Identification of the miRNA-mRNA regulatory pathways and a miR-21-5p based nomogram model in clear cell renal cell carcinoma

• Main Authors: Yiqiao Zhao, Zijia Tao, Xiaonan Chen
• Format: Article
• Language: English
• Published: PeerJ Inc. 2020-11-01
• Series: PeerJ
• Subjects: MicroRNAs; Clear cell renal cell carcinoma; Regulatory network; Bioinformatics methods
• Online Access: https://peerj.com/articles/10292.pdf

Background The purpose of this study was to determine the key microRNAs (miRNAs) and their regulatory networks in clear cell renal cell carcinoma (ccRCC). Methods Five mRNA and three microRNA microarray datasets were downloaded from the Gene Expression Omnibus database and used to screen the differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs). Gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed with Metascape. A miRNA-mRNA network was mapped with the Cytoscape tool. The results were validated with data from The Cancer Genome Atlas (TCGA) and qRT-PCR. A nomogram model based on independent prognostic key DEMs, stage and grade was constructed for further investigation. Results A total of 26 key DEMs and 307 DEGs were identified. Dysregulation of four key DEMs (miR-21-5p, miR-142-3p, miR-155-5p and miR-342-5p) was identified to correlate with overall survival. The results were validated with TCGA data and qRT-PCR. The nomogram model showed high accuracy in predicting the prognosis of patients with ccRCC. Conclusion We identified 26 DEMs that may play vital roles in the regulatory networks of ccRCC. Four miRNAs (miR-21-5p, miR-142-3p, miR-155-5p and miR-342-5p) were considered as potential biomarkers in the prognosis of ccRCC, among which only miR-21-5p was found to be an independent prognostic factor. A nomogram model was then created on the basis of independent factors for better prediction of prognosis for patients with ccRCC. Our results suggest a need for further experimental validation studies.