Anoikis resistance of small airway epithelium is involved in the progression of chronic obstructive pulmonary disease

被引:6
作者
Chen, Dian [1 ]
Yi, Rongbing [2 ]
Hong, Weifeng [3 ]
Wang, Kai [4 ,5 ]
Chen, Yahong [1 ,6 ]
机构
[1] Peking Univ Third Hosp, Dept Resp & Crit Care Med, Beijing, Peoples R China
[2] Harbin Med Univ, Dept Emergency Surg, Affiliated Hosp 1, Harbin, Peoples R China
[3] Fudan Univ, Zhongshan Hosp, Dept Radiat Oncol, Shanghai, Peoples R China
[4] Peking Univ, Sch Basic Med Sci, Dept Physiol & Pathophysiol, Beijing, Peoples R China
[5] Minist Educ, Key Lab Mol Cardiovasc Sci, Beijing, Peoples R China
[6] Peking Univ, Res Ctr Chron Airway Dis, Hlth Sci Ctr, Beijing, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
基金
中国国家自然科学基金;
关键词
anoikis resistance; COPD; small airway epithelium; TNMD; immune cell; INTEGRATING INFORMATION; E-CADHERIN; EXPRESSION; TENOMODULIN; INVASION; GENES; CELLS; RAS; TRANSFORMATION; INACTIVATION;
D O I
10.3389/fimmu.2023.1155478
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
BackgroundAnoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to abscond anoikis when detached from the extracellular matrix. However, no study has investigated the involvement of anoikis in the small airway epithelium (SAE) of chronic obstructive pulmonary disease (COPD). MethodsAnoikis-related genes (ANRGs) exhibiting differential expression in COPD were identified using microarray datasets obtained from the Gene Expression Omnibus (GEO) database. Unsupervised clustering was performed to classify COPD patients into anoikis-related subtypes. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to annotate the functions between different subtypes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were leveraged to identify key molecules. The relative proportion of infiltrating immune cells in the SAE was quantified using the CIBERSORT and ssGSEA computational algorithms, and the correlation between key molecules and immune cell abundance was analyzed. The expression of key molecules in BEAS-2B cells exposed to cigarette smoke extract (CSE) was validated using qRT-PCR. ResultsA total of 25 ANRGs exhibited differential expression in the SAE of COPD patients, based on which two subtypes of COPD patients with distinct anoikis patterns were identified. COPD patients with anoikis resistance had more advanced GOLD stages and cigarette consumption. Functional annotations revealed a different immune status between COPD patients with pro-anoikis and anoikis resistance. Tenomodulin (TNMD) and long intergenic non-protein coding RNA 656 (LINC00656) were subsequently identified as key molecules involved in this process, and a close correlation between TNMD and the infiltrating immune cells was observed, such as activated CD4(+) memory T cells, M1 macrophages, and activated NK cells. Further enrichment analyses clarified the relationship between TNMD and the inflammatory and apoptotic signaling pathway as the potential mechanism for regulating anoikis. In vitro experiments showed a dramatic upregulation of TNMD and LINC00656 in BEAS-2B cells when exposed to 3% CSE for 48 hours. ConclusionTNMD contributes to the progression of COPD by inducing anoikis resistance in SAE, which is intimately associated with the immune microenvironment.
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页数:17
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