High-prevalence and broad spectrum of Cell Adhesion and Extracellular Matrix gene pathway mutations in epithelial ovarian cancer
- Equal contributors
1 Stem cell and microenvironment laboratory, Weill Cornell Medical College in Qatar, Education city, Qatar Foundation, Doha, Qatar
2 Department of Genetic Medicine, Weill Cornell Medical College, NY, NY, USA
3 Genomics Core, Weill Cornell Medical College in Qatar, Education city, Qatar Foundation, Doha, Qatar
4 Department of Genetic Medicine, Weill Cornell Medical College, Genomics Core Laboratory, Weill Cornell Medical College in Qatar, Qatar-Foundation, Doha, Qatar
Journal of Clinical Bioinformatics 2012, 2:15 doi:10.1186/2043-9113-2-15Published: 24 September 2012
Ovarian cancer is the most deadly gynecological cancer because of late diagnosis, frequently with diffuse peritoneal metastases. Recent findings have shown that serous epithelial ovarian cancer has a narrow mutational spectrum with TP53 being the most frequently targeted when single genes are considered. It is, however, important to understand which pathways as a whole may be targeted for mutation.
Previously published mutational data provided by the cancer genome atlas networks findings on ovarian cancer was searched for statistically significant enrichment of genes in pathways. These pathways were then searched in all patients to identify the spectrum of mutations. Statistical significance was further shown through in-silico permutations of exome sequences using empirically observed mutation rates. We detected mutations in the cell adhesion pathway genes in more than 89% of serous epithelial ovarian cancer patients. This level of near universal mutational targeting of the cell adhesion pathway, including the extracellular matrix pathway, is previously unreported in epithelial ovarian cancer.
Taken together with previous studies on the role of cell adhesion and extracellular matrix gene expression in ovarian cancer and metastasis, our results identify pathways for which the mutational prevalence has previously been overlooked using single gene approaches. Analysis of mutations at the pathway level will be critical in studying heterogeneous diseases such as ovarian cancer.