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
- Talk: S. Haupt. Mathematical Oncology – Understanding tumor evolution and developing new clinical concepts. HGS MathComp / 4EU+ Mathematical and Computational Methods in Science Annual Colloquium 2020, online, 1st December 2020 – 2nd December 2020.
- Minisymposium: Data-based modeling in cancer research with focus on clinical applications. eSMB2020, Oncology subgroup, online, 17th August 2020 - 20th August 2020.
- 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
- S. Haupt, N. Gleim, A. Ahadova, H. Bläker, M. von Knebel Doeberitz, M. Kloor, V. Heuveline: Computational model investigates the evolution of colonic crypts during Lynch syndrome carcinogenesis. bioRxiv 2020.12.29.424555; 12/29/2020; doi: 10.1101/2020.12.29.424555
- A. Ballhausen, M. J. Przybilla, M. Jendrusch, S. Haupt, E. Pfaffendorf, F. Seidler, J. Witt, A. Hernandez Sanchez, K. Urban, M. Draxlbauer, S. Krausert, A. Ahadova, M. S. Kalteis, P. L. Pfuderer, D. Heid, D. Stichel, J. Gebert, M. Bonsack, S. Schott, H. Bläker, T. Seppälä, J.-P. Mecklin, S. Ten Broeke, M. Nielsen, V. Heuveline, J. Krzykalla, A. Benner, A. B. Riemer, M. von Knebel Doeberitz, M. Kloor: The shared frameshift mutation landscape of microsatellite-unstable cancers suggests immunoediting during tumor evolution. Nature Communications, Sep 2020; doi: 10.1038/s41467-020-18514-5
- 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: Age‐dependent performance of BRAF mutation testing in Lynch syndrome diagnostics. International Journal of Cancer, Sep 2020; doi: 10.1002/ijc.33273
- S. Haupt, A. Zeilmann, A. Ahadova, M. von Knebel Doeberitz, M. Kloor, V. Heuveline: Mathematical Modeling of Multiple Pathways in Colorectal Carcinogenesis using Dynamical Systems with Kronecker Structure. bioRxiv 2020.08.14.250175; 08/14/2020; doi: 10.1101/2020.08.14.250175
- 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: 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: 10.1101/691469
- Further information about the project with ATB