Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Zhou, Sijianga; 1 | Mo, Kanglinb; 1 | Yang, Xiac | Ning, Zongc; *
Affiliations: [a] Department of Emergency Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China | [b] Department of Respiratory Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China | [c] Department of General Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
Correspondence: [*] Corresponding author. Zong Ning, Department of General Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, China. E-mail: ningzong68@outlook.com.
Note: [1] These authors contributed equally to this work and should be considered as co-first authors.
Abstract: OBJECTIVE:This research aims to pinpoint key biomarkers and immunological infiltration of idiopathic pulmonary fibrosis (IPF) through bioinformatics analysis. METHODS:From the GEO database, 12 gene expression profiles were obtained. The LIMMA tool in Bioconductor accustomed to identify the genes that are expressed differently (DEGs), and analyses of functional enrichment were performed. A protein-protein interaction network (PPI) was constructed using STRING and Cytoscape, and a modular analysis was performed. Analysis of the immunological infiltration of lung tissue between IPF and healthy groups was done using the CIBERSORTx method. RESULTS:11,130 genes with differential expression (including 7,492 up-regulated and 3,638 down-regulated) were found. The selected up-regulated DEGs were mainly involved in the progression of pulmonary fibrosis and the selected down-regulated DEGs maintain the relative stability of intracellular microenvironment, according to functional enrichment analysis. KEGG enrichment analysis revealed that up-regulated DEGs were primarily abundant in the PI3K-Akt signaling mechanism, whereas down-regulated DEGs were associated with cancer pathways. The most significant modules involving 8 hub genes were found after the PPI network was analyzed. IPF lung tissue had a greater percentage of B memory cells, plasma cells, T cells follicular helper, T cells regulatory, T cells gamma delta, macrophages M0 and resting mast cells. while a relatively low proportion of T cells CD4 memory resting, NK cells resting and neutrophils. CONCLUSION:This research demonstrates the differences of hub genes and immunological infiltration in IPF.
Keywords: Idiopathic pulmonary fibrosis, biomarkers, immunological infiltration, lung tissue, bioinformatics analysis
DOI: 10.3233/JIFS-234957
Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 5479-5489, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl