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Integrative analysis of lncRNAs and miRNAs with coding RNAs associated with ceRNA crosstalk network in triple negative breast cancer

Authors Yuan NJ, Zhang G, Bie FJ, Ma M, Ma Y, Jiang X, Wang Y, Hao X

Received 16 August 2017

Accepted for publication 26 September 2017

Published 12 December 2017 Volume 2017:10 Pages 5883—5897


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 2

Editor who approved publication: Dr Yao Dai

Naijun Yuan,1,* Guijuan Zhang,2,* Fengjie Bie,1 Min Ma,1 Yi Ma,3 Xuefeng Jiang,1 Yurong Wang,1,* Xiaoqian Hao1

1College of Traditional Chinese Medicine of Jinan University, Institute of Integrated Traditional Chinese and Western Medicine of Jinan University, 2The First Affiliated Hospital of Jinan University, 3Department of Cellular Biology, Guangdong Province Key Lab of Bioengineering Medicine, Institute of Biomedicine, Jinan University, Guangdong, China

*These authors contributed equally to this work

Abstract: Triple negative breast cancer (TNBC) is a particular subtype of breast malignant tumor with poorer prognosis than other molecular subtypes. Currently, there is increasing focus on long non-coding RNAs (lncRNAs), which can act as competing endogenous RNAs (ceRNAs) and suppress miRNA functions involved in post-transcriptional regulatory networks in the tumor. Therefore, to investigate specific mechanisms of TNBC carcinogenesis and improve treatment efficiency, we comprehensively integrated expression profiles, including data on mRNAs, lncRNAs and miRNAs obtained from 116 TNBC tissues and 11 normal tissues from The Cancer Genome Atlas. As a result, we selected the threshold with |log2FC|>2.0 and an adjusted p-value >0.05 to obtain the differentially expressed mRNAs, miRNAs and lncRNAs. Hereafter, weighted gene co-expression network analysis was performed to identify the expression characteristics of dysregulated genes. We obtained five co-expression modules and related clinical feature. By means of correlating gene modules with protein–protein interaction network analysis that had identified 22 hub mRNAs which could as hub target genes. Eleven key dysregulated differentially expressed micro RNAs (DEmiRNAs) were identified that were significantly associated with the 22 hub potential target genes. Moreover, we found that 14 key differentially expressed lncRNAs could interact with the key DEmiRNAs. Then, the ceRNA crosstalk network of TNBC was constructed by utilizing key lncRNAs, key miRNAs, and hub mRNAs in Cytoscape software. We analyzed and described the potential characteristics of biological function and pathological roles of the TNBC ceRNA co-regulatory network; also, the survival analysis was performed for each molecule. These findings revealed that ceRNA crosstalk network could play an important role in the development and progression for TNBC. In addition, we also identified that some molecules in the ceRNA network possess clinical correlation and prognosis.

Keywords: triple negative breast cancer, The Cancer Genome Atlas, weighted gene co-expression network analysis, ceRNA crosstalk network, survival prognosis

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