Aims and Objectives
Cancer is one of the leading causes of disease-related death worldwide. In recent years, rapid increase in the molecular understanding of cancer has unraveled significant additional complexity of the disease. Although large amounts of data on cancer genetics and molecular characteristics are available and accumulating with increasing speed, adequate interpretation of these data still represents a major bottleneck. This is exactly where mathematics can be applied to oncology: Through mathematical modeling of complex biological processes we are able to gain novel, unprecedented medical insights. The fields of application of mathematical models include the analysis of biological concepts and medical hypotheses about cancer evolution, and the prediction of clinical outcomes using existing clinical and molecular information. On the other hand, the medical applications give rise to mathematical challenges, which can lead to new methods and algorithms in various fields of mathematics, like data analysis, mathematical modeling and machine learning. Therefore, applying mathematics in the field of oncology will facilitate data interpretation and improve our understanding of carcinogenic processes.
We implement mathematical modeling on the example of Lynch syndrome (LS). LS is the most common inherited cancer syndrome and predisposes affected individuals to developing cancer in the large bowel (colorectal cancer) and other organs. LS is reflects general principles of tumorigenesis and tumor immunology beyond the hereditary context in an exemplary manner. We are focusing on three main parts:
- Mathematically modeling the evolution of hereditary tumors to improve the existing prevention strategies
- Elevating tumor immunology to a genome-wide level
- Predicting the efficacy of clinical approaches for diagnostics, prevention and treatment
- Engineering Mathematics and Computing Lab (EMCL), Prof. Dr. Vincent Heuveline, IWR, Heidelberg University
- Department of Applied Tumor Biology (ATB), PD Dr. Matthias Kloor and Prof. Dr. Magnus von Knebel Doeberitz, Heidelberg University Hospital
People from EMCL
- Talk: S. Haupt, M. Kloor. Mathematical Oncology - Understanding tumor evolution and developing new clinical concepts. HITS-S3 Scientific Seminar Series, Heidelberg, Germany, 28th October 2019.
- Talk & poster presentation: How mathematics can help in the fight against cancer. European Hereditary Tumor Group (EHTG) Meeting 2019, Barcelona, Spain, 17th October 2019 - 20th October 2019
- Poster presentation: S. Haupt, M. Kloor, M. von Knebel Doeberitz, V. Heuveline. Mathematical Modeling of the Pathogenesis of Mismatch Repair-Deficient Cancers. CSBC-PSON Mathematical Oncology Meeting 2019, Portland, USA, 13th May 2019 - 14th May 2019
- Talk: Mathematical Modeling of Tumorigenesis - A Main Goal in Mathematical Oncology. HGS Annual Colloquium 2018, Altleiningen, Germany, 29th November 2018 - 30th November 2018
- H. Bläker, S. Haupt, M. Morak, E. Holinski-Feder, A. Arnold, D. Horst, J. Sieber-Frank, F. Seidler, M. von Winterfeld, E. Alwers, J. Chang-Claude, H. Brenner, W. Roth, C. Engel, M. Löffler, G. Möslein, H.-K. Schackert, J. Weitz, C. Perne, S. Aretz, R. Hüneburg, W. Schmiegel, D. Vangala, N. Rahner, V. Steinke-Lange, V. Heuveline, M. von Knebel Doeberitz, A. Ahadova, M. Hoffmeister, M. Kloor, the German Consortium for Familial Intestinal Cancer: BRAF mutation testing of MSI CRCs in Lynch syndrome diagnostics: performance and efficiency according to patient`s age. medRxiv 19009274; 10/16/2019; doi: https://doi.org/10.1101/19009274
- A. Ballhausen, M. J. Przybilla, M. Jendrusch, S. Haupt, E. Pfaffendorf, M. Draxlbauer, F. Seidler, S. Krausert, A. Ahadova, M. S. Kalteis, D. Heid, J. Gebert, M. Bonsack, S. Schott, H. Bläker, T. Seppälä, J.-P. Mecklin, S. T. Broeke, M. Nielsen, V. Heuveline, J. Krzykalla, A. Benner, A. B. Riemer, M. von Knebel Doeberitz, M. Kloor: The shared neoantigen landscape of MSI cancers reflects immunoediting during tumor evolution. bioRxiv 691469; 07/16/2019; doi:
- Further information about the project with ATB