Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer

Wrzeszczynski, K. O., Varadan, V., Byrnes, J., Lum, E., Kamalakaran, S., Levine, D. A., Dimitrova, N., Zhang, M. Q., Lucito, R. (December 2011) Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer. PLoS ONE, 6 (12). ISSN 1932-6203

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DOI: e28503 10.1371/journal.pone.0028503

Abstract

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.

Item Type: Paper
Uncontrolled Keywords: oligonucleotide microarray analysis circular binary segmentation high resolution method copy number breast cancer dna methylation gene expression hypermethylation hybridization carcinomas
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > DNA methylation
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > copy number variants
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > epigenetics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > epigenetics
diseases & disorders > cancer > cancer types > ovarian cancer
CSHL Authors:
Communities: CSHL Cancer Center Program > Cancer Genetics
CSHL labs > Lucito lab
CSHL labs > Zhang lab
Depositing User: Brian Soldo
Date: December 2011
Date Deposited: 29 Mar 2012 14:16
Last Modified: 28 Feb 2018 17:32
PMCID: PMC3234280
Related URLs:
URI: https://repository.cshl.edu/id/eprint/25534

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