Abstract 5193: Identification of molecular predictors of differential chemotherapy response using patient-derived xenografts

Background: Clinical oncology trials in humans have major limitations, not the least of which is the inability to treat a single tumor with multiple drugs simultaneously to identify the most effective treatment options. In theory, this and other limitations can be overcome using an “animal clinical trial” platform that exploits collections of human cancer patient-derived xenograft (PDX) models. Clinically, breast cancers are divided into three distinct groups: those that express the estrogen hormone receptor (ER+) (which typically also express the progesterone hormone receptor (PR+)), those with amplified or overexpressed ErbB2 (HER2) oncogene (HER2+), and those that express none of these three markers (“triple negative” breast cancer TNBC). Unlike ER+ and HER2+ breast cancers, there are currently no targeted therapies against TNBC. Treatment of TNBC entails surgery coupled with radio- or chemotherapy, or both. Chemotherapy options include Taxanes (e.g. Docetaxel, Paclitaxel), Anthracyclin based therapies (Adriamycin/Doxorubicin plus Cytoxan (cyclophosphamide) (AC), and more recently, and platinum-based agents (e.g. Cisplatin, Carboplatin). However, other than BRCA1/2 mutation status correlating with increased efficacy of platinum-based agents, there are currently no clinically useful predictors of differential treatment response among these three commonly used chemotherapeutics. Hypothesis: We hypothesized that a molecular predictor of differential chemotherapy response could be developed using human breast cancer patient-derived xenografts as the discovery platform. Materials and Methods: We tested this hypothesis in an “animal clinical trial” using 20 PDX treated with three chemotherapies vs. control. Molecular correlates of response were identified in RNAseq and proteomic data, and are being validated in a separate cohort of PDX. Results: We show that animal clinical trials are feasible, and can be conducted efficiently, using minimal staff. Further, we extend our previous analysis showing that treatment responses observed clinically are recapitulated in the PDX lines, thereby establishing clinical relevance of observed responses. Finally, we demonstrate that PDX show largely non-overlapping sensitivity to only one of the three agents tested, with corresponding largely non-overlapping molecular signatures delineating those PDX that respond to a given treatment from those that do not. Validation studies in newly developed PDX lines are ongoing. Conclusions: Together, these data suggest that PDX models should be useful for generating predictors of treatment response. Ultimately, if robust genetic, epigenetic, or molecular predictors of differential treatment response can be identified and applied clinically, it may be possible to avoid ineffective treatments, minimize exposure to cytotoxic agents, and ultimately increase survivorship. Citation Format: Michael T. Lewis, Lacey E. Dobrolecki, Susan G. Hilsenbeck, Lukas M. Simon, Chad A. Shaw. Identification of molecular predictors of differential chemotherapy response using patient-derived xenografts. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5193.