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Transcription profiling by array of human hepatocellular carcinomas with hepatitis C virus etiology

ABSTRACT: To characterize the genetic alterations that instigate hepatitis C virus-induced hepatocellular carcinoma (HCC), we conducted an integrative genomic analysis of 103 HCCs. Most tumors harbored 1q gain, 8q gain or 8p loss, with occasional alterations in 13 additional chromosome arms. In addition to amplifications at 11q13 in 6 tumors, 4 tumors harbored focal gains at 6p21 incorporating VEGFA, which were confirmed in 4 of 113 HCC in an independent validation set. Strikingly, this locus overlapped with copy gains in 4 of 371 lung adenocarcinomas. Overexpression of VEGFA via 6p21 gain suggested a cell-nonautonomous mechanism of oncogene activation. Hierarchical clustering of gene expression among 91 tumors identified 5 classes, including 'Wnt-CTNNB1', 'proliferation' and 'nterferon-related' gene classes. We also discovered a novel class defined by polysomy of chromosome 7, gains of which were associated with early tumor recurrence after resection. These findings reveal key alterations in HCC pathogenesis and implicate potential therapeutic targets. Experiment Overall Design: 91 hepatocellular carcinomas were obtained at the time of surgical resection or orthotopic transplantation.

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PROVIDER: S-DIXA-D-1178 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes’. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform. 16 IDC samples analyzed with the U133 Plus 2.0 array compared to 4 normal control samples.

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Transcription profiling by array of human hepatocellular carcinomas with hepatitis C virus etiology

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