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Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE38326 | GEO | 2013/05/22

SECONDARY ACCESSION(S): PRJNA167678

REPOSITORIES: GEO

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Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2013-05-22 | E-GEOD-38326 | biostudies-arrayexpress

Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma [tumor]

Project description:Cancer is a genetic disease with frequent somatic alterations in DNA. Study of recurrent copy number aberrations (CNAs) in human cancers would enable the elucidation of disease mechanisms and the identification of key oncogenic drivers with causal roles in oncogenesis. We have comprehensively and systematically characterized CNAs and accompanied gene expression changes in the tumors and their matched non-tumor liver tissues from 286 hepatocellular carcinoma (HCC) patients. Our analysis identified 29 recurrently amplified regions and 22 deleted regions with a high level of copy number changes, harboring established oncogenes and tumor suppressors, including CCND1, MET, CDKN2A and CDKN2B, as well as many other genes not previously reported to be involved in liver carcinogenesis. Cis-acting genes in the amplification and deletion peaks were enriched in core cancer pathways, including cell cycle, p53, PI3K, MAPK, Wnt and TGFβ signaling in large proportions of HCCs. We further validated two candidate driver genes, BCL9 and MTDH, from the recurrent focal amplification peaks and showed that they play a significant role in HCC growth and survival. In summary, we have demonstrated that characterizing the CNA landscape in HCC will facilitate the understanding of disease mechanisms and the identification of oncogenic drivers that may serve as potential therapeutic targets for the treatment of this devastating disease. Two hundred and eighty-six hepatocellular carcinoma tumors and their matched non-tumor adjacent liver tissue samples were genotyped using Illumina HumanOmni1-Quad BeadChip to estimate their somatic copy number profiles.

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Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma [cell line]

Project description:Cancer is a genetic disease with frequent somatic alterations in DNA. Study of recurrent copy number aberrations (CNAs) in human cancers would enable the elucidation of disease mechanisms and the identification of key oncogenic drivers with causal roles in oncogenesis. We have comprehensively and systematically characterized CNAs and accompanied gene expression changes in the tumors and their matched non-tumor liver tissues from 286 hepatocellular carcinoma (HCC) patients. Our analysis identified 29 recurrently amplified regions and 22 deleted regions with a high level of copy number changes, harboring established oncogenes and tumor suppressors, including CCND1, MET, CDKN2A and CDKN2B, as well as many other genes not previously reported to be involved in liver carcinogenesis. Cis-acting genes in the amplification and deletion peaks were enriched in core cancer pathways, including cell cycle, p53, PI3K, MAPK, Wnt and TGFβ signaling in large proportions of HCCs. We further validated two candidate driver genes, BCL9 and MTDH, from the recurrent focal amplification peaks and showed that they play a significant role in HCC growth and survival. In summary, we have demonstrated that characterizing the CNA landscape in HCC will facilitate the understanding of disease mechanisms and the identification of oncogenic drivers that may serve as potential therapeutic targets for the treatment of this devastating disease. Thirty hepatocellular carcinoma cell lines were genotyped using Illumina HumanOmni1-Quad BeadChip to estimate their copy number profiles relative to pooled Hapmap samples.

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Genomic landscape of copy number aberrations enables the identification of oncogenic drivers in hepatocellular carcinoma [tumor]

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