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Mathematical modelling leads to a better understanding of prostate cancer

Date:
November 14, 2024
Source:
University of Cologne
Summary:
Researchers have developed a three-dimensional mathematical model of prostate cancer. The model depicts various processes, including tumour growth, genetic evolution and tumour cell competition.
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Researchers at the University of Cologne develop three-dimensional mathematical model of prostate cancer. The model depicts various processes, including tumour growth, genetic evolution and tumour cell competition. It may also be applicable to other forms of cance.

A team led by Dr Yuri Tolkach at the University of Cologne's Faculty of Medicine and University Hospital Cologne has investigated prostate tumours and developed an advanced, realistic, three-dimensional model of prostate cancer with the help of mathematical modelling. The model depicts tumour growth, genetic evolution and the competition between subclones -- different cell populations within a tumour. It shows, among other things, that the development of an aggressive tumour requires 'strong' genetic changes that immediately give the tumour cells special survival advantages. These must occur early in the course of tumour development, when the tumour is still small. The study also shows that the distribution of subclones within a tumour has an impact on diagnostic approaches such as biopsies.

The paper "Tumour architecture and emergence of strong genetic alterations are bottlenecks for clonal evolution in primary prostate cancer" has been published in Cell Systems.

Prostate cancer is the most common cancer in men. However, the mechanisms of tumour development, particularly the development of aggressive tumours, are still largely unclear in prostate cancer and other malignant tumours for two reasons: Firstly, tumours are often only discovered when they have already reached a considerable size. The time span between the development of the tumour and the diagnosis, which can be 10 to 30 years, is therefore not taken into account. Secondly, state-of-the-art methods such as next-generation sequencing (NGS), which make it possible to comprehensively characterize the tumour at subclone level, are costly and extremely complex to evaluate. For these reasons, only a few tumours worldwide have so far been examined in this way.

"Our study shows that we can use mathematical modelling to address important, previously unanswered questions about the development of malignant tumours and thus gain clinically relevant insights. Our model is universally applicable and can also be used for other malignant tumour types," explained senior physician and co-leader of the study, Dr Yuri Tolkach from the Institute of General Pathology and Pathological Anatomy at University Hospital Cologne.

"With our new model, we can reproduce the complex spatial structure of a prostate tumour, which grows like a root system in the tissue," explained postdoc and co-leader of the study, Dr Florian Kreten, who previously worked at the Institute for Applied Mathematics at the University of Bonn. He added: "Conventional mathematical models of tumour growth and evolution could not be applied to these structures. From a mathematical point of view, the underlying growth mechanism is extremely fascinating and has raised a number of new questions. Our work shows how biology can inspire mathematical research." In future, the scientists hope to be able to further develop the models and to include the interaction between the tumour and the immune system.


Story Source:

Materials provided by University of Cologne. Note: Content may be edited for style and length.


Journal Reference:

  1. Florian Kreten, Reinhard Büttner, Martin Peifer, Christian Harder, Axel M. Hillmer, Nima Abedpour, Anton Bovier, Yuri Tolkach. Tumor architecture and emergence of strong genetic alterations are bottlenecks for clonal evolution in primary prostate cancer. Cell Systems, 2024; DOI: 10.1016/j.cels.2024.10.005

Cite This Page:

University of Cologne. "Mathematical modelling leads to a better understanding of prostate cancer." ScienceDaily. ScienceDaily, 14 November 2024. <www.sciencedaily.com/releases/2024/11/241114125646.htm>.
University of Cologne. (2024, November 14). Mathematical modelling leads to a better understanding of prostate cancer. ScienceDaily. Retrieved December 14, 2024 from www.sciencedaily.com/releases/2024/11/241114125646.htm
University of Cologne. "Mathematical modelling leads to a better understanding of prostate cancer." ScienceDaily. www.sciencedaily.com/releases/2024/11/241114125646.htm (accessed December 14, 2024).

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