The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients.

Abstract

Most patients with advanced ovarian cancer (OC) relapse and progress despite systemic therapy, pointing to the need for improved and tailored therapy options. Functional precision medicine can help to identify effective therapies for individual patients in a clinically relevant timeframe. Here, we present a scalable functional precision medicine platform: DET3Ct (Drug Efficacy Testing in 3D Cultures), where the response of patient cells to drugs and drug combinations are quantified with live-cell imaging. We demonstrate the delivery of individual drug sensitivity profiles in 20 samples from 16 patients with ovarian cancer in both 2D and 3D culture formats, achieving over 90% success rate in providing results six days after operation. In this cohort all patients received carboplatin. The carboplatin sensitivity scores were significantly different for patients with a progression free interval (PFI) less than or equal to 12 months and those with more than 12 months (p < 0.05). We find that the 3D culture format better retains proliferation and characteristics of the in vivo setting. Using the DET3Ct platform we evaluate 27 tailored combinations with results available 10 days after operation. Notably, carboplatin and A-1331852 (Bcl-xL inhibitor) showed an additive effect in four of eight OC samples tested, while afatinib and A-1331852 led to synergy in five of seven OC models. In conclusion, our 3D DET3Ct platform can rapidly define potential, clinically relevant data on efficacy of existing drugs in OC for precision medicine purposes, as well as provide insights on emerging drugs and drug combinations that warrant testing in clinical trials.

• Authors: Emma Åkerlund, Greta Gudoityte, Elisabeth Moussaud-Lamodière, Olina Lind, Henri Colyn Bwanika, Kaisa Lehti, Sahar Salehi, Joseph Carlson, Emelie Wallin, Josefin Fernebro, Päivi Östling, Olli Kallioniemi, Ulrika Joneborg, Brinton Seashore-Ludlow
• Journal: NPJ precision oncology (NPJ Precis Oncol) Vol. 7 Issue 1 Pg. 111 (Oct 31 2023) ISSN: 2397-768X [Print] England
• PMID: 37907613 (Publication Type: Journal Article)
• Copyright: © 2023. The Author(s).