Dataset Information

RNA-Seq analyses generate comprehensive transcriptomic landscape and reveal complex transcript patterns in hepatocellular carcinoma.

ABSTRACT: RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3-24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels.

SUBMITTER: Huang Q

PROVIDER: S-EPMC3197143 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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RNA-Seq analyses generate comprehensive transcriptomic landscape and reveal complex transcript patterns in hepatocellular carcinoma.

Huang Qichao Q Lin Biaoyang B Liu Hanqiang H Ma Xi X Mo Fan F Yu Wei W Li Lisha L Li Hongwei H Tian Tian T Wu Dong D Shen Feng F Xing Jinliang J Chen Zhi-Nan ZN

PloS one 20111017 10

RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million ...[more]

PMID: 22043308

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Project description:BackgroundThe expression of microRNAs (miRNAs) is a promising prognostic and diagnostic tool in hepatocellular carcinoma (HCC). Here we performed small RNA sequencing (sRNA-seq) of tissue, serum and serum exosomes to investigate changes in miRNA expression between the different sample types and correlated the expression with clinical parameters. We also performed gene expression arrays on tumor and normal tissue.ResultsPaired tissue, serum and serum exosomes sequencing revealed consistent positive correlation of miR-21 between serum exosomes and tumor tissue, indicating that miR-21 could be exported from tissue to circulation via exosomes. We found that let-7 miRNAs are generally upregulated in serum exosomes compared to whole serum, indicating that these miRNAs could be preferentially loaded into exosomes. Comparing serum from HCC patients with serum from healthy individuals revealed a global increase of miRNAs in serum from HCC patients, including an almost 4-fold increase of several miRNAs, including the liver-specific miR-122. When correlating miRNA expression with clinical parameters we detected significant association between hepatitis B virus (HBV) infection and miR-122 in serum as well as several serum and tissue-miRNAs that correlated with surgery type. We found that miR-141 and miR-146 correlated with cirrhosis in tumor tissue and normal tissue, respectively. Finally, high expression of miR-21 in tumors were associated with poor survival. Focusing on gene expression we found several significant messenger RNAs (mRNAs) between tumor and normal tissue and a Gene Ontology (GO) analysis revealed that these changes were mainly related to cell cycle and metabolism. Further, we detected mRNAs that correlated with cirrhosis and HBV infection in tissue. Finally, GO analysis of predicted targets for miRNAs down-regulated in tumor found that these were enriched for functions related to collagen synthesis.ConclusionsOur combined data point to altered miRNA and mRNA expression contributing to both generally impaired lipid metabolism and increased cell proliferation and a miRNA-driven increase in collagen synthesis in HCC. Our results further indicate a correlation in miRNA expression between exosomes, serum, and tissue samples suggesting export from tumors via exosomes. This correlation could provide a basis for a more tumor-specific miRNA profile in serum.

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.MethodsWe first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.ResultsWith the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The 'upregulated' ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the 'downregulated' network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.ConclusionsIn conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Dataset Information

RNA-Seq analyses generate comprehensive transcriptomic landscape and reveal complex transcript patterns in hepatocellular carcinoma.

Publications

RNA-Seq analyses generate comprehensive transcriptomic landscape and reveal complex transcript patterns in hepatocellular carcinoma.

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