Precision medicine approaches based on DNA or RNA analyses, are often not identifying actionable mutations in the patients, and have not been established for predicting presonse to commonly used drugs such as platins and taxols. In epithelial ovarian cancer (EOC), where paclitaxel and carboplatin is the most commonly used first-line treatment, however, local practice and a host of clinical studies have/are evaluating combinations with other drugs, implying that first line treatment regimens may vary in different countries and regions. As EOC patients that respond to first-line treatment have much better prognosis that those who don't, there is an urgent need for methods to predict the outcome to various available first line therapies, prior to treatment onset, so that the optimal treatment can be identified and offered to every patient. Zebrafish tumor xenograft (ZTX) models have recently been used to predict treatment outcome to first line therapy in multiple myeloma, neuroendocrine cancer, colorectal cancer and gastric cancer, but these studies have been small case studies including only a few patients. Furthermore, EOC, and the main drugs used to treat them have, however, not been studied in ZTX models in the past. Here we present results from the first 81 patients in an ongoing clinical study to delineate the sensitivity and specificity of ZTX models to predict treatment outcome to paclitaxel and carboplatin. Of these 81 patients, 21 presented with a primary tumor only, whereas 60 had metastatic disease. To date, 25 patient-derived tumor xenograft models have been developed by random selection of samples from this patient cohort, of which 12 were from paired primary and metastatic lesions from 6 patients. We show that tumors generated from metastatic omental lesions exhibited similar growth and metastatic dissemination as those generated from samples taken from ovarian lesions. Among the 25 patient models generated, 15 were analyzed for efficacy of paclitaxel and carboplatin in the ZTX models. We found that 11 of 15 responded to paclitaxel, 12 of 15 to carboplatin and 10 of 15 to both drugs. In conclusion, ZTX EOC models established from surgical samples allow prediction of treatment outcomes to 1st line treatment and thereby may aid treatment planning in the future.

Citation Format: Karthik Selvaraj, Malin Vildevall, Lina Wirestam, Zaheer Ali, Anna Erkstam, Annelie Abrahamsson, Åsa Rydmark Kersley, Preben Kjölhede, Stig Linder, Charlotta Dabrosin, Anna Fahlgren, Lasse Jensen. Zebrafish tumor-derived xenograft-models for improved diagnosis and treatment planning in ovarian cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3000.