Abstract
Platinum-based chemotherapy constitutes the backbone of clinical care in advanced solid cancers such as high-grade serous ovarian cancer (HGSOC) and has prolonged survival of millions of patients with cancer. Most of these patients, however, become resistant to chemotherapy, which generally leads to a fatal refractory disease. We present a comprehensive stochastic mathematical model and simulator approach to describe platinum resistance and standard-of-care (SOC) therapy in HGSOC. We used pre- and posttreatment clinical data, including 18F-FDG-PET/CT images, to reliably estimate the model parameters and simulate "virtual patients with HGSOC." Treatment responses of the virtual patients generated by our mathematical model were indistinguishable from real-life patients with HGSOC. We demonstrated the utility of our approach by evaluating the survival benefit of combination therapies that contain up to six drugs targeting platinum resistance mechanisms. Several resistance mechanisms were already active at diagnosis, but combining SOC with a drug that targets the most dominant resistance subpopulation resulted in a significant survival benefit. This work provides a theoretical basis for a cancer treatment paradigm in which maximizing platinum's killing effect on cancer cells requires overcoming resistance mechanisms with targeted drugs. This freely available mathematical model and simulation framework enable rapid and rigorous evaluation of the benefit of a targeted drug or combination therapy in virtual patients before clinical trials, which facilitates translating preclinical findings into clinical practice.Significance: These findings present a comprehensive mathematical model for platinum resistance and standard-of-care therapy in a solid cancer, allowing virtual evaluation of novel therapy regimens. Cancer Res; 78(14); 4036-44. ©2018 AACR.
Highlights
Platinum-based chemotherapy constitutes the backbone of clinical care in advanced solid cancers
We introduce here a stochastic mathematical model for chemotherapy resistance in high-grade serous ovarian cancer (HGSOC) and use it to create "virtual HGSOC patients." These virtual patients can be used to estimate the number of active resistance mechanisms at diagnosis or after treatment and to suggest guidelines for developing effective combination therapy regimens
Platinum therapy changes the number and proportion of active resistant mechanisms Given the significant effect of tumor aggressiveness on platinum-free interval (PFI), we explored the number of active resistance mechanisms present in HGSOC tumors at the time of diagnosis by using the virtual cohort of 1,000 patients
Summary
Platinum-based chemotherapy constitutes the backbone of clinical care in advanced solid cancers. HGSOC tumors are characterized by high intratumoral heterogeneity [11], which leads to cancer cell subpopulations with various platinum resistance mechanisms. We introduce here a stochastic mathematical model for chemotherapy resistance in HGSOC and use it to create "virtual HGSOC patients." These virtual patients can be used to estimate the number of active resistance mechanisms at diagnosis or after treatment and to suggest guidelines for developing effective combination therapy regimens. The benefit of a targeted drug or combination therapy over SOC can be evaluated rapidly and rigorously with our approach This facilitates translating preclinical findings efficiently into clinical trials and, eventually, patient care
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