Teresa Davoli, Laura Sack, Kamila Naxerova, Hajime Uno, Kristen E. Mengwasser and Stephen J. Elledge
Department of Genetics, Harvard Medical School, Boston, MA, USA
Aneuploidy has been recognized as a hallmark of cancer for over 100 years, yet no general theory to explain the recurring patterns of aneuploidy in cancer has emerged. We developed Tumor Suppressor and Oncogene (TUSON) Explorer, a computational method that analyzes the patterns of mutational signatures in tumors and predicts the likelihood that any individual gene functions as a tumor suppressor (TSG) or oncogene (OG). By analyzing >8200 tumor-normal pairs we provide statistical evidence suggesting many more genes possess cancer driver properties than anticipated, forming a continuum of oncogenic potential. These genes represent the vast majority of cancer drivers and the genetic networks they drive are a focus of future cancer system biological approaches to cancer research. Integrating our driver predictions with information on somatic copy number alterations, we find that the distribution and the potency of TSGs (STOP genes), OGs and essential genes (GO genes) on chromosomes can predict the complex patterns of aneuploidy and copy number variation characteristic of cancer genomes. We propose that the cancer genome is shaped through a process of cumulative haploinsufficiency and triplosensitivity. We are now assessing how aneuploidy drives cancer and the potency with which it does so. We have found that aneuploidy predicts survival better than mutational drivers and as well as existing clinical parameters in many cases. We have also discovered that different classes of aneuploidy drive transcriptional programs for two hallmarks of cancer. High aneuploidy promotes a cell proliferation program but also inhibits the infiltration of immune cels leading to immune evasion. Melanoma patients with tumors exiting high aneuploidy show poorer responses to immunotherapy with anti-CTLA4 antibodies. Reversing the ability of aneuploidy to inhibit immune surveillance could improve cancer therapeutics.