Prof. Dr. Stefan Legewie

How cells make decisions

New at the university

Systems biologist Prof. Stefan Legewie combines cell biology, computer science, biophysics, and mathematics in order to holistically analyze complex biological data sets.
[Photo: University of Stuttgart, Uli Regenscheit]

How do cells respond when the environmental conditions change? And how how is the activity of genes controlled? These questions play an important role in cancer research. Legewie, who recently joined the University of Stuttgart as a professor of systems biology, wants to better understand these processes and is using mathematical modeling and artificial intelligence to do so. “We are primarily concerned with signal transduction cascades that transmit information from the cell membrane to the nucleus. We are also concerned with the processing – or modification – of RNA,” says Legewie, summarizing his research interests. “In cancer research, the focus is mainly on breast cancer cell lines. We are looking at a signaling pathway that has a tumor-suppressive – or tumor-blocking – effect.”

You can imagine this signal path like this: A small peptide, the hormone TGF-β (transforming growth factor beta), docks with the receptors on the surface of a normal cell and triggers enzyme-catalyzed reactions that transmit the signal to the nucleus. This stimulates the cell in such a way that the growth of the tissue is slowed. “The signaling pathway is important for homeostasis, the balance of the tissue. If the pathway changes, the hormone can no longer block growth. This results in uncontrolled cell growth and ultimately cancer.”


Control of an agar plate with E. Coli cultures

In the course of this, the cells do not completely switch off the signaling pathway but rather modify it. Accordingly, the signaling pathway can not only stop cell growth but also stimulate the cells to migrate. In the case of tumors, this leads to metastases elsewhere in the body. “We want to understand how this specificity – the behavior of the pathway – is changed. However, not all cells behave the same way: In a cell population, some cells stop growing, while others migrate. And some do both.

“Therefore, in addition to analyzing different stages of tumor development, we analyze many individual cells and use the heterogeneity in order to understand how the cell behavior is developing,” says Legewie. Mathematical methods can help with this. The way in which cells respond to a given hormone stimulus is not very precise; however, the percentage of cells that respond is: “It takes a critical threshold of stimulation. The switch is then flipped, and the cell decides to divide. The goal of our basic research is to find biomarkers that can be used to reverse tumor development and metastasis.” Researchers hope that it will eventually be possible to develop medication that can reverse metastatic tumors.


"Using systems biology approaches, we want to develop quantitative models with which the effects of complex mutations on gene products can be predicted."

Prof. Stefan Legewie

Hope for leukemia patients

Legewie’s secondary field of research, the processing of messenger RNA, which plays a central role in cellular protein synthesis, is leading him much closer to therapies. As a result of this processing, or alternative splicing, human cells do not have considerably more genes than yeast cells or other lower organisms. However, they do have many more protein variants. “We want to better understand this process,” says Legewie. For example, as part of a therapy for the treatment of end-stage leukemia, the patient’s own immune cells (T cells) are removed and reprogrammed (CAR T cell therapy). The T cells are modified so that they attack leukemia cells after they are re-injected into the patient. In principle, this is a highly efficient treatment method. However, the leukemia cells no longer respond to the T cells, which are programmed to target a specific receptor on the cell surface. It is precisely this receptor that is altered in resistant leukemia cells. The therapy thus no longer works.

Legewie’s group wants to solve this problem with Big Data: In cooperation with Julian König from the Institute of Molecular Biology in Mainz, he has developed a screening approach that allows the characterization and quantification of tens of thousands of mutations. “Based on this data, we try to predict before starting therapy whether the patient will develop resistance and whether the use of the expensive medication even makes sense. Our goal is also to develop strategies to combine CAR T-cell therapy with other therapeutic approaches in order to prevent the development of resistance,” says Legewie.

Prof. Stefan Legewie in front of a quantitative PCR machine.

One challenge is the sheer complexity of the data sets. Even a relatively short gene segment of the surface protein can yield about 100 variants in the course of mRNA processing. There are also numerous possible combinations of mutations. It is difficult to predict how these mutations will interact with each other. In order to resolve this complexity, the Legewie group is developing mathematical models. "Using systems biology approaches, we want to develop quantitative models with which the effects of complex mutations on gene products can be predicted."

Legewie benefits from the long-standing establishment of the Stuttgart Research Center Systems Biology (SRCSB) at the University of Stuttgart, the strong engineering sciences department, and the numerous research groups in the field of “red biotechnology” (i.e., the biotechnology of human cells). At the SRCSB, Legewie’s group will scale up the genomic approaches and methods for theoretically and experimentally characterizing gene expression. Legewie also benefits from the findings of the research groups led by Monilola Olayioye, Albert Jeltsch, and Nicole Radde, who, also in the fight against breast cancer, are also studying the interactions of signal transduction pathways on gene regulation.

Combining data sciences with biology

Legewie also wants to convey the link between theory, experiment, and model development to his students in order to generate enthusiasm for interdisciplinary research and quantitative approaches in biology. “They should understand how a large number of proteins interact and translate this into quantitative behavior. Data sciences – the analysis of large data sets – also play an important role.”


About Stefan Legewie

Stefan Legewie, born in 1977 in Aachen, studied biochemistry at the University of Witten/Herdecke and specialized in the then fledgling field of systems biology. In 2008, he received his doctorate in biophysics (summa cum laude) from the Humboldt University in Berlin. After a fellowship at the German Cancer Research Center, Legewie moved to the newly founded Institute of Molecular Biology (IMB) in Mainz as a group leader in 2010. There, he worked on the robustness and heterogeneity of biological systems and addressed the question of how the activity of genes can be reliably controlled. Since September 1, 2020, he has been Professor of Systems Biology at the University of Stuttgart.


Prof. Stefan Legewie, Institute of Industrial Genetics (IIG), Department of Systems Biology, Tel. +49 711 685 64573, e-mail

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