Bioinformatics analysis of prognosis-related long non-coding RNAs in invasive breast carcinoma
- Yuanyuan Hu
- Xidong Gu
- Yin Duan
- Yong Shen
- Xiaohong Xie
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
- Published online on: April 21, 2020 https://doi.org/10.3892/ol.2020.11558
Copyright: © Hu
et al. This is an open access article distributed under the
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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.