Modeling Heterogeneity of Triple‐Negative Breast Cancer Uncovers a Novel Combinatorial Treatment Overcoming Primary Drug Resistance

Abstract

Abstract Triple‐negative breast cancer (TNBC) is a highly aggressive breast cancer subtype characterized by a remarkable molecular heterogeneity. Currently, there are no effective druggable targets and advanced preclinical models of the human disease. Here, a unique mouse model (MMTV‐R26Met mice) of mammary tumors driven by a subtle increase in the expression of the wild‐type MET receptor is generated. MMTV‐R26Met mice develop spontaneous, exclusive TNBC tumors, recapitulating primary resistance to treatment of patients. Proteomic profiling of MMTV‐R26Met tumors and machine learning approach show that the model faithfully recapitulates intertumoral heterogeneity of human TNBC. Further signaling network analysis highlights potential druggable targets, of which cotargeting of WEE1 and BCL‐XL synergistically kills TNBC cells and efficiently induces tumor regression. Mechanistically, BCL‐XL inhibition exacerbates the dependency of TNBC cells on WEE1 function, leading to Histone H3 and phosphoS33RPA32 upregulation, RRM2 downregulation, cell cycle perturbation, mitotic catastrophe, and apoptosis. This study introduces a unique, powerful mouse model for studying TNBC formation and evolution, its heterogeneity, and for identifying efficient therapeutic targets.

Keywords

• BCL‐XL
• cancer mouse model
• drug resistance
• MET
• signaling reprogramming
• triple‐negative breast cancer