Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Langthaler, Sonja, Rienmüller, Theresa, Scheruebel, Susanne, Pelzmann, Brigitte, Shrestha, Niroj, Zorn-Pauly, Klaus, Schreibmayer, Wolfgang, Koff, Andrew, Baumgartner, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219159/
https://www.ncbi.nlm.nih.gov/pubmed/34157016
http://dx.doi.org/10.1371/journal.pcbi.1009091
_version_ 1783710875939504128
author Langthaler, Sonja
Rienmüller, Theresa
Scheruebel, Susanne
Pelzmann, Brigitte
Shrestha, Niroj
Zorn-Pauly, Klaus
Schreibmayer, Wolfgang
Koff, Andrew
Baumgartner, Christian
author_facet Langthaler, Sonja
Rienmüller, Theresa
Scheruebel, Susanne
Pelzmann, Brigitte
Shrestha, Niroj
Zorn-Pauly, Klaus
Schreibmayer, Wolfgang
Koff, Andrew
Baumgartner, Christian
author_sort Langthaler, Sonja
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8219159
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-82191592021-07-07 A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma Langthaler, Sonja Rienmüller, Theresa Scheruebel, Susanne Pelzmann, Brigitte Shrestha, Niroj Zorn-Pauly, Klaus Schreibmayer, Wolfgang Koff, Andrew Baumgartner, Christian PLoS Comput Biol Research Article 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. Public Library of Science 2021-06-22 /pmc/articles/PMC8219159/ /pubmed/34157016 http://dx.doi.org/10.1371/journal.pcbi.1009091 Text en © 2021 Langthaler et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Langthaler, Sonja
Rienmüller, Theresa
Scheruebel, Susanne
Pelzmann, Brigitte
Shrestha, Niroj
Zorn-Pauly, Klaus
Schreibmayer, Wolfgang
Koff, Andrew
Baumgartner, Christian
A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title_full A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title_fullStr A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title_full_unstemmed A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title_short A549 in-silico 1.0: A first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
title_sort a549 in-silico 1.0: a first computational model to simulate cell cycle dependent ion current modulation in the human lung adenocarcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219159/
https://www.ncbi.nlm.nih.gov/pubmed/34157016
http://dx.doi.org/10.1371/journal.pcbi.1009091
work_keys_str_mv AT langthalersonja a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT rienmullertheresa a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT scheruebelsusanne a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT pelzmannbrigitte a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT shresthaniroj a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT zornpaulyklaus a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT schreibmayerwolfgang a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT koffandrew a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma
AT baumgartnerchristian a549insilico10afirstcomputationalmodeltosimulatecellcycledependentioncurrentmodulationinthehumanlungadenocarcinoma