Human Synthetic Lethal Inference as Potential Anti-cancer Target Gene Detection

Background:. Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in the organism’s fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the determination of these mutated genes’ SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results:. In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogeneticallyinferred SL gene network for humans. In addition, available data on cancer mutated genes (COSMIC and GeneCensus databases) as well as on existent approved drugs (DrugBank database) provides supporting evidence of our selection of cancer-therapy candidates. Conclusions:. Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research.