Discovery of coding and non-coding driver mutations across >8,000 TCGA whole genomes

Cancer driver genes are oncogenes and tumor suppressor genes whose changes in function or expression promotes tumorigenesis. They are used to study cancer behavior, to classify cancer types, and to guide precision medicine. Cancer driver genes are usually identified by statistical analysis of coding mutations in tumor genomes. However, studies searching for new drivers are limited by statistical power, since mutations in each specific driver are often rare, and drivers are often specific to tumor subtypes. In addition, studies relying on whole-exome sequencing miss functionally important noncoding regions, such as promoters, and sequencing using PCR amplification often misses GC-rich and GC-poor regions. As a result, PCR-free whole-genome sequencing (WGS) of larger cohorts is required to continue the discovery of cancer drivers. To comprehensively identify single nucleotide variant (SNV) and indel drivers in cancer, we analyzed >8,000 tumor-normal pairs spanning 31 cancer types from The Cancer Genome Atlas (TCGA) sequenced using PCR-free WGS. We identified somatic SNVs and indels using a custom pipeline, then used MutSig2CV and dNdScv to identify genes under positive selection in coding regions and used Dig to detect increased mutation rates in coding and non-coding regions, including 5'-UTR, 3'-UTR, and promoter sequences. Our analysis identified well-known noncoding drivers, including TERT promoter mutations, TP53 5'-UTR mutations, and NFKBIZ 3'-UTR mutations, as well as some novel candidate cancer drivers, including in non-coding regions. We believe that the new drivers we discovered will provide new insights into the genetic mechanisms of tumorigenesis, aid in the development of cancer therapeutics, and offer a foundation for the use of noncoding driver events in precision oncology.