The world's first digital cell twin in cancer electrophysiology: a digital revolution in cancer research?

Background: The introduction of functional in-silico models, in addition to in-vivo tumor models, opens up new and unlimited possibilities in cancer research and drug development. The world's first digital twin of the A549 cell's electrophysiology in the human lung adenocarcinoma, unveiled in 2021, enables the investigation and evaluation of new research hypotheses about modulating the function of ion channels in the cell membrane, which are important for better understanding cancer development and progression, as well as for developing new drugs and predicting treatments. Main body: The developed A549 in-silico model allows virtual simulations of the cell's rhythmic oscillation of the membrane potential, which can trigger the transition between cell cycle phases. It is able to predict the promotion or interruption of cell cycle progression provoked by targeted activation and inactivation of ion channels, resulting in abnormal hyper- or depolarization of the membrane potential, a potential key signal for the known cancer hallmarks. For example, model simulations of blockade of transient receptor potential cation channels (TRPC6), which are highly expressed during S-G2/M transition, result in a strong hyperpolarization of the cell's membrane potential that can suppress or bypass the depolarization required for the S-G2/M transition, allowing for possible cell cycle arrest and inhibition of mitosis. All simulated research hypotheses could be verified by experimental studies. Short conclusion: Functional, non-phenomenological digital twins, ranging from single cells to cell-cell interactions to 3D tissue models, open new avenues for modern cancer research through dry lab approaches that optimally complement established in-vivo and in-vitro methods.

Automated summary

The introduction of functional in-silico models opens up new possibilities in cancer research and drug development. The digital twin of A549 cell's electrophysiology allows investigation of ion channel function and prediction of cell cycle progression changes. The model provides a platform for verifying research hypotheses and optimizing experimental methods.