Correlation between autophagy-related genes and immune infiltration in tuberculous granuloma
LI Guanghui1, LI Zhiwei1, FENG Hao2, LIANG Zhenzhen3
1. Wuzhong District Center for Disease Control and Prevention (Wuzhong District Institute of Public Health Supervision), Suzhou, Jiangsu 215100, China; 2. Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang 314050, China; 3. School of Public Health, Henan Medical University, Xinxiang, Henan 453003, China
Abstract：Objective To screen differentially expressed autophagy-related genes (DEARGs) in tuberculous granuloma using bioinformatics analysis and to analyze their correlation with immune infiltration, so as to provide a theoretical basis for investigating the pathogenesis of tuberculosis (TB). Methods The GSE184537 dataset of human tuberculous granuloma was obtained from the Gene Expression Omnibus (GEO) database as the analysis set, and the GSE157671 dataset was used as the validation set. A total of 232 autophagy-related genes (ARGs) were retrieved from the Human Autophagy Gene Database. DEARGs in tuberculous granuloma tissues were screened. Enrichment analysis and protein-protein interaction network analysis were performed on the DEARGs to identify key genes. Single-sample gene set enrichment analysis was used to evaluate the infiltration abundance of 24 immune cell types, and Spearman's rank correlation analysis was used to examine the correlation between key genes and immune cell infiltration abundance. The GSE157671 dataset was used to validate the expression differences of key genes. Results A total of 24 DEARGs were obtained by intersecting the GSE184537 dataset with 232 ARGs. Enrichment analysis showed that the biological processes were significantly enriched in autophagy, protein phosphorylation, and cell growth regulation, and the pathways were enriched in 10 pathways including autophagy, apoptosis, hypoxia-inducible factor-1 signaling pathway, and mitogen-activated protein kinase signaling pathway. Protein-protein interaction network analysis was performed to screen a total of 8 key genes, including BIRC5, IFNG, CXCR4, FOS, ERBB2, TNFSF10, EGFR, and CTSB. Immune infiltration analysis showed that the infiltration abundances of CD4+ T lymphocytes, iTreg cells, and Tfh cells were relatively high in tuberculous granuloma tissues, while those of monocytes, neutrophils, and NK cells were relatively low (all P<0.05). Spearman's rank correlation analysis showed that the eight key genes were correlated with the infiltration levels of 24 immune cell types. Among them, ERBB2 exhibited a strong positive correlation and CXCR4 exhibited a strong negative correlation with NK cells (both P<0.05). Validation results in the GSE157671 dataset showed the differential expression trends of the 6 key genes were consistent with those in the GSE184537 dataset. Conclusion This study identified eight key ARGs, including BIRC5, IFNG, and CXCR4, which may participate in the development and progression of TB by regulating immune cell infiltration and could serve as potential candidate genes for further research on the pathogenesis of TB.
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