Xi’an Jiaotong University Health Science Center, Xi’an 710061,Shaanxi Province, PR ChinaFulltext PDF
Background: Non-obstructive azoospermia (NOA) is a vital form of male infertility, which is often suspected to be linked to undefined genetic abnormalities. It is essential to explore potential biomarkers and accurate molecular mechanisms that might be associated with NOA and move towards the potential application value for the diagnosis and treatment.
Methods: We acquired the microarray expression profiles of NOA patients from the GEO database. Using the limma package in R software, differentially expressed genes (DEGs) in NOA were identified. Afterwards, we analyzed GO enrichment and KEGG pathway analysis, then used STRING to construct protein-protein interaction (PPI) network of DEGs. Cytoscape software was used to visualize the PPI network for DEGs and explore the hub genes that were contained in the PPI network. Finally, we tried to predict potential drugs or molecular compounds that interacted with the hub genes and visualized drug–gene interaction networks by the Cytoscape software.
Results: We integrated co-expressed DEGs in two datasets and 136 up-regulated genes and 311 down-regulated genes were screened out. The results of GEO analysis displayed that CC and BP that DEGs were obviously enriched in were associated with spermatogenesis. KEGG indicated that DEGs were mainly enriched in Antigen Processing and Presentation and Staphylococcus Aureus Infection. We identified 10 central genes (CDCA8, CENPF, CCNB2, MND1, TYMS, RACGAP1, HMMR, RFC4, PTTG1 and KIF15) from the PPI network. 46 drugs or molecular compounds differentially regulated the expression of TYMS, five regulated HMMR, and 70 were found to interact with RACGAP1.
Conclusion: These findings demonstrate that the identification of the above hub genes and potential drugs helps us get a deeper understanding of the mechanisms associated with NOA and offer potential biomarkers for its diagnosis and treatment.
Non-obstructive azoospermia (NOA); Biomarkers; Hub genes; Functional enrichment analysis
Yalin Ju, Yuxin Ma, Yaohui Jiang, Xiaoyu Zhou ,Yujiao Dong, Shaobo Wu. Integrative Bioinformatics Analyses of Potential Therapeutic Targets for Non-Obstructive Azoospermia. Int Clinc Med Case Rep Jour. 2023;2(6):1-9.