Abstract
The canonical model for hereditary cancer predisposition is a cancer predisposition gene (CPG) that drives either one or both of two fundamental hallmarks of cancer, defective genomic integrity and deregulated cell proliferation, ultimately resulting in the accumulation of mutations within cells. Thus, the genes most commonly associated with cancer-predisposing genetic syndromes are tumor suppressor genes that regulate DNA repair (eg, BRCA1, BRCA2, MMR genes) and/or cell cycle (eg, APC, RB1). In recent years, however, the spectrum of high-penetrance CPGs has expanded considerably to include genes in non-canonical pathways such as oncogenic signaling, metabolism, and protein translation. We propose here that, given the variety of pathways that may ultimately affect genome integrity and cell proliferation, the model of cancer genetic predisposition needs to be expanded to account for diverse mechanisms. This synthesis calls for modeling and multi-omic studies applying novel experimental and computational approaches to understand cancer genetic predisposition.
Acknowledgments
The authors thank J. Gregory for making the figure and members of the Mount Sinai Computational Omics lab for discussions.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors declare no potential conflicts of interest.