Determining susceptibility loci in triple negative breast cancer using a novel pre-clinical model

ABSTRACT Breast cancer (BC) is the most common cancer and the second cause of death in US women. Our lack of understanding of how genetic variants affect molecular mechanisms that mediate BC aggression poses a substantial obstacle to advancements in cancer diagnosis and therapy. To examine genetic variants on BC traits, a novel murine model was created with robust phenotypic and genomic variation. The FVB C3(1)-T-antigen (“C3Tag”) mouse develops spontaneous tumors in the mammary glands of female mice with a mean latency of 4-5 months of age. This genetically engineered mouse model (GEMM) is well established to resemble human basal-like TNBC. TNBC is an aggressive subtype with few clinical approaches and poor patient outcomes. Thus, to model human heterogeneity in BC outcomes, we systematically crossed the C3Tag GEMM into the BXD recombinant inbred family – the largest and best characterized genetic reference population. The new model is termed “BXD-BC” and F1 hybrids of the cross have isogenic genomes that are reproducible. BXD-BCs are a potent tool to determine the impact of genetic modifiers on BC tumor traits. We hypothesized that examination of BXD-BC GEMMs will enable the identification of susceptibility loci, candidate genes, and molecular networks that underlie variation of multiple BC phenotypes. Using N=29 BXD-BC strains, we demonstrated significant heritable variations in the severity of TNBC characteristics such as tumor latency, multiplicity, and survival. Interestingly, 2 BXD-BC strains never developed tumors out to 1 year of age. Thus, BXD-BC strains demonstrate variance in cancer susceptibility and progression compared to the parent C3Tag GEMM, indicating the presence of genetic modifiers. Through an unbiased systematic quantification of breast cancer severity across BXD-BC hybrids, we identified several significant quantitative trait loci (QTL) and candidate genes for specific tumor traits. In combination with public human GWAS datasets, we defined syntenic regions, candidate genes, and underlying networks through cross-species systems genetics analyses to demonstrate the translational validity of conserved, biologically relevant, and targetable candidates. Our findings suggest conserved candidates predicting TNBC patient survival. In sum, the BXD-BC resource is an innovative, reliable, and robust preclinical model that reflects robust genetic heterogeneity. Using cutting edge systems genetics, we have identified genetic modifiers of BC phenotypic variation that could be targeted to advance therapeutic limitations or as biomarkers of risk or response to therapy.