Abstract
Breast cancer (BRCA) is the second leading cause of cancer-related mortality in women worldwide. However, the molecular mechanism involved in the development of BRCA is not fully understood. In this study, based on the miRNA-mediated long non-coding RNA (lncRNA)–protein coding gene (PCG) relationship and lncRNA–PCG co-expression information, we constructed and analyzed a specific dysregulated lncRNA–PCG co-expression network in BRCA. Then, we performed the random walk with restart (RWR) method to prioritize BRCA-related lncRNAs through comparing their RWR score and significance. As a result, we identified 30 risk lncRNAs for BRCA, which can distinguish normal and tumor samples. Moreover, through gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, we found that these risk lncRNAs mainly synergistically exerted functions related to cell cycle and DNA separation and replication. At last, we developed a four-lncRNA prognostic signature (including AP000851.1, LINC01977, MAFG-DT, SIAH2-AS1) and assessed the survival accuracy of the signature by performing time-dependent receiver operating characteristic (ROC) analysis. The areas under the ROC curve for 1, 3, 5, and 10 years of survival prediction were 0.68, 0.61, 0.62, and 0.63, respectively. The multivariable Cox regression results verified that the four-lncRNA signature could be used as an independent prognostic biomarker in BRCA. In summary, these results have important reference value for the study of diagnosis, treatment, and prognosis evaluation of BRCA.
Highlights
Breast cancer (BRCA) is one of the most prevalent malignancies and is the second leading cause of cancer-related mortality in women worldwide (Bray et al, 2018; DeSantis et al, 2019)
We identified 30 risk long non-coding RNA (lncRNA) associated with BRCA and constructed a prognostic signature based on the The Cancer Genome Atlas (TCGA) expression data with clinical survival characters
With the development of high-throughput sequencing technology, a large number of lncRNA expression data involved in the occurrence and progression of cancer are emerging
Summary
Breast cancer (BRCA) is one of the most prevalent malignancies and is the second leading cause of cancer-related mortality in women worldwide (Bray et al, 2018; DeSantis et al, 2019). Long non-coding RNAs (lncRNAs) are a group of RNAs with length >200 bp, which serve as key regulators in diverse cellular functions such as development, differentiation, and apoptosis (Ulitsky and Bartel, 2013; Quinn and Chang, 2016; Trovero et al, 2020). The important function of lncRNA is that it can act as a competitive endogenous RNA (ceRNA) to regulate the expression level of other transcripts especially for protein coding gene (PCG) by sponging miRNA (Quinn and Chang, 2016). Herrera-Solorio et al (2020) showed that lncRNA SOX2-OT modulates an orchestrated resistance mechanism, promoting poor prognosis and human lung malignancy through genetic, epigenetic, and posttranslational mechanisms. Viable ways have been considered to predict the potential BRCA lncRNAs by performing highthroughput data based on bioinformatics methods (Guo et al, 2018; Chi et al, 2019; Wang et al, 2019)
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