Analysis of the inflammatory gene expression characteristics and immune microenvironment regulatory mechanisms in the testicular tissue of patients with non-obstructive azoospermia - Ling, Qiang; Liu, Mingqi; Xu, Wei; Liao, Chunhua; Pang, Guijian (PloS one, 2025)
This study aimed to deepen understanding of the molecular mechanisms and key characteristic genes of non-obstructive azoospermia (NOA). A systematic retrieval method was used to collect the mRNA expression data of NOA and obstructive azoospermia (OA) samples from the GEO database. Data preprocessing, differential gene expression screening, functional annotation, and signal pathway enrichment analysis were conducted using R software. The differences in immune microenvironment between NOA and OA samples were compared through CIBERSORT analysis. LASSO and SVM-RFE, two machine learning algorithms, were applied to select NOA-related characteristic genes. Subsequently, our investigation further identified genes differentially expressed in NOA that are associated with inflammatory responses. NOA samples were clustered based on these inflammation-related genes, while molecular features between different types were explored through pathway enrichment analysis of gene set variation analysis (GSVA). Finally, potential traditional Chinese medicine components targeting these inflammation-related genes were screened from the Chinese medicine database, followed by drug-protein docking simulations. The study identified 772 DEGs mainly involved in the generation and maturation of sperm. Immune microenvironment analysis revealed significant differences in the infiltration levels of resting NK cells and activated dendritic cells between NOA and OA samples. Eight NOA-related characteristic genes were identified through LASSO and SVM-RFE algorithms. Further analysis revealed that three inflammation-related genes, namely LAMP3, PROK2, and CD14, exhibited significant differential expression in samples of NOA and OA. After clustering of these NOA samples based on the three inflammation-related DEGs, GSVA pathway enrichment analysis revealed molecular features between different NOA subtypes. Finally, potential traditional Chinese medicine components targeting these inflammation-related genes were selected. This study revealed the key molecular mechanisms and characteristic genes of NOA, especially the role of inflammation-related genes, providing new therapeutic targets and directions for the treatment of NOA.