The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients
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Published on: July 5, 2019
Emma Åkerlund1, Greta Gudoityte1, Elisabeth Moussaud-Lamodière1
1Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden.
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.
Insights
A new 3D culture platform, DET3Ct, rapidly tests ovarian cancer (OC) patient cells for drug sensitivity. It predicts treatment response, aiding precision medicine and identifying effective drug combinations for clinical trials.
Area of Science:
- Oncology
- Biotechnology
- Pharmacology
Background:
- Advanced ovarian cancer (OC) frequently relapses, necessitating improved, personalized therapies.
- Functional precision medicine offers a way to identify effective treatments for individual patients within a clinically relevant timeframe.
Purpose of the Study:
- To present a scalable functional precision medicine platform, DET3Ct (Drug Efficacy Testing in 3D Cultures), for assessing patient-derived ovarian cancer cell response to drugs.
- To evaluate the utility of 3D versus 2D culture formats in predicting drug sensitivity and to identify promising drug combinations for OC.
Main Methods:
- Developed and validated the DET3Ct platform using 20 ovarian cancer patient samples, quantifying drug response via live-cell imaging in 2D and 3D cultures.
- Assessed carboplatin sensitivity in relation to progression-free interval (PFI) and tested 27 drug combinations, including novel agents like A-1331852 (Bcl-xL inhibitor).
Main Results:
- Achieved >90% success in delivering drug sensitivity profiles within six days post-operation.
- Carboplatin sensitivity scores significantly differed between patients with PFI ≤ 12 months and those with PFI > 12 months (p < 0.05).
- The 3D culture model better reflected in vivo characteristics; notable drug combinations included carboplatin/A-1331852 (additive effect) and afatinib/A-1331852 (synergy in several models).
Conclusions:
- The 3D DET3Ct platform rapidly generates clinically relevant efficacy data for existing and emerging drugs in ovarian cancer.
- This platform supports precision medicine by identifying tailored drug sensitivities and promising combinations for future clinical trials.
