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Breast Cancer Res Treat. 2018 Jun;169(2):267-275. doi: 10.1007/s10549-018-4678-1. Epub 2018 Feb 1.

Systematical analysis of lncRNA-mRNA competing endogenous RNA network in breast cancer subtypes.

Author information

1
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China.
2
Department of Pathophysiology, School of Medicine, Southeast University, Nanjing, 210009, China.
3
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
4
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. wangsy@hrbmu.edu.cn.
5
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China. weijiang@nuaa.edu.cn.

Abstract

BACKGROUND:

Breast cancer is one of the most common solid tumors in women involving multiple subtypes. However, the mechanism for subtypes of breast cancer is still complicated and unclear. Recently, several studies indicated that long non-coding RNAs (lncRNAs) could act as sponges to compete miRNAs with mRNAs, participating in various biological processes.

METHODS:

We concentrated on the competing interactions between lncRNAs and mRNAs in four subtypes of breast cancer (basal-like, HER2+, luminal A and luminal B), and analyzed the impacts of competing endogenous RNAs (ceRNAs) on each subtype systematically. We constructed four breast cancer subtype-related lncRNA-mRNA ceRNA networks by integrating the miRNA target information and the expression data of lncRNAs, miRNAs and mRNAs.

RESULTS:

We constructed the ceRNA network for each breast cancer subtype. Functional analysis revealed that the subtype-related ceRNA networks were enriched in cancer-related pathways in KEGG, such as pathways in cancer, miRNAs in cancer, and PI3k-Akt signaling pathway. In addition, we found three common lncRNAs across the four subtype-related ceRNA networks, NEAT1, OPI5-AS1 and AC008124.1, which played specific roles in each subtype through competing with diverse mRNAs. Finally, the potential drugs for treatment of basal-like subtype could be predicted through reversing the differentially expressed lncRNA in the ceRNA network.

CONCLUSION:

This study provided a novel perspective of lncRNA-involved ceRNA network to dissect the molecular mechanism for breast cancer.

KEYWORDS:

Breast cancer; Drug repositioning; ceRNA network; lncRNA; miRNA sponge

PMID:
29388017
DOI:
10.1007/s10549-018-4678-1
[Indexed for MEDLINE]

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