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    Sertoli cell-only syndrome (SCOS), a severe testicular spermatogenic failure, is characterized by total absence of male germ cells. To better expand the understanding of the potential molecular mechanisms of SCOS, we used microarray datasets from the Gene Expression Omnibus (GEO) and ArrayExpress databases to determine the differentially expressed genes (DEGs). In addition, functional enrichment analysis including the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed. Protein-protein interaction (PPI) networks, modules, and miRNA-mRNA regulatory networks were constructed and analyzed and the validation of hub genes was performed. A total of 601 shared DEGs were identified, including 416 down-regulated and 185 up-regulated genes. The findings of the enrichment analysis indicated that the shared DEGs were mostly enriched in sexual reproduction, reproductive process, male gamete generation, immune response, and immunity-related pathways. In addition, six hub genes (CCNA2, CCNB2, TOP2A, CDC20, BUB1, and BUB1B) were selected from the PPI network by using the cytoHubba and MCODE plug-ins. The expression levels of the hub genes were significantly decreased in patients with SCOS compared to that in normal spermatogenesis controls as indicated by the microarray data, single-cell transcriptomic data, and clinical sample levels. Furthermore, the potential miRNAs were predicted via the miRNA-mRNA network construction. These hub genes and miRNAs can be used as potential biomarkers that may be related to SCOS. However, it has not been proven that the differential expression of these biomarkers is the molecular pathogenesis mechanisms of SCOS. Our findings suggest that these biomarkers can be serve as clinical tool for diagnosis targets and may have some impact on the spermatogenesis of SCOS from a testicular germ cell perspective. © 2023. The Author(s).


    Yuting Jiang, Xiao Yang, Linlin Li, Xin Lv, Ruixue Wang, Hongguo Zhang, Ruizhi Liu. Identification and verification of potential biomarkers in sertoli cell-only syndrome via bioinformatics analysis. Scientific reports. 2023 Jul 27;13(1):12164

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    PMID: 37500704

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