Diversity Spectrum Analysis Identifies Allele-Specific Effects of Cancer Driver Mutations

Abstract

Allele-specific effects of cancer driver mutations influence drug responses and the success of clinical trials. We reasoned that these effects could unbalance the distribution of each mutation across different cancer types, as a result, the cancer preference can be used to distinguish the effects of the causal allele. Here, we developed a network-based framework to systematically measure cancer diversity for each driver mutation. We found that half of the driver genes harbor cancer type-specific and pancancer mutations simultaneously, suggesting that the pervasive functional heterogeneity of the mutations from even the same driver gene. We further demonstrated that the specificity of the mutations significantly influenced drug responses, and observed that diversity was generally increased in advanced tumors. Finally, a new protocol was designed to predict cancer genes based on the diversity spectrum. Overall, our diversity spectrum analysis provides a new approach to define driver mutations and optimize off-label clinical trials.