Exploring dysregulated miRNAs in cryptorchidism: a systematic review

Abstract

Objective: To identify dysregulated miRNAs in testicular tissues from animal models and patients with cryptorchidism.

Methods: Databases were systematically searched for studies published before 10 May 2020 that had investigated miRNAs in cryptorchidism. Predicted targets of the identified miRNA biomarkers were obtained by searching TargetScan and Starbase. Gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were subsequently conducted.

Results: Five publications met the eligibility criteria for the review. 21 differentially expressed miRNAs were the most abundantly reported in 185 animal and human tissue samples. Three miRNAs (miR-210, miR-449a and miR-34c) were dysregulated in both animal and human testicular tissues. The top five relevant lncRNAs associated with the miRNAs were NEAT1, KCNQ1OT1, XIST, AC005154.1, and TUG1.

Conclusions: Further research is warranted to explore the potential of these dysregulated miRNAs as biomarkers or therapeutic targets for male infertility associated with cryptorchidism.

Keywords: Cryptorchidism; biomarkers; miRNA; systematic review.

Figure 1.

Flow diagram of study selection.

Figure 2.

Venn diagram showing the most abundant miRNAs detected in testicular tissue samples obtained from animal models and patients with cryptorchidism. Of the 21 dysregulated miRNAs detected, 10 were in human tissues, eight in animal tissues and three (miR-210 [upregulated], miR-449a and miR-34c [downregulated]) were in both animal and human tissues.

Figure 3.

The top 20 lncRNAs most closely related to the dysregulated miRNAs.

Figure 4.

(a) The lncLocator predicted five subcellular localizations of the 12 validated lncRNAs and the results were sorted by possible proportions. Among the top five lncRNAs, NEAT1, KCNQ1OT1, XIST, TUG1 tended to be located in the nucleus. (b) Subcellular localization plot displayed by lncATLAS for NEAT1 and TUG1 genes. Bars represent CN-RCI (relative concentration index calculated for the cytoplasm and nucleus) values for the genes across the cell lines. Nuclear expression values (FPKMs) for the genes are shown for both compartments (cytoplasm >zero, nucleus 

Figure 5.

(a) Functional enrichment analysis of differentially expressed miRNAs by Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. The bubble size was directly proportional to the number of miRNAs. Among the most enriched KEGG pathways, the top five terms were prostate cancer, miRNAs in cancer, autophagy, cellular senescence, and bacterial invasion of epithelial cells. (b) GO enrichment analysis of the differentially expressed miRNAs (Top 10 GO enrichment are presented). The most significant GO term under the biological process category was ‘cotranslational protein targeting to membrane’. ‘Endosome’ and ‘synapse’ were the most enriched GO terms under cellular component category and ‘glutamate binding’ was the most enriched term under molecular function category.