Comprehensive analysis of miRNA-gene regulatory network with clinical significance in human cancers

microRNAs (miRNAs), particularly the exosomal miRNAs have been widely used as biomarkers and promising therapeutic targets in cancer. However, a comprehensive analysis of miRNA-gene regulatory network with clinical significance remains scarce. The emergence of high-throughput multi-omics data over l...

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Published inScience China. Life sciences Vol. 63; no. 8; pp. 1201 - 1212
Main Authors Cui, Xiuliang, Liu, Yang, Sun, Wen, Ding, Jin, Bo, Xiaochen, Wang, Hongyang
Format Journal Article
LanguageEnglish
Published Beijing Science China Press 01.08.2020
Springer Nature B.V
Subjects
Biomarkers
Biomedical and Life Sciences
Cancer
Clinical significance
DNA methylation
Drug development
Life Sciences
MicroRNAs
miRNA
mRNA
Research Paper
Therapeutic applications
exosomal miRNA
biomarker
clinical significance
prognosis
TCGA
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Summary:microRNAs (miRNAs), particularly the exosomal miRNAs have been widely used as biomarkers and promising therapeutic targets in cancer. However, a comprehensive analysis of miRNA-gene regulatory network with clinical significance remains scarce. The emergence of high-throughput multi-omics data over large, well-characterized patient cohorts provides an unprecedented opportunity to address this problem. Herein, we performed a clinic-centered analysis to identify cancer-associated miRNAs, miRNA-target axis. We first calculated the correlation among miRNA, mRNA and 75 unique clinico-pathological characteristics (CPCs) in 26 cancer types, and established an online resource (4CR). Interestingly, we found that the high expression of several DNA methylation-related enzymes was associated with adverse outcomes of cancer patients, and these genes were regulated by a cluster of miRNAs. Furthermore, by integrating exosomal miRNA and mRNA databases, we identified exosomal miRNA biomarkers for non-invasive cancer surveillance and therapy monitoring. Finally, we explored the role of CPC-related miRNAs for therapeutic effect prediction of drugs based on their shared targets. Our analysis pipeline illustrated the significance of clinic-centered analysis in miRNA-gene pair identification and provided helpful clues for future cancer studies.
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ISSN:1674-7305
1869-1889
1869-1889
DOI:10.1007/s11427-019-9667-0