GenBlosum: On Determining Whether Cancer Mutations Are Functional or Random

Genetic mutations have proven to be the epicenters of cancer and disease progression. Traditional WXS sequencing and BLOSUM scoring can be used to infer the evolutionary conservation of amino acid substitutions, though these approaches are not informed by evolutionary variants or probable base pair sequence changes. Within gene mutation analysis, most tools focus on the probability of amino acid changes, evolutionary conservation, or codon switching; however, no method is available that can integrate all levels of probability to compare onto a distributionally neutral model. We took the TCGA BRCA cohort and analyzed all mutation sequences for TP53 and PIK3CA, and developed a model that uses BLOSUM scoring and statistical analysis of base pair changes to generate the statistical significance of genetic mutations within the cohort. The mutational distribution was compared against a stochastic neutral model to determine the significance of all mutations in the cohort. Within the TCGA BRCA cohort, the model showed that TP53 and PIK3CA mutations were significant , and that TP53 was significantly more mutated than observationally neutral patterns relative to a codon-aware stochastic neutral model.