Evidence map›Paper›PMID 39707362›Full record

ArticleJournal of translational medicine2024

ANGPTL4 mediated mesothelial-mesenchymal transition in pulmonary fibrosis: a potential therapeutic target.

Yuechong Xia, Fang Zhou, Hongyan Hui, Liping Dai, Songyun Ouyang

Abstract read
In one paragraph

Article in Journal of translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yuechong XiaDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Fang ZhouDepartment of Clinical Pharmacy, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.
Hongyan HuiDepartment of Clinical Pharmacy, The First Affiliated Hospital of Xinxiang Medical University, Weihui, China.
Liping DaiHenan Institute of Medical and Pharmaceutical Sciences & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, 450052, China. lpdai@zzu.edu.cn.
Songyun OuyangDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. ouyangsy@163.com.

Funding

National Natural Science Foundation of China No. U1804195
6 · The paper itself

Abstract

backgroundGlycolysis plays a major role in progression of idiopathic pulmonary fibrosis (IPF). Here, we aim to explore the predictive signature based on glycolysis-related genes for predicting the prognosis and identified a potential therapeutic target for IPF.

methodsGene expression data of bronchoalveolar lavage (BAL) cells and clinical information were downloaded from the Gene Expression Omnibus database. Bioinformatic analysis was then performed to identify differentially expressed genes (DEGs). Lasso multivariate cox analysis and multivariate Cox regression were used to establish a gene signature. The prediction model was evaluated using the time-dependent receiver operating characteristic (ROC) curve and validated using an external independent dataset. The expression of these key genes in cellular level analyzed from Single Cell Expression Atlas. Cell Counting Kit-8 assay, immunofluorescence, wound healing and plasmid transfection were performed.

resultsA total of 4 gene (ANGPTL4, ME2, TPBG and IER3), which were associated with the prognosis of IPF patients, were selected to establish our signature. The prediction model was an independent prognostic indicator for IPF patients. ANGPTL4 was significantly upregulated in pleural mesothelial cells (PMCs). In vitro assay showed that ANGPTL4 promoted PMCs proliferation and migration. Knockdown of ANGPTL4 can inhibit mesothelial-mesenchymal transition by suppressed glycolysis-associated gene, such as PGM1, GPI, PGK1, LDHA, ALDOA, ENO1 and TPI1.

conclusionsOur research established a glycolysis-associated gene signature that holds potential to assist clinicians in the personalized management of IPF. Furthermore, we identified that ANGPTL4 mediates mesothelial-mesenchymal transition, suggesting its viability as a therapeutic target for IPF treatment.

Indexed as

Epithelial-Mesenchymal TransitionAngiopoietin-Like Protein 4Cell MovementCell ProliferationEpitheliumFemaleGlycolysisHumansIdiopathic Pulmonary FibrosisMaleMiddle AgedMolecular Targeted TherapyPleuraPrognosisProportional Hazards ModelsReproducibility of ResultsAngiopoietin-Like Protein 4ANGPTL4 protein, humanANGPTL4GlycolysisIdiopathic pulmonary fibrosisMesothelial-mesenchymal transition

Identifiers

PMID39707362
PMCPMC11662423

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.