The combinatorial complexity of cancer precision medicine

Abstract

Precision medicine approaches have recently been developed that offer therapies targeting mainly single genetic alterations in malignant tumors. However, next generation sequencing studies have shown that tumors normally harbor multiple genetic alterations, which could explain the so far limited successes of personalized medicine, despite considerable benefits in certain cases. Combination therapies may contribute to a solution, but will pose a major challenge for clinical trials evaluating those therapies. As we discuss here, reasons include the low abundance of most of the relevant mutations and particularly the combinatorial complexity of possible combination therapies. Our report provides a systematic and quantitative account of the implications of combinatorial complexity for cancer precision medicine and clinical trial design. We also present an outlook on how systems biological approaches may be harnessed to contribute to a solution of the complexity challenge by predicting optimal combination therapies for individual patients and how clinical trial design may be adapted by combining and extending basket and umbrella design features.