Study of gene expression of human liver Hepatocellular carcinoma
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE25097 | GEO | 2011/07/05
SECONDARY ACCESSION(S): PRJNA134719
REPOSITORIES: GEO
Similar Datasets
Project description:Hepatocellular carcinoma (HCC) affects millions of people worldwide and is a lethal malignancy for which there are no effective therapies. To identify prognostic gene markers for liver cancer, we conducted transcriptome profiling of frozen tissues (tumor and non-tumor) from 300 early-to-advanced stage HCCs plus 40 cirrhotic and 6 normal livers. We have profiles 268 HCC tumor, 243 adjacent non-tumor, 40 cirrhotic and 6 healthy liver samples.
2011-07-05 | E-GEOD-25097 | biostudies-arrayexpress
Project description:<p>Despite the growing incidence of hepatocellular carcinoma (HCC) due to increased hepatitis C virus infection and non-alcoholic steatohepatitis in Western populations, the genetic determinants of this cancer have yet to be established. A minority (15-20%) of HCC occurs in livers without cirrhosis or other chronic disease. Because the liver is functionally preserved in these patients and surgical resection of the tumor may be performed safely, and because of the scarcity of livers available for transplantation, non-cirrhotic patients undergo surgical resection for HCC treatment. These resected tumors present investigatory opportunities in two ways: First, they provide tumor specimen which have not been treated with chemotherapy and embolization. Second, the absence of cirrhosis may provide an unconfounded background from which to investigate the genetic tumorigenesis of HCC. In livers with cirrhosis, genetic instability is prevalent as assessed by assays for microsatellite instability, loss of heterozygosity and aberrant DNA methylation. In contrast, in livers without cirrhosis, the non-tumor tissue surrounding HCC have been found to have fewer genetic aberrations. It has been postulated that the pathologic process of cirrhosis may result in the accumulation of many "passenger"; as well as "driver" mutations, and that the examination of the HCC cancer genome may be facilitated in non-cirrhotic livers because of the absence of an accumulated background noise of mutations.</p>
| phs001106 | dbGaP
Project description:Six frozen hepatocellular carcinoma (HCC) samples (three without cirrhotic and three with cirrhotic background) were selected to analyze the circRNA expression profile through circRNA-seq. A total of 20334 circRNAs were identified in these tumor tissues, which were widely distributed in all chromosomes. Differential analysis revealed that 393 were significantly dysregulated in non-cirrhotic HCC when compared with cirrhotic HCC tissues (log2(fold change) > 1 and p < 0.05). Our study undoubtedly provide a new insight in investigating the initiation of HCC.
2022-05-10 | GSE193862 | GEO
Project description:Fibrolamellar hepatocellular carcinoma (FLC) is a rare primary hepatic cancer usually developed in non-cirrhotic livers of children and young adults with unknown etiology. Treatment is limited to surgical intervention. To date, molecular pathogenesis of FLC has been poorly characterized. A cohort of FLCs was analyzed through SNP-array. GISTIC algorithm identified chromosomal aberrations. FLC tumors corresponding to 25 different patients. In all cases, tumor and corresponding non-tumor samples were frozen (-80°C) after hepatic resection at diagnosis. Comparative Genomic Hybridization analysis was done using Illumina HumanHap370CNV Genotyping BeadChip SNP array
2015-02-12 | E-GEOD-59443 | biostudies-arrayexpress
Project description:Gene expression, histone modification, DNA methylation, and DNA hydroxymethylation from normal, cirrhotic, and HCC livers
2018-09-09 | GSE112221 | GEO
Project description:A large fraction of HCC in Peru arises in younger, non-cirrhotic patients. Transcriptomic analysis of the HCC and non-tumor liver (NTL) tissues highlights a divergent gene expression profile that coincides with Amerind haplogrouping. This metagene is also associated with a peculiar molecular signature that does not conform with the current molecular classifications of HCCs. We used microarrays to compare gene expression between tumors and non-tumor counter parts in order to identify genes and ontologies that are differentially expressed.
2021-01-31 | GSE136247 | GEO
Project description:Hepatocellular carcinoma (HCC) remains a major health problem worldwide, and HCC patients have a poor prognostic outcome. In this study, we systematically disclose mechanisms of hepatocarcinogenesis, and also effectively identify and validate novel anticancer targets in HCCs. Keywords: disease state analysis total 58 cDNA microarrays, all experiment samples are hepatocellular carcinoma. RNAs from 33 corresponding noncancerous livers and 5 normal livers were used as the reference, respectively. The tumor samples were labeled with Cy5-dUTP.The nontumor samples were labeled with Cy3-dUTP.
2009-01-06 | E-GEOD-4108 | biostudies-arrayexpress
Project description:Introduction: Hepatocellular carcinoma (HCC) is one of the most aggressive solid tumors and oncogenic pathways (e.g Akt, IGF signaling) are often activated in high proliferating HCC. Among several genetic alterations, epigenetic changes seem to be involved in the development and progression of HCC. DNA hypermethylation of promoter regions is almost always associated with transcriptional silencing and can lead to inactivation of tumor suppressor genes (TSG) in cancer cells. Aim: (1) To identify genes differently methylated in a subclass of HCC associated with proliferation and, (2) To correlate methylation changes with activation of molecular pathways. Methods: gDNA of 20 HCC, 8 cirrhotic and 8 normal liver samples was extracted and the methylation status was detected by the Illumina HumanMethylation27 BeadChip and immunohistochemistry of p-AKT, pIGF IR, p-S6 was analyzed. Results: Unsupervised clustering clearly classified normal livers, cirrhosis and HCC in 3 different groups. 961 genes were significantly hypermethylated in HCC compared to cirrhotic and 3942 genes showed hypermethylation in cirrhotic compared to normal liver tissue. 163 genes showed stepwise significant hypermethylation from normal to cirrhotic to HCC, including well described (p16, SOCS2, SFRP5, RBP1) and potential (SRD5A2, PCDH8, IGF-1R, UCHL1) TSGs, and the miR-10a. 133 genes were specifically hypermethylated in HCC. Among them the transcription factors GATA2, DLX1, and KLF14, all significantly inversely correlated to gene expression (p=0.003, p=0.03, and p=0.007, respectively). The methylation status of SOCS2 (p=0.025) and DLX1 (p=0.025) was significantly correlated to phosphorylation of IGFR1. Samples with RBP1 hypermethylation showed significantly higher AFP serum levels (p=0.018). Conclusion: Whole genome methylation analysis markedly classifies normal, cirrhotic and HCC samples. 8 TSGs play a key role in this stepwise progression of hypermethylation in the development of HCC and could be a promising point of action in anticancer therapy. Genomic DNA extracted from fresh frozen tissue specimens and cell lines was hybridized to genome-wide mthylation beadarray after bisulphite treatment. Keywords: DNA methylation, hepatocellular carcinoma, tissue, cell line
2013-09-27 | E-GEOD-44970 | biostudies-arrayexpress
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.
2014-03-25 | E-GEOD-56140 | biostudies-arrayexpress
Project description:Most hepatocellular carcinomas in younger patients from Peru arise from non-cirrhotic livers. Histological examination of the non-tumor liver tissues highlights the presence of clear cell foci in a significant fraction of Peruvian patients with hepatocellular carcinoma. We used microarrays to compare gene expression between non-tumor liver tissues with and without clear cell foci and identified ontologies that are distinctively differentially expressed between subsets.
2018-08-29 | GSE111580 | GEO