Loss of DOK2 induces carboplatin resistance in ovarian cancer via suppression of apoptosis.

OBJECTIVE: Ovarian cancers are highly heterogeneous and while chemotherapy is the preferred treatment many patients are intrinsically resistant or quickly develop resistance. Furthermore, all tumors that recur ultimately become resistant. Recent evidence suggests that epigenetic deregulation may be a key factor in the onset and maintenance of chemoresistance. We set out to identify epigenetically silenced genes that affect chemoresistance. METHODS: The epigenomes of a total of 45 ovarian samples were analyzed to identify epigenetically altered genes that segregate with platinum response, and further filtered with expression data to identify genes that were suppressed. A tissue culture carboplatin resistance screen was utilized to functionally validate this set of candidate platinum resistance genes. RESULTS: Our screen correctly identified 19 genes that when suppressed altered the chemoresistance of the cells in culture. Of the genes identified in the screen we further characterized one gene, docking protein 2 (DOK2), an adapter protein downstream of tyrosine kinase, to determine if we could elucidate the mechanism by which it increased resistance. The loss of DOK2 decreased the level of apoptosis in response to carboplatin. Furthermore, in cells with reduced DOK2, the level of anoikis was decreased. CONCLUSIONS: We have developed a screening methodology that analyzes the epigenome and informatically identifies candidate genes followed by in vitro culture screening of the candidate genes. To validate our screening methodology we further characterized one candidate gene, DOK2, and showed that loss of DOK2 induces chemotherapy resistance by decreasing the level of apoptosis in response to treatment.

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.

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.