Changes in gene expression variability reveal a stable synthetic lethal interaction network in BRCA2-ovarian cancers.

Abstract

Synthetic lethal interactions (SLIs) are robust mechanisms that provide cells with the ability to remain viable despite having mutations in genes critical to the DNA damage response, a core cellular process. Studies in model organisms such as S. cerevisiae showed that thousands of genes important in maintaining DNA integrity cooperated in a SLI network. Two genes participate in a SLI when a mutation in one gene has no effect on the cell, but mutations in both interacting genes are lethal. Furthermore in C. elegans, a mutation in a critical gene that is important for development induced a change in expression variability in the synthetic lethal interactor. In cancer, targeting SLIs shows promise in selectively killing cancer cells. For example, targeting PARP1 is an effective treatment for BRCA1/2- breast and ovarian cancers. Although PARP1 is already identified as having a SLI with BRCA1/2-, computationally searching for other genes that cooperate in the SLI network could highlight genes that may have promise for being a cancer-specific drug target. Using RNA sequencing data for ovarian cancer patients with BRCA2 mutations and the R Bioconductor package pathVar, we showed that genes whose expression changes to an invariant, stable expression state are likely candidates for SLIs with BRCA2. Our results highlight the interactions between the genes with predicted SLIs and protein-coding genes that are functionally important in the DNA damage response. The method of analyzing expression variability to computationally identify genes with SLIs can be applied to query SLIs in other tumor types.