November 28, 2021

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Graz University of Technology: The world’s first digital model of cancer cells

Graz University of Technology: The world's first digital model of cancer cells

Graz University of Technology: The world’s first digital model of cancer cells

 


Graz University of Technology: The world’s first digital model of cancer cells.  This computer model was developed under the leadership of researchers from Graz University of Technology (TU Graz). Taking human lung adenocarcinoma as an example, it simulates the periodic changes of the membrane potential of cancer cells and opens up a new way for cancer research.

 


Graz University of Technology: The world's first digital model of cancer cells

Sonja Langthaler, Christian Baumgartner and Theresa Rienmüller are all from the School of Healthcare Engineering at Graz University of Technology. They are the first to pursue the idea of ​​a simulation model…

Source: Lunghammer-TU Graz

 

For many years, computer models have been the standard tool for basic biomedical research. However, about 70 years after Hodgkin and Huxley first published the ionic current model of nerve cells in 1952, researchers from the Graz University of Technology (TU Graz) collaborated with the Medical University of Graz and the Memorial Sloan Kettering Cancer Center in New York. The cooperation finally succeeded in developing the world’s first cancer cell model, and therefore introduced “the necessary tools for modern cancer research and drug development,” Christian Baumgartner reported happily.

The head of the Institute of Healthcare Engineering at the European Medical Device Testing Center of the Graz University of Technology is the senior author of the digital model published in the journal Computational Biology of the Public Library of Science.

 

 

Excitable cells and non-excitable cells

So far, digital cell models have focused on excitable cells such as nerves or cardiomyocytes. They can simulate electrophysiological processes not only at the cellular level, but also at the tissue and organ level. These models have been used to support diagnosis and treatment in daily clinical practice. For the first time, an international research team led by Baumgartner focused on the specific electrophysiological properties of non-excitatory cancer cells.

In excitable cells, electrical stimulation triggers so-called action potentials. This results in a short-term change in electric potential that lasts for a few milliseconds on the cell membrane that transmits “electric” messages between cells. Through this mechanism, neural networks can communicate with each other, or the heart muscle can be activated to produce contraction. It is known from experimental studies that “unexcitable” cells also exhibit characteristic fluctuations in cell membrane potential. However, compared with excitable cells, the underlying changes happen very slowly, throughout the entire cell cycle, that is, hours or days, and serve as a transition signal between individual cell cycle phases,” explains Christian Baumgartner. And Research The Institute’s Deputy Director Theresa Rienmüller and PhD student Sonja Langthaler, Christian Baumgartner was the first to pursue the idea of ​​developing simulation models of these mechanisms.

 

 

Lung adenocarcinoma

The pathological changes of cell membrane voltage, especially during the cell cycle, are the basis for the development and progression of cancer. Sonja Langthaler went on to introduce in detail: “Ion channels connect the outside and inside of cells. They can promote the exchange of potassium, calcium, and sodium ions, thereby regulating membrane potential. Changes in ion channel composition and changes in ion channel functional behavior can lead to cell division. Disruption may even affect cell differentiation, thereby transforming healthy cells into diseased (carcinogenic) cells.”

For their digital cancer cell model, the research team chose the human lung adenocarcinoma cell line A549 as an example. The computer model simulates the rhythmic oscillations of the cell membrane potential during the transition between cell cycle phases, and can predict the changes in membrane potential caused by the opening and closing of selected ion channels induced by drugs. Baumgartner added: “So we got information about the impact of targeted interventions on cancer cells.”

 


“Freezing” cancer cells to grow or induce them to commit suicide

The activity of certain ion channels can also drive the division of diseased cells, thereby accelerating tumor growth. If ion channels are now being manipulated in a targeted manner, like new and promising drugs and drugs, it can be said that cell membrane voltage and the entire electrophysiological system can be off track. “This can be used to stop cancer cells at a certain stage of the cell cycle, and it can also induce premature cell death (apoptosis). It can “freeze” cancer cells as they grow, or induce cancer cells to commit suicide. This mechanism can be simulated with the help of models.” Baumgartner and his team believe that the first digital cancer cell model is the beginning of a more comprehensive study. In order to improve the level of detail of the model, a plan for further experiments and measurement verification has been developed, and has been submitted to the Austrian Science Foundation FWF for funding.

 

 

 

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Publication details: “A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma”. Sonja Langthaler, Theresa Rienmüller, Susanne Scheruebel, Brigitte Pelzmann, Niroj Shrestha, Klaus Zorn-Pauly, Wolfgang Schreibmayer, Andrew Koff and Christian Baumgartner. PLoS Compuational Biology, June 2021. https://doi.org/10.1371/journal.pcbi.1009091

 

(source:internet, reference only)


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