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Integrative analysis reveals novel driver genes and molecular subclasses of hepatocellular carcinoma.


ABSTRACT: Hepatocellular carcinoma (HCC) is a heterogeneous disease with various genetic and epigenetic abnormalities. Previous studies of HCC driver genes were primarily based on frequency of mutations and copy number alterations. Here, we performed an integrative analysis of genomic and epigenomic data from 377 HCC patients to identify driver genes that regulate gene expression in HCC. This integrative approach has significant advantages over single-platform analyses for identifying cancer drivers. Using this approach, HCC tissues were divided into four subgroups, based on expression of the transcription factor E2F and the mutation status of TP53. HCC tissues with E2F overexpression and TP53 mutation had the highest cell cycle activity, indicating a synergistic effect of E2F and TP53. We found that overexpression of the identified driver genes, stratifin (SFN) and SPP1, correlates with tumor grade and poor survival in HCC and promotes HCC cell proliferation. These findings indicate SFN and SPP1 function as oncogenes in HCC and highlight the important role of enhancers in the regulation of gene expression in HCC.

SUBMITTER: Yang L 

PROVIDER: S-EPMC7762459 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Integrative analysis reveals novel driver genes and molecular subclasses of hepatocellular carcinoma.

Yang Liguang L   Zhang Zhengtao Z   Sun Yidi Y   Pang Shichao S   Yao Qianlan Q   Lin Ping P   Cheng Jinming J   Li Jia J   Ding Guohui G   Hui Lijian L   Li Yixue Y   Li Hong H  

Aging 20201120 23


Hepatocellular carcinoma (HCC) is a heterogeneous disease with various genetic and epigenetic abnormalities. Previous studies of HCC driver genes were primarily based on frequency of mutations and copy number alterations. Here, we performed an integrative analysis of genomic and epigenomic data from 377 HCC patients to identify driver genes that regulate gene expression in HCC. This integrative approach has significant advantages over single-platform analyses for identifying cancer drivers. Usin  ...[more]

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