Statins, routinely used to treat hypercholesterolemia, selectively induce apoptosis in some tumor cells by inhibiting the mevalonate pathway. Recent clinical studies suggest that a subset of breast tumors is particularly susceptible to lipophilic statins, such as fluvastatin. To quickly advance statins as effective anticancer agents for breast cancer treatment, it is critical to identify the molecular features defining this sensitive subset. We have therefore characterized fluvastatin sensitivity by MTT assay in a panel of 19 breast cell lines that reflect the molecular diversity of breast cancer, and have evaluated the association of sensitivity with several clinicopathological and molecular features. A wide range of fluvastatin sensitivity was observed across breast tumor cell lines, with fluvastatin triggering cell death in a subset of sensitive cell lines. Fluvastatin sensitivity was associated with an estrogen receptor alpha (ERa)-negative, basal-like tumor subtype, features that can be scored with routine and/or strong preclinical diagnostics. To ascertain additional candidate sensitivity-associated molecular features, we mined publicly available gene expression datasets, identifying genes encoding regulators of mevalonate production, nonsterol lipid homeostasis, and global cellular metabolism, including the oncogene MYC. Further exploration of this data allowed us to generate a 10-gene mRNA abundance signature predictive of fluvastatin sensitivity, which showed preliminary validation in an independent set of breast tumor cell lines. Here, we have therefore identified several candidate predictors of sensitivity to fluvastatin treatment in breast cancer, which warrant further preclinical and clinical evaluation. Fil: Goard, Carolyn A.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; Canadá Fil: Chan Seng Yue, Michelle . University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; Canadá Fil: Mullen, Peter J.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá Fil: Quiroga, Ariel Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina. University of Alberta; Canadá Fil: Wasylishen, Amanda R.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; Canadá Fil: Clendening, James W.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; Canadá Fil: Sendorek, Dorota H. S.. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; Canadá Fil: Haider, Syed. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; Canadá Fil: Lehner, Richard. University of Alberta; Canadá Fil: Boutros, Paul C.. University Of Toronto; Canadá. Ontario Institute of Cancer Research. Informatics and Biocomputing Platform; Canadá Fil: Penn, Linda Z.. University Health Network. Princess Margaret Cancer Centre. Ontario Cancer Institute and Campbell Family Institute for Breast Cancer Research; Canadá. University Of Toronto; Canadá
