One of the greatest challenges in improving treatment strategies for pancreatic cancer patients is to translate results obtained in the basic research laboratory directly to patient care. To improve this process, known as translation, appropriate human model systems that are predictive of the clinic are needed. Equally important, hypotheses generated by clinical observations must be reflected back to the research laboratory (reverse translation) to be tested experimentally.
With the professorship for Translational Pancreatic Cancer Research, Prof. Reichert (Principal Investigator of P12, S01) aims to establish a clinically relevant and internationally visible translational pancreatic cancer research platform at TUM. As a physician working in basic science in gastrointestinal oncology, he has been able to train unique expertise and skills over the past years, which are essential for innovative and successful translation and reverse translation.
The translational research platform is composed of three main pillars:
1) strong basic research in pancreatic cancer to identify novel therapeutic targets and generate clinically relevant hypotheses,
2) a translational technology platform to test scientific hypotheses (generated in 1.) in preclinical model systems, in particular pancreatic cancer patient derived organoids (PDOs). This technology platform needs to continuously evolve in terms of quality measures and integration of new technological advances in the biomedical field (e.g., single-cell sequencing, single-cell imaging, artificial intelligence, high-throughput methods, therapy testing, etc.).
3) The knowledge and technological systems generated in the research laboratory must be implemented in precision oncology in the clinic and tested in multicenter randomized clinical trials.
Clinical observations and results from translational clinical trials (3.) - based on the application of novel translational technologies (2.) - will then feed back into basic research (1.). This continuous workflow contributes to the ongoing development of clinically relevant questions and clinical trial designs.
In particular, the technological improvement (pillar 2.) of patient-derived model systems developed by Prof. Reichert requires strong interaction with the natural sciences at TUM. To strengthen these interactions and synergies, Prof. Reichert will lead research laboratories at the MRI Campus and Campus Garching in the future and act as a bridgehead between both locations.