GRK 2424:  Computational Methods for Oncology: Towards Personalized Therapies in Cancer

• Subject Area: Basic Research in Biology and Medicine ; Medicine
• Term: since 2019
• Website: Homepage
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 377984878

Advances in molecular profiling techniques and computational methods for analysing complex and large data sets have triggered a major shift in cancer research. Traditional coarse-grained and phenomenological examinations are replaced by unbiased molecular profiling methods. These generate mechanistic and molecular insights on tumour aetiology, progression and treatment resistance. Various forms of systematic molecular profiling of tumours combined with specific forms of computational analyses are used in cancer research and also increasingly to stratify patients and to influence therapy decisions. This shift has triggered a strong increase in the importance of computational methods in cancer research, as more and more complex, increasingly large, and ever more heterogeneous data sets must be properly integrated and analysed to derive actionable biomedical knowledge that can ultimately be the basis for clinical decision support. Development and application of such methods requires profound knowledge (i) in molecular biology, (ii) in clinical aspects of cancer, and (iii) in advanced techniques for precise computational data analysis. This poses a major challenge for current graduate education which typically focusses on just one of these three pillars, whereas future ‘computational oncologists’ need state-of-the-art supervision and training in all of them. Here, we lay out our plans for continuing the successful work of the research training group CompCancer on computational approaches in cancer research. Within CompCancer, students work on computational research problems targeting research questions related to modern personalized therapy, tumor heterogeneity and therapy resistance. To cover all necessary aspects of such an undertaking, CompCancer builds on an interdisciplinary faculty whose expertise ranges from computer science to bioinformatics and systems biology/systems medicine to molecular biology, molecular pathology and clinical oncology. All students are co-supervised by at least one expert in computational research and by one clinical/experimental researcher, ensuring expert supervision in both areas. A specifically designed training program will ensure that PhD students become experts in computational biology and gain expert understanding of cancer biology and its translational aspects.

• DFG Programme: Research Training Groups
• Participating Institution: Max-Delbrück-Centrum für Molekulare Medizin (MDC); Max-Planck-Institut für molekulare Genetik (MPIMG)
• Applicant Institution: Humboldt-Universität zu Berlin
• Co-Applicant Institution: Charité - Universitätsmedizin Berlin
• Spokesperson: Professor Dr. Nils Blüthgen
• Participating Researchers: Professor Dr. Dieter Beule; Professor Dr. David Capper; Dr. Stefanie Grosswendt; Professor Dr. Anton Henssen; Dr. Dagmar Kainmüller; Professorin Dr. Kirsten Kübler; Professor Dr. Ulf Leser; Professorin Dr. Il-Kang Na; Professor Dr. Johannes Hubertus Schulte; Professorin Dr. Christine Sers; Professor Dr. Martin Vingron