Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

Abstract

Background: Breast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics. Results: Herein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes. Conclusions: We conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.