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Article Open Access

Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma

  • Authors:
    • Yuanyuan Hu
    • Xidong Gu
    • Yin Duan
    • Yong Shen
    • Xiaohong Xie
  • View Affiliations / Copyright

    Affiliations: Department of Breast Surgery, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang 310006, P.R. China
    Copyright: © Hu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 113-122
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    Published online on: April 21, 2020
       https://doi.org/10.3892/ol.2020.11558
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Abstract

Breast cancer is one of the most common types of cancer among women worldwide and needs more sensitive prognostic biomarkers to improve its treatment. In the present study, differentially expressed long non‑coding RNAs (lncRNAs) in invasive breast carcinoma from The Cancer Genome Atlas and cBioPortal database were investigated, identifying 292 differentially expressed lncRNAs in 1,100 cases. By analyzing the overall survival rate, 10 lncRNAs were significantly correlated with poor prognosis. To explore the underlying molecular mechanisms of the 10 prognosis‑related lncRNAs, bioinformatic methods were used to predict the potential target miRNAs, mRNAs and proteins, and to construct a lncRNA‑miRNA‑mRNA regulatory network and lncRNA‑protein interaction network. Finally, the functions of the target genes and proteins were insvestigated using Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses. The results showed that these 10 lncRNAs could be novel prognostic markers for invasive breast carcinoma and the present study aimed to provide novel insight into the diagnosis and treatment of breast cancer.
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Copy and paste a formatted citation
Spandidos Publications style
Hu Y, Gu X, Duan Y, Shen Y and Xie X: Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma. Oncol Lett 20: 113-122, 2020.
APA
Hu, Y., Gu, X., Duan, Y., Shen, Y., & Xie, X. (2020). Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma. Oncology Letters, 20, 113-122. https://doi.org/10.3892/ol.2020.11558
MLA
Hu, Y., Gu, X., Duan, Y., Shen, Y., Xie, X."Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma". Oncology Letters 20.1 (2020): 113-122.
Chicago
Hu, Y., Gu, X., Duan, Y., Shen, Y., Xie, X."Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma". Oncology Letters 20, no. 1 (2020): 113-122. https://doi.org/10.3892/ol.2020.11558
Copy and paste a formatted citation
x
Spandidos Publications style
Hu Y, Gu X, Duan Y, Shen Y and Xie X: Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma. Oncol Lett 20: 113-122, 2020.
APA
Hu, Y., Gu, X., Duan, Y., Shen, Y., & Xie, X. (2020). Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma. Oncology Letters, 20, 113-122. https://doi.org/10.3892/ol.2020.11558
MLA
Hu, Y., Gu, X., Duan, Y., Shen, Y., Xie, X."Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma". Oncology Letters 20.1 (2020): 113-122.
Chicago
Hu, Y., Gu, X., Duan, Y., Shen, Y., Xie, X."Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma". Oncology Letters 20, no. 1 (2020): 113-122. https://doi.org/10.3892/ol.2020.11558
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