Abstract
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.
Highlights
Lung cancer is one of the most prevalent forms of tumor and the leading cause of cancer death worldwide.[1,2,3] Increasing knowledge of molecular cancer biology and the identification of key and potentially targetable genetic and molecular aberrations that drive tumor growth provide efficient diagnostic and therapeutic approaches for lung cancer
Our hidden Markov-based in-silico cell model represents the electrophysiology behind proliferation of the A549 cell line, explaining the cell’s rhythmic oscillation from hyperpolarized to depolarized states of the membrane potential, able to trigger
In this work we introduce for the first time an ion current model of the A549 human lung adenocarcinoma cell, representing an initial description of a cell model as a whole in cancer electrophysiology
Summary
Lung cancer is one of the most prevalent forms of tumor and the leading cause of cancer death worldwide.[1,2,3] Increasing knowledge of molecular cancer biology and the identification of key and potentially targetable genetic and molecular aberrations that drive tumor growth provide efficient diagnostic and therapeutic approaches for lung cancer. Advances in our understanding of molecular alterations at genetic, epigenetic or protein expression levels together with their functional significance, and in recent years, expanding knowledge in the mechanisms and modulation of ion channel function in cancer biology lead to the development of promising cancer biomarkers and oncological targets.[8,9]
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