In Silico Identification of Differentially Expressed Micrornas in Thyroid Cancer

Abstract

Background: Abnormal expression of microRNAs is one of the crucial features contributing to the thyroid cancer (TC) progression. However, a comprehensive identification of the dysregulated microRNA profile and the associated molecular pathways that underlie the TC pathogenesis has not been completely provided. In the current study, bioinformatic analysis tools and microarray datasets were used to evaluate the biological roles of differentially expressed microRNAs and their targets in TC. Methods: GEO2R was used to identify differentially expressed microRNAs in TC samples. The mRNA targets of these microRNAs were predicted using different databases. DAVID and Reactome databases were used to perform gene ontology and pathway enrichment analyses of target genes. Then, the protein-protein interaction networks were constructed among them through the STRING database. MCODE was applied to screen hub genes. The prognostic values of hub genes were examined in TCGA THCA dataset using GEPIA2 platform. The relationship between hub genes and the ERBB2 protein was revealed using GeneMANIA. Results: We found a significant decrease in five microRNAs and a significant increase in five others in TC samples. Target genes of upregulated and downregulated microRNAs in TC were associated with ERBB2 signaling and ion exchanger pathways, respectively. CUX2 and DCUN1D4, the targets of upregulated microRNAs, were downregulated, whereas AP1S1, the target of downregulated microRNAs, were overexpressed in TCGA THCA samples. EZR and CUL5 were mediators for the interaction of ERBB2 with CUX2 or DCUN1D4, respectively. Conclusion: We suggest that CUX2/DCUN1D4 and AP1S1 may act as tumor suppressor and oncogene in TC onset and progression, respectively.