Long non-coding RNAs (lncRNAs), which competitively bind
miRNAs to regulate target
mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in
breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for
breast cancer.
LncRNA,
mRNA and
miRNA expression profiles of
breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all
miRNAs to perform weighted gene co-expression network analysis. The correlation between modules and clinical information of
breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a
ceRNA network of
breast cancer. Additionally, the standard Kaplan-Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and
miRNAs co-expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of
miRNAs, our constructed
ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2-AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with
breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of
breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of
breast cancer and provided novel insights into the use of
breast cancer drugs and prognosis.