In a major development, researchers at the Graz University of Technology (TU Graz)in Austria have created a highly advanced digital twin of a human lung cancer cell—a breakthrough that promises to speed up the development of new targeted treatments and improve personalised cancer treatment approaches. The model represents a giant advancement in the nascent discipline of digital biology, which uses complicated computer simulations to anticipate how cancer cells would behave and respond to possible treatments. 

The DigLungCancer project, coordinated by Christian Baumgartner at TU Graz's Institute of Health Care Engineering, builds on the team's 2021 development of the world's first digital ion current model of cancer cells. This current iteration includes a detailed model of bioelectric processes and, more importantly, the dynamics of calcium ions within the cell.

Calcium has a contradictory role in cell biology: it is required for survival, but an excess can cause cell death. Because of its dual nature, accurate calcium regulation is an important target for cancer treatment. The TU Graz team made a big step forward by recreating small areas in the cell with high calcium levels and the CRAC channels that control them. These channels are critical for intracellular signalling, which regulates the cell cycle and cancer cell development. 

"One of the significant advances in our improved cell model is the detailed simulation of intracellular calcium distribution," explained Christian Baumgartner. "For the first time, we were able to add small areas, called microdomains, where calcium accumulates... This innovation allowed us to display the electrical events in cancer cells with unparalleled detail. 

The digital twin is made up of hundreds of mathematical equations that generate a functioning replica of the A549 lung cancer cell line. This enables researchers to conduct extensive, computer-based studies to predict how medicines influence calcium regulation and ion channels. One significant observation is that blocking certain CRAC channels can interrupt the cancer cell cycle and perhaps cause cell death. This computer-modelling approach has a significant advantage: it can simulate complicated drug interactions and scenarios that would be prohibitively difficult, expensive, and time-consuming to recreate in a wet lab. 

In terms of public health, this technology has the potential to significantly lower the cost and time required for medication discovery. Identifying the most promising therapeutic targets in silico (by computer simulation) allows researchers to prioritise only the most feasible options for laboratory and clinical testing, shortening the path to novel treatments. 

One present drawback is the model's emphasis on a single cell. The next rounds of research will replicate cell communication, cancer formation, and metastasis. The long-term goal is to apply this technology to generate digital twins based on unique patient data, paving the way for highly customised treatment programs. The researchers also mention that the method could be used for other diseases, such as breast and prostate cancer. 

The DigLungCancer project, funded by Austrian Cancer Aid  (Österreichische Krebshilfe), demonstrates the potential of digital biology to revolutionise oncology by providing faster, more precise, and cost-effective treatments.