Dataset Information

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

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.

SUBMITTER: Langthaler S

PROVIDER: S-EPMC8219159 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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

Langthaler Sonja S Rienmüller Theresa T Scheruebel Susanne S Pelzmann Brigitte B Shrestha Niroj N Zorn-Pauly Klaus K Schreibmayer Wolfgang W Koff Andrew A Baumgartner Christian C

PLoS computational biology 20210622 6

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 ...[more]

PMID: 34157016

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Project description:BackgroundMany anticancer agents and carcinogens are DNA damaging chemicals and exposure to such chemicals results in the deregulation of cell cycle progression. The molecular mechanisms of DNA damage-induced cell cycle alteration are not well understood. We have studied the effects of etoposide (an anticancer agent), cryptolepine (CLP, a cytotoxic alkaloid), benzo [a]pyrene (BaP, a carcinogenic polycyclic aromatic hydrocarbon) and 2-amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP, a cooked-meat derived carcinogen) on the expression of cell cycle regulatory genes to understand the molecular mechanisms of the cell cycle disturbance.ResultsA549 cells were treated with DMSO or chemicals for up to 72 h and periodically sampled for cell cycle analysis, mRNA and protein expression. DMSO treated cells showed a dominant G1 peak in cell cycle at all times examined. Etoposide and CLP both induced G2/M phase arrest yet the former altered the expression of genes functioning at multiple phases, whilst the latter was more effective in inhibiting the expression of genes in G2-M transition. Both etoposide and CLP induced an accumulation of p53 protein and upregulation of p53 transcriptional target genes. Neither BaP nor PhIP had substantial phase-specific cell cycle effect, however, they induced distinctive changes in gene expression. BaP upregulated the expression of CYP1B1 at 6-24 h and downregulated many cell cycle regulatory genes at 48-72 h. By contrast, PhIP increased the expression of many cell cycle regulatory genes. Changes in the expression of key mRNAs were confirmed at protein level.ConclusionOur experiments show that DNA damaging agents with different mechanisms of action induced distinctive changes in the expression pattern of a panel of cell cycle regulatory genes. We suggest that examining the genomic response to chemical exposure provides an exceptional opportunity to understand the molecular mechanism involved in cellular response to toxicants.

Dataset Information

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

Publications

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

Similar Datasets

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