Shared Cancer Dataset Analysis Identifies and Predicts the Quantitative Effects of Pan-Cancer Somatic Driver Variants

Driver mutations endow tumors with selective advantages and produce an array of pathogenic effects. Determining the function of somatic variants is important for understanding cancer biology and identifying optimal therapies. Here, we compiled a shared dataset from several cancer genomic data-bases. Two measures were applied to 535 cancer genes based on observed and expected frequencies of driver variants as derived from cancer-specific rates of somatic mutagenesis. The first measure comprised a binary classifier based on a binomial test; the second was tumor variant amplitude (TVA), a continuous measure representing the selective advantage of individual var-iants. TVA outperformed all other computational tools in terms of its correlation with experimentally derived functional scores of cancer mutations. TVA also highly correlated with drug response, overall survival, and other clinical implications in relevant cancer genes. This study demonstrates how a selective advantage measure based on a large cancer dataset significantly impacts our understanding of the spectral effect of driver variants in cancer. The impact of this information will increase as cancer treatment becomes more precise and personalized to tumor-specific mutations.

Automated summary

Driver mutations provide tumors with selective advantages and cause various pathogenic effects. Understanding the function of somatic variants is crucial in cancer biology and treatment selection. In this study, a shared dataset from multiple cancer genomic databases was compiled, and two measures were used to analyze 535 cancer genes. The tumor variant amplitude (TVA) outperformed other computational tools in predicting functional scores of cancer mutations, drug response, overall survival, and clinical implications in relevant cancer genes. This study highlights the importance of a large cancer dataset in understanding the impact of driver variants and their clinical implications.