Abstract 2240: Redefining personalized medicine by drug response profiling of patient-derived spheroids
Authors: Stephen Shuford, Christine Wilhelm, Ashley M. Smith, Melissa Rayner, Jeremy Stuart, Lillia Holmes, Matt Gevaert, Howland E. Crosswell, Teresa M. DesRochers
Journal: Cancer Research (2019)

Abstract Personalized medicine in cancer typically refers to the use of genetics and/or biomarkers to direct the use of targeted therapy or predict overall prognosis based on statistical probability. Therapy selection and predictions are not based on any physical interaction between a patient’s tumor cells to clinically relevant therapies based on their disease indication. We have developed an assay using 3D cell culture that exposes a patient’s tumor cells to standard of care chemotherapies for the purpose of predicting their clinical response to potential treatment options prior to treatment. We have analytically validated this assay enabling its performance under CLIA regulations as a Laboratory Developed Test (LDT) and prospectively validated it against clinical patient outcome in ovarian cancer. The test utilizes excess fresh patient tissue acquired during standard of care surgical debulking or biopsy and returns results within 7 business days of tissue receipt, typically well before the start of chemotherapy. Previously, we have shown in newly diagnosed ovarian cancer, the test has an accuracy of 87% with a specificity of 100% and a sensitivity of 84% in the prediction of standard first-line carboplatin/taxol combination therapy using the biomarker CA-125 and CT imaging as clinical readouts. We have similar results for the prediction of response to neoadjuvant therapy following laparoscopic biopsy using RECIST criteria. We have now analytically validated the assay in glioblastoma (GBM) and rare tumors. Preliminary clinical validation in GBM has shown the ability of the test to accurately predict response to standard first-line temozolomide using RANO criteria as the clinical readout. Rare tumor validation has included a panel of 12 drugs covering those used as standard of care for most rare tumors. Aspects of validation have included examining inter- and intra-assay variability and drug panel response in a defined number of rare tumors including sarcomas, neuroendocrine, and other tumors such as Sertoli-Leydig. In breast cancer, we have validated the assay for the use of a single diagnostic biopsy core as the tissue source and established preliminary clinical validation against standard of care such as doxorubicin and paclitaxel with pathologic complete response (pCR) as the clinical readout. We are further validating the predictive ability of the test in newly diagnosed and relapsed ovarian cancer and GBM patients (clinical trial NCT03561207). With demonstrated accurate prediction of patient specific response, the transition to cancer therapy selection based on physical evidence vs statistical probability would significantly improve patient outcomes and benefit economic stakeholders. Citation Format: Stephen Shuford, Christine Wilhelm, Ashley M. Smith, Melissa Rayner, Jeremy Stuart, Lillia Holmes, Matt Gevaert, Howland E. Crosswell, Teresa M. DesRochers. Redefining personalized medicine by drug response profiling of patient-derived spheroids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2240.