Finding Driver Mutations in Cancer: Elucidating the Role of Background Mutational Processes

Abstract

Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation in patients remains one of the most reliable markers of mutation driver status. However, some mutations are more likely to occur than others due to differences in background mutation rates arising from various forms of infidelity of DNA replication and repair machinery, endogenous, and exogenous mutagens.\n\nWe used cancer-type and mutagen-specific mutability to study the contribution of background processes of mutagenesis and DNA repair in shaping the observed mutational spectrum in cancer. We developed and tested probabilistic model that adjusts the number of mutation recurrences in patients by background mutability in order to find mutations which may be under selection in cancer.\n\nWe showed that observed recurrence frequency of cancer mutations scaled with the background mutability, especially for tumor suppressor genes. In oncogenes, however, highly recurring mutations were characterized by relatively low mutability, resulting in a U-shaped trend. Mutations not yet observed in any tumor had relatively low mutability values, indicating that background mutability might limit the mutation occurrence.\n\nWe compiled a dataset of missense mutations from 58 genes with experimentally validated functional and transforming impacts from different studies. We found that mutability of driver mutations was lower than the mutability of passengers and consequently adjusting mutation recurrence frequency by mutability significantly improved ranking of mutations and driver prediction. Even though no training on existing data was involved, our approach performed similar or better to the existing state-of-the-art methods.\n\nAvailabilityhttps://www.ncbi.nlm.nih.gov/research/mutagene/gene