The landscape of miRNA-related ceRNA networks for marking different renal cell carcinoma subtypes. (16th November 2018)

• Record Type: Journal Article
• Authors: Qin, Liu; Liu, Yanhong; Li, Menglong; Pu, Xuemei; Guo, Yanzhi
• Is Part Of: Briefings in bioinformatics. Volume 21:Number 1(2020)
• Page Start: 73
• Page End: 84
• Publication Date: 2018-11-16
• Subjects: renal cell carcinoma (RCC) -- subtype identification -- ceRNA-ceRNA interaction network -- ceRNA biomarker; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bby101
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: We know that different types of cancers usually have different responses to the same treatment. Therefore, it is important to understand the similarities and differences across subtypes of cancers, so as to provide a basis for the individualized treatments. Until now, no comprehensive investigation on competing endogenous RNAs (ceRNAs) has been reported for the three main subtypes of renal cell carcinoma (RCC), so the regulation characteristics of ceRNAs in three subtypes are not well revealed. This paper firstly describes a comparative analysis of ceRNA–ceRNA interaction networks for all the three subtypes of RCC based on differential microRNAs (miRNAs). We comprehensively summarized all miRNA and messenger RNAdata of RCC from 126 matched tumor-normal tissues in The Cancer Genome Atlas, systematically analyzed a total of more than 80 000 ceRNA interactions and highlighted the common and specific properties among them, aiming to identify critical genes to classify them for providing supplementary help in the precise diagnosis of RCC. From three aspects, including common or specific ceRNAs, upregulated or downregulated and classifications across the three subtypes, we highlighted the common and specific properties for the three subtypes and also explored the classification of RCC by combining the specific ceRNAs with differential regulations. Moreover, for the most major subtype of clear cell renal cell carcinoma (KIRC), three critical genes were screened out from KIRC ceRNA network and further demonstrated to be the potential biomarkers of KIRC by performing biological experiments at the transcriptional level.