Innovative Digital Cell Twin Advances Lung Cancer Research

Researchers at Graz University of Technology, led by Christian Baumgartner from the Institute of Health Care Engineering, have developed a highly detailed digital replica of the A549 lung cancer cell line. This innovative model simulates key bioelectric processes, including calcium dynamics within the cell, offering unprecedented insights into cancer cell behavior. Calcium plays a crucial role in cell survival and death; abnormal calcium regulation can lead to cell death, making it a significant focus in cancer treatment research.

The digital cell twin builds upon a previous 2021 model, regarded as the first of its kind to mimic ion currents in a human lung cancer cell. This enhanced model allows scientists to explore how calcium currents and electrical voltages influence tumor growth and progression. Although these cancer cells do not respond to neurophysiological stimuli like nerve cells, they do exhibit electrical activity that can now be depicted with remarkable precision.

By employing hundreds of mathematical equations and computer simulations, the model enables testing of how drugs impacting calcium channels or ion transport influence cell growth and viability. This approach can predict responses that are difficult and time-consuming to reproduce experimentally, helping to identify new drug targets and personalized treatment strategies.

A major breakthrough in this research is the detailed simulation of calcium distribution inside the cell, including specialized microdomains where calcium accumulates. These areas, regulated by CRAC channels, are pivotal in controlling signaling pathways associated with cell cycle regulation and apoptosis. The ability to model these processes in detail opens new pathways for understanding and potentially disrupting cancer progression.

While current models focus on individual cells, future research aims to include interactions between multiple cells, such as tumor development, metastasis, and vascularization. This progression could lead to personalized cancer treatments based on specific cell line characteristics or patient data. The methodology also holds promise for studying other cancers, including breast and prostate cancer.

The findings, published in Clinical and Translational Medicine, highlight the potential of digital twin technology to revolutionize cancer research by enabling precise, computer-based experiments that complement laboratory work. The integration of bioelectric and calcium signaling models marks a significant step toward targeted therapies and improved patient outcomes.

Source: https://medicalxpress.com/news/2025-09-digital-cell-twin-avenues-lung.html