A549 In-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma

Sonja Langthaler, Theresa Margarethe Rienmüller, Susanne Scherübel, Brigitte Pelzmann, Niroj Shrestha , Klaus Zorn-Pauly, Wolfgang Schreibmayer, Andrew Koff, Christian Baumgartner*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article numbere1009091
Number of pages28
JournalPLoS Computational Biology
Issue number6
Publication statusPublished - 22 Jun 2021


  • A549 cell line
  • io current model
  • Hidden Markov models (HMMs)
  • electrophysiology
  • cell cycle
  • cancer
  • lung adenocarcinoma

ASJC Scopus subject areas

  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Cellular and Molecular Neuroscience
  • Molecular Biology
  • Ecology
  • Computational Theory and Mathematics
  • Modelling and Simulation

Fields of Expertise

  • Human- & Biotechnology


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