Data from Mathematical Modeling Predicts Response to Chemotherapy and Drug Combinations in Ovarian Cancer

• DOI: 10.1158/0008-5472.c.6510459.v1
• Publication Date: 2023-03-31T04:16:49Z
• Authors: Emilia Kozłowska; Anniina Färkkilä; Tuulia Vallius; Olli Carpén; Jukka Kemppainen; Seija Grénman; Rainer Lehtonen; Johanna Hynninen; Sakari Hietanen; Sampsa Hautaniemi
• Keywords: Refractory (planetary science)

<div>Abstract<p>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 millions patients with cancer. Most these patients, however, become resistant to chemotherapy, which generally leads a fatal refractory disease. We present comprehensive stochastic mathematical model simulator approach describe platinum resistance standard-of-care (SOC) therapy HGSOC. used pre- posttreatment data, including <sup>18</sup>F-FDG-PET/CT images, reliably estimate parameters simulate “virtual HGSOC.” Treatment responses virtual generated by our were indistinguishable from real-life demonstrated utility evaluating benefit combination therapies that contain up six drugs targeting mechanisms. Several mechanisms already active at diagnosis, but combining SOC drug targets most dominant subpopulation resulted significant benefit. This work provides theoretical basis for treatment paradigm maximizing platinum's killing effect on cells requires overcoming targeted drugs. freely available simulation framework enable rapid rigorous evaluation or before trials, facilitates translating preclinical findings into practice.</p><p><b>Significance:</b> These cancer, allowing novel regimens. <i>Cancer Res; 78(14); 4036–44. ©2018 AACR</i>.</p></div>