Optimizing Prognosis-related Key MiRNA-target Interactions Responsible for Cancer Metastasis

Overview

Journal Oncotarget

Specialty Oncology

Date 2018 Jan 10

PMID 29312626

Citations 1

Authors

Hongying Zhao

Huating Yuan

Jing Hu

Chaohan Xu

Gaoming Liao

Wenkang Yin

Liwen Xu

Li Wang

Xinxin Zhang

Aiai Shi

Jing Li

Yun Xiao

Affiliations

Soon will be listed here.

Abstract

Increasing evidence suggests that the abnormality of microRNAs (miRNAs) and their downstream targets is frequently implicated in the pathogenesis of human cancers, however, the clinical benefit of causal miRNA-target interactions has been seldom studied. Here, we proposed a computational method to optimize prognosis-related key miRNA-target interactions by combining transcriptome and clinical data from thousands of TCGA tumors across 16 cancer types. We obtained a total of 1,956 prognosis-related key miRNA-target interactions between 112 miRNAs and 1,443 their targets. Interestingly, these key target genes are specifically involved in tumor progression-related functions, such as 'cell adhesion' and 'cell migration'. Furthermore, they are most significantly correlated with 'tissue invasion and metastasis', a hallmark of metastasis, in ten distinct types of cancer through the hallmark analysis. These results implicated that the prognosis-related key miRNA-target interactions were highly associated with cancer metastasis. Finally, we observed that the combination of these key miRNA-target interactions allowed to distinguish patients with good prognosis from those with poor prognosis both in most TCGA cancer types and independent validation sets, highlighting their roles in cancer metastasis. We provided a user-friendly database named miRNATarget (freely available at http://biocc.hrbmu.edu.cn/miRNATar/), which provides an overview of the prognosis-related key miRNA-target interactions across 16 cancer types.

Citing Articles

LncRNA PVT1 Acts as a Tumor Promoter in Thyroid Cancer and Promotes Tumor Progression by Mediating miR-423-5p-PAK3.

Lin Q, Qi Q, Hou S, Chen Z, Zhang L, Zhao H Cancer Manag Res. 2021; 12:13403-13413.

PMID: 33408513 PMC: 7779291. DOI: 10.2147/CMAR.S283443.

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