Expression profiling of HCC patients with different recurrent-free survival time
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE11260 | GEO | 2009/04/24
SECONDARY ACCESSION(S): PRJNA106773
REPOSITORIES: GEO
Similar Datasets
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:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design
2008-01-14 | GSE6857 | 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.
2010-04-14 | GSE17856 | GEO
Project description:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design Gene expression profiles were conducted in primary HCC and corresponding noncancerous hepatic tissues from 244 Chinese HCC patients. A total of 134 well-defined cases were used as a training group. Among them, 30 had primary HCC lesions accompanied by tumor emboli and 104 had solitary HCC with no metastasis/recurrence found at follow-up (3 yr). We used a testing group of 110 independent cases. The testing cases included 43 multinodular and 67 solitary HCC. In addition, eight normal liver tissues from disease-free patients were included as normal controls. In the analysis of the 244 HCC cases, RNA was isolated in a pairwise fashion from tumor or non-tumor tissue and samples were selected in random order for miRNA analysis to avoid grouping bias.
2008-01-14 | E-GEOD-6857 | biostudies-arrayexpress
Project description:CTNNB1 is the most frequently mutated gene in hepatocellular carcinoma (HCC). However, its clinical relevance remains controversial. We determined an evolutionarily conserved β-catenin signature by comparative analysis of gene expression data from human HCC and a mouse model (GSE43628). We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for prognosis of HCC after surgery. We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment.
2015-05-21 | E-GEOD-43619 | biostudies-arrayexpress
Project description:CTNNB1 is the most frequently mutated gene in hepatocellular carcinoma (HCC). However, its clinical relevance remains controversial. We determined an evolutionarily conserved β-catenin signature by comparative analysis of gene expression data from human HCC and a mouse model (GSE43628). We generated gene expression data from the tumors of 88 HCC patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for prognosis of HCC after surgery.
2015-05-21 | GSE43619 | GEO
Project description:BACKGROUND & AIMS: Expression of microRNAs (miRNAs) in metastatic foci of hepatocellular carcinoma (HCC) is unknown. We identified metastasis-related miRNAs in recurrent cases after living donor liver transplantation (LDLT). Methods: We performed a comprehensive analysis of primary HCC (T), noncancerous liver (N), and resected recurrent (metastatic) HCC (M) using microarray analyses to identify metastasis-related miRNAs in in three patients with post-transplant recurrence. The RNA samples from three cases that underwent resection of recurrences after LDLT were made available for miRNA microarray analysis. The three cases included a 57-year-old man (case 1) with peritoneal recurrence and infected by hepatitis B virus (HBV), and a 48-year-old woman (case 2) and a 51-year-old man (case 3) with lung recurrences and hepatitis C virus (HCV) infection. Microarray analysis was performed for each RNA sample from the (T), (N) in the explanted liver, and (M). A sample containing equal amounts of RNAs from histologically normal livers of three living donors (NL: normal liver) was analyzed as a control. The RNA samples from three cases that underwent resection of recurrences after living donor liver transplantation were made available for microRNA microarray analysis. Microarray analysis was performed for each RNA sample from the primary HCC (T), noncancerous liver (N) in the explanted liver, and resected recurrent metastatic HCC (M). A sample containing equal amounts of RNAs from histologically normal livers of three living donors (NL: normal liver) was analyzed as a control.
2013-10-25 | E-GEOD-41874 | biostudies-arrayexpress
Project description:While we and others have uncovered and validated several genomic predictors for metastatic recurrences, a molecular or genomic predictor that can reliably identify high-risk patients for late de novo recurrence has not been firmly established. We analyzed previously reported gene expression data from human livers that underwent partial hepatectomy or transplantation, which were representative physiological conditions that trigger liver regeneration signals. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 hepatocellular carcinoma (HCC) patients who underwent surgical resection as the primary treatment. We used these gene expression data to develop a new prognostification model for recurrence of HCC after surgery. We generated gene expression data from tumor and matched non-tumor surrounding tissues of 72 HCC patients who underwent surgical resection as the primary treatment.
2014-11-03 | E-GEOD-39791 | biostudies-arrayexpress
Project description:Tumor samples and matching healthy tissue from 23 human hepatocellular carcinoma (HCC) patients and one hepatocellular adenoma patient were collected after surgical resection. Total RNA was harvested and sequenced with a strand-specific single-end RNA-seq protocol.
2021-12-23 | E-MTAB-8915 | biostudies-arrayexpress
Project description:BACKGROUND & AIMS: Expression of microRNAs (miRNAs) in metastatic foci of hepatocellular carcinoma (HCC) is unknown. We identified metastasis-related miRNAs in recurrent cases after living donor liver transplantation (LDLT). Methods: We performed a comprehensive analysis of primary HCC (T), noncancerous liver (N), and resected recurrent (metastatic) HCC (M) using microarray analyses to identify metastasis-related miRNAs in in three patients with post-transplant recurrence. The RNA samples from three cases that underwent resection of recurrences after LDLT were made available for miRNA microarray analysis. The three cases included a 57-year-old man (case 1) with peritoneal recurrence and infected by hepatitis B virus (HBV), and a 48-year-old woman (case 2) and a 51-year-old man (case 3) with lung recurrences and hepatitis C virus (HCV) infection. Microarray analysis was performed for each RNA sample from the (T), (N) in the explanted liver, and (M). A sample containing equal amounts of RNAs from histologically normal livers of three living donors (NL: normal liver) was analyzed as a control.
2013-10-25 | GSE41874 | GEO