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Transcriptome sequencing of human hepatocellular carcinoma

ABSTRACT: Deep high-throughput transcriptome sequencing (RNA-seq) performed on 3 pairs of matched tumor and adjacent non-tumorours (NT) tissues from HCC patients of Chinese origin generated 183.6-million reads that could be aligned. We discovered a number of differentially expressed genes and multiple types of somatic single nucleotide variations (SNVs) in expressed genes. After the removal of the error alignments, high-quality reads were mapped to the human reference sequence (GRCh37/hg19) using three different softwares TopHat, Burrows-Wheeler Aligner (BWA) and CLC Genomics Workbench (CLC). The high-quality variants were identified using VarScan with the following parameters: minimum coverage depth of 10, variation frequency of more than 30% and base quality of more than 15. A total of 568, 545 and 494 potential somatic single nucleotide variants (SNVs), including 94, 89 and 101 coding somatic SNVs (cSNVs), were identified in 3 tumor samples HCC448T, HCC473T and HCC510T, respectively. Validation analysis was carried out for 10 of the intersected cSNVs (all are non-synonymous substitutions) within selected genes of interests with the majority confirmed. Examination of 3 paired human hepatocellular carcinoma and matched non-tumor tissues

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PROVIDER: S-DIXA-D-1107 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:BACKGROUND:Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC. METHODS:Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed. RESULTS:Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis. CONCLUSIONS:Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

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Transcriptome sequencing of human hepatocellular carcinoma

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