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. 2021 Jan;10(1):243-257.
doi: 10.21037/tau-20-1029.

Integrative bioinformatics approaches for identifying potential biomarkers and pathways involved in non-obstructive azoospermia

Tengfei Hu  1 , Shaoge Luo  1 , Yu Xi  1 , Xuchong Tu  1 , Xiaojian Yang  1 , Hui Zhang  1 , Jiarong Feng  1 , Chunlin Wang  2 , Yan Zhang  1
Affiliations

Integrative bioinformatics approaches for identifying potential biomarkers and pathways involved in non-obstructive azoospermia

Tengfei Hu et al. Transl Androl Urol. 2021 Jan.

Abstract

Background: Non-obstructive azoospermia (NOA) is a disease related to spermatogenic disorders. Currently, the specific etiological mechanism of NOA is unclear. This study aimed to use integrated bioinformatics to screen biomarkers and pathways involved in NOA and reveal their potential molecular mechanisms.

Methods: GSE145467 and GSE108886 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between NOA tissues and matched obstructive azoospermia (OA) tissues were identified using the GEO2R tool. Common DEGs in the two datasets were screened out by the VennDiagram package. For the functional annotation of common DEGs, DAVID v.6.8 was used to perform Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. In accordance with data collected from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, a protein-protein interaction (PPI) network was constructed by Cytoscape. Cytohubba in Cytoscape was used to screen the hub genes. Furthermore, the hub genes were validated based on a separate dataset, GSE9210. Finally, potential micro RNAs (miRNAs) of hub genes were predicted by miRWalk 3.0.

Results: A total of 816 common DEGs, including 52 common upregulated and 764 common downregulated genes in two datasets, were screened out. Some of the more important of these pathways, including focal adhesion, PI3K-Akt signaling pathway, cell cycle, oocyte meiosis, AMP-activated protein kinase (AMPK) signaling pathway, FoxO signaling pathway, and Huntington disease, were involved in spermatogenesis. We further identified the top 20 hub genes from the PPI network, including CCNB2, DYNLL2, HMMR, NEK2, KIF15, DLGAP5, NUF2, TTK, PLK4, PTTG1, PBK, CEP55, CDKN3, CDC25C, MCM4, DNAI1, TYMS, PPP2R1B, DNAI2, and DYNLRB2, which were all downregulated genes. In addition, potential miRNAs of hub genes, including hsa-miR-3666, hsa-miR-130b-3p, hsa-miR-15b-5p, hsa-miR-6838-5p, and hsa-miR-195-5p, were screened out.

Conclusions: Taken together, the identification of the above hub genes, miRNAs and pathways will help us better understand the mechanisms associated with NOA, and provide potential biomarkers and therapeutic targets for NOA.

Keywords: Non-obstructive azoospermia (NOA); biomarkers; expression profiling data; functional enrichment analysis; protein–protein interactions.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tau-20-1029). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Identification of 816 (52 upregulated and 764 downregulated) common differentially expression genes (DEGs) from GSE145467 and GSE108886 microarray profile datasets. The FDR <0.05 and |FC| ≥2.5 as the cut-off criterion. FDR, false discovery rate; FC, fold change.
Figure 2
Figure 2
Gene ontology analysis of the common DEGs. (A) Common upregulated DEGs. (B) Common downregulated DEGs. BP, biological process; CC, cellular component; MF, molecular function; DEGs, differentially expressed genes.
Figure 3
Figure 3
KEGG pathway enrichment analysis of the common DEGs. (A) Common upregulated DEGs. (B) Common downregulated DEGs. KEGG, Kyoto Encyclopedia of Genes and Genomes; DEGs, differentially expression genes.
Figure 4
Figure 4
PPI network analysis and hub genes in the protein–protein interaction network. (A) The PPI network for common DEGs. Red circle denotes common upregulated genes; green circle denotes common downregulated genes. (B) The top 20 hub genes in Degree score from the cytoHubba. Redder color indicates higher degree. PPI, protein–protein interaction; DEGs, differentially expressed genes.
Figure 5
Figure 5
GO map of 20 hub genes. (A) Biological process categories. (B) Cellular component categories. (C) Molecular function categories. GO, Gene ontology.
Figure 6
Figure 6
KEGG pathway analysis of 20 hub genes. KEGG, Kyoto Encyclopedia of Genes and Genomes.
Figure 7
Figure 7
The differential expression level of 20 hub genes between NOA-MA and NOA-PreMA subgroups of NOA in GSE108886 dataset (*, P<0.05). NOA-MA, non-obstructive azoospermia with meiotic arrest; NOA-PreMA, non-obstructive azoospermia with pre-meiotic arrest.
Figure 8
Figure 8
The differential expression level of 20 hub genes between NOA and OA groups in GSE9210 dataset. (*, P<0.05, **, P<0.01, ***, P<0.001). NOA, non-obstructive azoospermia; OA, obstructive azoospermia.
Figure 9
Figure 9
The miRNA-gene regulated network, green color: down- regulated hub genes, blue color: miRNAs.
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