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

    Collaboration Partners

    People from EMCL



    • Talk: S. Haupt. A computational model for investigating the evolution of colonic crypts during Lynch syndrome carcinogenesis. SMB2021, Oncology subgroup, online, 13th June 2021 – 17th June 2021.
    • Two-session minisymposium organization and chair: S. Haupt, M. Kloor, V. Heuveline. Mathematical Oncology: From methodological studies to clinical applications. MS11 & MS12 at SMB2021, Oncology subgroup, online, 13th June 2021 – 17th June 2021.
    • 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