Discovery and Analysis of Oncogenic Alterations in Triple-Negative Breast Cancer
Shaver, Timothy MacKenzie
Despite significant progress in breast cancer therapeutics and survival in recent decades, treatment of triple-negative breast cancer (TNBC) has lagged behind in these advances, with cytotoxic chemotherapy remaining the sole standard of care. Recent analyses of TNBC have identified it to be a highly molecularly heterogeneous disease with a variety of low-frequency mutations, and a significant fraction of TNBC cases lack any known clinically actionable alterations. Two mechanistically linked features shared by a majority of TNBC cases are mutations in the p53 tumor suppressor, which can confer oncogenic mutant gain of function (GOF), and genomic instability, which can result in formation of oncogenic gene fusions and rearrangements. To explore potential targetable features of the mutant p53 adapted state in TNBC, we engineered an isogenic cell line panel in which endogenous wild-type, mutant, and null TP53 alleles were compared in an identical cell background. The missense mutant p53-expressing cells recapitulated numerous previously identified GOF phenotypes, including elevated metabolic rate, enhanced tumor formation in xenograft, and increased frequency of aneuploidy. Through clonal analysis, we identified variable acquisition of distinct mutant GOF phenotypes, demonstrating the difficulty of reproducing GOF phenotypes and mechanisms across differing cellular contexts. We additionally assessed the extent of potential oncogenic gene rearrangements arising from the genomic instability common to TNBCs through the development of a novel algorithm, Segmental Transcript Analysis, which uses population-based expression comparison to quantitatively predict gene rearrangements. Analyzing over 100 TNBC cases from The Cancer Genome Atlas (TCGA), we identified a number of biologically and clinically relevant rearrangements, including kinase fusions targetable by inhibitors already in clinical use or development. Extending our analysis to a number of additional cancers, we identified a diverse array of gene rearrangements, including functionally activating rearrangements of protein-coding genes with non-coding regions of DNA.