Abstract PO022: Multidimensional longitudinal assessment of patients under treatment for advanced endometrial cancer: a new tool to advance research on human disease
Evolutionary biology-based methods to characterize human cancer increasingly inform screening, surveillance, and early stage disease treatment strategies. Advanced metastatic disease presents distinct challenges in research and effective treatment. We have established the Advanced Solid Tumor Registry at the Inova Schar Cancer Institute to systematically track quantitative behavior of advanced solid tumors in a “real world” treatment setting. The study supports collection of serial: plasma samples for ctDNA analysis, computed tomography digital images and semi-automated segmentation of lesions for tumor burden volume measurement, and collection of tumor marker measures among patients receiving routine, longitudinal treatment in a community oncology practice. At submission, the study has enrolled 53 patients, 6 with recurrent metastatic endometrial cancer. Study operations have been enhanced by development of R code and workflow to enable graphical display for individual patients in clinically relevant time. In addition to enhancing clinical decision-making for the individual patients, the collective endometrial cancer patient data currently cover 207 patient-months of observation, 119 circulating marker time-points, 73 CT scans, 27 individual lesions, and 20 different courses of treatment. Treatments included palliative radiation, and: cytotoxic, hormonal, immune-, and targeted therapeutics. We propose this registry represents a new tool to support application of evolutionary science-based methods to clinical care and reciprocally to collect “real world” data with sufficient detail to inform computational science assumptions and inferences in multi-scale modeling projects. In this pilot study, individual cases effectively display multiple observations relevant to understanding treatment response in advanced metastatic disease in the clinical care environment. This project was supported, in part, by R01-CA194783. Citation Format: Erik Dvergsten, Sanja Karovic, Vasiliki Thomeas-McEwing, Danielle Kimble, Pingzhen Guo, Hao Yang, Binsheng Zhao, Lawrence H. Schwartz, Michael L. Maitland. Multidimensional longitudinal assessment of patients under treatment for advanced endometrial cancer: a new tool to advance research on human disease [abstract]. In: Proceedings of the AACR Virtual Special Conference: Endometrial Cancer: New Biology Driving Research and Treatment; 2020 Nov 9-10. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(3_Suppl):Abstract nr PO022.