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ARHGAP11A promotes proliferation and invasion through RhoA/RAC1 in LUAD

Year: 2025
Type: article
Abstract: Lung adenocarcinoma (LUAD) ranks among the most common subtypes of lung cancer, characterized by a poor prognosis due to the scarcity of effective treatment options. Functional role and underlying mechanisms of Rho GTPase-activating protein 11A (ARHGAP11A) in LUAD remain insufficiently characterized. The study aims to explore it, with the hypothesis that ARHGAP11A is a pivotal driver of tumor progression and a potential therapeutic target. The research employed bioinformatics analysis to identify ARHGAP11A's overexpression in LUAD and its correlation with poor prognosis. To evaluate how reducing ARHGAP11A affects LUAD cell movement and invasion, various functional tests such as cell scratch and transwell cell invasion assays were conducted. Additionally, the study investigated ARHGAP11A's involvement in LUAD epithelial-mesenchymal transition and its regulation through the RhoA/RAC1 pathway using RAC1-specific inhibitor EHT-1864. In vivo tumor growth was assessed following ARHGAP11A knockdown, and the efficacy of the RAC1-specific inhibitor EHT-1864 in reducing tumor growth was tested. The bioinformatics investigation indicated that ARHGAP11A is upregulated in LUAD and correlates with unfavorable outcomes. Cell migration and invasion were inhibited after ARHGAP11A knockdown. The study also implicated ARHGAP11A in LUAD epithelial-mesenchymal transition and demonstrated its regulation through the RhoA/RAC1 pathway using a RAC1-specific inhibitor. In vivo tumor growth was significantly inhibited by ARHGAP11A knockdown, and treatment with EHT-1864 reduced tumor growth, indicating a potential therapeutic strategy. The study's findings establish ARHGAP11A as a key factor in LUAD progression, enhancing cell proliferation and invasion. These results warrant further exploration of ARHGAP11A's mechanisms and clinical applications, potentially leading to new therapeutic strategies for LUAD treatment.
Authors: Xinyu Liu, Xuesong Zhao, Haifeng Hu, Tianyu Zhang, Yi Qi, Bo Liu, Bing Lan, Bin Li
Language: English
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4417484581
FWCI:
Cites: 26
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