Systems biologist Prof. Stefan Legewie and his team at the Institute of Biomedical Genetics and the Stuttgart Research Center Systems Biology combine cell biology, computer science, biophysics, and mathematics to develop a systemic understanding of intracellular processes.
Working with cells. Image credit: CDC
The central focus of systems biology is the holistic analysis of complex biological data sets, which helps to give us a better understanding of important questions in such areas as cancer research, for example: how do cells respond to changes in their immediate environment, and how is genetic activity controlled during this process?
“Our primary focus is on signal transduction cascades, which transmit information from the cell membrane to the cell nucleus,” says Legewie, summarizing the scope of his research.
“After that, we're interested in processing, by which I'm referring to the modification of ribonucleic acids (RNA).” In an attempt to answer these questions, the working group is not only using experiments but also mathematical modeling and artificial intelligence.
Understanding the decision-making processes involved in cancer
In terms of cancer research, the group is investigating a specific signaling pathway with a tumor-suppressive effect, i.e., it is able to block the growth of tumors. One way to picture this is to imagine a hormone-like protein called TGFß, which attaches to receptors on the cell surface.
Once this signal has been transmitted to the cell nucleus it activates genes that inhibit cell growth but if the signaling pathway changes, due to mutations for example, TGFß can no longer inhibit the growth leading to excessive cell growth and ultimately cancer. Other changes in the same signaling pathway can cause cells to migrate and a tumor to metastasize.
The primary goal of Legewie's research group is to gain a better understanding of these decision-making processes in the TGFß signaling pathway that play a role in cancer, whereby they exploit the fact that not all cells in a cell population behave in the same way: some stop growing, whereas others migrate or do not respond in any way at all.
“So, what we do,” as Legewie explains, “is to analyze a large number of individual cells and exploit their heterogeneity to understand the underlying decision-making principles.” The findings, which were obtained in collaboration with the University of Darmstadt, were recently published in the scientific journal “PNAS”.1.
Ultimately, the scientists are trying to identify potential targets that can be targeted to reverse the process of tumor development and metastasis. The hope is that it will eventually be possible to develop drugs that will be able to shrink metastasizing tumors.
Legewie's second field of research, which involves the processing of messenger RNA in cellular protein synthesis, is already much closer to use in therapeutic settings.
The result of this processing, which is referred to as alternative splicing, is that human cells have many more protein variants than such things as yeast cells or other lower organisms, which becomes important in treatments, such as CAR-T cell therapy, which is used for end-stage leukemias when the patients' own immune cells (T cells) are extracted and reprogrammed to make them attack leukemia cells after they are reintroduced to the body.
This treatment is extremely efficient in principle but sometimes the leukemia cells simply don’t respond to the T cells, because T cells are programmed to target a specific receptor on the surface of the cell. This is the very receptor that is processed in a different way in resistant leukemia cells as a result of mutations in the genome, which renders the therapy ineffective.
Predicting the effects of complex mutations
Legewie's team, is collaborating with groups in Mainz and Frankfurt to gain a better understanding of the principles of resistance development by devising a screening approach that can be used to characterize several tens of thousands of mutations in a high-throughput mapping process, which was reported on last year in the journal Nature Communications.2
What they found was that processing mRNA is enormously complex, as even a relatively short genetic segment of the surface protein gives rise to about 100 variants that could potentially confer resistance. There are also numerous potential combinations of mutations and it is difficult to predict how they will interact.
Mathematics has been instrumental in interpreting the relevant data: the research group used various approaches based on systems biology to develop quantitative models that accurately predict the effects of complex mutations on the products of gene transcriptions.
“Going forward,” says Legewie,” we may be able to use this data to predict whether a patient will develop resistance as soon as the treatment starts.” The findings also indicate which other therapeutic approaches CAR T-cell therapy could be combined with in order to guard against resistance.
1 Bohn et.al.: State- and stimulus-specific dynamics of SMAD signaling determine fate decisions in individual cells. Proceedings of the National Academy of Sciences (in press), https://doi.org/10.1073/pnas.2210891120
2 Cortés-López et.al.: High-throughput mutagenesis identifies mutations and RNAbinding proteins controlling CD19 splicing and CART-19 therapy resistance. Nature Communications 2022, https://www.nature.com/articles/s41467-022-31818-y
Source: University of Stuttgart