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Background mutability shapes observed mutational spectrum in cancer and improves driver mutation prediction
- Publication Year :
- 2018
- Publisher :
- Cold Spring Harbor Laboratory, 2018.
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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. We 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. We 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. We 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. Availability: https://www.ncbi.nlm.nih.gov/research/mutagene/gene
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....e36cd14dafed2b5e31957983713b0e03
- Full Text :
- https://doi.org/10.1101/354506