An enhanced computer model is now helping to provide fresh insights into cancer-cell growth and how it can be stopped. The digital cell model represents another step towards individualised cancer treatment.

A team led by Christian Baumgartner of the Institute of Health Care Engineering at Graz University of Technology (TU Graz) has developed a highly detailed digital twin of the A549 lung cancer cell line. The twin builds on bioelectric processes and calcium dynamics in the cell interior in innovative new ways. Calcium is a vital component in the survival of biological cells. However, if the concentration of calcium within a cell is too high, this can cause cell death – which is what makes the element such an interesting factor in cancer treatment. Created under the DigLungCancer project, the cell model builds on an earlier model from 2021 – regarded as the world’s first digital ion current model of a human A549 lung adenocarcinoma cell line. The improved model will pave the way for research into the ways in which calcium currents and electrical voltages on the cell membrane influence cancer-cell growth. Although these cells cannot be activated in the conventional neurophysiological sense, they do demonstrate electrical activity. The digital model provides the most detailed functional depiction of bioelectricity in cancer cells to date. The long-term aim is to identify new targets for drugs and computer-aided, personalised treatment strategies. The project is funded by the Styrian branch of Austrian cancer advisory and support organisation Österreichische Krebshilfe.

Insight into cell-cycle control

“One of the significant advances in our improved cell model is the detailed simulation of intracellular calcium distribution,” comments Christian Baumgartner. “For the first time, we were able to include small areas, or microdomains, where calcium builds up and where the interior cell networks are close to the cell membrane. In these areas, what we refer to as calcium release-activated calcium or CRAC channels regulate the inflow of calcium, which plays a central role in the activation of intracellular signal pathways – including those that influence the cell cycle. This improvement enabled us to depict the electrical processes in cancer cells with unprecedented precision, including calcium storage, transportation mechanisms, buffer capacities, and the effects of the localised spread of calcium inside the cell.”

At its core, the digital cell twin consists of hundreds of mathematical equations that merge to form computer simulations. This detailed digital cell allows the researchers to run computer-supported tests on the impacts of drugs on cell behaviour. For instance, it is possible to predict the effect of substances that influence calcium distribution or the function of ion channels in certain areas. In turn, this enables testing of assumptions on cell growth or potential cell death; if the results are relevant, they can then be tested in the lab. The digital cell also allows for examination of complex combinations of changes in ion channel function – replicating them in real life in the lab would be difficult and extremely time-consuming. The researchers have already demonstrated that inhibiting certain CRAC channels can change local calcium dynamics and influence the activity of other calcium-regulating signal pathways. This can result in interruption of the cell cycle or trigger cell-death mechanisms.

Next step: communication between several cells

So far, the model only includes a single cell, meaning that some important mechanisms cannot yet be represented, such as communication between cells in clusters, the development of a tumour, the spread of cancer cells (metastasis) and the formation of new blood vessels in the tumour (vascularisation). The next phases of the research project will move in this direction. In the long term, the findings could potentially support adaptation to specific cell lines or patient data for the purposes of personalised cancer research and treatment. According to the researchers, the methodology could also be applied to other forms of cancer, including breast cancer and prostate cancer.