MicroRNA expression profiling predicts clinical outcome of chronic hepatitis C by interferon administration
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PROVIDER: S-DIXA-D-1036 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:We attempt to catalog the microRNA (miRNA) expression profile according to the response of combination therapy in order to predict the outcome of drug-response before administration and clarify the relationship between aberrant expression of miRNAs and chronic liver disease.
2010-12-30 | GSE16922 | GEO
Project description:We attempt to catalog the microRNA (miRNA) expression profile according to the response of combination therapy in order to predict the outcome of drug-response before administration and clarify the relationship between aberrant expression of miRNAs and chronic liver disease. We quantified expression profile of 474 mature miRNAs by microarray in the liver biopsy specimen from 99 CH patients without history of anti-viral therapy.
2010-12-30 | E-GEOD-16922 | biostudies-arrayexpress
Project description:Chronic hepatitis C (CH) frequently developed liver cirrhosis and hepatocellular carcinoma without suitable treatment. However, peginterferon(IFN) and ribavirin therapy (combination therapy), which is present standard therapy, is imperfect effect because of several side effect. We attempt to catalog IFN related gene expression profile according to the response of combination therapy in to predict the outcome of drug-response before administration and establish the adequate treatment according to the individual clinical information.
2010-02-11 | GSE20119 | GEO
Project description:Chronic hepatitis C (CH) frequently developed liver cirrhosis and hepatocellular carcinoma without suitable treatment. However, peginterferon(IFN) and ribavirin therapy (combination therapy), which is present standard therapy, is imperfect effect because of several side effect. We attempt to catalog IFN related gene expression profile according to the response of combination therapy in to predict the outcome of drug-response before administration and establish the adequate treatment according to the individual clinical information. Chip1 [GPL9960-related Samples]: We quantified expression profile of 200 IFN related genes by microarray in the liver biopsy specimen from 88 CH patients without history of anti-viral therapy, 10 fatty liver patients without HCV infection were also enrolled. Chip2 [GPL9962-related Samples]: We quantified expression profile of 37 IFN related genes by microarray in the liver biopsy specimen from 88 CH patients without history of anti-viral therapy, 10 fatty liver patients without HCV infection were also enrolled.
2010-02-10 | E-GEOD-20119 | biostudies-arrayexpress
Project description:One of the major problems in management of prostate cancer is the lack of reliable genetic markers predicting the clinical course of the disease. We analyzed expression profiles of 12,625 transcripts in prostate tumors from patients with distinct clinical outcomes after therapy as well as metastatic human prostate cancer xenografts in nude mice. We identified small clusters of genes discriminating recurrent versus nonrecurrent disease with 90% and 75% accuracy in two independent cohorts of patients. We examined one group of samples (21 tumors) to discover the recurrence predictor genes and then validated the predictive power of these genes in a different set (79 tumors). Kaplan-Meier analysis demonstrated that recurrence predictor signatures are highly informative (P < 0.0001) in stratification of patients into subgroups with distinct relapse-free survival after therapy. A gene expression-based recurrence predictor algorithm was informative in predicting the outcome in patients with early-stage disease, with either high or low preoperative prostate-specific antigen levels and provided additional value to the outcome prediction based on Gleason sum or multiparameter nomogram. Overall, 88% of patients with recurrence of prostate cancer within 1 year after therapy were correctly classified into the poor-prognosis group. The identified algorithm provides additional predictive value over conventional markers of outcome and appears suitable for stratification of prostate cancer patients at the time of diagnosis into subgroups with distinct survival probability after therapy.
| S-EPMC362118 | biostudies-literature
Project description:Hepatitis C virus (HCV) infection is a major cause of chronic liver disease worldwide. The current standard therapy for chronic hepatitis C (CHC) consists of a combination of pegylated IFN alpha (pegIFN-alpha) and ribavirin. It achieves a sustained viral clearance in only 50–60% of patients. To learn more about molecular mechanisms underlying treatment failure, we investigated IFN-induced signaling in paired liver biopsies collected from CHC patients before and after administration of pegIFN-alpha. In patients with a rapid virological response to treatment, pegIFN-alpha induced a strong up-regulation of IFN-stimulated genes (ISGs). As shown previously, nonresponders had high expression levels of ISGs before therapy. Analysis of posttreatment biopsies of these patients revealed that pegIFN-alpha did not induce expression of ISGs above the pretreatment levels. In accordance with ISG expression data, phosphorylation, DNA binding, and nuclear localization of STAT1 indicated that the IFN signaling pathway in nonresponsive patients is preactivated and refractory to further stimulation. Some features characteristic of nonresponders were more accentuated in patients infected with HCV genotypes 1 and 4 compared with genotypes 2 and 3, providing a possible explanation for the poor response of the former group to therapy. Taken together with previous findings, our data support the concept that activation of the endogenous IFN system in CHC not only is ineffective in clearing the infection but also may impede the response to therapy, most likely by inducing a refractory state of the IFN signaling pathway. Keywords: Comparison of human patient biopses before and after interferon treatment
2008-04-17 | GSE11190 | GEO
Project description:Hepatitis C virus (HCV) infection is a major cause of chronic liver disease worldwide. The current standard therapy for chronic hepatitis C (CHC) consists of a combination of pegylated IFN alpha (pegIFNalpha) and ribavirin. It achieves a sustained viral clearance in only 50-60% of patients. To learn more about molecular mechanisms underlying treatment failure, we investigated IFN-induced signaling in paired liver biopsies collected from CHC patients before and after administration of pegIFNalpha. In patients with a rapid virological response to treatment, pegIFNalpha induced a strong up-regulation of IFN-stimulated genes (ISGs). As shown previously, nonresponders had high expression levels of ISGs before therapy. Analysis of posttreatment biopsies of these patients revealed that pegIFNalpha did not induce expression of ISGs above the pretreatment levels. In accordance with ISG expression data, phosphorylation, DNA binding, and nuclear localization of STAT1 indicated that the IFN signaling pathway in nonresponsive patients is preactivated and refractory to further stimulation. Some features characteristic of nonresponders were more accentuated in patients infected with HCV genotypes 1 and 4 compared with genotypes 2 and 3, providing a possible explanation for the poor response of the former group to therapy. Taken together with previous findings, our data support the concept that activation of the endogenous IFN system in CHC not only is ineffective in clearing the infection but also may impede the response to therapy, most likely by inducing a refractory state of the IFN signaling pathway.
| S-EPMC2383932 | biostudies-literature
Project description:BACKGROUND: Ion channels play a critical role in a wide variety of biological processes, including the development of human cancer. However, the overall impact of ion channels on tumorigenicity in breast cancer remains controversial. METHODS: We conduct microarray meta-analysis on 280 ion channel genes. We identify candidate ion channels that are implicated in breast cancer based on gene expression profiling. We test the relationship between the expression of ion channel genes and p53 mutation status, ER status, and histological tumor grade in the discovery cohort. A molecular signature consisting of ion channel genes (IC30) is identified by Spearman's rank correlation test conducted between tumor grade and gene expression. A risk scoring system is developed based on IC30. We test the prognostic power of IC30 in the discovery and seven validation cohorts by both Cox proportional hazard regression and log-rank test. RESULTS: 22, 24, and 30 ion channel genes are found to be differentially expressed with a change in p53 mutation status, ER status, and tumor histological grade in the discovery cohort. We assign the 30 tumor grade associated ion channel genes as the IC30 gene signature. We find that IC30 risk score predicts clinical outcome (P < 0.05) in the discovery cohort and 6 out of 7 validation cohorts. Multivariate and univariate tests conducted in two validation cohorts indicate that IC30 is a robust prognostic biomarker, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node status, tumor size, tumor grade, estrogen and progesterone receptor status, and p53 mutation status. CONCLUSIONS: We identified a molecular gene signature IC30, which represents a promising diagnostic and prognostic biomarker in breast cancer. Our results indicate that information regarding the expression of ion channels in tumor pathology could provide new targets for therapy in human cancers.
| S-EPMC3849355 | biostudies-literature
Project description:The expression levels of miR-16, miR-193b, miR-199a, miR-222, and miR-324 in PBMCs were significantly higher in CHC patients compared with healthy controls and significantly different between CHC patients with HCV genotype 1 (GT-1) and non-genotype-1 (non-GT-1). Multivariate logistic regression analysis also showed that patients with high expression levels of the six target miRNAs had an approximately 7.202-fold risk of CHC compared with those with low expression levels of the target miRNAs. We concluded that the expression levels of miR-16, miR-193b, miR-199a, miR-222, and miR-324 target miRNAs in PBMCs of CHC may act as significant risk biomarkers for the development of CHC.
| S-EPMC4255053 | biostudies-literature
Project description:BackgroundHCV infection frequently induces chronic liver diseases. The current standard treatment for chronic hepatitis (CH) C combines pegylated interferon (IFN) and ribavirin, and is less than ideal due to undesirable effects. MicroRNAs (miRNAs) are endogenous small non-coding RNAs that control gene expression by degrading or suppressing the translation of target mRNAs. In this study we administered the standard combination treatment to CHC patients. We then examined their miRNA expression profiles in order to identify the miRNAs that were associated with each patient's drug response.Methods99 CHC patients with no anti-viral therapy history were enrolled. The expression level of 470 mature miRNAs found their biopsy specimen, obtained prior to the combination therapy, were quantified using microarray analysis. The miRNA expression pattern was classified based on the final virological response to the combination therapy. Monte Carlo Cross Validation (MCCV) was used to validate the outcome of the prediction based on the miRNA expression profile.ResultsWe found that the expression level of 9 miRNAs were significantly different in the sustained virological response (SVR) and non-responder (NR) groups. MCCV revealed an accuracy, sensitivity, and specificity of 70.5%, 76.5% and 63.3% in SVR and non-SVR and 70.0%, 67.5%, and 73.7% in relapse (R) and NR, respectively.ConclusionsThe hepatic miRNA expression pattern that exists in CHC patients before combination therapy is associated with their therapeutic outcome. This information can be utilized as a novel biomarker to predict drug response and can also be applied to developing novel anti-viral therapy for CHC patients.
| S-EPMC2984584 | biostudies-literature