Abstract

IntroductionIn epithelial ovarian cancer (EOC) patients, 15%–20% of the tumours do not respond to first-line chemotherapy treatment, i.e., paclitaxel combined with a platinum-based therapy. The aim of this pilot study was to validate a new approach to measure the sensitivity of ovarian cancer cells to chemotherapeutics. Furthermore, we aimed to relate the in vitro response of tumour cells from ascites to clinical response of ovarian cancer patients.Material and methodsFor this pilot study, we selected 18 patients with advanced stage EOC and collected ascites. Proliferation assays on tumour cells isolated from the ascites were performed using intracellular ATP content as an indirect measure of cell number. Clinical outcome was determined using status of remission after primary treatment, disease free survival (DFS), and the platinum-sensitivity. Complete remission was defined as a serum-CA125 <35 E/ml, a complete or optimal debulking surgery, and a complete response on CT-scan. We related the sensitivity tests and the clinical outcome using descriptive statistics.Results and discussionsThe outcome of the proliferation assays, expressed by GI50 and using dose-response curves, corresponded to the clinical outcome in the patient in most cases. Of the 14 ascites samples eventually tested, seven of the in vitro responses were poor as well as the DFS of the patient. Four samples showed good in vitro response and the patient showed a good DFS as well. Only two of the samples tested did not show similarity in in vitro response and in clinical outcome of the patient. We also determined the in vitro response to second line therapies and new targeted therapies, including PARP- and bromodomain inhibitors.ConclusionThis pilot study demonstrates the feasibility of using ascites tumour cells to perform drug sensitivity tests. These are promising results because it seems possible to predict accurately the response on first-line chemotherapy in advanced stages of EOC. However, larger observational studies are required to show a statistical significant relation, to determine the best clinical response measurements and to test second line therapies.

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