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

  • Preclinical study
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

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.

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Acknowledgements

This work was supported by National Natural Science Foundation of China [61571169]; Natural Science Foundation of Heilongjiang Province of China [QC2014C017]; University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province [UNPYSCT-2015037].

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Author notes

  1. Shunheng Zhou and Lihong Wang have contributed equally to this work.

Authors and Affiliations

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Shunheng Zhou & Wei Jiang

  2. Department of Pathophysiology, School of Medicine, Southeast University, Nanjing, 210009, China

    Lihong Wang

  3. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China

    Qian Yang, Haizhou Liu, Qianqian Meng, Leiming Jiang & Shuyuan Wang

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  1. Shunheng Zhou
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Correspondence to Shuyuan Wang or Wei Jiang.

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Electronic supplementary material

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10549_2018_4678_MOESM1_ESM.tif

Fig. S1 The intersection diagram of lncRNAs and mRNAs of breast cancer subtypes. A) The intersection of lncRNAs of four subtypes, each bar stand for the number of lncRNAs exists in the sets of the circular painted green. B) The intersection of mRNAs of four subtypes, each bar stand for the number of mRNAs exists in the sets of the circular painted green. Supplementary material 1 (TIFF 470 kb)

10549_2018_4678_MOESM2_ESM.tif

Fig. S2 Function annotation of common lncRNA OPI5-AS1 and AC008124.1, in four subtypes. A) C) The lncRNA OPI5-AS1 and AC008124.1 acted as miRNA sponge to compete miRNAs with other mRNAs. The four petals in the graph stood for four subtypes, respectively, the common mRNAs in different subtypes displayed in the same color, respectively. B) D) The function annotation of OPI5-AS1 and AC008124.1 on hallmark associated GO terms of mRNAs in each subtype, respectively. Supplementary material 2 (TIFF 681 kb)

10549_2018_4678_MOESM3_ESM.tif

Fig. S3 The display of Breast Cancer pathway for basal-like subtype from KEGG pathway. The yellow nodes stand for the down-regulated genes. The red nodes stand for lncRNA XIST competing with IGF1R and CDKN1A. Supplementary material 3 (TIFF 567 kb)

10549_2018_4678_MOESM4_ESM.xlsx

Supplementary Table S1: The sample barcodes of basal-like, HER2+, luminal A, luminal B subtype. Supplementary material 4 (XLSX 14 kb)

10549_2018_4678_MOESM5_ESM.xlsx

Supplementary Table S2: The verified miRNA target information of mRNAs and lncRNAs from miRTarBase and lncBase database. Supplementary material 5 (XLSX 285 kb)

10549_2018_4678_MOESM6_ESM.xlsx

Supplementary Table S3: The statistic significant competing triplets of basal-like, HER2+, luminal A, luminal B subtype. Supplementary material 6 (XLSX 16 kb)

10549_2018_4678_MOESM7_ESM.xlsx

Supplementary Table S4: The unique lncRNA–mRNA ceRNA pairs of basal-like, HER2+, luminal A, luminal B subtype to construct ceRNA networks. Supplementary material 7 (XLSX 15 kb)

10549_2018_4678_MOESM8_ESM.xlsx

Supplementary Table S5: The significant enriched KEGG pathways (p < 0.05) of basal-like, HER2+, luminal A, luminal B subtype-related networks. Supplementary material 8 (XLSX 29 kb)

10549_2018_4678_MOESM9_ESM.xlsx

Supplementary Table S6: The annotated biological process category GO terms of three lncRNAs in basal-like, HER2+, luminal A, luminal B subtype-related networks. Supplementary material 9 (XLSX 72 kb)

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Zhou, S., Wang, L., Yang, Q. et al. Systematical analysis of lncRNA–mRNA competing endogenous RNA network in breast cancer subtypes. Breast Cancer Res Treat 169, 267–275 (2018). https://doi.org/10.1007/s10549-018-4678-1

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