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

Abstract

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.

CEACAM6 expression and function in tumor biology: a comprehensive review

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Deciphering the molecular regulatory of RAB32/GPRC5A axis in chronic obstructive pulmonary disease

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Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches

“…Besides, gene correlation networks have been widely constructed to extensively understand the mechanism underlying the high-throughput sequencing data [3]. Weighted gene coexpression network analysis (WGCNA) was a common gene correlation analysis method [4], which supplied complete interpretation into the detail of molecular interactions [5][6][7][8]. In this study, RNA sequencing datasets referred to kidney IRI were collected from the Gene Expression Omnibus (GEO) database.…”