HCC prediction after clearance of HCV in chronic hepatitis C II
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PROVIDER: PRJNA488280 | ENA |
REPOSITORIES: ENA
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Project description:HCC prediction after clearance of HCV in chronic hepatitis C I
| PRJNA488275 | ENA
Project description:We attempted to development prediction methods for hepatocellular carcinoma (HCC) in chronic hepatitis C patients who have been successfully treated by anti-viral therapy. 2565 miRNAs in 139 exosome specimens were analyzed.
2020-01-24 | GSE119159 | GEO
Project description:We attempted to development prediction methods for hepatocellular carcinoma (HCC) in chronic hepatitis C patients who have been successfully treated by anti-viral therapy. 2565 miRNAs in 43 liver tissues specimens were analyzed.
2020-01-24 | GSE119156 | GEO
Project description:The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) is not completely understood, particularly at the molecular level. We studied gene expression in normal, pre-malignant (cirrhosis), and tumor (HCC) liver tissues using Affymetrix GeneChips. Experiment Overall Design: Liver tissue samples were obtained from patients waiting for liver transplantation at one of the GR2HCC Centers. Additionally, normal liver and tumor samples were also obtained from the Liver Tissue Cell Distribution System. For each sample, RNA was extracted and hybridized to an Affymetrix GeneChip.
2009-01-18 | E-GEOD-14323 | biostudies-arrayexpress
Project description:The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) is not completely understood, particularly at the molecular level. We studied gene expression in normal, pre-malignant (cirrhosis), and tumor (HCC) liver tissues using Affymetrix GeneChips. Keywords: cross-sectional
2009-01-08 | GSE14323 | GEO
Project description:Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy. 43 tumor (JT) and 44 non-tumor (JNT) liver tissues surgically resected from patients with HCV-associated hepatocellular carcinoma; 8 non-tumor liver tissues (control samples, JC) surgically resected from HCV- or HBV-free patients with metastatic liver tumor. Inter-batch normalization was carried out using Distance Weighted Discrimination procedure. The supplementary file 'GSE17856_Readme.txt' contains a description of the replicates used for normalization. The 'GSE17856_US14702406_2514850*' files are the raw data files for the replicates.
2010-04-14 | E-GEOD-17856 | biostudies-arrayexpress
Project description:Background/Aims: Recurrence-free survival (RFS) following curative resection of hepatocellular carcinoma (HCC) in subjects with hepatitis C virus (HCV) infection is highly variable. Traditional clinico-pathological endpoints are recognized as weak predictors of RFS. It has been suggested that gene expression profiling of HCC and nontumoral liver tissue may improve prediction of RFS, aid in understanding of the underlying liver disease, and guide individualized therapy. The goal of this study was to create a gene expression predictor of HCC recurrence in subjects with HCV. Methods: Frozen samples of the tumors and nontumoral liver were obtained from 47 subjects with HCV-associated HCC. Additional nontumoral liver samples were obtained from HCV-free subjects with metastatic liver tumors. Gene expression profiling data was used to determine the molecular signature of HCV-associated HCC and to develop a predictor of RFS. Results: The molecular profile of the HCV-associated HCC confirmed central roles for MYC and TGF-beta1 in liver tumor development. Gene expression in tumors was found to have poor predictive power with regards to RFS, but analysis of nontumoral tissues yielded a strong predictor for RFS in late-recurring (>1 year) subjects. Importantly, nontumoral tissue-derived gene expression predictor of RFS was highly significant in both univariable and multivariable Cox proportional hazard model analyses. Conclusions: Microarray analysis of the nontumoral tissues from subjects with HCV-associated HCC delivers novel molecular signatures of RFS, especially among the late-recurrence subjects. The gene expression signature of the predictor gives important insights into the pathobiology of HCC recurrence and used in design of the individualized therapy.
2010-04-14 | GSE17856 | GEO
Project description:Chronic hepatitis C (CHC) is one of the major risk factor for the progressive development of end stage liver diseases including liver cirrhosis (LC) and HCC worldwide. A deep insight into the molecular mechanism of development and progression of liver fibrosis into cirrhosis and HCC following chronic HCV infection leads to characterization of multiple cellular processes and the underlying regulatory mechanisms. Non-coding RNAs (sncRNAs) including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are found to be the prime regulators of multiple cellular pathways. Using such tools several studies have identified myriads of differentially regulated non-coding RNAs and genes in HCV disease progression to HCC. Our study attempted to look into the integrative network of regulatory non-coding RNAs and target genes involved in HCV related HCC and thereby identify a potential diagnostic molecule as well as therapeutic target for HCC surveillance and management.
2019-11-23 | GSE140845 | GEO
Project description:Little is known on the immune status in liver and blood of chronic HCV patients long after therapy-induced viral clearance. In this study, we demonstrate that 4 years after clearance, regulation of HCV-specific immunity in blood by regulatory T-cells (Treg) and the immunosuppressive cytokines IL-10 and TGF-β is still ongoing. Importantly, sampling of the liver 4 years after clearance shows that intrahepatic Treg are still present in all patients, suggesting that liver T-cells remain regulated. Identifying mechanisms that regulate HCV-specific memory T-cell responses after clearance is highly relevant for the development of protective vaccines, especially in patients at high-risk of reinfection. A genome-wide gene expression analysis was performed on a blood cohort of 5 chronic HCV patients. For each patient, blood was collected at 4 years after ending of HCV therapy, and blood transcriptomes was compared to the paired transcriptomes at baseline and 24 weeks after ending HCV therapy (GSE59312).
2015-04-06 | E-GEOD-64603 | biostudies-arrayexpress
Project description:Gene expression profiling of hepatocellular carcinoma (HCC) and background liver has been studied extensively; however, the relationship between the gene expression profiles of different lesions has not been assessed. We examined the expression profiles of 34 HCC specimens (17 hepatitis B virus [HBV]-related and 17 hepatitis C virus [HCV]-related) and 71 non-tumor liver specimens (36 chronic hepatitis B [CH-B] and 35 chronic hepatitis C [CH-C]) using an in-house cDNA microarray consisting of liver-predominant genes. Graphical Gaussian modeling (GGM) was applied to elucidate the interactions of gene clusters among the HCC and non-tumor lesions. Gene expression profiling of HCC and non-tumor lesions revealed the predisposing changes of gene expression in HCC. This approach has potential for the early diagnosis and possible prevention of HCC. We examined the expression profiles of 34 HCC specimens (17 hepatitis B virus [HBV]-related and 17 hepatitis C virus [HCV]-related) and 71 non-tumor liver specimens (36 chronic hepatitis B [CH-B] and 35 chronic hepatitis C [CH-C]) using an in-house cDNA microarray consisting of liver-predominant genes. Graphical Gaussian modeling (GGM) was applied to elucidate the interactions of gene clusters among the HCC and non-tumor lesions.
2013-11-14 | E-GEOD-44074 | biostudies-arrayexpress