Novel insights into the mechanism of formaldehyde-induced lung cancer: a network toxicology and molecular docking approach.
TL;DR
This study provides key targets and pathways for understanding the complex molecular mechanisms by which FA affects lung cancer, reveals complex relationships that are difficult to find by traditional toxicological methods, and provides insights into strategies for preventing lung cancer caused by FA exposure.
OpenAlex 토픽 ·
Indoor Air Quality and Microbial Exposure
Ferroptosis and cancer prognosis
Bioinformatics and Genomic Networks
This study provides key targets and pathways for understanding the complex molecular mechanisms by which FA affects lung cancer, reveals complex relationships that are difficult to find by traditional
APA
Yizhe Wei, Yiming Zhao, et al. (2026). Novel insights into the mechanism of formaldehyde-induced lung cancer: a network toxicology and molecular docking approach.. Toxicology mechanisms and methods, 36(4), 469-479. https://doi.org/10.1080/15376516.2026.2621747
MLA
Yizhe Wei, et al.. "Novel insights into the mechanism of formaldehyde-induced lung cancer: a network toxicology and molecular docking approach.." Toxicology mechanisms and methods, vol. 36, no. 4, 2026, pp. 469-479.
PMID
41641566
Abstract
We explored the complex effects of formaldehyde (FA) on lung cancer through network toxicology and molecular docking techniques, focusing on understanding the molecular mechanisms by which FA affects lung cancer from a biological network perspective. With the information of formaldehyde and lung cancer targets provided by databases (ChEMBL, STITCH, GeneCards, OMIM), we identified key potential targets that are closely related to formaldehyde and lung cancer. Protein-protein interaction(PPI) networks for core targets were constructed using the STRING database, and ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the David database. Subsequently, molecular docking simulations of key target proteins with FA were performed using AutoDock software to visualize binding interactions. Finally, utilizing the PanglaoDB database, we conducted data mining of single-cell RNA sequencing data to find cell types where a certain set of genes are expressed. The results showed that the key genes for formaldehyde effects on lung cancer were mainly concentrated in metabolism-related signaling cascades, including pyruvate metabolism, fatty acid metabolism, and Pantothenate and CoA biosynthesis pathways, and the core genes ADH5, ADH4, ADH1B, ADH6, and ADH7 were screened by PPI with GO and KEGG analysis. Subsequently, molecular docking simulations of the screened key genes with FA confirmed the robust binding interactions between formaldehyde and the core targets in the key genes (binding energies were all less than -1kcal/mol). Single-cell RNA sequencing distribution analysis showed that ADH5 and ADH1B were significantly enriched in Fibroblasts cell clusters, and ADH7 was significantly enriched in Basal cells cell clusters. Our study provides key targets and pathways for understanding the complex molecular mechanisms by which FA affects lung cancer, reveals complex relationships that are difficult to find by traditional toxicological methods, and provides insights into strategies for preventing lung cancer caused by FA exposure.
MeSH Terms
Molecular Docking Simulation; Formaldehyde; Lung Neoplasms; Humans; Protein Interaction Maps
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