Unified framework for patient-derived, tumor-organoid-based predictive testing of standard-of-care therapies in metastatic colorectal cancer
Tao Tan, Dmitri Mouradov, Margaret Lee, Grace Gard, Yumiko Hirokawa, Shan Li, Cong Lin, Fuqiang Li, Huijuan Luo, Kui Wu, Michelle Palmieri, Evelyn Leong, Jordan Clarke, Anuratha Sakthianandeswaren, H. Brasier, Jeanne Tie, Niall C. Tebbutt, Azim Jalali, Rachel Wong, Antony W. Burgess, Peter Gibbs, Oliver M. Sieber
Abstract
Predictive drug testing of patient-derived tumor organoids (PDTOs) holds promise for personalizing treatment of metastatic colorectal cancer (mCRC), but prospective data are limited to chemotherapy regimens with conflicting results. We describe a unified framework for PDTO-based predictive testing across standard-of-care chemotherapy and biologic and targeted therapy options. In an Australian community cohort, PDTO predictions based on treatment-naive patients (n = 56) and response rates from first-line mCRC clinical trials achieve 83% accuracy for forecasting responses in patients receiving palliative treatments (18 patients, 29 treatments). Similar assay accuracy is achieved in a prospective study of third-line or later mCRC treatment, AGITG FORECAST-1 (n = 30 patients). "Resistant" predictions are associated with inferior progression-free survival; misclassification rates are similar by regimen. Liver metastases are the optimal site for sampling, with testing achievable within 7 weeks for 68.8% cases. Our findings indicate that PDTO drug panel testing can provide predictive information for multifarious standard-of-care therapies for mCRC.