Mathematics to Fight Cancer

Mathematicians and physicians at the University of Bonn have developed a new model for immunotherapy of cancer. The method could help to develop new treatment strategies and to understand why some approaches do not work with certain tumors. The study is now appearing in the technical journal Scientific Reports.

One of the greatest problems in the fight against cancer is the great hardiness of the tumors. Drug therapy often leads to initial success, which is then wiped out by a relapse. Sometimes the therapy has no affect at all against some cancer cells. Other cells develop resistance over the course of therapy.

Certain cells of the immune system, the so-called T-cells, can fight malignant tumors. Such cells are used or activated in a targeted manner to treat cancers. The research groups of Prof. Dr. Thomas Tüting and Prof. Dr. Michael Hölzel or the University of Bonn have demonstrated in their experiments on skin cancer that tumor cells can change their external appearance, if an inflammatory reaction occurs in the course of treatment. Consequently, the T-cells no longer recognize them as harmful, and the cancer can continue to spread unimpeded.

A new model from mathematicians and physicians from the Excellence Cluster of the Hausdorff Center for Mathematics and ImmunoSensation of the University of Bonn now describes this effect mathematically, thus making it possible to analyse it. In the future, the model could be used, among other things, for computer simulation of various therapeutic approaches and thus for the development of optimal treatment strategies.

Tumors as population
"The initial results show that treatment with several types of immune cells could in fact be a promising approach", says the lead scientist of this work, Prof. Dr. Anton Bovier of the Hausdorff Center for Mathematics. The studies are based on a stochastic model from the area of adaptive dynamics, which was developed by the mathematicians for application, for example, in cancer research. "Tumors are nothing other than populations of cancer cells, which interact with one another in a very complex manner and react to their environment in the form of the body and its immune system," explains Prof. Bovier.

Simulation of therapy
In numerical simulations by the Bonn researchers, the long-term success of a therapy, even when the starting conditions were the same, depended on random fluctuations in the population sizes of cancer and immune cells. Whether this effect also occurs in reality and not just on the computer still needs to be investigated experimentally. The virtual research of the Excellence Cluster has also showed that treatment, under certain circumstances, can even increase the probability of mutation in cancer cells. In some cases in the simulation, a therapy actually accelerated the development toward aggressive variants of cancer.

Prof. Hölzel of ImmunoSensation summarises the results of the interdisciplinary work as follows: "This project can both call the attention of mathematicians to possible applications of their work in a medical context and also sensitize physicians to the use of mathematical methods. In any case, we will continue to do joint research in the fight against cancer". To make it possible to use the model in practice, more experimental data still needs to be developed.

Martina Baar, Loren Coquille, Hannah Mayer, Michael Hölzel, Meri Rogava, Thomas Tüting & Anton Bovier (2016): A stochastic model for immunotherapy of cancer. Scientific Reports. DOI: 10.1038/srep24169.

Most Popular Now

Giving Doctors an AI-Powered Head Start …

Detection of melanoma and a range of other skin diseases will be faster and more accurate with a new artificial intelligence (AI) powered tool that analyses multiple imaging types simultaneously...

Philips Foundation 2024 Annual Report: E…

Marking its tenth anniversary, Philips Foundation released its 2024 Annual Report, highlighting a year in which the Philips Foundation helped provide access to quality healthcare for 46.5 million people around...

Scientists Argue for More FDA Oversight …

An agile, transparent, and ethics-driven oversight system is needed for the U.S. Food and Drug Administration (FDA) to balance innovation with patient safety when it comes to artificial intelligence-driven medical...

AI Agents for Oncology

Clinical decision-making in oncology is challenging and requires the analysis of various data types - from medical imaging and genetic information to patient records and treatment guidelines. To effectively support...

Start-ups in the Spotlight at MEDICA 202…

17 - 20 November 2025, Düsseldorf, Germany. MEDICA, the leading international trade fair and platform for healthcare innovations, will once again confirm its position as the world's number one hotspot for...

AI Medical Receptionist Modernizing Doct…

A virtual medical receptionist named "Cassie," developed through research at Texas A&M University, is transforming the way patients interact with health care providers. Cassie is a digital-human assistant created by Humanate...

Using Data and AI to Create Better Healt…

Academic medical centers could transform patient care by adopting principles from learning health systems principles, according to researchers from Weill Cornell Medicine and the University of California, San Diego. In...

AI Tool Set to Transform Characterisatio…

A multinational team of researchers, co-led by the Garvan Institute of Medical Research, has developed and tested a new AI tool to better characterise the diversity of individual cells within...

AI Detects Hidden Heart Disease Using Ex…

Mass General Brigham researchers have developed a new AI tool in collaboration with the United States Department of Veterans Affairs (VA) to probe through previously collected CT scans and identify...

Highland Marketing Announced as Official…

Highland Marketing has been named, for the second year running, the official communications partner for HETT Show 2025, the UK's leading digital health conference and exhibition. Taking place 7-8 October...

Human-AI Collectives Make the Most Accur…

Diagnostic errors are among the most serious problems in everyday medical practice. AI systems - especially large language models (LLMs) like ChatGPT-4, Gemini, or Claude 3 - offer new ways...

MHP-Net: A Revolutionary AI Model for Ac…

Liver cancer is the sixth most common cancer globally and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is a crucial step for the management of the...