Identification of candidate RNA signatures in triple-negative breast cancer by the construction of a competing endogenous RNA network with integrative analyses of Gene Expression Omnibus and The Cancer Genome Atlas data.

Abstract

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is characterized by aggressive and metastatic clinical characteristics and generally leads to earlier distant recurrence and poorer prognosis than other molecular subtypes. Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) serve a crucial role in a wide variety of biological processes by interacting with microRNAs (miRNAs) as competing endogenous RNAs (ceRNAs) and, thus, affect the expression of target genes in multiple types of cancer. Seven datasets from the Gene Expression Omnibus (GEO) database, including 444 tumor and 88 healthy tissue samples, were utilized to investigate the underlying mechanisms of TNBC and identify prognostic biomarkers. Differentially expressed genes (DEGs) were further validated in The Cancer Genome Atlas database and the associations between their expression levels and clinical information were analyzed to identify prognostic values. A potential lncRNA-miRNA-mRNA ceRNA network was also constructed. Finally, 69 mRNAs from the integrated Gene Expression Omnibus datasets were identified as DEGs using the robust rank aggregation method with |log2FC|>1 and adjusted P<0.01 set as the significance cut-off levels. In addition, 29 lncRNAs, 21 miRNAs and 27 mRNAs were included in the construction of the ceRNA network. The present study elucidated the mechanisms underlying the progression of TNBC and identified novel prognostic biomarkers for TNBC.