  The Cancer Genome Atlas (TCGA) project, a federally funded U.S. research program, supported jointly by the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI), sought to characterize the genomic features of each cancer type and subtype, resulting in thirty-three “marker” papers, laying out molecular features of each cancer type, often yielding novel subclassifications of each type. For example, in 2016, a working group affiliated with TCGA published “Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma,” which identified three subtypes of adrenocortical carcinoma, and in 2015, another working group published “Comprehensive Genomic Characterization of Head and Neck Squamous Cell Carcinomas,” which identified specific mutations associated with human-papillomavirus-associated versus smoking-related head and neck cancers. While TCGA did result in a more comprehensive understanding of cancer biology, it also raised many questions. One particular challenge has been determining which mutations to which genes are the “drivers” of cancer, or which ones enable cancer cells to “succeed” in an environment that would (ordinarily) prevent their growth. Cancer genomes have many mutations, so a central puzzle has been determining which among the many changes to cancer genomes are causally relevant to cancer progression. Solving this puzzle has been difficult, because cancers are far more heterogeneous than they initially anticipated. Or, perhaps it is better to say: sorting the “signal” from the noise has proven more difficult than anticipated, as Meyerson, et al. (2010) explains, paraphrasing Tolstoi: