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Rationally designed drug combination screen in more physiologically relevant in vitro organoid models: can we improve personalized therapy for pancreatic cancer?

Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing and usually fatal disease with a 5-year overall survival rate of less than 8%. Despite significant advances in understanding the molecular disease pathways and treatment of cancer, predicting individual responses to both standard of care and targeted therapies remains a stumbling block. The recent introduction of patient-derived tumor organoids as more physiological relevant models has revolutionized both basic and translational cancer research. However, current readouts to study these multicellular constructs only provide limited information. Considering the limitations described above, I aim to develop an innovative and more physiological relevant predictive co-culture platform that implements the effects of cancer associated fibroblast (CAFs) and hypoxia on treatment response. By using these state-of-the-art high-throughput multiplex endpoint and real-time live-cell imaging assays, I will screen a broad range of rationally designed combination strategies. Through this approach, I aim to unravel more effective and personalized combination strategies for pancreatic cancer. Eventually, I will also associate treatment sensitivity of the most promising combinations with gene mutation and expression signatures to identify novel predictive biomarkers for our innovative combination strategies.
Date:1 Nov 2020  →  Today
Disciplines:Cell death , Cell signalling, Cancer biology, Cancer therapy