Project description: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 HCC has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from Chinese HBV-related hepatocelluar carcinoma patients using 36bp single-end sequencing approach 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, from by far the largest database of transcripts expressed in HCC tissues, 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 levels 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 (ATPase family, AAA domain containing 2) gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of the 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. A comprehensive analysis of transcriptome for 10 match-paired HBV-related Chinese HCC and non-cancerous adjacent tissues. Processed data files: Exon-level results, gene-level results, differentially expressed exons, and differently expressed genes (DEGs).

Project description: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 HCC has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from Chinese HBV-related hepatocelluar carcinoma patients using 36bp single-end sequencing approach 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, from by far the largest database of transcripts expressed in HCC tissues, 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 levels 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 (ATPase family, AAA domain containing 2) gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of the 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.

Project description:Purpose: Aberrantly methylated DNA are hallmarks for many cancers, HCC included. Tumor shed its DNA into circulation stream, and serum DNA methylation analysis is a less-invasive and accessable way to judge the primary tumor status. The goals of this study are to compare DNA methylation profiling in serum cell-free DNA from different stages of HCC progression including healthy control, chronic HBV carrier, HBV-related liver Cirrhosis and HCC, to establish HCC development-related aberrnat DNA methylation patterns. Methods: MBD methylCap/seq was carried out to screen differentially methylated CpG islands in serum cell-free DNA on four different stage of HBV-related HCC development. MSP and multiplex-BSP validation was performed using independent serum DNA or tumor and adjacent tissues. Results: Using a MBD methylCap/seq platform, we produced 33- to 37- million raw reads per sample and mapped them, in about half of the raw reads, to human genome(build h19) in the serum cf DNA of healthy control, HBV carrier, HBV cirrhosis and HCC. The mapped reads formed 180k to 260k peaks per sample, with 160 k common peaks shared by four samples. After subtraction of the common peaks, there left 51k, 107k and 78 k DMRs representing hypermethylations, in HBV carrier, HBV cirrhosis and HCC, respectively. We define those DMRs as early, middle and late when these DMRS occurred and maintained in HBV carrier, HBV cirrhosis and HCC, which including 27k, 24k and 19k DMRs, corresponding to 1,416, 1,337, 1,006 genes. GO analysis of them revealed gene categories and pathways associated with tumorogenenisis related process Conclusions: Our study represents the first detailed analysis of serum cf-DNA methylation profiling in the progression of HBV related HCC development. The processed data analysis here offers a comprehensive evaluation of DNA methylation in serum cf DNA. We conclude that MBD methylCap/seq based methylation profiling would benefit epigenetic research in HCC.

Dataset Information

Comprehensive analysis of the miRNA profile between HBV-related Hepatocellular carcinoma (HBCC) and no HBV-related Hepatocellular carcinoma (HNCC)

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