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.
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.
Project description:Background: Several studies have investigated the association of miRNAs with hepatocellular carcinoma (HCC) but the data are not univocal. Methods: We performed a microarray study of miRNAs in hepatitis C virus (HCV)-associated HCC and other liver diseases and healthy conditions. Results and Conclusions: The simultaneous comparison of different liver diseases and normal livers allowed the identification of 18 miRNAs exclusively expressed in HCV-associated HCC, with sensitivity and specificity values of diagnostic-grade. A total number of 76 liver specimens obtained from 43 patients were analyzed: 26 liver specimens obtained from 10 patients with HCV-associated HCC, including 9 specimens from the tumor area (HCC) and 17 specimens from the surrounding non-tumorous tissue affected by cirrhosis (HCC-CIR); 18 specimens from 10 patients with HCV-associated cirrhosis without HCC (CIR); 13 specimens from 4 patients with HBV-associated acute liver failure (ALF); 12 specimens from 12 liver donors (LD); and 7 from normal liver of 7 subjects who underwent hepatic resection for liver angioma (NL).
Project description:We applied small RNA Solexa sequencing technology to identify microRNA expression in human liver samples from surgically removed liver tissues including three normal liver tissues (distal normal liver tissue of liver hemangioma), an hepatitis B virus (HBV)-infected liver, a severe chronic hepatitis B liver, two HBV-related hepatocellular carcinoma (HCC), an hepatitis C virus (HCV)-related HCC, and an HCC without HBV or HCV infection. All samples were collected with the informed consent of the patients and the experiments were approved by the ethics committee of Second Military Medical University, Shanghai, China. We investigated the miRNome in human normal liver and suggested some deregulated abundantly expressed microRNAs in HCC. center_name: National Key Laboratory of Medical Immunology & Institute of Immunology, Second Military Medical University, Shanghai, China.
Project description:We applied small RNA Solexa sequencing technology to identify microRNA expression in human liver samples from surgically removed liver tissues including three normal liver tissues (distal normal liver tissue of liver hemangioma), an hepatitis B virus (HBV)-infected liver, a severe chronic hepatitis B liver, two HBV-related hepatocellular carcinoma (HCC), an hepatitis C virus (HCV)-related HCC, and an HCC without HBV or HCV infection. All samples were collected with the informed consent of the patients and the experiments were approved by the ethics committee of Second Military Medical University, Shanghai, China. We investigated the miRNome in human normal liver and suggested some deregulated abundantly expressed microRNAs in HCC. center_name: National Key Laboratory of Medical Immunology & Institute of Immunology, Second Military Medical University, Shanghai, China. Examination of miRNome in human liver samples from surgically removed liver tissues including three normal liver tissues (distal normal liver tissue of liver hemangioma), an hepatitis B virus (HBV)-infected liver tissue, a severe chronic hepatitis B liver tissue, an HBV-related hepatocellular carcinoma (HCC) tissue and adjacent liver tissues of different regions,an HBV-related HCC tissue and adjacent liver tissue, an hepatitis C virus (HCV)-related HCC tissue and adjacent liver tissue, and an HCC without HBV or HCV infection and adjacent liver tissue. All 15 human liver tissue samples.
Project description:Liver cancer was the fourth leading cause of cancer-related deaths worldwide in 2018, of which Hepatocellular carcinoma accounts for 75-85% of all liver cancers and is therefore the most common type of liver cancer. In this study, total RNA were extracted from sections of formalin-fixed paraffin embedded (FFPE) archival human liver biopsies from 24 patients, including ten HCV-associated HCC (HCV-HCC), ten virus-unrelated HCC (VU-HCC) and four normal liver patients. By comparing the expression profiles of HCV-HCC and VU-HCC to that of the normal liver biopsies respectively, 18 lncRNAs were identified to be differentially expressed.
Project description:Chronic infections by hepatitis B virus (HBV) and hepatitis C virus (HCV) appear to be the most significant causes of hepatocellular carcinoma (HCC). Aberrant promoter methylation is known to be deeply involved in cancer, including HCC. In this study, we analyzed aberrant promoter methylation on genome-wide scale in 6 HCCs including 3 HBV-related and 3 HCV-related HCCs, 6 matched noncancerous liver tissues and 3 normal liver tissues by methylated DNA immunoprecipitation-on-chip analysis. Candidate genes with promoter methylation were detected more frequently in HCV-related HCC. Candidate genes methylated preferentially to HBV-related or HCV-related HCCs were detected and selected, and methylation levels of the selected genes were validated using 125 liver tissue samples, including 61 HCCs (28 HBV-related HCCs and 33 HCV-related HCCs) and matched 59 matched noncancerous livers, and 5 normal livers, by quantitative methylation analysis using MALDI-TOF mass spectrometry. Among analyzed genes, preferential methylation in HBV-related HCC was validated in 1 gene only. However, 15 genes were found methylated preferentially in HCV-related HCC, which was independent from age. Hierarchical clustering of HCC using these 15 genes stratified HCV-related HCC as a cluster of frequently methylated samples. The 15 genes included genes inhibitory to cancer-related signaling such as RAS/RAF/ERK and Wnt/b-catenin pathways. It was indicated that genes methylated preferentially in HCV-related HCC exist, and it was suggested that DNA methylation might play an important role in HCV-related HCC by silencing cancer-related pathway inhibitors.