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

Autor: Fabienne Lamballe, Fahmida Ahmad, Yaron Vinik, Olivier Castellanet, Fabrice Daian, Anna‐Katharina Müller, Ulrike A. Köhler, Anne‐Laure Bailly, Emmanuelle Josselin, Rémy Castellano, Christelle Cayrou, Emmanuelle Charafe‐Jauffret, Gordon B. Mills, Vincent Géli, Jean‐Paul Borg, Sima Lev, Flavio Maina
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Advanced Science, Vol 8, Iss 3, Pp n/a-n/a (2021)
Druh dokumentu: article
ISSN: 2198-3844
DOI: 10.1002/advs.202003049
Popis: 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.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje