Treffer: Nickel Nanoparticles Promote Lung Adenocarcinoma Progression via CDK1-Mediated Fatty Acid Metabolism Regulation.

Title:
Nickel Nanoparticles Promote Lung Adenocarcinoma Progression via CDK1-Mediated Fatty Acid Metabolism Regulation.
Source:
International Journal of Molecular Sciences; Nov2025, Vol. 26 Issue 21, p10624, 16p
Database:
Complementary Index

Weitere Informationen

Nickel nanoparticles (NiNPs) are extensively used in nanotechnology, electronics, and biomedical fields, raising concerns about their pulmonary toxicity and potential role in inducing lung adenocarcinoma (LUAD). While heavy metals, like arsenic and cadmium, are well-known to drive LUAD through metabolic reprogramming, the molecular mechanism linking NiNPs to LUAD—particularly their impact on fatty acid metabolism (FAM)—remains unclear. This study is the first to explore whether NiNPs promote LUAD progression via the CDK1/STAT3/FASN axis, a key regulator of FAM, and to evaluate the natural compound apigenin (API) as a potential inhibitory agent. When human (A549) and mouse (LLC) LUAD cells were exposed to NiNPs, assessments of cell function and protein expression revealed increased malignant phenotypes, including enhanced proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT), along with activation of the CDK1/STAT3/FASN axis and upregulation of FAM-related markers. Genetic silencing of either CDK1 or FASN reversed the dysregulation of FAM and reduced the malignant characteristics of the cells. Molecular docking analysis confirmed that API binds strongly to CDK1, and further experiments demonstrated that API suppresses NiNP-induced tumor growth both in laboratory cell models and in living organisms, while also blocking the activity of the CDK1/STAT3/FASN axis. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Molecular Sciences is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)