Zhang L, Yuan Y, Lu KH, Zhang L. Identification of recurrent focal copy number variations and their putative targeted driver genes in ovarian cancer.
BMC Bioinformatics 2016;
17:222. [PMID:
27230211 PMCID:
PMC4881176 DOI:
10.1186/s12859-016-1085-7]
[Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Accepted: 05/14/2016] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND
Genomic regions with recurrent DNA copy number variations (CNVs) are generally believed to encode oncogenes and tumor suppressor genes (TSGs) that drive cancer growth. However, it remains a challenge to delineate the key cancer driver genes from the regions encoding a large number of genes.
RESULTS
In this study, we developed a new approach to CNV analysis based on spectral decomposition of CNV profiles into focal CNVs and broad CNVs. We performed an analysis of CNV data of 587 serous ovarian cancer samples on multiple platforms. We identified a number of novel focal regions, such as focal gain of ESR1, focal loss of LSAMP, prognostic site at 3q26.2 and losses of sub-telomere regions in multiple chromosomes. Furthermore, we performed network modularity analysis to examine the relationships among genes encoded in the focal CNV regions. Our results also showed that the recurrent focal gains were significantly associated with the known oncogenes and recurrent losses associated with TSGs and the CNVs had a greater effect on the mRNA expression of the driver genes than that of the non-driver genes.
CONCLUSIONS
Our results demonstrate that spectral decomposition of CNV profiles offers a new way of understanding the role of CNVs in cancer.
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