Treatment selection for cancer patients is still a challenge. Average response rates for standard chemotherapy are low due to a lack of predictive markers. Genetic approaches to improve treatment efficacy have not yet delivered solutions for the day-to-day clinic. Functional testing of 3D cultures of patient tumour biopsies has the potential to identify tumours that are sensitive to standard drugs, search for alterative drugs when treatment options appear exhausted, and prevent overtreatment. Our technology based on image analysis of 3D tumour cultures accommodates accurate evaluation of drug sensitivity with small amounts of heterogeneous tumour material. We aim to validate our methods, and develop diagnostics to predict drug response for cancer patients.
3D cultures embedded in a protein-rich hydrogel are generated from tumour biopsies, and exposed to standard-of-care therapies, targeted therapies and drug combinations. An automated high content screening platform measures cell and tissue morphology, and reports responses such as tumour cell killing, growth arrest and local invasion. Per tumour type and drug, morphological features are selected as standard read-outs for the response. Proof of Concept (PoC) trials have been initiated to compare drug sensitivity of tumour cultures with treatment response in the clinic.
We present results of PoC experiments showing drug sensitivity in 3D cultures of fresh and cryopreserved tumour material of gastric, endometrial, cervical, and ovarian cancer patients. Standard-of-care therapies were tested and results were compared per drug (combination). Differentiated drug responses are identified for treatment schedules including platinum-based drugs, taxanes, anthracyclines, 5-FU. In addition, responses to drugs that are not (yet) considered standard of care (PARP inhibitors) were measured.
Our technology enables drug sensitivity testing in 3D cultures of tumour tissues. This allows patient-specific treatment responses to developmental and standard-of-care drugs to be determined. Ongoing PoC trials will reveal the correlation of our in vitro test with treatment responses in the clinic.
Clinical trial identification
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All authors have declared no conflicts of interest.