Novel computational frameworks for driver gene identification and evolutionary informed genomics analysis in melanoma and prostate cancer

Abstract

We performed harmonized molecular and clinical analysis on 1,048 melanoma whole-exomes and discovered markedly different global genomic properties among genomic subtypes (BRAF, (N)RAS, NF1, Triple Wild-Type), subtype-specific preferences for secondary driver genes, and active mutational processes previously unreported in melanoma. Secondary driver genes significantly enriched in specific subtypes reflected preferential dysregulation of additional pathways beyond MAPK, such as induction of TGF-β signaling in BRAF melanomas and inactivation of the SWI/SNF complex in (N)RAS melanomas. Additionally, select co-mutation patterns coordinated selective response to immune checkpoint blockade. We also defined the mutational landscape of Triple Wild-Type melanomas and revealed enrichment of DNA repair defect signatures in this subtype, which were associated with transcriptional downregulation of key DNA repair genes and may revive previously discarded or currently unconsidered therapeutic modalities for genomically stratified melanoma patient subsets. Broadly, harmonized meta-analysis of melanoma whole-exomes revealed distinct molecular drivers that may point to multiple opportunities for biological and therapeutic investigation. Extension of this analysis to structural variants in 355 melanoma whole-genomes revealed similar secondary driver genes among the genomic subtypes, as well as novel subtype specific drivers specifically affected by structural variants. Integration of Hi-C data also identified histology (cutaneous, acral, mucosal) specific, recurrently altered, topologically associated domain (TAD) boundaries, some of which are adjacent to TADs containing known cancer genes. Finally, the extent to which clinical and genomic characteristics relate to prostate cancer clonal architecture, tumor evolution, and therapeutic response remains unclear. Here, we also reconstructed the clonal architecture and evolutionary trajectories of 845 prostate cancer tumors with harmonized clinical and molecular data. We show that the clonal architecture of prostate cancer tumors are associated with various clinical risk factors, and demonstrate that a novel approach to evolutionarily-informed mutational signature analysis that leverages clonal architecture can uncover additional cases of homologous recombination deficient and mismatch repair deficient tumors, link the origin of mutational signatures to the specific subclones, and has immediate therapeutic implications. Broadly, clonal architecture and evolutionary informed analysis reveal novel biological insights that are clinically actionable, and more generally may provide multiple opportunities for biological and clinical investigation.