Key result
The A549 in-silico 1.0 computational model successfully simulated the rhythmic oscillation of the membrane potential during cell cycle progression and predicted changes provoked by targeted ion channel modulation.
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The first in-silico whole-cell ion current model of the A549 lung adenocarcinoma cell line accurately simulates cell cycle-dependent electrophysiological changes, providing a tool for studying ion channel interactions in tumor progression.
Lung cancer is still a leading cause of death worldwide. In recent years, knowledge has been obtained of the mechanisms modulating ion channel kinetics and thus of cell bioelectric properties, which is promising for oncological biomarkers and targets. The complex interplay of channel expression and its consequences on malignant processes, however, is still insufficiently understood. We here introduce the first approach of an in-silico whole-cell ion current model of a cancer cell, in particular of the A549 human lung adenocarcinoma, including the main functionally expressed ion channels in the plasma membrane as so far known. This hidden Markov-based model represents the electrophysiology behind proliferation of the A549 cell, describing its rhythmic oscillation of the membrane potential able to trigger the transition between cell cycle phases, and it predicts membrane potential changes over the cell cycle provoked by targeted ion channel modulation. This first A549 in-silico cell model opens up a deeper insight and understanding of possible ion channel interactions in tumor development and progression, and is a valuable tool for simulating altered ion channel function in lung cancer electrophysiology.
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Langthaler et al. (2021) studied Lung adenocarcinoma (n=16). A549 in-silico 1.0 computational model was evaluated on Simulation of whole-cell ion current and membrane potential changes. The A549 in-silico 1.0 computational model successfully simulated the rhythmic oscillation of the membrane potential during cell cycle progression and predicted changes provoked by targeted ion channel modulation.
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