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...
Autores principales: | , , , , , , , , |
---|---|
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 |