Integrated bioinformatics analysis reveals significant genes associated with cryptorchidism (CO)

Abstract Objective: we performed a comprehensive bioinformatics analysis to identify potential genes and signaling pathways associated with cryptorchidism. Materials and Methods: This study aimed to identify genes significantly associated with cryptorchidism (CO), between the LE and ORL gubernaculum groups at GD17 and GD19 stages, using a GSE57924 dataset. We identified other DEGs which were changed to up-regulation or down-regulation between the groups by adjusting the cut-off (|log2 fold change (FC)| ≥0.5 and adjusted p <0.05). We subjected the identified DEGs to gene ontology (GO) and pathway enrichment analyses, using an online database DAVID, then employed Cytoscape v3.7.1 to construct a protein-protein interaction network. Results: We detected functional hub genes using MCODE. Overall, we identified 147 DEGs between the LE gubernaculum group and ORL gubernaculum group, of which 33 genes were up-regulated (21 genes always down-regulated and 13 genes from down-regulated in GD17 to up-regulated in GD19) while 96 was down-regulated (27 genes always down-regulated and 69 genes from up-regulated in GD17 to down-regulated in GD19). Gene Ontology (GO) revealed that cell adhesion and extracellular matrix were the most abundant biological processes and Cellular Components, whereas the ECM-receptor interaction was the most significant pathway. Analysis of hub genes in the PPI network revealed that 7 genes including Igfbp5, Cyr61, Lamb1, Lamc1, Cp, Fn1, and Ltbp1, were significantly associated with CO. Conclusions: we successfully identified 7 significant markers that provide valuable insights into the molecular mechanism of cryptorchidism. Of note, one of the genes (Fn1) was verified significant differential expression gene in human testicular cancer.