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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 |

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Transcriptome sequencing of human hepatocellular carcinoma

Project description: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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Transcriptome sequencing of human hepatocellular carcinoma

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Integrative Transcriptome Analysis Reveals Common Molecular Subtypes of Human Hepatocellular Carcinoma

Project description: Not available

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Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma.

Project description:Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum alpha-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of beta-catenin mutation but rather was the result of transforming growth factor-beta activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene expression profiles and highlight the power of integrating multiple data sets to define a robust molecular taxonomy of the disease.

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Project description:Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis. Differentially expressed protein-coding genes were subjected to transcriptome sequencing in 11 pairs of liver cancer tissue and matched adjacent non-cancerous tissue. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. Hub genes were identified via centralities analysis and verified using published datasets. In total, 720 significantly differentially expressed protein-coding genes were identified in the samples, including 335 upregulated genes and 385 downregulated genes. The upregulated genes were significantly enriched in cell adhesion, biological adhesion and cell-cell adhesion GO terms under biological process (BP). Conversely, the downregulated genes were significantly enriched in embryonic organ morphogenesis, embryonic organ development and embryonic morphogenesis. The KEGG pathway analysis showed that the upregulated genes were enriched in ECM-receptor interaction and focal adhesion pathways. Furthermore, the downregulated genes were enriched in the ErbB, VEGF and MAPK signaling pathways. The PPI network and centralities analysis suggested that ITGA2 and 12 alternate genes were significant hub genes. These findings improve current understanding of the molecular mechanisms underlying HCC development and may be helpful in identifying candidate molecular biomarkers for use in diagnosing, treating and monitoring the prognosis of HCC.

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Project description:Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and it remains a challenge to understand the genetic mechanisms underlying hepatocarcinogenesis. A global gene network of differential expression profiles in HCC has yet to be fully characterized. In the present study, we performed transcriptome sequencing (mRNA and lncRNA) in liver cancer and cirrhotic tissues of nine HCC patients. We identified differentially expressed genes (DEGs) and constructed a weighted gene co-expression network for the DEGs. In total, 755 DEGs (747 mRNA and eight lncRNA) were identified, and several co-expression modules were significantly associated with HCC clinical traits, including tumor location, tumor grade, and the α-fetoprotein (AFP) level. Of note, we identified 15 hub genes in the module associated with AFP level, and three (SPX, AFP and ADGRE1) of four hub genes were validated in an independent HCC cohort (n=78). Identification of hub genes for HCC clinical traits has implications for further understanding of the molecular genetic basis of HCC.

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