ABSTRACT
PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor (ER)-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. FOXM1 drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II). The downstream metabolic changes can therefore be detected using MRI of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by positron emission tomography measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose. Rapid assessment of treatment response in breast cancer using this imaging method could help identify patients that benefit from PI3Kα inhibition and design drug combinations to counteract the emergence of resistance.
Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Breast Neoplasms/drug therapy , Class I Phosphatidylinositol 3-Kinases/antagonists & inhibitors , Forkhead Box Protein M1/metabolism , Protein Kinase Inhibitors/pharmacology , Animals , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , Cell Line, Tumor , Class I Phosphatidylinositol 3-Kinases/genetics , Class I Phosphatidylinositol 3-Kinases/metabolism , Drug Resistance, Neoplasm/genetics , Female , Forkhead Box Protein M1/genetics , Fulvestrant/administration & dosage , Humans , Imidazoles/administration & dosage , MCF-7 Cells , Magnetic Resonance Imaging/methods , Mice, Inbred NOD , Mice, Knockout , Mice, SCID , Oxazepines/administration & dosage , Receptors, Estrogen/metabolism , Tamoxifen/administration & dosage , Xenograft Model Antitumor Assays/methodsABSTRACT
Despite remarkable advances in our understanding of the drivers of human malignancies, new targeted therapies often fail to show sufficient efficacy in clinical trials. Indeed, the cost of bringing a new agent to market has risen substantially in the last several decades, in part fuelled by extensive reliance on preclinical models that fail to accurately reflect tumour heterogeneity. To halt unsustainable rates of attrition in the drug discovery process, we must develop a new generation of preclinical models capable of reflecting the heterogeneity of varying degrees of complexity found in human cancers. Patient-derived tumour xenograft (PDTX) models prevail as arguably the most powerful in this regard because they capture cancer's heterogeneous nature. Herein, we review current breast cancer models and their use in the drug discovery process, before discussing best practices for developing a highly annotated cohort of PDTX models. We describe the importance of extensive multidimensional molecular and functional characterisation of models and combination drug-drug screens to identify complex biomarkers of drug resistance and response. We reflect on our own experiences and propose the use of a cost-effective intermediate pharmacogenomic platform (the PDTX-PDTC platform) for breast cancer drug and biomarker discovery. We discuss the limitations and unanswered questions of PDTX models; yet, still strongly envision that their use in basic and translational research will dramatically change our understanding of breast cancer biology and how to more effectively treat it.
