MATHEMATICS IN ONCOLOGY
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.
Research Topics
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
Funding
The project is officially funded by the Klaus Tschira Foundation, 2021-2024.
Collaboration Partners
- 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
Contact
News & Blogposts
2021
- Aysel Ahadova and Saskia Haupt have written a blog post on the MathOnco Blog: Using mathematics for deciphering molecular pathways of carcinogenesis in hereditary cancer syndromes, 12/2021
- Our project Mathematics in Oncology is now officially funded for 3-years by the Klaus Tschira Foundation.
- I like Interdisciplinary research – or how to combine mathematics and medicine, SciLogs Blog post, Spektrum.de, 12/2021
- Mathematical Oncology: Exploring the Origin of Colon Cancer, HITS Newsletter Issue 3, 09/2021
- Computational Oncology: Exploring the origin of Colon Cancer, HITS Blog, 22/07/2021
- Cover Art, This Week in Mathematical Oncology: Week 166, The Mathematical Oncology Newsletter, 06/2021
- Modeling multiple pathways of carcinogenesis using the Kronecker structure: Behind the paper, The Mathematical Oncology Blog, 06/2021
- EMCL is contributing in SMB2021 with a two-session mini-symposium, EMCL News, 06/2021
- Investigating cancer development with the help of mathematics, HITS Blog, 28/05/2021
- New publication in PLOS Computational Biology, EMCL News, 05/2021
2020
- New publication in Nature Communications, EMCL News, 09/2020
- The calculated tumor – how algorithms support the search for vaccines against cancer, HITS Blog, 25/09/2020
- Vaccination against altered proteins could prevent cancer development, German Cancer Research Center (DKFZ) press release, 22/09/2020
- New publication in the Mathematics in Oncology collaboration, EMCL News, 09/2020
Publications
- S. Haupt, N. Gleim, A. Ahadova, H. Bläker, M. von Knebel Doeberitz, M. Kloor, V. Heuveline: A computational model for investigating the evolution of colonic crypts during Lynch syndrome carcinogenesis.Computational and Systems Oncology, July 2021, doi:10.1002/cso2.1020 (Preprint on bioRxiv, Code on GitHub)
- S. Haupt, A. Zeilmann, A. Ahadova, H. Bläker, M. von Knebel Doeberitz, M. Kloor, V. Heuveline: Mathematical modeling of multiple pathways in colorectal carcinogenesis using dynamical systems with Kronecker structure. PLOS Computational Biology, May 2021; doi: 10.1371/journal.pcbi.1008970 (Preprint on bioRxiv)
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 (Preprint on bioRxiv)
- 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 (Preprint on medRxiv)
Links
- Further information about the project with ATB