Abstract PR015: Developing adaptive therapy to suppress the evolution of treatment resistance in high-grade serous ovarian cancer

Abstract

Abstract Survival in high grade serous ovarian cancer (HGSOC) is impacted by the emergence of resistance to platinum chemotherapy. The traditional ethos of killing the greatest number of cancer cells with the maximum tolerated dose of chemotherapy may be flawed in evolutionary terms, facilitating the growth of resistant subclones. Adaptive therapy is a new model of cancer treatment that exploits the competitive interactions between subclones. Its aim is to maintain a stable tumor burden by keeping a sufficient population of sensitive cells which suppress the proliferation of the ‘less fit’ resistant cells. Our lab has generated unique panels of carboplatin- and cisplatin-resistant OVCAR4 and COV318 HGSOC cell lines to model acquired resistance to chemotherapy. We have demonstrated competition between platinum-sensitive and resistant cells in vitro in a resource-poor environment. The competitive effect was removed on administration of chemotherapy but restored upon re-growth of the sensitive cell population. Flow cytometry for annexin V revealed that resistant cells undergo more apoptosis when cultured with sensitive cells, which increased in proportion to the size of the sensitive population. Competitive growth was also demonstrated in vivo in subcutaneous and intraperitoneal co-culture murine models. Importantly, carboplatin adaptive therapy significantly extended tumor control compared to standard treatment (60mg/kg carboplatin every 4 days for 3 doses) in a subcutaneous co-culture model, maintaining a stable tumor volume for up to 6 months. A challenge in bringing adaptive therapy to the clinical setting is quantifying the relative proportions of therapy-sensitive and resistant disease to guide the personalized scheduling of treatment. In HGSOC, chemotherapy resistance is correlated with a higher burden of copy number aberrations (CNAs). Our novel method “liquidCNA” quantifies the relative proportion of chemotherapy-resistant disease using low pass whole genome sequencing and CNAs as clonal markers. The method was verified using samples of sensitive and resistant HGSOC cells of varying tumor purity and subclonal ratio (proportion of resistant cells), and subsequently applied to longitudinal human samples collected from 18 patients, using the copy number profile from a diagnostic biopsy as a baseline for sensitive disease. We have demonstrated competition between chemo-sensitive and resistant cells both in vitro and in vivo. We have shown that adaptive therapy controls tumor burden for longer than standard therapy in a murine HGSOC model. Our novel method liquidCNA can be applied to liquid biopsies to monitor the relative drug-sensitive/resistant composition of tumors and could potentially be used to guide personalized treatment scheduling in future adaptive therapy clinical trials. Based on this research, we have developed the UK’s first clinical trial of adaptive therapy (ACTOv: Adaptive ChemoTherapy for Ovarian cancer), which will commence recruitment in Q2 2022. Citation Format: Helen Hockings, Michelle Lockley, Trevor Graham, Eszter Lakatos, Weini Huang. Developing adaptive therapy to suppress the evolution of treatment resistance in high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR015.