Research Papers:
Validation of a multi-omics strategy for prioritizing personalized candidate driver genes
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Abstract
Li Liang1,*, Liting Song1,*, Yi Yang1, Ling Tian1, Xiaoyuan Li2, Songfeng Wu3, Wenxun Huang1, Hong Ren1, Ni Tang1, Keyue Ding1
1Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, 400010 PR China
2Department of Medical Oncology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, 100730 P.R. China
3State Key Laboratory of Proteomics, National Protein Science Beijing Center, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing, 102206 P.R. China
*These authors contributed equally to this work
Correspondence to:
Ni Tang, email: [email protected]
Keyue Ding, email: [email protected]
Keywords: personalized mutation-driver genes, multi-omics, validation, structure-function relationship, in vitro experiment
Received: February 11, 2016 Accepted: May 08, 2016 Published: May 21, 2016
ABSTRACT
Significant heterogeneity between different tumors prevents the discovery of cancer driver genes, especially in a patient-specific manner. We previously prioritized five personalized candidate mutation-driver genes in a hyper-mutated hepatocellular carcinoma patient using a multi-omics strategy. However, the roles of the prioritized driver genes and patient-specific mutations in hepatocarcinogenesis are unclear. We investigated the impact of the tumor-mutated allele on structure-function relationship of the encoded protein and assessed both loss- and gain-of-function of these genes and mutations on hepatoma cell behaviors in vitro. The prioritized mutation-driver genes act as tumor suppressor genes and inhibit cell proliferation and migration. In addition, the loss-of-function effect of the patient-specific mutations promoted cell proliferation and migration. Of note, the HNF1A S247T mutation significantly reduced the HNF1A transcriptional activity for hepatocyte nuclear factor 4 alpha (HNF4A) but did not disrupt nuclear localization of HNF1A. The results provide evidence for supporting the validity of our proposed multi-omics strategy, which supplies a new avenue for prioritizing mutation-drivers towards personalized cancer therapy.
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