Identification of biomarkers and construction of a microRNA‑mRNA regulatory network for clear cell renal cell carcinoma using integrated bioinformatics analysis

• Published in: PloS one Vol. 16; no. 1; p. e0244394
• Main Authors: Han, Miaoru, Yan, Haifeng, Yang, Kang, Fan, Boya, Liu, Panying, Yang, Hongtao
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 12.01.2021; Public Library of Science (PLoS)
• Subjects: Biological markers; Biology and life sciences; Biomarkers, Tumor - genetics; Cancer; Carcinoma, Renal cell; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - mortality; Carcinoma, Renal Cell - pathology; Computational biology; Computational Biology - methods; Databases, Genetic; Diagnosis; DNA microarrays; Gene Expression Regulation, Neoplastic; Gene Ontology; Gene Regulatory Networks; Genetic aspects; Health aspects; Humans; Identification and classification; Kidney Neoplasms - genetics; Kidney Neoplasms - mortality; Kidney Neoplasms - pathology; Medicine and Health Sciences; Messenger RNA; MicroRNA; MicroRNAs - metabolism; Oncology, Experimental; Protein Interaction Maps - genetics; RNA, Messenger - metabolism; Survival Analysis; China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0244394

With the recent research development, the importance of microRNAs (miRNAs) in renal clear cell carcinoma (CCRCC) has become widely known. The purpose of this study is to screen out the potential biomarkers of renal clear cell carcinoma (CCRCC) by microarray analysis. The miRNA chip (GSE16441) and mRNA chip (GSE66270) related to CCRCC were downloaded from the Gene Expression Omnibus (GEO) database. After data filtering and pretreating, R platform and a series of analysis tools (funrich3.1.3, string, Cytoscape_ 3.2.1, David, etc.) were used to analyze chip data and identify the specific and highly sensitive biomarkers. Finally, by constructing the miRNA -mRNA interaction network, it was determined that five miRNAs (hsa-mir-199a-5p, hsa-mir-199b-5p, hsa-mir-532-3p and hsa-mir-429) and two key genes (ETS1 and hapln1) are significantly related to the overall survival rate of patients.