Journal
ONCOTARGET
Volume 7, Issue 48, Pages 78841-78849Publisher
IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.12879
Keywords
comparative network analysis; protein interaction networks; prioritization of cancer genes; network centrality; systems biology
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Funding
- Cancer Prevention and Research Institute of Texas (CPRIT) [RR160021]
- University of Texas System Rising STARs award
- NIH/NCI [P30CA016672]
- University Center Foundation via the Institutional Research Grant program at the University of Texas MD Anderson Cancer Center
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Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.
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