnosis to treatment. Each model also predicted OS and added value to the best clinical models. To determine which contributed the most value when added to clinical variables, we applied the Akaike Information Criterion. Two genes were consistently retained in the models with clinical variables: SKI (v-SKI avian sarcoma viral oncogene homolog) and SLAMF1 (signaling lymphocytic activation molecule family member 1; CD150). We optimized a two-gene model and validated it on an independent test set of 66 samples. This two-gene model predicted prognosis better on the test set than any of the known predictors, including ZAP70 and serum β2-microglobulin. PMID:22194822

  18. 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

  19. Predicted and observed magnetic signatures of martian (de)magnetized impact craters

    NASA Astrophysics Data System (ADS)

    Langlais, Benoit; Thébault, Erwan

    2011-04-01

    The current morphology of the martian lithospheric magnetic field results from magnetization and demagnetization processes, both of which shaped the planet. The largest martian impact craters, Hellas, Argyre, Isidis and Utopia, are not associated with intense magnetic fields at spacecraft altitude. This is usually interpreted as locally non- or de-magnetized areas, as large impactors may have reset the magnetization of the pre-impact material. We study the effects of impacts on the magnetic field. First, a careful analysis is performed to compute the impact demagnetization effects. We assume that the pre-impact lithosphere acquired its magnetization while cooling in the presence of a global, centered and mainly dipolar magnetic field, and that the subsequent demagnetization is restricted to the excavation area created by large craters, between 50- and 500-km diameter. Depth-to-diameter ratio of the transient craters is set to 0.1, consistent with observed telluric bodies. Associated magnetic field is computed between 100- and 500-km altitude. For a single-impact event, the maximum magnetic field anomaly associated with a crater located over the magnetic pole is maximum above the crater. A 200-km diameter crater presents a close-to-1-nT magnetic field anomaly at 400-km altitude, while a 100-km diameter crater has a similar signature at 200-km altitude. Second, we statistically study the 400-km altitude Mars Global Surveyor magnetic measurements modelled locally over the visible impact craters. This approach offers a local estimate of the confidence to which the magnetic field can be computed from real measurements. We conclude that currently craters down to a diameter of 200 km can be characterized. There is a slight anti-correlation of -0.23 between magnetic field intensity and impact crater diameters, although we show that this result may be fortuitous. A complete low-altitude magnetic field mapping is needed. New data will allow predicted weak anomalies above

  20. MicroRNA expression profiling and DNA methylation signature for deregulated microRNA in cutaneous T-cell lymphoma.

    PubMed

    Sandoval, Juan; Díaz-Lagares, Angel; Salgado, Rocío; Servitje, Octavio; Climent, Fina; Ortiz-Romero, Pablo L; Pérez-Ferriols, Amparo; Garcia-Muret, Maria P; Estrach, Teresa; Garcia, Mar; Nonell, Lara; Esteller, Manel; Pujol, Ramon M; Espinet, Blanca; Gallardo, Fernando

    2015-04-01

    MicroRNAs usually regulate gene expression negatively, and aberrant expression has been involved in the development of several types of cancers. Microarray profiling of microRNA expression was performed to define a microRNA signature in a series of mycosis fungoides tumor stage (MFt, n=21) and CD30+ primary cutaneous anaplastic large cell lymphoma (CD30+ cALCL, n=11) samples in comparison with inflammatory dermatoses (ID, n=5). Supervised clustering confirmed a distinctive microRNA profile for cutaneous T-cell lymphoma (CTCL) with respect to ID. A 40 microRNA signature was found in MFt including upregulated onco-microRNAs (miR-146a, miR-142-3p/5p, miR-21, miR-181a/b, and miR-155) and downregulated tumor-suppressor microRNAs (miR-200ab/429 cluster, miR-10b, miR-193b, miR-141/200c, and miR-23b/27b). Regarding CD30+ cALCL, 39 differentially expressed microRNAs were identified. Particularly, overexpression of miR-155, miR-21, or miR-142-3p/5p and downregulation of the miR-141/200c clusters were observed. DNA methylation in microRNA gene promoters, as expression regulatory mechanism for deregulated microRNAs, was analyzed using Infinium 450K array and approximately one-third of the differentially expressed microRNAs showed significant DNA methylation differences. Two different microRNA methylation signatures for MFt and CD30+ cALCL were found. Correlation analysis showed an inverse relationship for microRNA promoter methylation and microRNA expression. These results reveal a subgroup-specific epigenetically regulated microRNA signatures for MFt and CD30+ cALCL patients.

  1. Using Chemical-Induced Gene Expression in Cultured Human Cells to Predict Chemical Toxicity.

    PubMed

    Liu, Ruifeng; Yu, Xueping; Wallqvist, Anders

    2016-11-21

    Chemical toxicity is conventionally evaluated in animal models. However, animal models are resource intensive; moreover, they face ethical and scientific challenges because the outcomes obtained by animal testing may not correlate with human responses. To develop an alternative method for assessing chemical toxicity, we investigated the feasibility of using chemical-induced genome-wide expression changes in cultured human cells to predict the potential of a chemical to cause specific organ injuries in humans. We first created signatures of chemical-induced gene expression in a vertebral-cancer of the prostate cell line for ∼15,000 chemicals tested in the US National Institutes of Health Library of Integrated Network-Based Cellular Signatures program. We then used the signatures to create naı̈ve Bayesian prediction models for chemical-induced human liver cholestasis, interstitial nephritis, and long QT syndrome. Detailed cross-validation analyses indicated that the models were robust with respect to false positives and false negatives in the samples we used to train the models and could predict the likelihood that chemicals would cause specific organ injuries. In addition, we performed a literature search for drugs and dietary supplements, not formally categorized as causing organ injuries in humans but predicted by our models to be most likely to do so. We found a high percentage of these compounds associated with case reports of relevant organ injuries, lending support to the idea that in vitro cell-based experiments can be used to predict the toxic potential of chemicals. We believe that this approach, combined with a robust technique to model human exposure to chemicals, may serve as a promising alternative to animal-based chemical toxicity assessment.

  2. Hepatocellular carcinoma associated microRNA expression signature: integrated bioinformatics analysis, experimental validation and clinical significance

    PubMed Central

    Shi, Ke-Qing; Lin, Zhuo; Chen, Xiang-Jian; Song, Mei; Wang, Yu-Qun; Cai, Yi-Jing; Yang, Nai-Bing; Zheng, Ming-Hua; Dong, Jin-Zhong; Zhang, Lei; Chen, Yong-Ping

    2015-01-01

    microRNA (miRNA) expression profiles varied greatly among current studies due to different technological platforms and small sample size. Systematic and integrative analysis of published datesets that compared the miRNA expression profiles between hepatocellular carcinoma (HCC) tissue and paired adjacent noncancerous liver tissue was performed to determine candidate HCC associated miRNAs. Moreover, we further validated the confirmed miRNAs in a clinical setting using qRT-PCR and Tumor Cancer Genome Atlas (TCGA) dataset. A miRNA integrated-signature of 5 upregulated and 8 downregulated miRNAs was identified from 26 published datesets in HCC using robust rank aggregation method. qRT-PCR demonstrated that miR-93-5p, miR-224-5p, miR-221-3p and miR-21-5p was increased, whereas the expression of miR-214-3p, miR-199a-3p, miR-195-5p, miR-150-5p and miR-145-5p was decreased in the HCC tissues, which was also validated on TCGA dataset. A miRNA based score using LASSO regression model provided a high accuracy for identifying HCC tissue (AUC = 0.982): HCC risk score = 0.180E_miR-221 + 0.0262E_miR-21 - 0.007E_miR-223 - 0.185E_miR-130a. E_miR-n = Log 2 (expression of microRNA n). Furthermore, expression of 5 miRNAs (miR-222, miR-221, miR-21 miR-214 and miR-130a) correlated with pathological tumor grade. Cox regression analysis showed that miR-21 was related with 3-year survival (hazard ratio [HR]: 1.509, 95%CI: 1.079–2.112, P = 0.016) and 5-year survival (HR: 1.416, 95%CI: 1.057–1.897, P = 0.020). However, none of the deregulated miRNAs was related with microscopic vascular invasion. This study provides a basis for further clinical application of miRNAs in HCC. PMID:26231037

  3. 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 ...

  4. 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 ...

  5. 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.

  6. 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

  7. 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.

  8. A gene expression signature of confinement in peripheral blood of red wolves (Canis rufus).

    PubMed

    Kennerly, Erin; Ballmann, Anne; Martin, Stanton; Wolfinger, Russ; Gregory, Simon; Stoskopf, Michael; Gibson, Greg

    2008-06-01

    The stresses that animals experience as a result of modification of their ecological circumstances induce physiological changes that leave a signature in profiles of gene expression. We illustrate this concept in a comparison of free range and confined North American red wolves (Canis rufus). Transcription profiling of peripheral blood samples from 13 red wolf individuals in the Alligator River region of North Carolina revealed a strong signal of differentiation. Four hundred eighty-two out of 2980 transcripts detected on Illumina HumanRef8 oligonucleotide bead arrays were found to differentiate free range and confined wolves at a false discovery rate of 12.8% and P < 0.05. Over-representation of genes in focal adhesion, insulin signalling, proteasomal, and tryptophan metabolism pathways suggests the activation of pro-inflammatory and stress responses in confined animals. Consequently, characterization of differential transcript abundance in an accessible tissue such as peripheral blood identifies biomarkers that could be useful in animal management practices and for evaluating the impact of habitat changes on population health, particularly as attention turns to the impact of climate change on physiology and in turn species distributions.

  9. Can specific transcriptional regulators assemble a universal cancer signature?

    NASA Astrophysics Data System (ADS)

    Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

    2013-10-01

    Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

  10. 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.

  11. Multi-walled carbon nanotube-induced gene signatures in the mouse lung: potential predictive value for human lung cancer risk and prognosis

    PubMed Central

    Guo, Nancy L; Wan, Ying-Wooi; Denvir, James; Porter, Dale W; Pacurari, Maricica; Wolfarth, Michael G; Castranova, Vincent; Qian, Yong

    2012-01-01

    Concerns over the potential for multi-walled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n=160) exposed to 0, 10, 20, 40, or 80 µg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 days post-exposure. By using pairwise-Statistical Analysis of Microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5 fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at day 56 post-exposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at day 56 post-exposure to 10 µg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n=256) and test set (n=186). Furthermore, both gene signatures were associated with human lung cancer risk (n=164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace. PMID:22891886

  12. KRAS driven expression signature has prognostic power superior to mutation status in non‐small cell lung cancer

    PubMed Central

    Nagy, Ádám; Pongor, Lőrinc Sándor; Szabó, András; Santarpia, Mariacarmela

    2016-01-01

    KRAS is the most frequently mutated oncogene in non‐small cell lung cancer (NSCLC). However, the prognostic role of KRAS mutation status in NSCLC still remains controversial. We hypothesize that the expression changes of genes affected by KRAS mutation status will have the most prominent effect and could be used as a prognostic signature in lung cancer. We divided NSCLC patients with mutation and RNA‐seq data into KRAS mutated and wild type groups. Mann‐Whitney test was used to identify genes showing altered expression between these cohorts. Mean expression of the top five genes was designated as a “transcriptomic fingerprint” of the mutation. We evaluated the effect of this signature on clinical outcome in 2,437 NSCLC patients using univariate and multivariate Cox regression analysis. Mutation of KRAS was most common in adenocarcinoma. Mutation status and KRAS expression were not correlated to prognosis. The transcriptomic fingerprint of KRAS include FOXRED2, KRAS, TOP1, PEX3 and ABL2. The KRAS signature had a high prognostic power. Similar results were achieved when using the second and third set of strongest genes. Moreover, all cutoff values delivered significant prognostic power (p < 0.01). The KRAS signature also remained significant (p < 0.01) in a multivariate analysis including age, gender, smoking history and tumor stage. We generated a “surrogate signature” of KRAS mutation status in NSCLC patients by computationally linking genotype and gene expression. We show that secondary effects of a mutation can have a higher prognostic relevance than the primary genetic alteration itself. PMID:27859136

  13. Gene expression profile predictive of response to chemotherapy in metastatic colorectal cancer.

    PubMed

    Estevez-Garcia, Purificacion; Rivera, Fernando; Molina-Pinelo, Sonia; Benavent, Marta; Gómez, Javier; Limón, Maria Luisa; Pastor, Maria Dolores; Martinez-Perez, Julia; Paz-Ares, Luis; Carnero, Amancio; Garcia-Carbonero, Rocio

    2015-03-20

    Fluoropyrimidine-based chemotherapy (CT) has been the mainstay of care of metastatic colorectal cancer (mCRC) for years. Response rates are only observed, however, in about half of treated patients, and there are no reliable tools to prospectively identify patients more likely to benefit from therapy. The purpose of our study was to identify a gene expression profile predictive of CT response in mCRC. Whole genome expression analyses (Affymetrix GeneChip HG-U133 Plus 2.0) were performed in fresh frozen tumor samples of 37 mCRC patients (training cohort). Differential gene expression profiles among the two study conditions (responders versus non-responders) were assessed using supervised class prediction algorithms. A set of 161 differentially expressed genes in responders (23 patients; 62%) versus non-responders (14 patients; 38%) was selected for further assessment and validation by RT-qPCR (TaqMan Low Density Arrays (TLDA) 7900 HT Micro Fluidic Cards) in an independent multi-institutional cohort (53 mCRC patients). Seven of these genes were confirmed as significant predictors of response. Patients with a favorable predictive signature had significantly greater response rate (58% vs. 13%, p = 0.024), progression-free survival (61% vs. 13% at 1 year, HR = 0.32, p = 0.009) and overall survival (32 vs. 16 months, HR = 0.21, p = 0.003) than patients with an unfavorable gene signature. This is the first study to validate a gene-expression profile predictive of response to CT in mCRC patients. Larger and prospective confirmatory studies are required, however, in order to successfully provide oncologists with adequate tools to optimize treatment selection in routine clinical practice.

  14. Measurement and Model Predicted Corrosion Related Magnetic Signature: Applied on CFAV Quest

    DTIC Science & Technology

    2010-10-01

    prises en vue de les réduire au minimum. En plus de la peinture anticorrosion, la partie submergée du navire auxiliaire de recherche canadien (NAFC...de la peinture . À titre de comparaison, la signature magnétique totale d’un navire démagnétisé du même tonnage peut avoir une amplitude d’environ 1

  15. 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.

  16. Proteomic analysis of MG132-treated germinating pollen reveals expression signatures associated with proteasome inhibition.

    PubMed

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

    2014-01-01

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

  17. 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

  18. Identification of a liver cirrhosis signature in plasma for predicting hepatocellular carcinoma risk in a population-based cohort of hepatitis B carriers.

    PubMed

    Liu, Chia-Chi; Wang, Ya-Hui; Chuang, Eric Y; Tsai, Mong-Hsun; Chuang, Ya-Hui; Lin, Chih-Lin; Liu, Chun-Jen; Hsiao, Bo-Yu; Lin, Shi-Ming; Liu, Li-Yu; Yu, Ming-Whei

    2014-01-01

    Liver cirrhosis is a critical state in the natural course of hepatocellular carcinoma (HCC). We sought to investigate the potential of in-depth proteomics to reveal plasma protein signatures that reflect common networks/pathways of liver cirrhosis, and to determine whether the cirrhosis-related signature in plasma is linked to the development of HCC among hepatitis B virus (HBV) carriers. We first compared plasma protein profiles using a 174-antibody microarray system between three groups of HBV carriers with different Child's grades of cirrhosis, which revealed a panel of 45 differentially expressed proteins with a high accuracy for discriminating Child's B/C. Ingenuity Pathway Analysis identified two main up-regulated networks connecting the 45 proteins that were most enriched for genes in the pathway of hepatic stellate cell activation. A parsimonious subset of 11 pathway-based proteins was then selected for quantification to correlate with HCC risk among 49 HCC cases and 50 controls in a nested case-control study within a 16-yr follow-up cohort of HBV carriers. A high risk score derived from a principal component analysis, which was used to extract the cluster structure of the 11 proteins, was associated with HCC (odds ratio = 4.83, 95% confidence interval: 1.26-18.56) even after adjustment for viral and clinical variables, implying the involvement of a pattern of coordinated proteins. Stepwise logistic regression on the 11 proteins revealed ICAM-2 as an independent predictor for HCC. These findings may give further insight into the pathobiology of hepatocarcinogenesis, allow testing of the cirrhosis-related plasma protein signature as a potential predictive biomarker for HCC.

  19. From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma

    PubMed Central

    Cai, Xiao-yong; Wen, Dong-yue; Ye, Zhi-hua; Liang, Liang; Zhang, Lu; Wang, Han-lin

    2017-01-01

    Background Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in. Methods Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values. Results A list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, ‘pathways in cancer,’ was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982–0.998], P < 0.001, sensitivity: 96.0%, specificity: 96.5%). BIRC5 (P = 0.021) and CCNE1 (P = 0.027) were associated with poor prognosis, while CDKN2A (P = 0.066) and E2F1 (P = 0.088) demonstrated no statistically significant differences. Discussion The study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, ‘pathways in cancer.’ The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be further investigated

  20. 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.

  1. Gene Expression Profiling to Predict Outcome After Chemoradiation in Head and Neck Cancer

    SciTech Connect

    Pramana, Jimmy; Brekel, Michiel van den; Velthuysen, Marie-Louise F. van; Wessels, Lodewijk F.A.; Nuyten, Dimitry S.; Hofland, Ingrid; Atsma, Douwe; Pimentel, Nuno; Hoebers, Frank J.P.; Rasch, Coen; Begg, Adrian C.

    2007-12-01

    Purpose: The goal of the present study was to improve prediction of outcome after chemoradiation in advanced head and neck cancer using gene expression analysis. Materials and Methods: We collected 92 biopsies from untreated head and neck cancer patients subsequently given cisplatin-based chemoradiation (RADPLAT) for advanced squamous cell carcinomas (HNSCC). After RNA extraction and labeling, we performed dye swap experiments using 35k oligo-microarrays. Supervised analyses were performed to create classifiers to predict locoregional control and disease recurrence. Published gene sets with prognostic value in other studies were also tested. Results: Using supervised classification on the whole series, gene sets separating good and poor outcome could be found for all end points. However, when splitting tumors into training and validation groups, no robust classifiers could be found. Using Gene Set Enrichment analysis, several gene sets were found to be enriched in locoregional recurrences, although with high false-discovery rates. Previously published signatures for radiosensitivity, hypoxia, proliferation, 'wound,' stem cells, and chromosomal instability were not significantly correlated with outcome. However, a recently published signature for HNSCC defining a 'high-risk' group was shown to be predictive for locoregional control in our dataset. Conclusion: Gene sets can be found with predictive potential for locoregional control after combined radiation and chemotherapy in HNSCC. How treatment-specific these gene sets are needs further study.

  2. MicroRNA expression signature of castration-resistant prostate cancer: the microRNA-221/222 cluster functions as a tumour suppressor and disease progression marker

    PubMed Central

    Goto, Yusuke; Kojima, Satoko; Nishikawa, Rika; Kurozumi, Akira; Kato, Mayuko; Enokida, Hideki; Matsushita, Ryosuke; Yamazaki, Kazuto; Ishida, Yasuo; Nakagawa, Masayuki; Naya, Yukio; Ichikawa, Tomohiko; Seki, Naohiko

    2015-01-01

    Background: Our present study of the microRNA (miRNA) expression signature in castration-resistant prostate cancer (CRPC) revealed that the clustered miRNAs microRNA-221 (miR-221) and microRNA-222 (miR-222) are significantly downregulated in cancer tissues. The aim of this study was to investigate the functional roles of miR-221 and miR-222 in prostate cancer (PCa) cells. Methods: A CRPC miRNA signature was constructed by PCR-based array methods. Functional studies of differentially expressed miRNAs were analysed using PCa cells. The association between miRNA expression and overall survival was estimated by the Kaplan–Meier method. In silico database and genome-wide gene expression analyses were performed to identify molecular targets regulated by the miR-221/222 cluster. Results: miR-221 and miR-222 were significantly downregulated in PCa and CRPC specimens. Kaplan–Meier survival curves showed that low expression of miR-222 predicted a short duration of progression to CRPC. Restoration of miR-221 or miR-222 in cancer cells revealed that both miRNAs significantly inhibited cancer cell migration and invasion. Ecm29 was directly regulated by the miR-221/222 cluster in PCa cells. Conclusions: Loss of the tumour-suppressive miR-221/222 cluster enhanced migration and invasion in PCa cells. Our data describing targets regulated by the tumour-suppressive miR-221/222 cluster provide insights into the mechanisms of PCa and CRPC progression. PMID:26325107

  3. Brief reports: A distinct DNA methylation signature defines breast cancer stem cells and predicts cancer outcome.

    PubMed

    El Helou, Rita; Wicinski, Julien; Guille, Arnaud; Adélaïde, Jose; Finetti, Pascal; Bertucci, François; Chaffanet, Max; Birnbaum, Daniel; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

    2014-11-01

    Self-renewal and differentiation are two epigenetic programs that regulate stem cells fate. Dysregulation of these two programs leads to the development of cancer stem cells (CSCs). Recent evidence suggests that CSCs are relatively resistant to conventional therapies and responsible for metastasis formation. Deciphering these processes will help understand oncogenesis and allow the development of new targeted therapies. Here, we have used a whole genome promoter microarray to establish the DNA methylation portraits of breast cancer stem cells (bCSCs) and non-bCSCs. A total of 68 differentially methylated regions (DMRs) were more hypomethylated in bCSCs than in non-bCSCs. Using a differentiation assay we demonstrated that DMRs are rapidly hypermethylated within the first 6 hours following induction of CSC differentiation whereas the cells reached the steady-state within 6 days, suggesting that these DMRs are linked to early CSC epigenetic regulation. These DMRs were significantly enriched in genes coding for TGF-β signaling-related proteins. Interestingly, DMRs hypomethylation was correlated to an overexpression of TGF-β signaling genes in a series of 109 breast tumors. Moreover, patients with tumors harboring the bCSC DMRs signature had a worse prognosis than those with non-bCSC DMRs signature. Our results show that bCSCs have a distinct DNA methylation landscape with TGF-β signaling as a key epigenetic regulator of bCSCs differentiation.

  4. IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma.

    PubMed

    Kickingereder, Philipp; Sahm, Felix; Radbruch, Alexander; Wick, Wolfgang; Heiland, Sabine; Deimling, Andreas von; Bendszus, Martin; Wiestler, Benedikt

    2015-11-05

    The recent identification of IDH mutations in gliomas and several other cancers suggests that this pathway is involved in oncogenesis; however effector functions are complex and yet incompletely understood. To study the regulatory effects of IDH on hypoxia-inducible-factor 1-alpha (HIF1A), a driving force in hypoxia-initiated angiogenesis, we analyzed mRNA expression profiles of 288 glioma patients and show decreased expression of HIF1A targets on a single-gene and pathway level, strong inhibition of upstream regulators such as HIF1A and downstream biological functions such as angio- and vasculogenesis in IDH mutant tumors. Genotype/imaging phenotype correlation analysis with relative cerebral blood volume (rCBV) MRI - a robust and non-invasive estimate of tumor angiogenesis - in 73 treatment-naive patients with low-grade and anaplastic gliomas showed that a one-unit increase in rCBV corresponded to a two-third decrease in the odds for an IDH mutation and correctly predicted IDH mutation status in 88% of patients. Together, these findings (1) show that IDH mutation status is associated with a distinct angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging and (2) highlight the potential future of radiogenomics (i.e. the correlation between cancer imaging and genomic features) towards a more accurate diagnostic workup of brain tumors.

  5. 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

  6. Identifying protective host gene expression signatures within the spleen during West Nile virus infection in the collaborative cross model.

    PubMed

    Green, Richard; Wilkins, Courtney; Thomas, Sunil; Sekine, Aimee; Ireton, Renee C; Ferris, Martin T; Hendrick, Duncan M; Voss, Kathleen; de Villena, Fernando Pardo-Manuel; Baric, Ralph; Heise, Mark; Gale, Michael

    2016-12-01

    Flaviviruses are hematophagous arthropod-viruses that pose global challenges to human health. Like Zika virus, West Nile Virus (WNV) is a flavivirus for which no approved vaccine exists [1]. The role host genetics play in early detection and response to WNV still remains largely unexplained. In order to capture the impact of genetic variation on innate immune responses, we studied gene expression following WNV infection using the collaborative cross (CC). The CC is a mouse genetics resource composed of hundreds of independently bred, octo-parental recombinant inbred mouse lines [2]. To accurately capture the host immune gene expression signatures of West Nile infection, we used the nanostring platform to evaluate expression in spleen tissue isolated from CC mice infected with WNV over a time course of 4, 7, and 12 days' post-infection [3]. Nanostring is a non-amplification based digital method to quantitate gene expression that uses color-coded molecular barcodes to detect hundreds of transcripts in a sample. Using this approach, we identified unique gene signatures in spleen tissue at days 4, 7, and 12 following WNV infection, which delineated distinct differences between asymptomatic and symptomatic CC lines. We also identified novel immune genes. Data was deposited into the Gene Expression Omnibus under accession GSE86000.

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

    PubMed

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

    2014-03-15

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

  8. Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis

    PubMed Central

    Zhan, Fenghuang; Barlogie, Bart; Arzoumanian, Varant; Huang, Yongsheng; Williams, David R.; Hollmig, Klaus; Pineda-Roman, Mauricio; Tricot, Guido; van Rhee, Frits; Zangari, Maurizio; Dhodapkar, Madhav; Shaughnessy, John D.

    2007-01-01

    Monoclonal gammopathy of undetermined significance (MGUS) can progress to multiple myeloma (MM). Although these diseases share many of the same genetic features, it is still unclear whether global gene-expression profiling might identify prior genomic signatures that distinguish them. Through significance analysis of microarrays, 52 genes involved in important pathways related to cancer were differentially expressed in the plasma cells of healthy subjects (normal plasma-cell [NPC]; n = 22) and patients with stringently defined MGUS/smoldering MM (n = 24) and symptomatic MM (n = 351) (P < .001). Unsupervised hierarchical clustering of 351 patients with MM, 44 with MGUS (24 + 20), and 16 with MM from MGUS created 2 major cluster branches, one containing 82% of the MGUS patients and the other containing 28% of the MM patients, termed MGUS-like MM (MGUS-L MM). Using the same clustering approach on an independent cohort of 214 patients with MM, 27% were found to be MGUS-L. This molecular signature, despite its association with a lower incidence of complete remission (P = .006), was associated with low-risk clinical and molecular features and superior survival (P < .01). The MGUS-L signature was also seen in plasma cells from 15 of 20 patients surviving more than 10 years after autotransplantation. These data provide insight into the molecular mechanisms of plasma-cell dyscrasias. PMID:17023574

  9. Engineering Genes for Predictable Protein Expression

    PubMed Central

    Gustafsson, Claes; Minshull, Jeremy; Govindarajan, Sridhar; Ness, Jon; Villalobos, Alan; Welch, Mark

    2013-01-01

    The DNA sequence used to encode a polypeptide can have dramatic effects on its expression. Lack of readily available tools has until recently inhibited meaningful experimental investigation of this phenomenon. Advances in synthetic biology and the application of modern engineering approaches now provide the tools for systematic analysis of the sequence variables affecting heterologous expression of recombinant proteins. We here discuss how these new tools are being applied and how they circumvent the constraints of previous approaches, highlighting some of the surprising and promising results emerging from the developing field of gene engineering. PMID:22425659

  10. Engineering genes for predictable protein expression.

    PubMed

    Gustafsson, Claes; Minshull, Jeremy; Govindarajan, Sridhar; Ness, Jon; Villalobos, Alan; Welch, Mark

    2012-05-01

    The DNA sequence used to encode a polypeptide can have dramatic effects on its expression. Lack of readily available tools has until recently inhibited meaningful experimental investigation of this phenomenon. Advances in synthetic biology and the application of modern engineering approaches now provide the tools for systematic analysis of the sequence variables affecting heterologous expression of recombinant proteins. We here discuss how these new tools are being applied and how they circumvent the constraints of previous approaches, highlighting some of the surprising and promising results emerging from the developing field of gene engineering.

  11. 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

  12. Prediction Signatures in the Brain: Semantic Pre-Activation during Language Comprehension

    PubMed Central

    Maess, Burkhard; Mamashli, Fahimeh; Obleser, Jonas; Helle, Liisa; Friederici, Angela D.

    2016-01-01

    There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG) data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context) or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: highly predictive (that is more informative) verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns. PMID:27895573

  13. 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.

  14. Computational Account of Spontaneous Activity as a Signature of Predictive Coding

    PubMed Central

    Koren, Veronika

    2017-01-01

    Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function. PMID:28114353

  15. Distance in cancer gene expression from stem cells predicts patient survival

    PubMed Central

    Zehir, Ahmet; Gönen, Mithat; Moreira, Andre L.; Downey, Robert J.; Michor, Franziska

    2017-01-01

    The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of

  16. 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

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

    PubMed Central

    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

    2014-01-01

    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

  18. 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.

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

    PubMed Central

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

    2015-01-01

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

  20. 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.

  1. 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

  2. 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...

  3. DNA methylation signatures in peripheral blood strongly predict all-cause mortality

    PubMed Central

    Zhang, Yan; Wilson, Rory; Heiss, Jonathan; Breitling, Lutz P.; Saum, Kai-Uwe; Schöttker, Ben; Holleczek, Bernd; Waldenberger, Melanie; Peters, Annette; Brenner, Hermann

    2017-01-01

    DNA methylation (DNAm) has been revealed to play a role in various diseases. Here we performed epigenome-wide screening and validation to identify mortality-related DNAm signatures in a general population-based cohort with up to 14 years follow-up. In the discovery panel in a case-cohort approach, 11,063 CpGs reach genome-wide significance (FDR<0.05). 58 CpGs, mapping to 38 well-known disease-related genes and 14 intergenic regions, are confirmed in a validation panel. A mortality risk score based on ten selected CpGs exhibits strong association with all-cause mortality, showing hazard ratios (95% CI) of 2.16 (1.10–4.24), 3.42 (1.81–6.46) and 7.36 (3.69–14.68), respectively, for participants with scores of 1, 2–5 and 5+ compared with a score of 0. These associations are confirmed in an independent cohort and are independent from the ‘epigenetic clock'. In conclusion, DNAm of multiple disease-related genes are strongly linked to mortality outcomes. The DNAm-based risk score might be informative for risk assessment and stratification. PMID:28303888

  4. Specific molecular signatures of non-tumor liver tissue may predict a risk of hepatocarcinogenesis

    PubMed Central

    Utsunomiya, Tohru; Shimada, Mitsuo; Morine, Yuji; Tajima, Atsushi; Imoto, Issei

    2014-01-01

    Hepatocellular carcinoma (HCC) is one of the most common human cancers and a major cause of cancer-related death worldwide. The bleak outcomes of HCC patients even after curative treatment have been, at least partially, attributed to its multicentric origin. Therefore, it is necessary to examine not only tumor tissue but also non-tumor liver tissue to investigate the molecular mechanisms operating during hepatocarcinogenesis based on the concept of “field cancerization”. Several studies previously investigated the association of molecular alterations in non-tumor liver tissue with clinical features and prognosis in HCC patients on a genome-wide scale. In particular, specific alterations of DNA methylation profiles have been confirmed in non-tumor liver tissue. This review focuses on the possible clinical value of array-based comprehensive analyses of molecular alterations, especially aberrant DNA methylation, in non-tumor liver tissue to clarify the risk of hepatocarcinogenesis. Carcinogenetic risk estimation based on specific methylation signatures may be advantageous for close follow-up of patients who are at high risk of HCC development. Furthermore, epigenetic therapies for patients with chronic liver diseases may be helpful to reduce the risk of HCC development because epigenetic alterations are potentially reversible, and thus provide promising molecular targets for therapeutic intervention. PMID:24766251

  5. 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

  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. 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

  8. Gene expression profiling by high throughput sequencing to determine signatures for the bovine receptive uterus at early gestation.

    PubMed

    Van Hoeck, Veerle; Scolari, Saara C; Pugliesi, Guilherme; Gonella-Diaza, Angela M; Andrade, Sónia C S; Gasparin, Gustavo R; Coutinho, Luiz L; Binelli, Mario

    2015-09-01

    The uterus plays a central role among the reproductive tissues in the context of early embryo-maternal communication and a successful pregnancy depends on a complex series of endometrial molecular and cellular events. The factors responsible for the initial interaction between maternal and embryonic tissues, leading to the establishment of pregnancy, remain poorly understood. In this context, Illumina's next-generation sequencing technology has been used to discover the uterine transcriptome signature that is favourable for ongoing pregnancy. More specifically, the present report documents on a retrospective in vivo study in which data on pregnancy outcome were linked to uterine gene expression signatures on day 6 (bovine model). Using the RNA-Seq method, 14.654 reference genes were effectively analysed for differential expression between pregnant and non-pregnant uterine tissue. Transcriptome data revealed that 216 genes were differently expressed when comparing uterine tissue from pregnant and non-pregnant cows. All read sequences were deposited in the Sequence Read Archive (SRA) of the NCBI (http://www.ncbi.nlm.nih.gov/sra). An overview of the gene expression data has been deposited in NCBI's Gene Expression Omnibus (GEO) and is accessible through GEO Series accession number GSE65117. This allows the research community to enhance reproducibility and allows for new discoveries by comparing datasets of signatures linked to receptivity and/or pregnancy success. The resulting information can serve as tool to identify valuable and urgently needed biomarkers for scoring maternal receptivity and even for accurate detection of early pregnancy, which is a matter of cross-species interest. Beyond gene expression analysis as a marker tool, the RNA-Seq information on pregnant uterine tissue can be used to gain novel mechanistic insights, such as by identifying alternative splicing events, allele-specific expression, and rare and novel transcripts that might be involved in

  9. Gene expression profiling by high throughput sequencing to determine signatures for the bovine receptive uterus at early gestation

    PubMed Central

    Van Hoeck, Veerle; Scolari, Saara C.; Pugliesi, Guilherme; Gonella-Diaza, Angela M.; Andrade, Sónia C.S.; Gasparin, Gustavo R.; Coutinho, Luiz L.; Binelli, Mario

    2015-01-01

    The uterus plays a central role among the reproductive tissues in the context of early embryo-maternal communication and a successful pregnancy depends on a complex series of endometrial molecular and cellular events. The factors responsible for the initial interaction between maternal and embryonic tissues, leading to the establishment of pregnancy, remain poorly understood. In this context, Illumina's next-generation sequencing technology has been used to discover the uterine transcriptome signature that is favourable for ongoing pregnancy. More specifically, the present report documents on a retrospective in vivo study in which data on pregnancy outcome were linked to uterine gene expression signatures on day 6 (bovine model). Using the RNA-Seq method, 14.654 reference genes were effectively analysed for differential expression between pregnant and non-pregnant uterine tissue. Transcriptome data revealed that 216 genes were differently expressed when comparing uterine tissue from pregnant and non-pregnant cows. All read sequences were deposited in the Sequence Read Archive (SRA) of the NCBI (http://www.ncbi.nlm.nih.gov/sra). An overview of the gene expression data has been deposited in NCBI's Gene Expression Omnibus (GEO) and is accessible through GEO Series accession number GSE65117. This allows the research community to enhance reproducibility and allows for new discoveries by comparing datasets of signatures linked to receptivity and/or pregnancy success. The resulting information can serve as tool to identify valuable and urgently needed biomarkers for scoring maternal receptivity and even for accurate detection of early pregnancy, which is a matter of cross-species interest. Beyond gene expression analysis as a marker tool, the RNA-Seq information on pregnant uterine tissue can be used to gain novel mechanistic insights, such as by identifying alternative splicing events, allele-specific expression, and rare and novel transcripts that might be involved in

  10. 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.

  11. 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

  12. Gene expression signature discriminates sporadic from post-radiotherapy-induced thyroid tumors

    PubMed Central

    Ory, Catherine; Ugolin, Nicolas; Levalois, Céline; Lacroix, Ludovic; Caillou, Bernard; Bidart, Jean-Michel; Schlumberger, Martin; Diallo, Ibrahima; de Vathaire, Florent; Hofman, Paul; Santini, José; Malfoy, Bernard; Chevillard, Sylvie

    2011-01-01

    Both external and internal exposure to ionizing radiation are strong risk factors for the development of thyroid tumors. Until now, the diagnosis of radiation-induced thyroid tumors has been deduced from a network of arguments taken together with the individual history of radiation exposure. Neither the histological features nor the genetic alterations observed in these tumors have been shown to be specific fingerprints of an exposure to radiation. The aim of our work is to define ionizing radiation-related molecular specificities in a series of secondary thyroid tumors developed in the radiation field of patients treated by radiotherapy. To identify molecular markers that could represent a radiation-induction signature, we compared 25K microarray transcriptome profiles of a learning set of 28 thyroid tumors, which comprised 14 follicular thyroid adenomas (FTA) and 14 papillary thyroid carcinomas (PTC), either sporadic or consecutive to external radiotherapy in childhood. We identified a signature composed of 322 genes which discriminates radiation-induced tumors (FTA and PTC) from their sporadic counterparts. The robustness of this signature was further confirmed by blind case-by-case classification of an independent set of 29 tumors (16 FTA and 13 PTC). After the histology code break by the clinicians, 26/29 tumors were well classified regarding tumor etiology, 1 was undetermined, and 2 were misclassified. Our results help shed light on radiation-induced thyroid carcinogenesis, since specific molecular pathways are deregulated in radiation-induced tumors. PMID:21148326

  13. 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

    2014-07-09

    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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  16. Prediction of Solar Flares Using Unique Signatures of Magnetic Field Images

    NASA Astrophysics Data System (ADS)

    Raboonik, Abbas; Safari, Hossein; Alipour, Nasibe; Wheatland, Michael S.

    2017-01-01

    Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and topology of solar magnetic fields. A new method for predicting large (M- and X-class) flares is presented, which uses machine learning methods applied to the Zernike moments (ZM) of magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for a period of six years from 2010 June 2 to 2016 August 1. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of ZMs and fed to the support vector machine classifier. ZMs have the capability to elicit unique features from any 2D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hr before their occurrence, with only 10 false negatives out of 385 flaring active region magnetograms and 21 false positives out of 179 non-flaring active region magnetograms. Our method may provide a useful tool for the prediction of solar flares, which can be employed alongside other forecasting methods.

  17. 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...

  18. 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...

  19. Detection and prediction of Sitophilus oryzae infestations in triticale via near infrared spectral signature

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The goal of this research was to detect and predict degree of triticale seed infestation with rice weevils using near-infrared (NIR) spectroscopy. Groups of seeds at 11 different levels (degrees) of infestation were tested by combining mixtures of infested and uninfested seeds at different ratios. S...

  20. 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...

  1. DNA Copy Number Signature to Predict Recurrence in Early-Stage Ovarian Cancer

    DTIC Science & Technology

    2015-08-01

    and select 330 samples for CNV analysis. Months :1 - 2 • Subtask 2 Prepare sections (10 μm) for microdissection to ensure>80% tumor. Months 3 - 8...Subtask 3 DNA preparation from microdissected specimens. Months 3 - 8 Major Task 2: To determine the copy number gain and loss for early stage high...to prepare chip compatible samples. Months : 9 - 18 • Subtask 2 Genomic abnormality analysis by IlluminaHumanOmniExpress-FFPE BeadChip system. Months

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

    PubMed

    Chan, Jessica E; Netland, Peter A

    2015-01-01

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

  3. 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

  4. 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.

  5. 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

  6. The PAX2-null immunophenotype defines multiple lineages with common expression signatures in benign and neoplastic oviductal epithelium

    PubMed Central

    Ning, Gang; Bijron, Jonathan G.; Yamamoto, Yusuke; Wang, Xia; Howitt, Brooke E.; Herfs, Michael; Yang, Eric; Hong, Yue; Cornille, Maxence; Wu, Lingyan; Hanamornroongruang, Suchanan; McKeon, Frank D.; Crum, Christopher P.; Xian, Wa

    2014-01-01

    The oviducts contain high grade serous cancer (HGSC) precursors (serous tubal intraepithelial neoplasia or STINs), which are γ-H2AXp- and TP53 mutation-positive. Although they express wild type p53, secretory cell outgrowths (SCOUTs) are associated with older age and serous cancer; moreover both STINs and SCOUTs share a loss of PAX2 expression (PAX2n). We evaluated PAX2 expression in proliferating adult and embryonic oviductal cells, normal mucosa, SCOUTs, Walthard cell nests (WCNs), STINs and HGSCs, and the expression of genes chosen empirically or from SCOUT expression arrays. Clones generated in vitro from embryonic gynecologic tract and adult fallopian tube were Krt7p/PAX2n/EZH2p and underwent ciliated (PAX2n/EZH2n/FOXJ1p) and basal (Krt7n/EZH2n/Krt5p) differentiation. Similarly non-ciliated cells in normal mucosa were PAX2p but became PAX2n in multilayered epithelium undergoing ciliated or basal (Walthard cell nests or WCN) cell differentiation. PAX2n SCOUTs fell into two groups; Type I were secretory or secretory/ciliated with a “tubal” phenotype and were ALDH1n and β-cateninmem (membraneous only). Type II displayed a columnar to pseudostratified (endometrioid) phenotype, with an EZH2p, ALDH1p, β-cateninnc (nuclear and cytoplasmic), stathminp, LEF1p, RCN1p and RUNX2p expression signature. STINs and HGSCs shared the Type I immunophenotype of PAX2n, ALDH1n, β-cateninmem, but highly expressed EZH2p, LEF1p, RCN1p, and stathminp. This study, for the first time, links PAX2n with proliferating fetal and adult oviductal cells undergoing basal and ciliated differentiation and shows that this expression state is maintained in SCOUTs, STINs and HGSCs. All three entities can demonstrate a consistent perturbation of genes involved in potential tumor suppressor gene silencing (EZH2), transcriptional regulation (LEF1), regulation of differentiation (RUNX2), calcium binding (RCN1) and oncogenesis (stathmin). This shared expression signature between benign and

  7. Microarray analysis of Ewing's sarcoma family of tumours reveals characteristic gene expression signatures associated with metastasis and resistance to chemotherapy.

    PubMed

    Schaefer, Karl-Ludwig; Eisenacher, Martin; Braun, Yvonne; Brachwitz, Kristin; Wai, Daniel H; Dirksen, Uta; Lanvers-Kaminsky, Claudia; Juergens, Heribert; Herrero, David; Stegmaier, Sabine; Koscielniak, Ewa; Eggert, Angelika; Nathrath, Michaela; Gosheger, Georg; Schneider, Dominik T; Bury, Carsten; Diallo-Danebrock, Raihanatou; Ottaviano, Laura; Gabbert, Helmut E; Poremba, Christopher

    2008-03-01

    In Ewing's sarcoma family of tumours (ESFT), the clinically most adverse prognostic parameters are the presence of tumour metastasis at time of diagnosis and poor response to neoadjuvant chemotherapy. To identify genes differentially regulated between metastatic and localised tumours, we analysed 27 ESFT specimens using Affymetrix microarrays. Functional annotation of differentially regulated genes revealed 29 over-represented pathways including PDGF, TP53, NOTCH, and WNT1-signalling. Regression of primary tumours (n=20) induced by polychemotherapy was found to be correlated with the expression of genes involved in angiogenesis, apoptosis, ubiquitin proteasome pathway, and PI3 kinase and p53 pathways. These findings could be confirmed by in vitro cytotoxicity assays. A set of 46 marker genes correctly classifies these 20 tumours as responding versus non-responding. We conclude that expression signatures of initial tumour biopsies can help to identify ESFT patients at high risk to develop tumour metastasis or to suffer from a therapy refractory cancer.

  8. 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

  9. A boosting approach for adapting the sparsity of risk prediction signatures based on different molecular levels.

    PubMed

    Sariyar, Murat; Schumacher, Martin; Binder, Harald

    2014-06-01

    Risk prediction models can link high-dimensional molecular measurements, such as DNA methylation, to clinical endpoints. For biological interpretation, often a sparse fit is desirable. Different molecular aggregation levels, such as considering DNA methylation at the CpG, gene, or chromosome level, might demand different degrees of sparsity. Hence, model building and estimation techniques should be able to adapt their sparsity according to the setting. Additionally, underestimation of coefficients, which is a typical problem of sparse techniques, should also be addressed. We propose a comprehensive approach, based on a boosting technique that allows a flexible adaptation of model sparsity and addresses these problems in an integrative way. The main motivation is to have an automatic sparsity adaptation. In a simulation study, we show that this approach reduces underestimation in sparse settings and selects more adequate model sizes than the corresponding non-adaptive boosting technique in non-sparse settings. Using different aggregation levels of DNA methylation data from a study in kidney carcinoma patients, we illustrate how automatically selected values of the sparsity tuning parameter can reflect the underlying structure of the data. In addition to that, prediction performance and variable selection stability is compared to the non-adaptive boosting approach.

  10. Improved regulatory element prediction based on tissue-specific local epigenomic signatures

    PubMed Central

    He, Yupeng; Gorkin, David U.; Dickel, Diane E.; Nery, Joseph R.; Castanon, Rosa G.; Lee, Ah Young; Shen, Yin; Visel, Axel; Pennacchio, Len A.; Ren, Bing; Ecker, Joseph R.

    2017-01-01

    Accurate enhancer identification is critical for understanding the spatiotemporal transcriptional regulation during development as well as the functional impact of disease-related noncoding genetic variants. Computational methods have been developed to predict the genomic locations of active enhancers based on histone modifications, but the accuracy and resolution of these methods remain limited. Here, we present an algorithm, regulatory element prediction based on tissue-specific local epigenetic marks (REPTILE), which integrates histone modification and whole-genome cytosine DNA methylation profiles to identify the precise location of enhancers. We tested the ability of REPTILE to identify enhancers previously validated in reporter assays. Compared with existing methods, REPTILE shows consistently superior performance across diverse cell and tissue types, and the enhancer locations are significantly more refined. We show that, by incorporating base-resolution methylation data, REPTILE greatly improves upon current methods for annotation of enhancers across a variety of cell and tissue types. REPTILE is available at https://github.com/yupenghe/REPTILE/. PMID:28193886

  11. Prevalence of interferon type I signature in CD14 monocytes of patients with Sjögren's syndrome and association with disease activity and BAFF gene expression

    PubMed Central

    Brkic, Zana; Maria, Naomi I; van Helden-Meeuwsen, Cornelia G; van de Merwe, Joop P; van Daele, Paul L; Dalm, Virgil A; Wildenberg, Manon E; Beumer, Wouter; Drexhage, Hemmo A; Versnel, Marjan A

    2013-01-01

    Objective To determine the prevalence of upregulation of interferon (IFN) type I inducible genes, the so called ‘IFN type I signature’, in CD14 monocytes in 69 patients with primary Sjögren's syndrome (pSS) and 44 healthy controls (HC) and correlate it with disease manifestations and expression of B cell activating factor (BAFF). Methods Expression of IFI44L, IFI44, IFIT3, LY6E and MX1 was measured using real time quantitative PCR in monocytes. Expression values were used to calculate IFN type I scores for each subject. pSS patients positive for the IFN type I signature (IFN score≥10) and patients negative for the signature (IFN score<10) were then compared for clinical disease manifestations and BAFF expression. A bioassay using a monocytic cell line was performed to study whether BAFF mRNA expression was inducible by IFN type I activity in serum of patients with pSS. Results An IFN type I signature was present in 55% of patients with pSS compared with 4.5% of HC. Patients with the IFN type I signature showed: (a) higher EULAR Sjögren's Syndrome Disease Activity Index scores; higher anti-Ro52, anti-Ro60 and anti-La autoantibodies; higher rheumatoid factor; higher serum IgG; lower C3, lower absolute lymphocyte and neutrophil counts; (b)higher BAFF gene expression in monocytes. In addition, serum of signature-positive patients induced BAFF gene expression in monocytes. Conclusions The monocyte IFN type I signature identifies a subgroup of patients with pSS with a higher clinical disease activity together with higher BAFF mRNA expression. Such patients might benefit from treatment blocking IFN type I production or activity. PMID:22736090

  12. 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

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

    PubMed

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-07-01

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

  14. Comparison of Magnetospheric Multiscale Ion Jet Signatures with Predicted Reconnection Site Locations at the Magnetopause

    NASA Technical Reports Server (NTRS)

    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.

    2016-01-01

    Magnetic reconnection at the Earths 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.

  15. 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

  16. 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.

  17. A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

    PubMed Central

    Hang, Bo; Zou, Xiaoping; Mao, Jian-Hua

    2016-01-01

    Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A network was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system. PMID:27419373

  18. 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.

  19. Outcome-based profiling of astrocytic tumours identifies prognostic gene expression signatures which link molecular and morphology-based pathology.

    PubMed

    Beetz, Christian; Bergner, Sven; Brodoehl, Stefan; Brodhun, Michael; Ewald, Christian; Kalff, Rolf; Krüger, Jutta; Patt, Stephan; Kiehntopf, Michael; Deufel, Thomas

    2006-11-01

    Astrocytomas are intracranial malignancies for which invasive growth and high motility of tumour cells preclude total resection; the tumours usually recur in a more aggressive and, eventually, lethal form. Clinical outcome is highly variable and the accuracy of morphology-based prognostic statements is limited. In order to identify novel molecular markers for prognosis we obtained expression profiles of: i) tumours associated with particularly long recurrence-free intervals, ii) tumours which led to rapid patient death, and iii) tumour-free control brain. Unsupervised data analysis completely separated the three sample entities indicating a strong impact of the selection criteria on general gene expression. Consequently, significant numbers of specifically expressed genes could be identified for each entity. An extended set of tumours was then investigated by RT-PCR targeting 12 selected genes. Data from these experiments were summarised into a sample-specific index which assigns tumours to high- and low-risk groups as successfully as does morphology-based grading. Moreover, this index directly correlates with definite survival suggesting that integrated gene expression data allow individualised prognostic statements. We also analysed localisation of selected marker transcripts by in situ hybridization. Our finding of cell-specificity for some of these outcome-determining genes relates global expression data to the presence of morphological correlates of tumour behaviour and, thus, provides a link between morphology-based and molecular pathology. Our identification of expression signatures that are associated individually with clinical outcome confirms the prognostic relevance of gene expression data and, thus, represents a step towards eventually implementing molecular diagnosis into clinical practice in neuro-oncology.

  20. 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.

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

    PubMed

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

    2013-10-01

    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.

  2. Exon-level expression analyses identify MYCN and NTRK1 as major determinants of alternative exon usage and robustly predict primary neuroblastoma outcome

    PubMed Central

    Schramm, A; Schowe, B; Fielitz, K; Heilmann, M; Martin, M; Marschall, T; Köster, J; Vandesompele, J; Vermeulen, J; de Preter, K; Koster, J; Versteeg, R; Noguera, R; Speleman, F; Rahmann, S; Eggert, A; Morik, K; Schulte, J H

    2012-01-01

    Background: Using mRNA expression-derived signatures as predictors of individual patient outcome has been a goal ever since the introduction of microarrays. Here, we addressed whether analyses of tumour mRNA at the exon level can improve on the predictive power and classification accuracy of gene-based expression profiles using neuroblastoma as a model. Methods: In a patient cohort comprising 113 primary neuroblastoma specimens expression profiling using exon-level analyses was performed to define predictive signatures using various machine-learning techniques. Alternative transcript use was calculated from relative exon expression. Validation of alternative transcripts was achieved using qPCR- and cell-based approaches. Results: Both predictors derived from the gene or the exon levels resulted in prediction accuracies >80% for both event-free and overall survival and proved as independent prognostic markers in multivariate analyses. Alternative transcript use was most prominently linked to the amplification status of the MYCN oncogene, expression of the TrkA/NTRK1 neurotrophin receptor and survival. Conclusion: As exon level-based prediction yields comparable, but not significantly better, prediction accuracy than gene expression-based predictors, gene-based assays seem to be sufficiently precise for predicting outcome of neuroblastoma patients. However, exon-level analyses provide added knowledge by identifying alternative transcript use, which should deepen the understanding of neuroblastoma biology. PMID:23047593

  3. Global MHD predictions of observational signatures of subsolar Flux Transfer Events

    NASA Astrophysics Data System (ADS)

    Dorelli, J.; Glocer, A.

    2012-12-01

    Previous global MHD simulations of Flux Transfer Events demonstrate that they are topologically complex flux ropes that form at the subsolar magnetopause before being blown toward one of the polar cusps by the magnetosheath flow. However, different simulations -- run under different conditions -- seem to show evidence for qualitatively different generation mechanisms. For example, Raeder [2006] used the OpenGGCM code to argue that FTEs form as a result of a "sequential X line" mechanism in which non-vanishing dipole tilt causes the stagnation point to separate from a pre-existing X line. Numerical reconnection then caused a second X line to form, resulting in the creation of a simple "O-type" magnetic structure that Raeder identified as a Flux Transfer Event. FTEs were not observed under zero dipole tilt conditions. In contrast, Dorelli and Bhattacharjee [2009] ran higher resolution OpenGGCM simulations with constant but high Lundquist number (large enough to produce a resolved thin current sheet at the subsolar magnetopause) and demonstrated that dipole tilt is not required to generate FTEs. While the local magnetic field geometry (projected into a 2D plane) was simple, consisting of an O-type projected magnetic null bounded by two X-type nulls (consistent with what Raeder [2006] saw), new 3D X lines did not form until the FTE generation process was well underway. Further, the FTE topology was observed to be complex, with multiple (more than 2) 3D X lines forming at the subsolar magnetopause during the generation process. In this talk, we revisit the question of FTE generation using the BATS-R-US global MHD code. Our goals are: 1) to determine whether BATS-R-US can produce FTEs under conditions similar to those for which they were seen by OpenGGCM, 2) to explore the role of dipole tilt and the resistivity model in FTE generation, and 3) to generate a list of observable predictions of FTEs as they form near the subsolar magnetopause.

  4. 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

  5. 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

  6. SLINGER: large-scale learning for predicting gene expression

    PubMed Central

    Vervier, Kévin; Michaelson, Jacob J.

    2016-01-01

    Recent studies have established that single nucleotide polymorphisms are sufficient to build accurate predictive models of gene expression. Gamazon, et al., found that gene expression values predicted from cis neighborhood SNPs show statistical association with disease status. In this work, we remove the cis neighborhood constraint during the learning process, and propose a novel predictive approach called SLINGER. We demonstrate that models drawing from a genome-wide set of SNPs are able to predict expression for more genes than the ones built on cis neighborhood only. Results indicate that these new models significantly improve accuracy for a large number of genes. Thanks to a penalized linear model, we also show that the number of features used in our models remains comparable to the cis-only models. Finally, SLINGER application on seven Wellcome Trust Case-Control Consortium genome-wide association studies demonstrate that compared to a cis-only approach, our models lead to associations with greater fidelity to actual gene expression values. PMID:27996030

  7. SLINGER: large-scale learning for predicting gene expression

    NASA Astrophysics Data System (ADS)

    Vervier, Kévin; Michaelson, Jacob J.

    2016-12-01

    Recent studies have established that single nucleotide polymorphisms are sufficient to build accurate predictive models of gene expression. Gamazon, et al., found that gene expression values predicted from cis neighborhood SNPs show statistical association with disease status. In this work, we remove the cis neighborhood constraint during the learning process, and propose a novel predictive approach called SLINGER. We demonstrate that models drawing from a genome-wide set of SNPs are able to predict expression for more genes than the ones built on cis neighborhood only. Results indicate that these new models significantly improve accuracy for a large number of genes. Thanks to a penalized linear model, we also show that the number of features used in our models remains comparable to the cis-only models. Finally, SLINGER application on seven Wellcome Trust Case-Control Consortium genome-wide association studies demonstrate that compared to a cis-only approach, our models lead to associations with greater fidelity to actual gene expression values.

  8. Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

    PubMed Central

    Yuan, Xiguo; Zhang, Junying

    2016-01-01

    Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data. PMID:27999797

  9. Matrix Metalloproteinases: The Gene Expression Signatures of Head and Neck Cancer Progression

    PubMed Central

    Iizuka, Shinji; Ishimaru, Naozumi; Kudo, Yasusei

    2014-01-01

    Extracellular matrix degradation by matrix metalloproteinases (MMPs) plays a pivotal role in cancer progression by promoting motility, invasion and angiogenesis. Studies have shown that MMP expression is increased in head and neck squamous cell carcinomas (HNSCCs), one of the most common cancers in the world, and contributes to poor outcome. In this review, we examine the expression pattern of MMPs in HNSCC by microarray datasets and summarize the current knowledge of MMPs, specifically MMP-1, -3, -7 -10, -12, -13, 14 and -19, that are highly expressed in HNSCCs and involved cancer invasion and angiogenesis. PMID:24531055

  10. 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

  11. 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

  12. Trophic factor-induced activity 'signature' regulates the functional expression of postsynaptic excitatory acetylcholine receptors required for synaptogenesis.

    PubMed

    Luk, Collin C; Lee, Arthur J; Wijdenes, Pierre; Zaidi, Wali; Leung, Andrew; Wong, Noelle Y; Andrews, Joseph; Syed, Naweed I

    2015-04-01

    Highly coordinated and coincidental patterns of activity-dependent mechanisms ("fire together wire together") are thought to serve as inductive signals during synaptogenesis, enabling neuronal pairing between specific sub-sets of excitatory partners. However, neither the nature of activity triggers, nor the "activity signature" of long-term neuronal firing in developing/regenerating neurons have yet been fully defined. Using a highly tractable model system comprising of identified cholinergic neurons from Lymnaea, we have discovered that intrinsic trophic factors present in the Lymnaea brain-conditioned medium (CM) act as a natural trigger for activity patterns in post- but not the presynaptic neuron. Using microelectrode array recordings, we demonstrate that trophic factors trigger stereotypical activity patterns that include changes in frequency, activity and variance. These parameters were reliable indicators of whether a neuron expressed functional excitatory or inhibitory nAChRs and synapse formation. Surprisingly, we found that the post- but not the presynaptic cell exhibits these changes in activity patterns, and that the functional expression of excitatory nAChRs required neuronal somata, de novo protein synthesis and voltage gated calcium channels. In summary, our data provides novel insights into trophic factor mediated actions on neuronal activity and its specific regulation of nAChR expression.

  13. Comprehensive Gene expression meta-analysis and integrated bioinformatic approaches reveal shared signatures between thrombosis and myeloproliferative disorders

    PubMed Central

    Jha, Prabhash Kumar; Vijay, Aatira; Sahu, Anita; Ashraf, Mohammad Zahid

    2016-01-01

    Thrombosis is a leading cause of morbidity and mortality in patients with myeloproliferative disorders (MPDs), particularly polycythemia vera (PV) and essential thrombocythemia (ET). Despite the attempts to establish a link between them, the shared biological mechanisms are yet to be characterized. An integrated gene expression meta-analysis of five independent publicly available microarray data of the three diseases was conducted to identify shared gene expression signatures and overlapping biological processes. Using INMEX bioinformatic tool, based on combined Effect Size (ES) approaches, we identified a total of 1,157 differentially expressed genes (DEGs) (697 overexpressed and 460 underexpressed genes) shared between the three diseases. EnrichR tool’s rich library was used for comprehensive functional enrichment and pathway analysis which revealed “mRNA Splicing” and “SUMO E3 ligases SUMOylate target proteins” among the most enriched terms. Network based meta-analysis identified MYC and FN1 to be the most highly ranked hub genes. Our results reveal that the alterations in biomarkers of the coagulation cascade like F2R, PROS1, SELPLG and ITGB2 were common between the three diseases. Interestingly, the study has generated a novel database of candidate genetic markers, pathways and transcription factors shared between thrombosis and MPDs, which might aid in the development of prognostic therapeutic biomarkers. PMID:27892526

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

    PubMed

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

    2016-01-01

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

  15. High Hepsin expression predicts poor prognosis in Gastric Cancer

    PubMed Central

    Zhang, Mingming; Zhao, Junjie; Tang, Wenyi; Wang, Yanru; Peng, Peike; Li, Lili; Song, Shushu; Wu, Hao; Li, Can; Yang, Caiting; Wang, Xuefei; Zhang, Chunyi; Gu, Jianxin

    2016-01-01

    Hepsin, a membrane-associated serine protease, is frequently upregulated in epithelial cancers and involved in cancer progression. Our study aims to describe the expression pattern and evaluate the clinical implication of hepsin in gastric cancer patients. The mRNA expression of hepsin was analyzed in 50 gastric cancer and matched non-tumor tissues, which was downregulated in 78% (39/50) of gastric cancer. By searching and analyzing four independent datasets from Oncomine, we obtained the similar results. Furthermore, we evaluated the hepsin expression by IHC in tissue microarray (TMA) containing 220 Gastric Cancer specimens. More importantly, Kaplan-Meier survival and Cox regression analyses were taken to access the prognosis of gastric cancer and predicted that hepsin protein expression was one of the significant and independent prognostic factors for overall survival of Gastric Cancer. PMID:27841306

  16. A predictive approach to identify genes differentially expressed

    NASA Astrophysics Data System (ADS)

    Saraiva, Erlandson F.; Louzada, Francisco; Milan, Luís A.; Meira, Silvana; Cobre, Juliana

    2012-10-01

    The main objective of gene expression data analysis is to identify genes that present significant changes in expression levels between a treatment and a control biological condition. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating credibility intervals from predictive densities which are constructed using sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained indicate that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a publicly available data set on Escherichia coli bacteria.

  17. Learning regulatory programs that accurately predict differential expression with MEDUSA.

    PubMed

    Kundaje, Anshul; Lianoglou, Steve; Li, Xuejing; Quigley, David; Arias, Marta; Wiggins, Chris H; Zhang, Li; Leslie, Christina

    2007-12-01

    Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes. Instead of using clustering or correlation of expression profiles to infer regulatory relationships, MEDUSA determines condition-specific regulators and discovers regulatory motifs that mediate the regulation of target genes. In this way, MEDUSA meaningfully models biological mechanisms of transcriptional regulation. MEDUSA solves the problem of predicting the differential (up/down) expression of target genes by using boosting, a technique from statistical learning, which helps to avoid overfitting as the algorithm searches through the high-dimensional space of potential regulators and sequence motifs. Experimental results demonstrate that MEDUSA achieves high prediction accuracy on held-out experiments (test data), that is, data not seen in training. We also present context-specific analysis of MEDUSA regulatory programs for DNA damage and hypoxia, demonstrating that MEDUSA identifies key regulators and motifs in these processes. A central challenge in the field is the difficulty of validating reverse-engineered networks in the absence of a gold standard. Our approach of learning regulatory programs provides at least a partial solution for the problem: MEDUSA's prediction accuracy on held-out data gives a concrete and statistically sound way to validate how well the algorithm performs. With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration.

  18. Human spontaneous labor without histologic chorioamnionitis is characterized by an acute inflammation gene expression signature

    PubMed Central

    Haddad, Ramsi; Tromp, Gerard; Kuivaniemi, Helena; Chaiworapongsa, Tinnakorn; Kim, Yeon Mee; Mazor, Moshe; Romero, Roberto

    2006-01-01

    OBJECTIVE The purpose of this study was to identify which biological processes may be involved in normal labor. STUDY DESIGN Transcriptional profiles for chorioamniotic membranes (n=24) and blood (n=20) were generated from patients at term with no labor (TNL) and in labor (TIL). RESULTS Expression of 197 transcripts (P≤0.02) differentiated TIL and TNL chorioamniotic membrane samples. Gene Ontology analysis indicated that TIL samples had increased expression of multiple chemokines and transcripts associated with neutrophil and monocyte recruitment. Microarray results were verified using quantitative real-time RT-PCR with independent samples. Transcriptional profiles from blood RNA revealed no Gene Ontology category enrichment of discriminant probe sets. CONCLUSION Labor induces gene expression changes consistent with localized inflammation, despite the absence of histologically detectable inflammation. PMID:16890549

  19. 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

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  1. 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.

  2. 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

  3. 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

  4. 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

  5. Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy.

    PubMed

    Blakely, Collin M; Stoddard, Alexander J; Belka, George K; Dugan, Katherine D; Notarfrancesco, Kathleen L; Moody, Susan E; D'Cruz, Celina M; Chodosh, Lewis A

    2006-06-15

    Women who have their first child early in life have a substantially lower lifetime risk of breast cancer. The mechanism for this is unknown. Similar to humans, rats exhibit parity-induced protection against mammary tumorigenesis. To explore the basis for this phenomenon, we identified persistent pregnancy-induced changes in mammary gene expression that are tightly associated with protection against tumorigenesis in multiple inbred rat strains. Four inbred rat strains that exhibit marked differences in their intrinsic susceptibilities to carcinogen-induced mammary tumorigenesis were each shown to display significant protection against methylnitrosourea-induced mammary tumorigenesis following treatment with pregnancy levels of estradiol and progesterone. Microarray expression profiling of parous and nulliparous mammary tissue from these four strains yielded a common 70-gene signature. Examination of the genes constituting this signature implicated alterations in transforming growth factor-beta signaling, the extracellular matrix, amphiregulin expression, and the growth hormone/insulin-like growth factor I axis in pregnancy-induced alterations in breast cancer risk. Notably, related molecular changes have been associated with decreased mammographic density, which itself is strongly associated with decreased breast cancer risk. Our findings show that hormone-induced protection against mammary tumorigenesis is widely conserved among divergent rat strains and define a gene expression signature that is tightly correlated with reduced mammary tumor susceptibility as a consequence of a normal developmental event. Given the conservation of this signature, these pathways may contribute to pregnancy-induced protection against breast cancer.

  6. 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

  7. Clinical significance of in vivo cytarabine-induced gene expression signature in AML.

    PubMed

    Lamba, Jatinder K; Pounds, Stanley; Cao, Xueyuan; Crews, Kristine R; Cogle, Christopher R; Bhise, Neha; Raimondi, Susana C; Downing, James R; Baker, Sharyn D; Ribeiro, Raul C; Rubnitz, Jeffrey E

    2016-01-01

    Despite initial remission, ∼60-70% of adult and 30% of pediatric patients experience relapse or refractory AML. Studies so far have identified base line gene expression profiles of pathogenic and prognostic significance in AML; however, the extent of change in gene expression post-initiation of treatment has not been investigated. Exposure of leukemic cells to chemotherapeutic agents such as cytarabine, a mainstay of AML chemotherapy, can trigger adaptive response by influencing leukemic cell transcriptome and, hence, development of resistance or refractory disease. It is, however, challenging to perform such a study due to lack of availability of specimens post-drug treatment. The primary objective of this study was to identify in vivo cytarabine-induced changes in leukemia cell transcriptome and to evaluate their impact on clinical outcome. The results highlight genes relevant to cytarabine resistance and support the concept of targeting cytarabine-induced genes as a means of improving response.

  8. Protein Sialylation Regulates a Gene Expression Signature that Promotes Breast Cancer Cell Pathogenicity.

    PubMed

    Kohnz, Rebecca A; Roberts, Lindsay S; DeTomaso, David; Bideyan, Lara; Yan, Peter; Bandyopadhyay, Sourav; Goga, Andrei; Yosef, Nir; Nomura, Daniel K

    2016-08-19

    Many mechanisms have been proposed for how heightened aerobic glycolytic metabolism fuels cancer pathogenicity, but there are still many unexplored pathways. Here, we have performed metabolomic profiling to map glucose incorporation into metabolic pathways upon transformation of mammary epithelial cells by 11 commonly mutated human oncogenes. We show that transformation of mammary epithelial cells by oncogenic stimuli commonly shunts glucose-derived carbons into synthesis of sialic acid, a hexosamine pathway metabolite that is converted to CMP-sialic acid by cytidine monophosphate N-acetylneuraminic acid synthase (CMAS) as a precursor to glycoprotein and glycolipid sialylation. We show that CMAS knockdown leads to elevations in intracellular sialic acid levels, a depletion of cellular sialylation, and alterations in the expression of many cancer-relevant genes to impair breast cancer pathogenicity. Our study reveals the heretofore unrecognized role of sialic acid metabolism and protein sialylation in regulating the expression of genes that maintain breast cancer pathogenicity.

  9. Using epigenomics data to predict gene expression in lung cancer

    PubMed Central

    2015-01-01

    Background Epigenetic alterations are known to correlate with changes in gene expression among various diseases including cancers. However, quantitative models that accurately predict the up or down regulation of gene expression are currently lacking. Methods A new machine learning-based method of gene expression prediction is developed in the context of lung cancer. This method uses the Illumina Infinium HumanMethylation450K Beadchip CpG methylation array data from paired lung cancer and adjacent normal tissues in The Cancer Genome Atlas (TCGA) and histone modification marker CHIP-Seq data from the ENCODE project, to predict the differential expression of RNA-Seq data in TCGA lung cancers. It considers a comprehensive list of 1424 features spanning the four categories of CpG methylation, histone H3 methylation modification, nucleotide composition, and conservation. Various feature selection and classification methods are compared to select the best model over 10-fold cross-validation in the training data set. Results A best model comprising 67 features is chosen by ReliefF based feature selection and random forest classification method, with AUC = 0.864 from the 10-fold cross-validation of the training set and AUC = 0.836 from the testing set. The selected features cover all four data types, with histone H3 methylation modification (32 features) and CpG methylation (15 features) being most abundant. Among the dropping-off tests of individual data-type based features, removal of CpG methylation feature leads to the most reduction in model performance. In the best model, 19 selected features are from the promoter regions (TSS200 and TSS1500), highest among all locations relative to transcripts. Sequential dropping-off of CpG methylation features relative to different regions on the protein coding transcripts shows that promoter regions contribute most significantly to the accurate prediction of gene expression. Conclusions By considering a comprehensive list of

  10. Heme-related gene expression signatures of meat intakes in lung cancer tissues.

    PubMed

    Lam, Tram Kim; Rotunno, Melissa; Ryan, Brid M; Pesatori, Angela C; Bertazzi, Pier Alberto; Spitz, Margaret; Caporaso, Neil E; Landi, Maria Teresa

    2014-07-01

    Lung cancer causes more deaths worldwide than any other cancer. In addition to cigarette smoking, dietary factors may contribute to lung carcinogenesis. Epidemiologic studies, including the environment and genetics in lung cancer etiology (EAGLE), have reported increased consumption of red/processed meats to be associated with higher risk of lung cancer. Heme-iron toxicity may link meat intake with cancer. We investigated this hypothesis in meat-related lung carcinogenesis using whole genome expression. We measured genome-wide expression (HG-U133A) in 49 tumor and 42 non-involved fresh frozen lung tissues of 64 adenocarcinoma EAGLE patients. We studied gene expression profiles by high-versus-low meat consumption, with and without adjustment by sex, age, and smoking. Threshold for significance was a false discovery rate (FDR) ≤ 0.15. We studied whether the identified genes played a role in heme-iron related processes by means of manually curated literature search and gene ontology-based pathway analysis. We found that gene expression of 232 annotated genes in tumor tissue significantly distinguished lung adenocarcinoma cases who consumed above/below the median intake of fresh red meats (FDR = 0.12). Sixty-three (∼ 28%) of the 232 identified genes (12 expected by chance, P-value < 0.001) were involved in heme binding, absorption, transport, and Wnt signaling pathway (e.g., CYPs, TPO, HPX, HFE, SLCs, and WNTs). We also identified several genes involved in lipid metabolism (e.g., NCR1, TNF, and UCP3) and oxidative stress (e.g., TPO, SGK2, and MTHFR) that may be indirectly related to heme-toxicity. The study's results provide preliminary evidence that heme-iron toxicity might be one underlying mechanism linking fresh red meat intake and lung cancer.

  11. 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.

  12. Blood-Based Gene Expression Signatures of Autistic Infants and Toddlers

    PubMed Central

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

    2013-01-01

    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 autism have yet emerged. Method Using a community-based, prospective, longitudinal method, we identified 60 infants and toddlers at-risk for ASDs (autistic disorder and pervasive developmental disorder), 34 at-risk for language delay (LD), 17 at-risk for global developmental delay (DD), and 68 typically developing (TD) comparison children. Diagnoses were confirmed via longitudinal follow-up. Each child's mRNA expression profile in peripheral blood mononuclear cells (PBMCs) was determined by microarray. Results Potential ASD biomarkers were discovered in one half of the sample and used to build a classifier with high diagnostic accuracy in the remaining half of the sample. Conclusions The mRNA expression abnormalities reliably observed in PBMCs, which are safely and easily assayed in babies, offer the first potential peripheral blood-based early biomarker panel of risk for autism in infants and toddlers. Future work should verify these biomarkers and evaluate if they may also serve as indirect indices of deviant molecular neural mechanisms in autism. PMID:22917206

  13. 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

  14. Alternate virtual populations elucidate the type I interferon signature predictive of the response to rituximab in rheumatoid arthritis

    PubMed Central

    2013-01-01

    Background Mechanistic biosimulation can be used in drug development to form testable hypotheses, develop predictions of efficacy before clinical trial results are available, and elucidate clinical response to therapy. However, there is a lack of tools to simultaneously (1) calibrate the prevalence of mechanistically distinct, large sets of virtual patients so their simulated responses statistically match phenotypic variability reported in published clinical trial outcomes, and (2) explore alternate hypotheses of those prevalence weightings to reflect underlying uncertainty in population biology. Here, we report the development of an algorithm, MAPEL (Mechanistic Axes Population Ensemble Linkage), which utilizes a mechanistically-based weighting method to match clinical trial statistics. MAPEL is the first algorithm for developing weighted virtual populations based on biosimulation results that enables the rapid development of an ensemble of alternate virtual population hypotheses, each validated by a composite goodness-of-fit criterion. Results Virtual patient cohort mechanistic biosimulation results were successfully calibrated with an acceptable composite goodness-of-fit to clinical populations across multiple therapeutic interventions. The resulting virtual populations were employed to investigate the mechanistic underpinnings of variations in the response to rituximab. A comparison between virtual populations with a strong or weak American College of Rheumatology (ACR) score in response to rituximab suggested that interferon β (IFNβ) was an important mechanistic contributor to the disease state, a signature that has previously been identified though the underlying mechanisms remain unclear. Sensitivity analysis elucidated key anti-inflammatory properties of IFNβ that modulated the pathophysiologic state, consistent with the observed prognostic correlation of baseline type I interferon measurements with clinical response. Specifically, the effects of IFN

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

    PubMed

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

    2014-01-01

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

  16. 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.

  17. 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.

  18. Gene expression signature in peripheral blood cells from medical students exposed to chronic psychological stress.

    PubMed

    Kawai, Tomoko; Morita, Kyoko; Masuda, Kiyoshi; Nishida, Kensei; Shikishima, Michiyo; Ohta, Masayuki; Saito, Toshiro; Rokutan, Kazuhito

    2007-10-01

    To assess response to chronic psychological stress, gene expression profiles in peripheral blood from 18 medical students confronting license examination were analyzed using an original microarray. Total RNA was collected from each subject 9 months before the examination and mixed to be used as a universal control. At that time, most students had normal scores on the state-trait anxiety inventory (STAI). However, STAI scores were significantly elevated at 2 months and at 2 days before the examination. Pattern of the gene expression profile was more uniform 2 days before than 2 months before the examination. We identified 24 genes that significantly and uniformly changed from the universal control 2 days before the examination. Of the 24 genes, real-time PCR validated changes in mRNA levels of 10 (PLCB2, CSF3R, ARHGEF1, DPYD, CTNNB1, PPP3CA, POLM, IRF3, TP53, and CCNI). The identified genes may be useful to assess chronic psychological stress response.

  19. 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.

  20. 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

  1. MicroRNA expression signature and the therapeutic effect of the microRNA-21 antagomir in hypertrophic scarring

    PubMed Central

    Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng; Wang, Tao; Chai, Linlin; Xu, Guozheng

    2017-01-01

    Hypertrophic scars (HS) area fibroproliferative disorder of the skin, which causes aesthetic and functional impairment. However, the molecular pathogenesis of this disease remains largely unknown and currently no efficient treatment exists. MicroRNAs (miRNAs) are involved in a variety of pathophysiological processes, however the role of miRNAs in HS development remains unclear. To investigate the miRNA expression signature of HS, microarray analysis was performed and 152 miRNAs were observed to be differentially expressed in HS tissue compared with normal skin tissues. Of the miRNAs identified, miRNA-21 (miR-21) was significantly increased in HS tissues and hypertrophic scar fibroblasts (HSFBs) as determined by reverse transcription-quantitative polymerase chain reaction analysis. It was also observed that, when miR-21 in HSFBs was blocked through use of an antagomir, the phenotype of fibrotic fibroblasts in vitro was reversed, as demonstrated by growth inhibition, induction of apoptosis and suppressed expression of fibrosis-associated genes collagen type I α 1 chain (COL1A1), COL1A2 and fibronectin. Furthermore, miR-21 antagomir administration significantly reduced the severity of HS formation and decreased collagen deposition in a rabbit ear HS model. The total scar area and scar elevation index were calculated and were demonstrated to be significantly decreased in the treatment group compared with control rabbits. These results indicated that the miR-21 antagomir has a therapeutic effect on HS and suggests that targeting miRNAs may be a successful and novel therapeutic strategy in the treatment of fibrotic diseases that are difficult to treat with existing methods. PMID:28075443

  2. EP300-ZNF384 fusion gene product up-regulates GATA3 gene expression and induces hematopoietic stem cell gene expression signature in B-cell precursor acute lymphoblastic leukemia cells.

    PubMed

    Yaguchi, Akinori; Ishibashi, Takeshi; Terada, Kazuki; Ueno-Yokohata, Hitomi; Saito, Yuya; Fujimura, Junya; Shimizu, Toshiaki; Ohki, Kentaro; Manabe, Atsushi; Kiyokawa, Nobutaka

    2017-04-04

    ZNF384-related fusion genes are associated with a distinct subgroup of B-cell precursor acute lymphoblastic leukemias in childhood, with a frequency of approximately 3-4%. We previously identified a novel EP300-ZNF384 fusion gene. Patients with the ZNF384-related fusion gene exhibit a hematopoietic stem cell (HSC) gene expression signature and characteristic immunophenotype with negative or low expression of CD10 and aberrant expression of myeloid antigens, such as CD33 and CD13. However, the molecular basis of this pathogenesis remains completely unknown. In the present study, we examined the biological effects of EP300-ZNF384 expression induced by retrovirus-mediated gene transduction in an REH B-cell precursor acute lymphoblastic leukemia cell line, and observed the acquisition of the HSC gene expression signature and an up-regulation of GATA3 gene expression, as assessed by microarray analysis. In contrast, the gene expression profile induced by wild-type ZNF384 in REH cells was significantly different from that by EP300-ZNF384 expression. Together with the results of reporter assays, which revealed the enhancement of GATA3-promoter activity by EP300-ZNF384 expression, these findings suggest that EP300-ZNF384 mediates GATA3 gene expression and may be involved in the acquisition of the HSC gene expression signature and characteristic immunophenotype in B-cell precursor acute lymphoblastic leukemia cells.

  3. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures

    PubMed Central

    Wirapati, Pratyaksha; Sotiriou, Christos; Kunkel, Susanne; Farmer, Pierre; Pradervand, Sylvain; Haibe-Kains, Benjamin; Desmedt, Christine; Ignatiadis, Michail; Sengstag, Thierry; Schütz, Frédéric; Goldstein, Darlene R; Piccart, Martine; Delorenzi, Mauro

    2008-01-01

    Introduction Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. Method To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. Results Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. Conclusion

  4. 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.

  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. Expression signature of lncRNAs and their potential roles in cardiac fibrosis of post-infarct mice

    PubMed Central

    Qu, Xuefeng; Song, Xiaotong; Yuan, Wei; Shu, You; Wang, Yuying; Zhao, Xuyun; Gao, Ming; Lu, Renzhong; Luo, Shenjian; Zhao, Wei; Zhang, Yue; Sun, Lihua; Lu, Yanjie

    2016-01-01

    The present study aimed to investigate whether long non-coding RNAs (lncRNAs) are involved in cardiac fibrogenesis induced by myocardial infarction (MI). The differentially expressed lncRNAs and mRNAs in peri-infarct region of mice 4 weeks after MI were selected for bioinformatic analysis including gene ontology (GO) enrichment, pathway and network analysis. Left ventricular tissue levels of lncRNAs and mRNAs were compared between MI and sham control mice, using a false discovery rate (FDR) of <5%. Out of 55000 lncRNAs detected, 263 were significantly up-regulated and 282 down-regulated. Out of 23000 mRNAs detected, 142 were significantly up-regulated and 67 down-regulated. Among the differentially expressed lncRNAs, 53 were up-regulated by ≥2.0-fold change and 37 down-regulated by ≤0.5-fold change. Nine up-regulated and five down-regulated lncRNAs were randomly selected for quantitative real-time PCR (qRT-PCR) verification. GO and pathway analyses revealed 173 correlated lncRNA–mRNA pairs for 57 differentially expressed lncRNAs and 20 differentially expressed genes which are related to the development of cardiac fibrosis. We identified TGF-β3 as the top-ranked gene, a critical component of the transforming growth factor-β (TGF-β) and mitogen activated protein kinase (MAPK) signalling pathways in cardiac fibrosis. NONMMUT022554 was identified as the top-ranked lncRNA, positively correlated with six up-regulated genes, which are involved in the extracellular matrix (ECM)–receptor interactions and the phosphoinositid-3 kinase/protein kinase B (PI3K-Akt) signalling pathway. Our study has identified the expression signature of lncRNAs in cardiac fibrosis induced by MI and unravelled the possible involvement of the deregulated lncRNAs in cardiac fibrosis and the associated pathological processes. PMID:27129287

  7. 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.

  8. Gene expression signature based screening identifies ribonucleotide reductase as a candidate therapeutic target in Ewing sarcoma

    PubMed Central

    Goss, Kelli L.; Gordon, David J.

    2016-01-01

    There is a critical need in cancer therapeutics to identify targeted therapies that will improve outcomes and decrease toxicities compared to conventional, cytotoxic chemotherapy. Ewing sarcoma is a highly aggressive bone and soft tissue cancer that is caused by the EWS-FLI1 fusion protein. Although EWS-FLI1 is specific for cancer cells, and required for tumorigenesis, directly targeting this transcription factor has proven challenging. Consequently, targeting unique dependencies or key downstream mediators of EWS-FLI1 represent important alternative strategies. We used gene expression data derived from a genetically defined model of Ewing sarcoma to interrogate the Connectivity Map and identify a class of drugs, iron chelators, that downregulate a significant number of EWS-FLI1 target genes. We then identified ribonucleotide reductase M2 (RRM2), the iron-dependent subunit of ribonucleotide reductase (RNR), as one mediator of iron chelator toxicity in Ewing sarcoma cells. Inhibition of RNR in Ewing sarcoma cells caused apoptosis in vitro and attenuated tumor growth in an in vivo, xenograft model. Additionally, we discovered that the sensitivity of Ewing sarcoma cells to inhibition or suppression of RNR is mediated, in part, by high levels of SLFN11, a protein that sensitizes cells to DNA damage. This work demonstrates a unique dependency of Ewing sarcoma cells on RNR and supports further investigation of RNR inhibitors, which are currently used in clinical practice, as a novel approach for treating Ewing sarcoma. PMID:27557498

  9. Molecular Signature of HPV-Induced Carcinogenesis: pRb, p53 and Gene Expression Profiling

    PubMed Central

    Buitrago-Pérez, Águeda; Garaulet, Guillermo; Vázquez-Carballo, Ana; Paramio, Jesús M; García-Escudero, Ramón

    2009-01-01

    The infection by mucosal human papillomavirus (HPV) is causally associated with tumor development in cervix and oropharynx. The mechanisms responsible for this oncogenic potential are mainly due to the product activities of two early viral oncogenes: E6 and E7. Although a large number of cellular targets have been described for both oncoproteins, the interaction with tumor suppressors p53 and retinoblastoma protein (pRb) emerged as the key functional activities. E6 degrades tumor suppressor p53, thus inhibiting p53-dependent functions, whereas E7 binds and degrades pRb, allowing the transcription of E2F-dependent genes. Since these two tumor suppressors exert their actions through transcriptional modulation, functional genomics has provided a large body of data that reflects the altered gene expression of HPVinfected cells or tissues. Here we will review the similarities and differences of these findings, and we also compare them with those obtained with transgenic mouse models bearing the deletion of some of the viral oncogene targets. The comparative analysis supports molecular evidences about the role of oncogenes E6 and E7 in the interference with the mentioned cellular functions, and also suggests that the mentioned transgenic mice can be used as models for HPV-associated diseases such as human cervical, oropharynx, and skin carcinomas. PMID:19721808

  10. Molecular Signature of HPV-Induced Carcinogenesis: pRb, p53 and Gene Expression Profiling.

    PubMed

    Buitrago-Pérez, Agueda; Garaulet, Guillermo; Vázquez-Carballo, Ana; Paramio, Jesús M; García-Escudero, Ramón

    2009-03-01

    The infection by mucosal human papillomavirus (HPV) is causally associated with tumor development in cervix and oropharynx. The mechanisms responsible for this oncogenic potential are mainly due to the product activities of two early viral oncogenes: E6 and E7. Although a large number of cellular targets have been described for both oncoproteins, the interaction with tumor suppressors p53 and retinoblastoma protein (pRb) emerged as the key functional activities. E6 degrades tumor suppressor p53, thus inhibiting p53-dependent functions, whereas E7 binds and degrades pRb, allowing the transcription of E2F-dependent genes. Since these two tumor suppressors exert their actions through transcriptional modulation, functional genomics has provided a large body of data that reflects the altered gene expression of HPVinfected cells or tissues. Here we will review the similarities and differences of these findings, and we also compare them with those obtained with transgenic mouse models bearing the deletion of some of the viral oncogene targets. The comparative analysis supports molecular evidences about the role of oncogenes E6 and E7 in the interference with the mentioned cellular functions, and also suggests that the mentioned transgenic mice can be used as models for HPV-associated diseases such as human cervical, oropharynx, and skin carcinomas.

  11. 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

  12. An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer

    PubMed Central

    Weichselbaum, Ralph R.; Ishwaran, Hemant; Yoon, Taewon; Nuyten, Dimitry S. A.; Baker, Samuel W.; Khodarev, Nikolai; Su, Andy W.; Shaikh, Arif Y.; Roach, Paul; Kreike, Bas; Roizman, Bernard; Bergh, Jonas; Pawitan, Yudi; van de Vijver, Marc J.; Minn, Andy J.

    2008-01-01

    Individualization of cancer management requires prognostic markers and therapy-predictive markers. Prognostic markers assess risk of disease progression independent of therapy, whereas therapy-predictive markers identify patients whose disease is sensitive or resistant to treatment. We show that an experimentally derived IFN-related DNA damage resistance signature (IRDS) is associated with resistance to chemotherapy and/or radiation across different cancer cell lines. The IRDS genes STAT1, ISG15, and IFIT1 all mediate experimental resistance. Clinical analyses reveal that IRDS(+) and IRDS(−) states exist among common human cancers. In breast cancer, a seven–gene-pair classifier predicts for efficacy of adjuvant chemotherapy and for local-regional control after radiation. By providing information on treatment sensitivity or resistance, the IRDS improves outcome prediction when combined with standard markers, risk groups, or other genomic classifiers. PMID:19001271

  13. Gene expression signatures associated with suppression of TRAMP prostate carcinogenesis by a kavalactone-rich Kava fraction.

    PubMed

    Tang, Su-Ni; Zhang, Jinhui; Jiang, Peixin; Datta, Palika; Leitzman, Pablo; O'Sullivan, M Gerard; Jiang, Cheng; Xing, Chengguo; Lü, Junxuan

    2016-12-01

    Kava (Piper methysticum Forster) extract and its major kavalactones have been shown to block chemically induced lung tumor initiation in mouse models. Here we evaluated the chemopreventive effect of a kavalactone-rich Kava fraction B (KFB), free of flavokavains, on carcinogenesis in a transgenic adenocarcinoma of mouse prostate (TRAMP) model and characterized the prostate gene expression signatures. Male C57BL/6 TRAMP mice were fed AIN93M diet with or without 0.4% KFB from 8 wk of age. Mice were euthanized at 16 or 28 wk. The growth of the dorsolateral prostate (DLP) lobes in KFB-treated TRAMP mice was inhibited by 66% and 58% at the respective endpoint. Anterior and ventral prostate lobes in KFB-treated TRAMP mice were suppressed by 40% and 49% at 28 wk, respectively. KFB consumption decreased cell proliferation biomarker Ki-67 and epithelial lesion severity in TRAMP DLP, without detectable apoptosis enhancement. Real time qRT-PCR detection of mRNA from DLP at 28 wk showed decreased expression of cell cycle regulatory genes congruent with Ki-67 suppression. Microarray profiling of DLP mRNA indicated that "oncogene-like" genes related to angiogenesis and cell proliferation were suppressed by KFB but tumor suppressor, immunity, muscle/neuro, and metabolism-related genes were upregulated by KFB in both TRAMP and WT DLP. TRAMP mice fed KFB diet developed lower incidence of neuroendocrine carcinomas (NECa) (2 out of 14 mice) than those fed the basal diet (8 out of 14 mice, χ(2)  = 5.6, P < 0.025). KFB may, therefore, inhibit not only TRAMP DLP epithelial lesions involving multiple molecular pathways, but also NECa. © 2016 Wiley Periodicals, Inc.

  14. 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 ...

  15. Expression Profiling of Mitochondrial Voltage-Dependent Anion Channel-1 Associated Genes Predicts Recurrence-Free Survival in Human Carcinomas

    PubMed Central

    Lim, Inja; Zhou, Tong; Bang, Hyoweon

    2014-01-01

    Background Mitochondrial voltage-dependent anion channels (VDACs) play a key role in mitochondria-mediated apoptosis. Both in vivo and in vitro evidences indicate that VDACs are actively involved in tumor progression. Specifically, VDAC-1, one member of the VDAC family, was thought to be a potential anti-cancer therapeutic target. Our previous study demonstrated that the human gene VDAC1 (encoding the VDAC-1 isoform) was significantly up-regulated in lung tumor tissue compared with normal tissue. Also, we found a significant positive correlation between the gene expression of VDAC1 and histological grade in breast cancer. However, the prognostic power of VDAC1 and its associated genes in human cancers is largely unknown. Methods We systematically analyzed the expression pattern of VDAC1 and its interacting genes in breast, colon, liver, lung, pancreatic, and thyroid cancers. The genes differentially expressed between normal and tumor tissues in human carcinomas were identified. Results The expression level of VDAC1 was uniformly up-regulated in tumor tissue compared with normal tissue in breast, colon, liver, lung, pancreatic, and thyroid cancers. Forty-four VDAC1 interacting genes were identified as being commonly differentially expressed between normal and tumor tissues in human carcinomas. We designated VDAC1 and the 44 dysregulated interacting genes as the VDAC1 associated gene signature (VAG). We demonstrate that the VAG signature is a robust prognostic biomarker to predict recurrence-free survival in breast, colon, and lung cancers, and is independent of standard clinical and pathological prognostic factors. Conclusions VAG represents a promising prognostic biomarker in human cancers, which may enhance prediction accuracy in identifying patients at higher risk for recurrence. Future therapies aimed specifically at VDAC1 associated genes may lead to novel agents in the treatment of cancer. PMID:25333947

  16. 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.

  17. Methylation of RAD51B, XRCC3 and other homologous recombination genes is associated with expression of immune checkpoints and an inflammatory signature in squamous cell carcinoma of the head and neck, lung and cervix

    PubMed Central

    Rieke, Damian T.; Ochsenreither, Sebastian; Klinghammer, Konrad; Seiwert, Tanguy Y.; Klauschen, Frederick; Tinhofer, Inge; Keilholz, Ulrich

    2016-01-01

    Immune checkpoints are emerging treatment targets, but mechanisms underlying checkpoint expression are poorly understood. Since alterations in DNA repair genes have been connected to the efficacy of checkpoint inhibitors, we investigated associations between methylation of DNA repair genes and CTLA4 and CD274 (PD-L1) expression. A list of DNA repair genes (179 genes) was selected from the literature, methylation status and expression of inflammation-associated genes (The Cancer Genome Atlas data) was correlated in head and neck squamous cell carcinoma (HNSCC), cervical and lung squamous cell carcinoma. A significant positive correlation of the methylation status of 15, 3 and 2 genes with checkpoint expression was identified, respectively. RAD51B methylation was identified in all cancer subtypes. In HNSCC and cervical cancer, there was significant enrichment for homologous recombination genes. Methylation of the candidate genes was also associated with expression of other checkpoints, ligands, MHC- and T-cell associated genes as well as an interferon-inflammatory immune gene signature, predictive for the efficacy of PD-1 inhibition in HNSCC. Homologous recombination deficiency might therefore be mediated by DNA repair gene hypermethylation and linked to an immune-evasive phenotype in SCC. The methylation status of these genes could represent a new predictive biomarker for immune checkpoint inhibition. PMID:27683114

  18. Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.

    PubMed

    Bing, Zhi-Tong; Yang, Guang-Hui; Xiong, Jie; Guo, Ling; Yang, Lei

    2016-12-01

    Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor in adults. Patients with this disease have a poor prognosis. The objective of this study is to identify survival-related individual genes (or miRNAs) and miRNA -mRNA pairs in GBM using a multi-step approach. First, the weighted gene co-expression network analysis and survival analysis are applied to identify survival-related modules from mRNA and miRNA expression profiles, respectively. Subsequently, the role of individual genes (or miRNAs) within these modules in GBM prognosis are highlighted using survival analysis. Finally, the integration analysis of miRNA and mRNA expression as well as miRNA target prediction is used to identify survival-related miRNA -mRNA regulatory network. In this study, five genes and two miRNA modules that significantly correlated to patient's survival. In addition, many individual genes (or miRNAs) assigned to these modules were found to be closely linked with survival. For instance, increased expression of neuropilin-1 gene (a member of module turquoise) indicated poor prognosis for patients and a group of miRNA -mRNA regulatory networks that comprised 38 survival-related miRNA -mRNA pairs. These findings provide a new insight into the underlying molecular regulatory mechanisms of GBM.

  19. Unique long non-coding RNA expression signature in ETV6/RUNX1-driven B-cell precursor acute lymphoblastic leukemia

    PubMed Central

    Ghazavi, Farzaneh; Moerloose, Barbara De; Loocke, Wouter Van; Wallaert, Annelynn; Helsmoortel, Hetty H.; Ferster, Alina; Bakkus, Marleen; Plat, Geneviève; Delabesse, Eric; Uyttebroeck, Anne; Nieuwerburgh, Filip Van; Deforce, Dieter; Roy, Nadine Van; Speleman, Frank; Benoit, Yves

    2016-01-01

    Overwhelming evidence indicates that long non-coding RNAs have essential roles in tumorigenesis. Nevertheless, their role in the molecular pathogenesis of pediatric B-cell precursor acute lymphoblastic leukemia has not been extensively explored. Here, we conducted a comprehensive analysis of the long non-coding RNA transcriptome in ETV6/RUNX1-positive BCP-ALL, one of the most frequent subtypes of pediatric leukemia. First, we used primary leukemia patient samples to identify an ETV6/RUNX1 specific expression signature consisting of 596 lncRNA transcripts. Next, integration of this lncRNA signature with RNA sequencing of BCP-ALL cell lines and lncRNA profiling of an in vitro model system of ETV6/RUNX1 knockdown, revealed that lnc-NKX2-3-1, lnc-TIMM21-5, lnc-ASTN1-1 and lnc-RTN4R-1 are truly regulated by the oncogenic fusion protein. Moreover, sustained inactivation of lnc-RTN4R-1 and lnc-NKX2-3-1 in ETV6/RUNX1 positive cells caused profound changes in gene expression. All together, our study defined a unique lncRNA expression signature associated with ETV6/RUNX1-positive BCP-ALL and identified lnc-RTN4R-1 and lnc-NKX2-3-1 as lncRNAs that might be functionally implicated in the biology of this prevalent subtype of human leukemia. PMID:27650541

  20. 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

  1. Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.

    PubMed

    Bhatlekar, Seema; Addya, Sankar; Salunek, Moreh; Orr, Christopher R; Surrey, Saul; McKenzie, Steven; Fields, Jeremy Z; Boman, Bruce M

    2014-01-15

    Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis.

  2. Prognostic value of a 92-probe signature in breast cancer.

    PubMed

    Akter, Salima; Choi, Tae Gyu; Nguyen, Minh Nam; Matondo, Abel; Kim, Jin-Hwan; Jo, Yong Hwa; Jo, Ara; Shahid, Muhammad; Jun, Dae Young; Yoo, Ji Youn; Nguyen, Ngoc Ngo Yen; Seo, Seong-Wook; Ali, Liaquat; Lee, Ju-Seog; Yoon, Kyung-Sik; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Jayoung; Kim, Sung Soo

    2015-06-20

    Clinical applications of gene expression signatures in breast cancer prognosis still remain limited due to poor predictive strength of single training datasets and appropriate invariable platforms. We proposed a gene expression signature by reducing baseline differences and analyzing common probes among three recent Affymetrix U133 plus 2 microarray data sets. Using a newly developed supervised method, a 92-probe signature found in this study was associated with overall survival. It was robustly validated in four independent data sets and then repeated on three subgroups by incorporating 17 breast cancer microarray datasets. The signature was an independent predictor of patients' survival in univariate analysis [(HR) 1.927, 95% CI (1.237-3.002); p < 0.01] as well as multivariate analysis after adjustment of clinical variables [(HR) 7.125, 95% CI (2.462-20.618); p < 0.001]. Consistent predictive performance was found in different multivariate models in increased patient population (p = 0.002). The survival signature predicted a late metastatic feature through 5-year disease free survival (p = 0.006). We identified subtypes within the lymph node positive (p < 0.001) and ER positive (p = 0.01) patients that best reflected the invasive breast cancer biology. In conclusion using the Common Probe Approach, we present a novel prognostic signature as a predictor in breast cancer late recurrences.

  3. Ion signatures of magnetic flux ropes in the Venusian ionosphere as observed by APSERA-4 and MAG onboard Venus Express

    NASA Astrophysics Data System (ADS)

    Guymer, G.; Grande, M.; Whittaker, I.

    2008-09-01

    Abstract Venus has a negligible intrinsic magnetic moment with an upper limit a factor 10-5 of earth's [1]. This entails that the ionosphere is vulnerable to scavenging by the solar wind. However, magnetic fields may be induced in the ionosphere by interaction with the interplanetary magnetic field frozen-in to the solar wind. The presence of small scale magnetic structures in the dayside ionosphere of the planet Venus has been long established and were first observed in Pioneer Venus Orbiter (PVO) data in 1979 [2] during the run up to solar maximum. These ionospheric `flux ropes' were observed in over 70% of passes in which the orbit of PVO intersected the dayside ionosphere [3]. Magnetic flux ropes are identified as brief, discrete disturbances from any background magnetic field, lasting a few seconds with a magnitude of up to many 10's of nano-Teslas in strength [3, 4]. Flux ropes have a strong central, axial field, that is wrapped with field lines of weakening strength and increased helical angle with distance from the central field lines [4]. Due to this particular structure, flux ropes present a specific signature in the three variance projections (also known as a hodogram) when minimum variance analysis is applied to the magnetic data set [2]. With Venus Express now in operational orbit around the planet, flux ropes are being observed in the data retrieved by the magnetometers (MAG [5]) onboard. The magnetic data used in this analysis is the 1Hz data set provided by H. Wei (of UCLA). Variance projections have been produced for several structures in 2006, revealing them to be flux ropes (see figure 1). Using the Ion Mass Analyser (IMA; part of the ASPERA-4 package [6]) and MAG, the ion composition within the ropes and the effect of such magnetic structures upon ionospheric erosion is being studied. Where flux ropes have been evident in the magnetic data, ion spectra have been produced in an attempt to deduce any compositional differences between a flux rope

  4. Specific regulatory motifs predict glucocorticoid responsiveness of hippocampal gene expression.

    PubMed

    Datson, N A; Polman, J A E; de Jonge, R T; van Boheemen, P T M; van Maanen, E M T; Welten, J; McEwen, B S; Meiland, H C; Meijer, O C

    2011-10-01

    The glucocorticoid receptor (GR) is an ubiquitously expressed ligand-activated transcription factor that mediates effects of cortisol in relation to adaptation to stress. In the brain, GR affects the hippocampus to modulate memory processes through direct binding to glucocorticoid response elements (GREs) in the DNA. However, its effects are to a high degree cell specific, and its target genes in different cell types as well as the mechanisms conferring this specificity are largely unknown. To gain insight in hippocampal GR signaling, we characterized to which GRE GR binds in the rat hippocampus. Using a position-specific scoring matrix, we identified evolutionary-conserved putative GREs from a microarray based set of hippocampal target genes. Using chromatin immunoprecipitation, we were able to confirm GR binding to 15 out of a selection of 32 predicted sites (47%). The majority of these 15 GREs are previously undescribed and thus represent novel GREs that bind GR and therefore may be functional in the rat hippocampus. GRE nucleotide composition was not predictive for binding of GR to a GRE. A search for conserved flanking sequences that may predict GR-GRE interaction resulted in the identification of GC-box associated motifs, such as Myc-associated zinc finger protein 1, within 2 kb of GREs with GR binding in the hippocampus. This enrichment was not present around nonbinding GRE sequences nor around proven GR-binding sites from a mesenchymal stem-like cell dataset that we analyzed. GC-binding transcription factors therefore may be unique partners for DNA-bound GR and may in part explain cell-specific transcriptional regulation by glucocorticoids in the context of the hippocampus.

  5. Signature control

    NASA Astrophysics Data System (ADS)

    Pyati, Vittal P.

    The reduction of vehicle radar signature is accomplished by means of vehicle shaping, the use of microwave frequencies-absorbent materials, and either passive or active cancellation techniques; such techniques are also useful in the reduction of propulsion system-associated IR emissions. In some anticipated scenarios, the objective is not signature-reduction but signature control, for deception, via decoy vehicles that mimic the signature characteristics of actual weapons systems. As the stealthiness of airframes and missiles increases, their propulsion systems' exhaust plumes assume a more important role in detection by an adversary.

  6. PDL1 expression in inflammatory breast cancer is frequent and predicts for the pathological response to chemotherapy.

    PubMed

    Bertucci, François; Finetti, Pascal; Colpaert, Cécile; Mamessier, Emilie; Parizel, Maxime; Dirix, Luc; Viens, Patrice; Birnbaum, Daniel; van Laere, Steven

    2015-05-30

    We retrospectively analyzed PDL1 mRNA expression in 306 breast cancer samples, including 112 samples of an aggressive form, inflammatory breast cancer (IBC). PDL1 expression was heterogeneous, but was higher in IBC than in non-IBC. Compared to normal breast samples, PDL1 was overexpressed in 38% of IBC. In IBC, PDL1 overexpression was associated with estrogen receptor-negative status, basal and ERBB2-enriched aggressive subtypes, and clinico-biological signs of anti-tumor T-cell cytotoxic response. PDL1 overexpression was associated with better pathological response to chemotherapy, independently of histo-clinical variables and predictive gene expression signatures. No correlation was found with metastasis-free and overall specific survivals. In conclusion, PDL1 overexpression in IBC correlated with better response to chemotherapy. This seemingly counterintuitive correlation between expression of an immunosuppressive molecule and improved therapeutic response may be resolved if PDL1 expression is viewed as a surrogate marker of a strong antitumor immune response among patients treated with immunogenic chemotherapy. In such patients, PDL1 inhibition could protect activated T-cells or reactivate inhibited T-cells and improve the therapeutic response, notably when associated with immunogenic chemotherapy.

  7. PDL1 expression in inflammatory breast cancer is frequent and predicts for the pathological response to chemotherapy

    PubMed Central

    Bertucci, François; Finetti, Pascal; Colpaert, Cécile; Mamessier, Emilie; Parizel, Maxime; Dirix, Luc; Viens, Patrice; Birnbaum, Daniel; van Laere, Steven

    2015-01-01

    We retrospectively analyzed PDL1 mRNA expression in 306 breast cancer samples, including 112 samples of an aggressive form, inflammatory breast cancer (IBC). PDL1 expression was heterogeneous, but was higher in IBC than in non-IBC. Compared to normal breast samples, PDL1 was overexpressed in 38% of IBC. In IBC, PDL1 overexpression was associated with estrogen receptor-negative status, basal and ERBB2-enriched aggressive subtypes, and clinico-biological signs of anti-tumor T-cell cytotoxic response. PDL1 overexpression was associated with better pathological response to chemotherapy, independently of histo-clinical variables and predictive gene expression signatures. No correlation was found with metastasis-free and overall specific survivals. In conclusion, PDL1 overexpression in IBC correlated with better response to chemotherapy. This seemingly counterintuitive correlation between expression of an immunosuppressive molecule and improved therapeutic response may be resolved if PDL1 expression is viewed as a surrogate marker of a strong antitumor immune response among patients treated with immunogenic chemotherapy. In such patients, PDL1 inhibition could protect activated T-cells or reactivate inhibited T-cells and improve the therapeutic response, notably when associated with immunogenic chemotherapy. PMID:25940795

  8. Discriminating Gene Expression Signature of Radiation-Induced Thyroid Tumors after Either External Exposure or Internal Contamination

    PubMed Central

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

    2011-01-01

    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. PMID:24704841

  9. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

    PubMed

    Yeoh, Eng-Juh; Ross, Mary E; Shurtleff, Sheila A; Williams, W Kent; Patel, Divyen; Mahfouz, Rami; Behm, Fred G; Raimondi, Susana C; Relling, Mary V; Patel, Anami; Cheng, Cheng; Campana, Dario; Wilkins, Dawn; Zhou, Xiaodong; Li, Jinyan; Liu, Huiqing; Pui, Ching-Hon; Evans, William E; Naeve, Clayton; Wong, Limsoon; Downing, James R

    2002-03-01

    Treatment of pediatric acute lymphoblastic leukemia (ALL) is based on the concept of tailoring the intensity of therapy to a patient's risk of relapse. To determine whether gene expression profiling could enhance risk assignment, we used oligonucleotide microarrays to analyze the pattern of genes expressed in leukemic blasts from 360 pediatric ALL patients. Distinct expression profiles identified each of the prognostically important leukemia subtypes, including T-ALL, E2A-PBX1, BCR-ABL, TEL-AML1, MLL rearrangement, and hyperdiploid >50 chromosomes. In addition, another ALL subgroup was identified based on its unique expression profile. Examination of the genes comprising the expression signatures provided important insights into the biology of these leukemia subgroups. Further, within some genetic subgroups, expression profiles identified those patients that would eventually fail therapy. Thus, the single platform of expression profiling should enhance the accurate risk stratification of pediatric ALL patients.

  10. 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.

  11. CD30 expression defines a novel subgroup of diffuse large B-cell lymphoma with favorable prognosis and distinct gene expression signature: a report from the International DLBCL Rituximab-CHOP Consortium Program Study

    PubMed Central

    Hu, Shimin; Xu-Monette, Zijun Y.; Balasubramanyam, Aarthi; Manyam, Ganiraju C.; Visco, Carlo; Tzankov, Alexander; Liu, Wei-min; Miranda, Roberto N.; Zhang, Li; Montes-Moreno, Santiago; Dybkær, Karen; Chiu, April; Orazi, Attilio; Zu, Youli; Bhagat, Govind; Richards, Kristy L.; Hsi, Eric D.; Choi, William W. L.; Han van Krieken, J.; Huang, Qin; Huh, Jooryung; Ai, Weiyun; Ponzoni, Maurilio; Ferreri, Andrés J. M.; Zhao, Xiaoying; Winter, Jane N.; Zhang, Mingzhi; Li, Ling; Møller, Michael B.; Piris, Miguel A.; Li, Yong; Go, Ronald S.; Wu, Lin; Medeiros, L. Jeffrey; Young, Ken H.

    2013-01-01

    CD30, originally identified as a cell-surface marker of Reed-Sternberg and Hodgkin cells of classical Hodgkin lymphoma, is also expressed by several types of non-Hodgkin lymphoma, including a subset of diffuse large B-cell lymphoma (DLBCL). However, the prognostic and biological importance of CD30 expression in DLBCL is unknown. Here we report that CD30 expression is a favorable prognostic factor in a cohort of 903 de novo DLBCL patients. CD30 was expressed in ∼14% of DLBCL patients. Patients with CD30+ DLBCL had superior 5-year overall survival (CD30+, 79% vs CD30–, 59%; P = .001) and progression-free survival (P = .003). The favorable outcome of CD30 expression was maintained in both the germinal center B-cell and activated B-cell subtypes. Gene expression profiling revealed the upregulation of genes encoding negative regulators of nuclear factor κB activation and lymphocyte survival, and downregulation of genes encoding B-cell receptor signaling and proliferation, as well as prominent cytokine and stromal signatures in CD30+ DLBCL patients, suggesting a distinct molecular basis for its favorable outcome. Given the superior prognostic value, unique gene expression signature, and significant value of CD30 as a therapeutic target for brentuximab vedotin in ongoing successful clinical trials, it seems appropriate to consider CD30+ DLBCL as a distinct subgroup of DLBCL. PMID:23343832

  12. CCR 20th Anniversary Commentary: Gene-Expression Signature in Breast Cancer--Where Did It Start and Where Are We Now?

    PubMed

    Gingras, Isabelle; Desmedt, Christine; Ignatiadis, Michail; Sotiriou, Christos

    2015-11-01

    Desmedt and colleagues published two articles, one in the June 1, 2007 issue, and the other in the August 15, 2008, issue of Clinical Cancer Research, that showed gene-expression signatures to be proliferation driven and time dependent, with their prognostic power decreasing with increasing follow-up years. Moreover, the articles showed that immune response is a crucial determinant of prognosis in the HER2-positive and estrogen receptor-negative/HER2-negative subtypes, providing a rationale to further explore the role of the antitumor immune response in these breast cancer subtypes.

  13. Improved Grading and Survival Prediction of human astrocytic brain tumours by artificial neural network analysis of gene expression microarray data

    PubMed Central

    Petalidis, Lawrence P.; Oulas, Anastasis; Backlund, Magnus; Wayland, Matthew T.; Liu, Lu; Plant, Karen; Happerfield, Lisa; Freeman, Tom C.; Poirazi, Panayiota; Collins, V. Peter

    2010-01-01

    Histopathological grading of astrocytic tumours based on current WHO criteria offers a valuable but simplified representation of oncological reality and is often insufficient to predict clinical outcome. In this study we report a new astrocytic tumour microarray gene expression dataset (n=65). We have used a simple Artificial Neural Network (ANN) algorithm to address grading of human astrocytic tumours, derive specific transcriptional signatures from histopathological subtypes of astrocytic tumours and asses whether these molecular signatures define survival prognostic subclasses. 59 classifier genes were identified and found to fall within three distinct functional classes namely angiogenesis, cell differentiation and lower grade astrocytic tumour discrimination. These gene classes were found to characterize three molecular tumour subtypes denoted ANGIO, INTER and LOWER. Grading of samples using these subtypes agreed with prior histopathological grading both for our dataset (96.15%) as well as an independent dataset. Six tumours were particularly challenging to diagnose histopathologically. We present an ANN grading for these samples, and offer an evidence-based interpretation of grading results using clinical metadata to substantiate findings. The prognostic value of the three identified tumour subtypes was found to outperform histopathological grading as well as tumour subtypes reported in other studies, indicating a high survival prognostic potential for the 59 gene classifiers. Finally, 11 gene classifiers that differentiate between primary and secondary glioblastomas were also identified. PMID:18445660

  14. Blood-based gene expression signatures of medication-free outpatients with major depressive disorder: integrative genome-wide and candidate gene analyses.

    PubMed

    Hori, Hiroaki; Sasayama, Daimei; Teraishi, Toshiya; Yamamoto, Noriko; Nakamura, Seiji; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

    2016-01-05

    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.

  15. 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

  16. Prognostic Value of microRNA Signature in Patients with Gastric Cancers

    PubMed Central

    Liu, Hai-Ting; Wang, Ya-Wen; Xing, Ai-Yan; Shi, Duan-Bo; Zhang, Hui-; Guo, Xiang-Yu; Xu, Jing-; Gao, Peng

    2017-01-01

    The occurrence of lymph node metastases (LNM) after endoscopic submucosal dissection (ESD) in patients with gastric cancer (GC) leads to poor prognosis. However, few biomarkers are available to predict LNM in GC patients. Thus, we measured expression of 6 cancer-related miRNAs using real-time RT-PCR in 102 GC samples that were randomized into a training set and a testing set (each, 51 cases). Using logistic regression, we identified 4-miRNA (miR-27b, miR-128, miR-100 and miR-214) signatures for predicting LNM in GC patients. Patients with high-risk scores for the 4-miRNA signature tended to have higher LNM than those with low-risk scores. Meanwhile, the ROC curve of the 4-miRNA signature was better for predicting LNM in GC patients. In addition, Cox regression analysis indicated that a 2-miRNA signature (miR-27b and miR-214) or a miR-214/N stage signature was predictive of survival for GC patients. This work describes a previously unrecognized 4-miRNA signature involved in LNM and a 2-miRNA signature or miR-214/N stage signature related to GC patients’ survival. PMID:28202938

  17. 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

  18. A Multi-Factorial Signature of DNA Sequence and Polycomb Binding Predicts Aberrant CpG Island Methylation

    PubMed Central

    McCabe, Michael T.; Lee, Eva K.; Vertino, Paula M.

    2008-01-01

    Aberrant CpG island methylation is associated with transcriptional silencing of regulatory genes in human cancer. While most CpG islands remain unmethylated, a subset accrues aberrant methylation in cancer via unknown mechanisms. Previously, we showed that CpG islands differ in their intrinsic propensity towards hypermethylation. We developed a classifier (PatMAn) based on the frequencies of seven DNA sequence patterns that discriminated methylation-prone (MP) and methylation-resistant (MR) CpG islands. Here we report on the genome-wide application and direct testing of PatMAn in cancer. Although trained on data from a cell culture model of de novo methylation involving overexpression of DNMT1, PatMAn accurately predicted CpG islands at increased risk of hypermethylation in cancer cell lines and primary tumors. Analysis of CpG islands predicted to be MP revealed a strong association with embryonic targets of Polycomb Repressive Complex 2 (PRC2), indicating that PatMAn predicts not only aberrant methylation, but also PRC2 binding. A second classifier (SUPER-PatMAn) that integrates the seven PatMAn DNA patterns with SUZ12 protein enriched regions as a marker of PRC2 occupancy showed improved performance (prediction accuracy=81-88%). In addition to many non-PRC2 targets, SUPER-PatMAn identified a subset of PRC2 targets that were more likely to be hypermethylated in cancer. Genome-wide, CpG islands predicted to be MP were enriched in genes known to undergo hypermethylation in cancer, genes functioning in transcriptional regulation, and components of developmental pathways. These findings demonstrate that hypermethylation of certain gene loci is controlled in part by an underlying susceptibility influenced by both local sequence context and trans-acting factors. PMID:19118013

  19. Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function

    PubMed Central

    2010-01-01

    Background Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. Results Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental

  20. Theoretical prediction of nonlinear propagation effects on noise signatures generated by subsonic or supersonic propeller or rotor-blade tips

    NASA Technical Reports Server (NTRS)

    Barger, R. L.

    1980-01-01

    The nonlinear propagation equations for sound generated by a constant speed blade tip are presented. Propagation from a subsonic tip is treated as well as the various cases that can occur at supersonic speeds. Some computed examples indicate that the nonlinear theory correlates with experimental results better than linear theory for large amplitude waves. For swept tips that generate a wave with large amplitude leading expansion, the nonlinear theory predicts a cancellation effect that results in a significant reduction of both amplitude and impulse.

  1. Alexithymia, not autism, predicts poor recognition of emotional facial expressions.

    PubMed

    Cook, Richard; Brewer, Rebecca; Shah, Punit; Bird, Geoffrey

    2013-05-01

    Despite considerable research into whether face perception is impaired in autistic individuals, clear answers have proved elusive. In the present study, we sought to determine whether co-occurring alexithymia (characterized by difficulties interpreting emotional states) may be responsible for face-perception deficits previously attributed to autism. Two experiments were conducted using psychophysical procedures to determine the relative contributions of alexithymia and autism to identity and expression recognition. Experiment 1 showed that alexithymia correlates strongly with the precision of expression attributions, whereas autism severity was unrelated to expression-recognition ability. Experiment 2 confirmed that alexithymia is not associated with impaired ability to detect expression variation; instead, results suggested that alexithymia is associated with difficulties interpreting intact sensory descriptions. Neither alexithymia nor autism was associated with biased or imprecise identity attributions. These findings accord with the hypothesis that the emotional symptoms of autism are in fact due to co-occurring alexithymia and that existing diagnostic criteria may need to be revised.

  2. Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors

    PubMed Central

    Savelyeva, Natalia; McCann, Katy J.; Singh, Divya; Jones, Terry; Peel, Lailah; Breen, Michael S.; Ward, Matthew; Martin, Eva Garrido

    2016-01-01

    Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(−)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(−) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(−) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment. PMID:27462861

  3. Gene expression analysis of TIL rich HPV-driven head and neck tumors reveals a distinct B-cell signature when compared to HPV independent tumors.

    PubMed

    Wood, Oliver; Woo, Jeongmin; Seumois, Gregory; Savelyeva, Natalia; McCann, Katy J; Singh, Divya; Jones, Terry; Peel, Lailah; Breen, Michael S; Ward, Matthew; Garrido Martin, Eva; Sanchez-Elsner, Tilman; Thomas, Gareth; Vijayanand, Pandurangan; Woelk, Christopher H; King, Emma; Ottensmeier, Christian

    2016-08-30

    Human papilloma virus (HPV)-associated head and neck squamous cell carcinoma (HNSCC) has a better prognosis than it's HPV negative (HPV(-)) counterpart. This may be due to the higher numbers of tumor-infiltrating lymphocytes (TILs) in HPV positive (HPV(+)) tumors. RNA-Sequencing (RNA-Seq) was used to evaluate whether the differences in clinical behaviour simply reflect a numerical difference in TILs or whether there is a fundamental behavioural difference between TILs in these two settings. Thirty-nine HNSCC tumors were scored for TIL density by immunohistochemistry. After the removal of 16 TILlow tumors, RNA-Seq analysis was performed on 23 TILhigh/med tumors (HPV(+) n=10 and HPV(-) n=13). Using EdgeR, differentially expressed genes (DEG) were identified. Immune subset analysis was performed using Functional Analysis of Individual RNA-Seq/ Microarray Expression (FAIME) and immune gene RNA transcript count analysis. In total, 1,634 DEGs were identified, with a dominant immune signature observed in HPV(+) tumors. After normalizing the expression profiles to account for differences in B- and T-cell number, 437 significantly DEGs remained. A B-cell associated signature distinguished HPV(+) from HPV(-) tumors, and included the DEGs CD200, GGA2, ADAM28, STAG3, SPIB, VCAM1, BCL2 and ICOSLG; the immune signal relative to T-cells was qualitatively similar between TILs of both tumor cohorts. Our findings were validated and confirmed in two independent cohorts using TCGA data and tumor-infiltrating B-cells from additional HPV(+) HNSCC patients. A B-cell associated signal segregated tumors relative to HPV status. Our data suggests that the role of B-cells in the adaptive immune response to HPV(+) HNSCC requires re-assessment.

  4. CD24 Expression May Play a Role as a Predictive Indicator and a Modulator of Cisplatin Treatment Response in Head and Neck Squamous Cellular Carcinoma

    PubMed Central

    Modur, Vishnu; Joshi, Pooja; Nie, Daotai; Robbins, K. Thomas; Khan, Aziz U.; Rao, Krishna

    2016-01-01

    Platinum-based therapy is most often used to treat advanced cases of head and neck cancers, but only a small fraction of the patient population responds to cisplatin, with a median survival time of less than a year. Although gene signatures and molecular etiology of head and neck cancers have been previously described, none of them are predictive indicators of cisplatin treatment response in particular. Therefore, currently, there is a lack of clinically employable predictive indicators of the disease beyond HPV status to specifically predict patients' response to platinum-based therapy. It beckons a substantial effort to look for predictive indicators of cisplatin treatment response. In this regard, CD24 expression level appears to be a significant molecular phenotype of cisplatin-resistant residual cells in laryngeal carcinoma lines. CD24 expression level directly affects cisplatin sensitivity and affects the expression of critical apoptotic, stem and drug resistance genes. A relatively small retrospective patient tumor analysis suggests that CD24 high tumors go on to show an unfavorable response to cisplatin treatment. Overall, based on the strength of further analysis, CD24 presents a strong rationale to be utilized as a predictive indicator to stratify head and neck cancer patients for platinum-based therapy. It also provides a rationale for using CD24 as a therapeutic adjuvant target along with standard cisplatin therapy. PMID:27276062

  5. A cancer specific hypermethylation signature of the TERT promoter predicts biochemical relapse in prostate cancer: a retrospective cohort study.

    PubMed

    Castelo-Branco, Pedro; Leão, Ricardo; Lipman, Tatiana; Campbell, Brittany; Lee, Donghyun; Price, Aryeh; Zhang, Cindy; Heidari, Abolfazl; Stephens, Derek; Boerno, Stefan; Coelho, Hugo; Gomes, Ana; Domingos, Celia; Apolonio, Joana D; Schäfer, Georg; Bristow, Robert G; Schweiger, Michal R; Hamilton, Robert; Zlotta, Alexandre; Figueiredo, Arnaldo; Klocker, Helmut; Sültmann, Holger; Tabori, Uri

    2016-09-06

    The identification of new biomarkers to differentiate between indolent and aggressive prostate tumors is an important unmet need. We examined the role of THOR (TERT Hypermethylated Oncological Region) as a diagnostic and prognostic biomarker in prostate cancer (PCa).We analyzed THOR in common cancers using genome-wide methylation arrays. Methylation status of the whole TERT gene in benign and malignant prostate samples was determined by MeDIP-Seq. The prognostic role of THOR in PCa was assessed by pyrosequencing on discovery and validation cohorts from patients who underwent radical prostatectomy with long-term follow-up data.Most cancers (n = 3056) including PCa (n = 300) exhibited hypermethylation of THOR. THOR was the only region within the TERT gene that is differentially methylated between normal and malignant prostate tissue (p < 0.0001). Also, THOR was significantly hypermethylated in PCa when compared to paired benign tissues (n = 164, p < 0.0001). THOR hypermethylation correlated with Gleason scores and was associated with tumor invasiveness (p = 0.0147). Five years biochemical progression free survival (BPFS) for PCa patients in the discovery cohort was 87% (95% CI 73-100) and 65% (95% CI 52-78) for THOR non-hypermethylated and hypermethylated cancers respectively (p = 0.01). Similar differences in BPFS were noted in the validation cohort (p = 0.03). Importantly, THOR was able to predict outcome in the challenging (Gleason 6 and 7 (3 + 4)) PCa (p = 0.007). For this group, THOR was an independent risk factor for BPFS with a hazard-ratio of 3.685 (p = 0.0247). Finally, THOR hypermethylation more than doubled the risk of recurrence across all PSA levels (OR 2.5, p = 0.02).

  6. A cancer specific hypermethylation signature of the TERT promoter predicts biochemical relapse in prostate cancer: a retrospective cohort study

    PubMed Central

    Lipman, Tatiana; Campbell, Brittany; Lee, Donghyun; Price, Aryeh; Zhang, Cindy; Heidari, Abolfazl; Stephens, Derek; Boerno, Stefan; Coelho, Hugo; Gomes, Ana; Domingos, Celia; Apolonio, Joana D.; Schäfer, Georg; Bristow, Robert G.; Schweiger, Michal R.; Hamilton, Robert; Zlotta, Alexandre; Figueiredo, Arnaldo; Klocker, Helmut; Sültmann, Holger; Tabori, Uri

    2016-01-01

    The identification of new biomarkers to differentiate between indolent and aggressive prostate tumors is an important unmet need. We examined the role of THOR (TERT Hypermethylated Oncological Region) as a diagnostic and prognostic biomarker in prostate cancer (PCa). We analyzed THOR in common cancers using genome-wide methylation arrays. Methylation status of the whole TERT gene in benign and malignant prostate samples was determined by MeDIP-Seq. The prognostic role of THOR in PCa was assessed by pyrosequencing on discovery and validation cohorts from patients who underwent radical prostatectomy with long-term follow-up data. Most cancers (n = 3056) including PCa (n = 300) exhibited hypermethylation of THOR. THOR was the only region within the TERT gene that is differentially methylated between normal and malignant prostate tissue (p < 0.0001). Also, THOR was significantly hypermethylated in PCa when compared to paired benign tissues (n = 164, p < 0.0001). THOR hypermethylation correlated with Gleason scores and was associated with tumor invasiveness (p = 0.0147). Five years biochemical progression free survival (BPFS) for PCa patients in the discovery cohort was 87% (95% CI 73–100) and 65% (95% CI 52–78) for THOR non-hypermethylated and hypermethylated cancers respectively (p = 0.01). Similar differences in BPFS were noted in the validation cohort (p = 0.03). Importantly, THOR was able to predict outcome in the challenging (Gleason 6 and 7 (3 + 4)) PCa (p = 0.007). For this group, THOR was an independent risk factor for BPFS with a hazard-ratio of 3.685 (p = 0.0247). Finally, THOR hypermethylation more than doubled the risk of recurrence across all PSA levels (OR 2.5, p = 0.02). PMID:27437772

  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. MicroRNA Expression Profiling of Peripheral Blood Samples Predicts Resistance to First-line Sunitinib in Advanced Renal Cell Carcinoma Patients12

    PubMed Central

    Gámez-Pozo, Angelo; Antón-Aparicio, Luis M; Bayona, Cristina; Borrega, Pablo; Gallegos Sancho, María I; García-Domínguez, Rocío; de Portugal, Teresa; Ramos-Vázquez, Manuel; Pérez-Carrión, Ramón; Bolós, María V; Madero, Rosario; Sánchez-Navarro, Iker; Fresno Vara, Juan A; Arranz, Enrique Espinosa

    2012-01-01

    Anti-angiogenic therapy benefits many patients with advanced renal cell carcinoma (RCC), but there is still a need for predictive markers that help in selecting the best therapy for individual patients. MicroRNAs (miRNAs) regulate cancer cell behavior and may be attractive biomarkers for prognosis and prediction of response. Forty-four patients with RCC were recruited into this observational prospective study conducted in nine Spanish institutions. Peripheral blood samples were taken before initiation of therapy and 14 days later in patients receiving first-line therapy with sunitinib for advanced RCC. miRNA expression in peripheral blood was assessed using microarrays and L2 boosting was applied to filtered miRNA expression data. Several models predicting poor and prolonged response to sunitinib were constructed and evaluated by binary logistic regression. Blood samples from 38 patients and 287 miRNAs were evaluated. Twenty-eight miRNAs of the 287 were related to poor response and 23 of the 287 were related to prolonged response to sunitinib treatment. Predictive models identified populations with differences in the established end points. In the poor response group, median time to progression was 3.5 months and the overall survival was 8.5, whereas in the prolonged response group these values were 24 and 29.5 months, respectively. Ontology analyses pointed out to cancer-related pathways, such angiogenesis and apoptosis. miRNA expression signatures, measured in peripheral blood, may stratify patients with advanced RCC according to their response to first-line therapy with sunitinib, improving diagnostic accuracy. After proper validation, these signatures could be used to tailor therapy in this setting. PMID:23308047

  9. High FOXRED1 expression predicted good prognosis of colorectal cancer

    PubMed Central

    Fei, Weiqiang; Liu, Shuiping; Hu, Xiaotong

    2016-01-01

    The human FAD-dependent oxidoreductase domain containing 1 (FOXRED1) protein is reported as an assembly factor which promotes the correct assembly and stability of mitochondrial Complex I (CI). Alterations of mitochondrial CI might cause tumorigenesis and metastasis, but it’s molecular mechanisms remain unclear. In this study, we selected 145 cases of colorectal cancer for immunohistochemistry to explore the role of FOXRED1 played in the tumor progression of colorectal cancer. The relationship between FOXRED1 expression and clinicopathological features of colorectal cancers was evaluated. FOXRED1 mainly localized in the cytoplasm in the colorectal cancer tissues, and had significant association with histopathological grading, depth of invasion, lymph node metastasis, distant metastasis and TNM stage (P<0.05 for each). However, age, gender and tumor location was not found to be associated with FOXRED1 expression. Colorectal cancer patients with higher expression of FOXRED1 had the higher 3 year survival rate (P=0.003). Moreover, FOXRED1 had potentiality to be an independent prognostic factor for survival in colorectal cancer (P=0.04). Low FOXRED1 expression correlated with poor prognosis of colorectal cancer and targeting this molecular will be a potential treatment strategy for colorectal cancer. PMID:27904784

  10. University of Texas Southwestern Medical Center: Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

    Cancer.gov

    The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

  11. 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

  12. 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.

  13. Prediction of recurrence of non muscle-invasive bladder cancer by means of a protein signature identified by antibody microarray analyses.

    PubMed

    Srinivasan, Harish; Allory, Yves; Sill, Martin; Vordos, Dimitri; Alhamdani, Mohamed Saiel Saeed; Radvanyi, Francois; Hoheisel, Jörg D; Schröder, Christoph

    2014-06-01

    About 70% of newly diagnosed cases of bladder cancer are low-stage, low-grade, non muscle-invasive. Standard treatment is transurethral resection. About 60% of the tumors will recur, however, and in part progress to become invasive. Therefore, surveillance cystoscopy is performed after resection. However, in the USA and Europe alone, about 54 000 new patients per year undergo repeated cystoscopies over several years, who do not experience recurrence. Analysing in a pilot study resected tumors from patients with (n = 19) and without local recurrence (n = 6) after a period of 5 years by means of an antibody microarray that targeted 724 cancer-related proteins, we identified 255 proteins with significantly differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. A multivariate classifier was constructed based on 20 proteins. It facilitates the prediction of recurrence with a sensitivity of 80% and a specificity of 100%. As a measure of overall accuracy, the area under the curve value was found to be 91%. After validation in additional sample cohorts with a similarly long follow-up, such a signature could support decision making about the stringency of surveillance or even different treatment options.

  14. Determining epithelial contribution to in vivo mesenchymal tumour expression signature using species-specific microarray profiling analysis of xenografts.

    PubMed

    Purdom, E; Restall, C; Busuttil, R A; Schluter, H; Boussioutas, A; Thompson, E W; Anderson, R L; Speed, T P; Haviv, I

    2013-02-01

    Gene expression profiling using microarrays and xenograft transplants of human cancer cell lines are both popular tools to investigate human cancer. However, the undefined degree of cross hybridization between the mouse and human genomes hinders the use of microarrays to characterize gene expression of both the host and the cancer cell within the xenograft. Since an increasingly recognized aspect of cancer is the host response (or cancer-stroma interaction), we describe here a bioinformatic manipulation of the Affymetrix profiling that allows interrogation of the gene expression of both the mouse host and the human tumour. Evidence of microenvironmental regulation of epithelial mesenchymal transition of the tumour component in vivo is resolved against a background of mesenchymal gene expression. This tool could allow deeper insight to the mechanism of action of anti-cancer drugs, as typically novel drug efficacy is being tested in xenograft systems.

  15. L1000CDS2: LINCS L1000 characteristic direction signatures search engine

    PubMed Central

    Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

    2017-01-01

    The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge

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

    PubMed

    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. Microtubule-Associated Protein Expression and Predicting Taxane Response

    DTIC Science & Technology

    2009-10-01

    taxanes. Our results indicate that MAP- tau functions as a prognostic factor in both the Yale cohort and the TAX 307 cohort with high MAP- tau ...expression associated with longer overall survival and TTP. Tau does NOT behave as a predictor of response to taxane-based chemotherapy since differences...between low and high MAP- tau groups by treatment arm and response rate were not observed in the TAX 307 clinical trial cohort. Our data supports the

  18. 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.

  19. A unique gene expression signature associated with serotonin 2C receptor RNA editing in the prefrontal cortex and altered in suicide.

    PubMed

    Di Narzo, Antonio Fabio; Kozlenkov, Alexey; Roussos, Panos; Hao, Ke; Hurd, Yasmin; Lewis, David A; Sibille, Etienne; Siever, Larry J; Koonin, Eugene; Dracheva, Stella

    2014-09-15

    Editing of the pre-mRNA for the serotonin receptor 2C (5-HT2CR) by site-specific adenosine deamination (A-to-I pre-mRNA editing) substantially increases the functional plasticity of this key neurotransmitter receptor and is thought to contribute to homeostatic mechanisms in neurons. 5-HT2CR mRNA editing generates up to 24 different receptor isoforms. The extent of editing correlates with 5-HT2CR functional activity: more highly edited isoforms exhibit the least function. Altered 5-HT2CR editing has been reported in postmortem brains of suicide victims. We report a comparative analysis of the connections among 5-HT2CR editing, genome-wide gene expression and DNA methylation in suicide victims, individuals with major depressive disorder and non-psychiatric controls. The results confirm previous findings of an overrepresentation of highly edited mRNA variants (which encode hypoactive 5-HT2CR receptors) in the brains of suicide victims. A large set of genes for which the expression level is associated with editing was detected. This signature set of editing-associated genes is significantly enriched for genes that are involved in synaptic transmission, genes that are preferentially expressed in neurons, and genes whose expression is correlated with the level of DNA methylation. Notably, we report that the link between 5-HT2CR editing and gene expression is disrupted in suicide victims. The results suggest that the postulated homeostatic function of 5-HT2CR editing is dysregulated in individuals who committed suicide.

  20. 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.

  1. Identification of co-expressed gene signatures in mouse B1, marginal zone and B2 B-cell populations

    PubMed Central

    Mabbott, Neil A; Gray, David

    2014-01-01

    In mice, three major B-cell subsets have been identified with distinct functionalities: B1 B cells, marginal zone B cells and follicular B2 B cells. Here, we used the growing body of publicly available transcriptomics data to create an expression atlas of 84 gene expression microarray data sets of distinct mouse B-cell subsets. These data were subjected to network-based cluster analysis using BioLayout Express3D. Using this analysis tool, genes with related functions clustered together in discrete regions of the network graph and enabled the identification of transcriptional networks that underpinned the functional activity of distinct cell populations. Some gene clusters were expressed highly by most of the cell populations included in this analysis (such as those with activity related to house-keeping functions). Others contained genes with expression patterns specific to distinct B-cell subsets. While these clusters contained many genes typically associated with the activity of the cells they were specifically expressed in, many novel B-cell-subset-specific candidate genes were identified. A large number of uncharacterized genes were also represented in these B-cell lineage-specific clusters. Further analysis of the activities of these uncharacterized candidate genes will lead to the identification of novel B-cell lineage-specific transcription factors and regulators of B-cell function. We also analysed 36 microarray data sets from distinct human B-cell populations. These data showed that mouse and human germinal centre B cells shared similar transcriptional features, whereas mouse B1 B cells were distinct from proposed human B1 B cells. PMID:24032749

  2. Modulation of perception and brain activity by predictable trajectories of facial expressions.

    PubMed

    Furl, N; van Rijsbergen, N J; Kiebel, S J; Friston, K J; Treves, A; Dolan, R J

    2010-03-01

    People track facial expression dynamics with ease to accurately perceive distinct emotions. Although the superior temporal sulcus (STS) appears to possess mechanisms for perceiving changeable facial attributes such as expressions, the nature of the underlying neural computations is not known. Motivated by novel theoretical accounts, we hypothesized that visual and motor areas represent expressions as anticipated motion trajectories. Using magnetoencephalography, we show predictable transitions between fearful and neutral expressions (compared with scrambled and static presentations) heighten activity in visual cortex as quickly as 165 ms poststimulus onset and later (237 ms) engage fusiform gyrus, STS and premotor areas. Consistent with proposed models of biological motion representation, we suggest that visual areas predictively represent coherent facial trajectories. We show that such representations bias emotion perception of subsequent static faces, suggesting that facial movements elicit predictions that bias perception. Our findings reveal critical processes evoked in the perception of dynamic stimuli such as facial expressions, which can endow perception with temporal continuity.

  3. IGFBP2 expression predicts IDH-mutant glioma patient survival.

    PubMed

    Huang, Lin Eric; Cohen, Adam L; Colman, Howard; Jensen, Randy L; Fults, Daniel W; Couldwell, William T

    2017-01-03

    Mutations of the isocitrate dehydrogenase (IDH) 1 and 2 genes occur in ~80% of lower-grade (WHO grade II and grade III) gliomas. Mutant IDH produces (R)-2-hydroxyglutarate, which induces DNA hypermethylation and presumably drives tumorigenesis. Interestingly, IDH mutations are associated with improved survival in glioma patients, but the underlying mechanism for the difference in survival remains unclear. Through comparative analyses of 286 cases of IDH-wildtype and IDH-mutant lower-grade glioma from a TCGA data set, we report that IDH-mutant gliomas have increased expression of tumor-suppressor genes (NF1, PTEN, and PIK3R1) and decreased expression of oncogenes(AKT2, ARAF, ERBB2, FGFR3, and PDGFRB) and glioma progression genes (FOXM1, IGFBP2, and WWTR1) compared with IDH-wildtype gliomas. Furthermore, each of these genes is prognostic in overall gliomas; however, within the IDH-mutant group, none remains prognostic except IGFBP2 (encodinginsulin-like growth factor binding protein 2). Through validation in an independent cohort, we show that patients with low IGFBP2 expressiondisplay a clear advantage in overall and disease-free survival, whereas those with high IGFBP2 expressionhave worse median survival than IDH-wildtype patients. These observations hold true across different histological and molecular subtypes of lower-grade glioma. We propose therefore that an unexpected biological consequence of IDH mutations in glioma is to ameliorate patient survival by promoting tumor-suppressor signaling while inhibiting that of oncogenes, particularly IGFBP2.

  4. A gene expression signature-based approach reveals the mechanisms of action of the Chinese herbal medicine berberine

    PubMed Central

    Lee, Kuen-Haur; Lo, Hsiang-Ling; Tang, Wan-Chun; Hsiao, Heidi Hao-yun; Yang, Pei-Ming

    2014-01-01

    Berberine (BBR), a traditional Chinese herbal medicine, was shown to display anticancer activity. In this study, we attempted to provide a global view of the molecular pathways associated with its anticancer effect through a gene expression-based chemical approach. BBR-induced differentially expressed genes obtained from the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) were analyzed using the Connectivity Map (CMAP) database to compare similarities of gene expression profiles between BBR and CMAP compounds. Candidate compounds were further analyzed using the Search Tool for Interactions of Chemicals (STITCH) database to explore chemical-protein interactions. Results showed that BBR may inhibit protein synthesis, histone deacetylase (HDAC), or AKT/mammalian target of rapamycin (mTOR) pathways. Further analyses demonstrated that BBR inhibited global protein synthesis and basal AKT activity, and induced endoplasmic reticulum (ER) stress and autophagy, which was associated with activation of AMP-activated protein kinase (AMPK). However, BBR did not alter mTOR or HDAC activities. Interestingly, BBR induced the acetylation of α-tubulin, a substrate of HDAC6. In addition, the combination of BBR and SAHA, a pan-HDAC inhibitor, synergistically inhibited cell proliferation and induced cell cycle arrest. Our results provide novel insights into the mechanisms of action of BBR in cancer therapy. PMID:25227736

  5. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures

    PubMed Central

    Zhang, Hang; Xie, Ziyang; Yang, Yuwen; Zhao, Yizhen

    2017-01-01

    Microarray analysis of gene expression is often used to diagnose different types of disease. Many studies report remarkable achievements in nervous system disease. Clinical diagnosis of schizophrenia (SCZ) still depends on doctors' experience, which is unreliable and needs to be more objective and quantified. To solve this problem, we collected whole blood gene expression data from four studies, including 152 individuals with schizophrenia (SCZ) and 138 normal controls in different regions. The correlation-based feature selection (CFS, one of the machine learning methods) algorithm was applied in this study, and 103 significantly differentially expressed genes between patients and controls, called “feature genes,” were selected; then, a model for SCZ diagnosis was built. The samples were subdivided into 10 groups, and cross-validation showed that the model we constructed achieved nearly 100% classification accuracy. Mathematical evaluation of the datasets before and after data processing proved the effectiveness of our algorithm. Feature genes were enriched in Parkinson's disease, oxidative phosphorylation, and TGF-beta signaling pathways, which were previously reported to be associated with SCZ. These results suggest that the analysis of gene expression in whole blood by our model could be a useful tool for diagnosing SCZ. PMID:28280741

  6. Signatures of selection and host-adapted gene expression of the Phytophthora infestans RNA silencing suppressor PSR2.

    PubMed

    de Vries, Sophie; von Dahlen, Janina K; Uhlmann, Constanze; Schnake, Anika; Kloesges, Thorsten; Rose, Laura E

    2017-01-01

    Phytophthora infestans is a devastating pathogen in agricultural systems. Recently, an RNA silencing suppressor (PSR2, 'Phytophthora suppressor of RNA silencing 2') has been described in P. infestans. PSR2 has been shown to increase the virulence of Phytophthora pathogens on their hosts. This gene is one of the few effectors present in many economically important Phytophthora species. In this study, we investigated: (i) the evolutionary history of PSR2 within and between species of Phytophthora; and (ii) the interaction between sequence variation, gene expression and virulence. In P. infestans, the highest PiPSR2 expression was correlated with decreased symptom expression. The highest gene expression was observed in the biotrophic phase of the pathogen, suggesting that PSR2 is important during early infection. Protein sequence conservation was negatively correlated with host range, suggesting host range as a driver of PSR2 evolution. Within species, we detected elevated amino acid variation, as observed for other effectors; however, the frequency spectrum of the mutations was inconsistent with strong balancing selection. This evolutionary pattern may be related to the conservation of the host target(s) of PSR2 and the absence of known corresponding R genes. In summary, our study indicates that PSR2 is a conserved effector that acts as a master switch to modify plant gene regulation early during infection for the pathogen's benefit. The conservation of PSR2 and its important role in virulence make it a promising target for pathogen management.

  7. A gene expression signature-based approach reveals the mechanisms of action of the Chinese herbal medicine berberine.

    PubMed

    Lee, Kuen-Haur; Lo, Hsiang-Ling; Tang, Wan-Chun; Hsiao, Heidi Hao-yun; Yang, Pei-Ming

    2014-09-17

    Berberine (BBR), a traditional Chinese herbal medicine, was shown to display anticancer activity. In this study, we attempted to provide a global view of the molecular pathways associated with its anticancer effect through a gene expression-based chemical approach. BBR-induced differentially expressed genes obtained from the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) were analyzed using the Connectivity Map (CMAP) database to compare similarities of gene expression profiles between BBR and CMAP compounds. Candidate compounds were further analyzed using the Search Tool for Interactions of Chemicals (STITCH) database to explore chemical-protein interactions. Results showed that BBR may inhibit protein synthesis, histone deacetylase (HDAC), or AKT/mammalian target of rapamycin (mTOR) pathways. Further analyses demonstrated that BBR inhibited global protein synthesis and basal AKT activity, and induced endoplasmic reticulum (ER) stress and autophagy, which was associated with activation of AMP-activated protein kinase (AMPK). However, BBR did not alter mTOR or HDAC activities. Interestingly, BBR induced the acetylation of α-tubulin, a substrate of HDAC6. In addition, the combination of BBR and SAHA, a pan-HDAC inhibitor, synergistically inhibited cell proliferation and induced cell cycle arrest. Our results provide novel insights into the mechanisms of action of BBR in cancer therapy.

  8. Laser Capture Microdissection Assisted Identification of Epithelial MicroRNA Expression Signatures for Prognosis of Stage I NSCLC

    DTIC Science & Technology

    2013-10-01

    et al: A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129:1401-14, 2007 6. Sica A, Mantovani A: Macrophage plasticity and polarization: in vivo veritas. J Clin Invest 122:787-95, 2012  

  9. WeGET: predicting new genes for molecular systems by weighted co-expression

    PubMed Central

    Szklarczyk, Radek; Megchelenbrink, Wout; Cizek, Pavel; Ledent, Marie; Velemans, Gonny; Szklarczyk, Damian; Huynen, Martijn A.

    2016-01-01

    We have developed the Weighted Gene Expression Tool and database (WeGET, http://weget.cmbi.umcn.nl) for the prediction of new genes of a molecular system by correlated gene expression. WeGET utilizes a compendium of 465 human and 560 murine gene expression datasets that have been collected from multiple tissues under a wide range of experimental conditions. It exploits this abundance of expression data by assigning a high weight to datasets in which the known genes of a molecular system are harmoniously up- and down-regulated. WeGET ranks new candidate genes by calculating their weighted co-expression with that system. A weighted rank is calculated for human genes and their mouse orthologs. Then, an integrated gene rank and p-value is computed using a rank-order statistic. We applied our method to predict novel genes that have a high degree of co-expression with Gene Ontology terms and pathways from KEGG and Reactome. For each query set we provide a list of predicted novel genes, computed weights for transcription datasets used and cell and tissue types that contributed to the final predictions. The performance for each query set is assessed by 10-fold cross-validation. Finally, users can use the WeGET to predict novel genes that co-express with a custom query set. PMID:26582928

  10. MMP-13 Regulates Growth of Wound Granulation Tissue and Modulates Gene Expression Signatures Involved in Inflammation, Proteolysis, and Cell Viability

    PubMed Central

    Toriseva, Mervi; Laato, Matti; Carpén, Olli; Ruohonen, Suvi T.; Savontaus, Eriika; Inada, Masaki; Krane, Stephen M.; Kähäri, Veli-Matti

    2012-01-01

    Proteinases play a pivotal role in wound healing by regulating cell-matrix interactions and availability of bioactive molecules. The role of matrix metalloproteinase-13 (MMP-13) in granulation tissue growth was studied in subcutaneously implanted viscose cellulose sponge in MMP-13 knockout (Mmp13−/−) and wild type (WT) mice. The tissue samples were harvested at time points day 7, 14 and 21 and subjected to histological analysis and gene expression profiling. Granulation tissue growth was significantly reduced (42%) at day 21 in Mmp13−/− mice. Granulation tissue in Mmp13−/− mice showed delayed organization of myofibroblasts, increased microvascular density at day 14, and virtual absence of large vessels at day 21. Gene expression profiling identified differentially expressed genes in Mmp13−/− mouse granulation tissue involved in biological functions including inflammatory response, angiogenesis, cellular movement, cellular growth and proliferation and proteolysis. Among genes linked to angiogenesis, Adamts4 and Npy were significantly upregulated in early granulation tissue in Mmp13−/− mice, and a set of genes involved in leukocyte motility including Il6 were systematically downregulated at day 14. The expression of Pdgfd was downregulated in Mmp13−/− granulation tissue in all time points. The expression of matrix metalloproteinases Mmp2, Mmp3, Mmp9 was also significantly downregulated in granulation tissue of Mmp13−/− mice compared to WT mice. Mmp13−/− mouse skin fibroblasts displayed altered cell morphology and impaired ability to contract collagen gel and decreased production of MMP-2. These results provide evidence for an important role for MMP-13 in wound healing by coordinating cellular activities important in the growth and maturation of granulation tissue, including myofibroblast function, inflammation, angiogenesis, and proteolysis. PMID:22880047

  11. WDR5 Supports an N-Myc Transcriptional Complex That Drives a Protumorigenic Gene Expression Signature in Neuroblastoma.

    PubMed

    Sun, Yuting; Bell, Jessica L; Carter, Daniel; Gherardi, Samuele; Poulos, Rebecca C; Milazzo, Giorgio; Wong, Jason W H; Al-Awar, Rima; Tee, Andrew E; Liu, Pei Y; Liu, Bing; Atmadibrata, Bernard; Wong, Matthew; Trahair, Toby; Zhao, Quan; Shohet, Jason M; Haupt, Ygal; Schulte, Johannes H; Brown, Peter J; Arrowsmith, Cheryl H; Vedadi, Masoud; MacKenzie, Karen L; Hüttelmaier, Stefan; Perini, Giovanni; Marshall, Glenn M; Braithwaite, Antony; Liu, Tao

    2015-12-01

    MYCN gene amplification in neuroblastoma drives a gene expression program that correlates strongly with aggressive disease. Mechanistically, trimethylation of histone H3 lysine 4 (H3K4) at target gene promoters is a strict prerequisite for this transcriptional program to be enacted. WDR5 is a histone H3K4 presenter that has been found to have an essential role in H3K4 trimethylation. For this reason, in this study, we investigated the relationship between WDR5-mediated H3K4 trimethylation and N-Myc transcriptional programs in neuroblastoma cells. N-Myc upregulated WDR5 expression in neuroblastoma cells. Gene expression analysis revealed that WDR5 target genes included those with MYC-binding elements at promoters such as MDM2. We showed that WDR5 could form a protein complex at the MDM2 promoter with N-Myc, but not p53, leading to histone H3K4 trimethylation and activation of MDM2 transcription. RNAi-mediated attenuation of WDR5 upregulated expression of wild-type but not mutant p53, an effect associated with growth inhibition and apoptosis. Similarly, a small-molecule antagonist of WDR5 reduced N-Myc/WDR5 complex formation, N-Myc target gene expression, and cell growth in neuroblastoma cells. In MYCN-transgenic mice, WDR5 was overexpressed in precancerous ganglion and neuroblastoma cells compared with normal ganglion cells. Clinically, elevated levels of WDR5 in neuroblastoma specimens were an independent predictor of poor overall survival. Overall, our results identify WDR5 as a key cofactor for N-Myc-regulated transcriptional activation and tumorigenesis and as a novel therapeutic target for MYCN-amplified neuroblastomas.

  12. Behaviorally activated mRNA expression profiles produce signatures of learning and enhanced inhibition in aged rats with preserved memory.

    PubMed

    Haberman, Rebecca P; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela

    2013-01-01

    Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to

  13. IGFBP2 expression predicts IDH-mutant glioma patient survival

    PubMed Central

    Huang, Lin Eric; Cohen, Adam L.; Colman, Howard; Jensen, Randy L.; Fults, Daniel W.; Couldwell, William T.

    2017-01-01

    Mutations of the isocitrate dehydrogenase (IDH) 1 and 2 genes occur in ~80% of lower-grade (WHO grade II and grade III) gliomas. Mutant IDH produces (R)-2-hydroxyglutarate, which induces DNA hypermethylation and presumably drives tumorigenesis. Interestingly, IDH mutations are associated with improved survival in glioma patients, but the underlying mechanism for the difference in survival remains unclear. Through comparative analyses of 286 cases of IDH-wildtype and IDH-mutant lower-grade glioma from a TCGA data set, we report that IDH-mutant gliomas have increased expression of tumor-suppressor genes (NF1, PTEN, and PIK3R1) and decreased expression of oncogenes(AKT2, ARAF, ERBB2, FGFR3, and PDGFRB) and glioma progression genes (FOXM1, IGFBP2, and WWTR1) compared with IDH-wildtype gliomas. Furthermore, each of these genes is prognostic in overall gliomas; however, within the IDH-mutant group, none remains prognostic except IGFBP2 (encodinginsulin-like growth factor binding protein 2). Through validation in an independent cohort, we show that patients with low IGFBP2 expressiondisplay a clear advantage in overall and disease-free survival, whereas those with high IGFBP2 expressionhave worse median survival than IDH-wildtype patients. These observations hold true across different histological and molecular subtypes of lower-grade glioma. We propose therefore that an unexpected biological consequence of IDH mutations in glioma is to ameliorate patient survival by promoting tumor-suppressor signaling while inhibiting that of oncogenes, particularly IGFBP2. PMID:27852048

  14. Tumor suppressive microRNAs (miR-222 and miR-31) regulate molecular pathways based on microRNA expression signature in prostate cancer.

    PubMed

    Fuse, Miki; Kojima, Satoko; Enokida, Hideki; Chiyomaru, Takeshi; Yoshino, Hirofumi; Nohata, Nijiro; Kinoshita, Takashi; Sakamoto, Shinichi; Naya, Yukio; Nakagawa, Masayuki; Ichikawa, Tomohiko; Seki, Naohiko

    2012-11-26

    microRNAs (miRNAs) have key roles in human tumorigenesis, tumor progression and metastasis. miRNAs are aberrantly expressed in many human cancers and can function as tumor suppressors or oncogenes that target many cancer-related genes. This study seeks to identify novel miRNA-regulated molecular pathways in prostate cancer (PCa). The miRNA expression signature in clinical specimens of PCa showed that 56 miRNAs were significantly downregulated in PCa compared with non-PCa tissues. We focused on the top four downregulated miRNAs (miR-187, miR-205, miR-222 and miR-31) to investigate their functional significance in PCa cells. Expression levels of these four miRNAs were validated in PCa specimens (15 PCa tissues and 17 non-PCa tissues) to confirm that they were significantly reduced in these PCa tissues. Gain-of-function analysis demonstrated that miR-222 and miR-31 inhibited cell proliferation, invasion and migration in PCa cell lines (PC3 and DU145), suggesting that miR-222 and miR-31 may act as tumor suppressors in PCa. Genome-wide gene expression analysis using miR-222 or miR-31 transfectants to identify the pathways they affect showed that many cancer-related genes are regulated by these miRNAs in PC3 cells. Identification and categorization of the molecular pathways regulated by tumor suppressive miRNAs could provide new information about the molecular mechanisms of PCa tumorigenesis.

  15. Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes

    PubMed Central

    Bolisetty, Mohan; Kursawe, Romy; Sun, Lili; Sivakamasundari, V.; Kycia, Ina

    2017-01-01

    Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type–specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis. PMID:27864352

  16. Huntington’s disease blood and brain show a common gene expression pattern and share an immune signature with Alzheimer’s disease

    PubMed Central

    Hensman Moss, Davina J.; Flower, Michael D.; Lo, Kitty K.; Miller, James R. C.; van Ommen, Gert-Jan B.; ’t Hoen, Peter A. C.; Stone, Timothy C.; Guinee, Amelia; Langbehn, Douglas R.; Jones, Lesley; Plagnol, Vincent; van Roon-Mom, Willeke M. C.; Holmans, Peter; Tabrizi, Sarah J.

    2017-01-01

    There is widespread transcriptional dysregulation in Huntington’s disease (HD) brain, but analysis is inevitably limited by advanced disease and postmortem changes. However, mutant HTT is ubiquitously expressed and acts systemically, meaning blood, which is readily available and contains cells that are dysfunctional in HD, could act as a surrogate for brain tissue. We conducted an RNA-Seq transcriptomic analysis using whole blood from two HD cohorts, and performed gene set enrichment analysis using public databases and weighted correlation network analysis modules from HD and control brain datasets. We identified dysregulated gene sets in blood that replicated in the independent cohorts, correlated with disease severity, corresponded to the most significantly dysregulated modules in the HD caudate, the most prominently affected brain region, and significantly overlapped with the transcriptional signature of HD myeloid cells. High-throughput sequencing technologies and use of gene sets likely surmounted the limitations of previously inconsistent HD blood expression studies. Our results suggest transcription is disrupted in peripheral cells in HD through mechanisms that parallel those in brain. Immune upregulation in HD overlapped with Alzheimer’s disease, suggesting a common pathogenic mechanism involving macrophage phagocytosis and microglial synaptic pruning, and raises the potential for shared therapeutic approaches. PMID:28322270

  17. 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.

  18. MGMT Expression Predicts PARP-Mediated Resistance to Temozolomide.

    PubMed

    Erice, Oihane; Smith, Michael P; White, Rachel; Goicoechea, Ibai; Barriuso, Jorge; Jones, Chris; Margison, Geoffrey P; Acosta, Juan C; Wellbrock, Claudia; Arozarena, Imanol

    2015-05-01

    Melanoma and other solid cancers are frequently resistant to chemotherapies based on DNA alkylating agents such as dacarbazine and temozolomide. As a consequence, clinical responses are generally poor. Such resistance is partly due to the ability of cancer cells to use a variety of DNA repair enzymes to maintain cell viability. Particularly, the expression of MGMT has been linked to temozolomide resistance, but cotargeting MGMT has proven difficult due to dose-limiting toxicities. Here, we show that the MGMT-mediated resistance of cancer cells is profoundly dependent on the DNA repair enzyme PARP. Both in vitro and in vivo, we observe that MGMT-positive cancer cells strongly respond to the combination of temozolomide and PARP inhibitors (PARPi), whereas MGMT-deficient cells do not. In melanoma cells, temozolomide induced an antiproliferative senescent response, which was greatly enhanced by PARPi in MGMT-positive cells. In summary, we provide compelling evidence to suggest that the stratification of patients with cancer upon the MGMT status would enhance the success of combination treatments using temozolomide and PARPi.

  19. 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

  20. Hippocampus neuronal metabolic gene expression outperforms whole tissue data in accurately predicting Alzheimer's disease progression.

    PubMed

    Stempler, Shiri; Waldman, Yedael Y; Wolf, Lior; Ruppin, Eytan

    2012-09-01

    Numerous metabolic alterations are associated with the impairment of brain cells in Alzheimer's disease (AD). Here we use gene expression microarrays of both whole hippocampus tissue and hippocampal neurons of AD patients to investigate the ability of metabolic gene expression to predict AD progression and its cognitive decline. We find that the prediction accuracy of different AD stages is markedly higher when using neuronal expression data (0.9) than when using whole tissue expression (0.76). Furthermore, the metabolic genes' expression is shown to be as effective in predicting AD severity as the entire gene list. Remarkably, a regression model from hippocampal metabolic gene expression leads to a marked correlation of 0.57 with the Mini-Mental State Examination cognitive score. Notably, the expression of top predictive neuronal genes in AD is significantly higher than that of other metabolic genes in the brains of healthy subjects. All together, the analyses point to a subset of metabolic genes that is strongly associated with normal brain functioning and whose disruption plays a major role in AD.

  1. High-resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury.

    PubMed

    Jeong, Heejin; Na, Young-Ji; Lee, Kihwan; Kim, Yong Ho; Lee, Yunsin; Kang, Minho; Jiang, Bao-Chun; Yeom, Young Il; Wu, Long-Jun; Gao, Yong-Jing; Kim, Junhyong; Oh, Seog Bae

    2016-04-01

    Microglial cells, the resident immune cells of the spinal cord, become activated in response to peripheral nerve injury. Microglia activation contributes to the development of neuropathic pain. Here we employed microarray analysis of individually collected pools of 10 spinal microglia cells to identify changes of levels and cell-to-cell expression variance of microglial genes during their activation after peripheral nerve injury. The analysis of microglia on postoperative day 1 (POD1) identified miR-29c as a critical factor for microglial activation and the development of neuropathic pain. Early POD1 microglia exhibited a very distinct expression profile compared to late POD7 microglia, possibly leading to the transition from initiation to maintenance of neuropathic pain. We found sample variance patterns that were consistent with the hypothesis that microglia were highly heterogeneous at the level of individual cells, and variation analysis identified 56 microglial genes potentially linked to the maintenance of neuropathic pain which included Gria1. This study provides insights into spinal microglial biology and reveals novel microglial targets for the treatment of neuropathic pain.

  2. The gene expression signature of relapse in paediatric acute lymphoblastic leukaemia: implications for mechanisms of therapy failure.

    PubMed

    Beesley, Alex H; Cummings, Aaron J; Freitas, Joseph R; Hoffmann, Katrin; Firth, Martin J; Ford, Jette; de Klerk, Nicolas H; Kees, Ursula R

    2005-11-01

    Despite significant improvements in the treatment of childhood acute lymphoblastic leukaemia (ALL), the prognosis for relapsing patients remains poor. The aim of this study was to generate a transcriptional profile of relapsed ALL to increase our understanding of the mechanisms involved in therapy failure. RNA was extracted from 11 pairs of cryopreserved pre-B ALL bone marrow specimens taken from the same patients at diagnosis and relapse, and analysed using HG-U133A microarrays. Relapse specimens overexpressed genes that are involved with cell growth and proliferation, in keeping with their aggressive phenotype. When tested in 72 independent specimens of pre-B ALL and T-ALL, the identified genes could successfully differentiate between diagnosis and relapse in either lineage, indicating the existence of relapse mechanisms common to both. These genes have functions relevant for oncogenesis, drug resistance and metastasis, but are not related to classical multidrug-resistance pathways. Increased expression of the top-ranked gene (BSG) at diagnosis was significantly associated with adverse outcome. Several chromosomal loci, including 19p13, were identified as potential hotspots for aberrant gene expression in relapsed ALL. Our results provide evidence for a link between drug resistance and the microenvironment that has previously only been considered in the context of solid tumour biology.

  3. 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.

  4. Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer.

    PubMed

    Huang, Yanqi; Liu, Zaiyi; He, Lan; Chen, Xin; Pan, Dan; Ma, Zelan; Liang, Cuishan; Tian, Jie; Liang, Changhong

    2016-12-01

    Purpose To develop a radiomics signature to estimate disease-free survival (DFS) in patients with early-stage (stage I-II) non-small cell lung cancer (NSCLC) and assess its incremental value to the traditional staging system and clinical-pathologic risk factors for individual DFS estimation. Materials and Methods Ethical approval by the institutional review board was obtained for this retrospective analysis, and the need to obtain informed consent was waived. This study consisted of 282 consecutive patients with stage IA-IIB NSCLC. A radiomics signature was generated by using the least absolute shrinkage and selection operator, or LASSO, Cox regression model. Association between the radiomics signature and DFS was explored. Further validation of the radiomics signature as an independent biomarker was performed by using multivariate Cox regression. A radiomics nomogram with the radiomics signature incorporated was constructed to demonstrate the incremental value of the radiomics signature to the traditional staging system and other clinical-pathologic risk factors for individualized DFS estimation, which was then assessed with respect to calibration, discrimination, reclassification, and clinical usefulness. Results The radiomics signature was significantly associated with DFS, independent of clinical-pathologic risk factors. Incorporating the radiomics signature into the radiomics-based nomogram resulted in better performance (P < .0001) for the estimation of DFS (C-index: 0.72; 95% confidence interval [CI]: 0.71, 0.73) than with the clinical-pathologic nomogram (C-index: 0.691; 95% CI: 0.68, 0.70), as well as a better calibration and improved accuracy of the classification of survival outcomes (net reclassification improvement: 0.182; 95% CI: 0.02, 0.31; P = .02). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinical-pathologic nomogram. Conclusion The

  5. T lymphocytes from chronic HCV-infected patients are primed for activation-induced apoptosis and express unique pro-apoptotic gene signature.

    PubMed

    Zhao, Bin-Bin; Zheng, Su-Jun; Gong, Lu-Lu; Wang, Yu; Chen, Cai-Feng; Jin, Wen-Jing; Zhang, Ding; Yuan, Xiao-Hui; Guo, Jian; Duan, Zhong-Ping; He, You-Wen

    2013-01-01

    Although extensive studies have demonstrated the functional impairment of antigen-specific CD4(+) and CD8(+) T-cells during chronic hepatitis C virus (HCV) infection, the functional status of global CD4(+) and CD8(+) T-cells remains unclear. In this report, we recruited 42 long-term (~20 years) treatment-naïve chronic HCV (CHC) patients and 15 healthy donors (HDs) to investigate differences in global CD4(+) and CD8(+) T-cells function. We show that CD4(+) and CD8(+) T-cells from CHC patients underwent increased apoptosis after TCR stimulation. Furthermore, IFN-γ, IL-9 and IP-10 were elevated in CHC patients' plasma and promoted activation-induced T-cells death. Global CD4(+) and CD8(+) T-cells also showed unique transcriptional profiles in the expression of apoptosis-related genes. We identified BCL2, PMAIP1, and CASP1 in CD4(+) T-cells and IER3 and BCL2A1 in CD8(+) T-cells from CHC patients as HCV-specific gene signatures. Importantly, the gene expression patterns of CD4(+) and CD8(+) T-cells from CHC patients differ from those in CD4(+) and CD8(+) T-cells from human immunodeficiency virus type 1 (HIV-1) or hepatitis B virus (HBV) infected individuals. Our results indicate that chronic HCV infection causes a systemic change in cytokine levels that primes T-cells for activation-induced apoptosis. Furthermore, HCV infection programs unique apoptosis-related gene expression profiles in CD4(+) and CD8(+) T-cells, leading to their enhanced activation-induced apoptosis. These results provide novel insights to the pathogenesis of chronic HCV infection.

  6. Gene expression in local stroma reflects breast tumor states and predicts patient outcome

    PubMed Central

    Bainer, Russell; Frankenberger, Casey; Rabe, Daniel; An, Gary; Gilad, Yoav; Rosner, Marsha Rich

    2016-01-01

    The surrounding microenvironment has been implicated in the progression of breast tumors to metastasis. However, the degree to which metastatic breast tumors locally reprogram stromal cells as they disrupt tissue boundaries is not well understood. We used species-specific RNA sequencing in a mouse xenograft model to determine how the metastasis suppressor RKIP influences transcription in a panel of paired tumor and stroma tissues. We find that gene expression in metastatic breast tumors is pervasively correlated with gene expression in local stroma of both mouse xenografts and human patients. Changes in stromal gene expression elicited by tumors better predicts subtype and patient survival than tumor gene expression, and genes with coordinated expression in both tissues predict metastasis-free survival. These observations support the use of stroma-based strategies for the diagnosis and prognosis of breast cancer. PMID:27982086

  7. 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

  8. "Fibrous nests" in human hepatocellular carcinoma express a Wnt-induced gene signature associated with poor clinical outcome.

    PubMed

    Désert, Romain; Mebarki, Sihem; Desille, Mireille; Sicard, Marie; Lavergne, Elise; Renaud, Stéphanie; Bergeat, Damien; Sulpice, Laurent; Perret, Christine; Turlin, Bruno; Clément, Bruno; Musso, Orlando

    2016-12-01

    Hepatocellular carcinoma (HCC) is the 3rd cause of cancer-related death worldwide. Most cases arise in a background of chronic inflammation, extracellular matrix (ECM) remodeling, severe fibrosis and stem/progenitor cell amplification. Although HCCs are soft cellular tumors, they may contain fibrous nests within the tumor mass. Thus, the aim of this study was to explore cancer cell phenotypes in fibrous nests. Combined anatomic pathology, tissue microarray and real-time PCR analyses revealed that HCCs (n=82) containing fibrous nests were poorly differentiated, expressed Wnt pathway components and target genes, as well as markers of stem/progenitor cells, such as CD44, LGR5 and SOX9. Consistently, in severe liver fibroses (n=66) and in HCCs containing fibrous nests, weighted correlation analysis revealed a gene network including the myofibroblast marker ACTA2, the basement membrane components COL4A1 and LAMC1, the Wnt pathway members FZD1; FZD7; WNT2; LEF1; DKK1 and the Secreted Frizzled Related Proteins (SFRPs) 1; 2 and 5. Moreover, unbiased random survival forest analysis of a transcriptomic dataset of 247 HCC patients revealed high DKK1, COL4A1, SFRP1 and LAMC1 to be associated with advanced tumor staging as well as with bad overall and disease-free survival. In vitro, these genes were upregulated in liver cancer stem/progenitor cells upon Wnt-induced mesenchymal commitment and myofibroblast differentiation. In conclusion, fibrous nests express Wnt target genes, as well as markers of cancer stem cells and mesenchymal commitment. Fibrous nests embody the specific microenvironment of the cancer stem cell niche and can be detected by routine anatomic pathology analyses.

  9. Predicting risk of breast cancer recurrence using gene-expression profiling.

    PubMed

    Ignatiadis, Michail; Desmedt, Christine

    2007-01-01

    The molecular profiling of breast tumors using the powerful microarray technology has uncovered the molecular heterogeneity of breast tumors and has offered novel insight into breast tumorigenesis. The estrogen receptor (ER) has been shown to be the most important discriminator dichotomizing breast cancer into two main subsets. At the same time, proliferation, as captured by the recently developed Genomic Grade Index (GGI) has been found to be the most important prognostic factor in breast cancer, far beyond ER status. Interestingly, this index encompasses a significant portion of the predictive power of many published prognostic signatures. The challenge now is to integrate all the prognostic gene signatures available to date towards a comprehensive genomic fingerprint of the primary tumor. In the future, we should be able to offer individualized treatment to our patients based on a clinical decision-making algorithm that takes into account the clinicopathological parameters, the genomic profile of the primary tumor, the presence of micrometastatic cells and pharmacogenetic data for drug response.

  10. Prediction of highly expressed genes in microbes based on chromatin accessibility

    PubMed Central

    Willenbrock, Hanni; Ussery, David W

    2007-01-01

    Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI) values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches. PMID:17295928

  11. HOX gene expression predicts response to BCL-2 inhibition in acute myeloid leukemia.

    PubMed

    Kontro, M; Kumar, A; Majumder, M M; Eldfors, S; Parsons, A; Pemovska, T; Saarela, J; Yadav, B; Malani, D; Fløisand, Y; Höglund, M; Remes, K; Gjertsen, B T; Kallioniemi, O; Wennerberg, K; Heckman, C A; Porkka, K

    2017-02-01

    Inhibitors of B-cell lymphoma-2 (BCL-2) such as venetoclax (ABT-199) and navitoclax (ABT-263) are clinically explored in several cancer types, including acute myeloid leukemia (AML), to selectively induce apoptosis in cancer cells. To identify robust biomarkers for BCL-2 inhibitor sensitivity, we evaluated the ex vivo sensitivity of fresh leukemic cells from 73 diagnosed and relapsed/refractory AML patients, and then comprehensively assessed whether the responses correlated to specific mutations or gene expression signatures. Compared with samples from healthy donor controls (nonsensitive) and chronic lymphocytic leukemia (CLL) patients (highly sensitive), AML samples exhibited variable responses to BCL-2 inhibition. Strongest CLL-like responses were observed in 15% of the AML patient samples, whereas 32% were resistant, and the remaining exhibited intermediate responses to venetoclax. BCL-2 inhibitor sensitivity was associated with genetic aberrations in chromatin modifiers, WT1 and IDH1/IDH2. A striking selective overexpression of specific HOXA and HOXB gene transcripts were detected in highly BCL-2 inhibitor sensitive samples. Ex vivo responses to venetoclax showed significant inverse correlation to β2-microglobulin expression and to a lesser degree to BCL-XL and BAX expression. As new therapy options for AML are urgently needed, the specific HOX gene expression pattern can potentially be used as a biomarker to identify venetoclax-sensitive AML patients for clinical trials.

  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. 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

  14. 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,