Integrated analysis of coexpression and a tumor-specific ceRNA network revealed a potential prognostic biomarker in breast cancer.

Background: Breast cancer, a type of tumor associated with high heterogeneity, is top among the common malignancies threatening women's health worldwide. Emerging evidence suggests that competing endogenous RNA (ceRNA) plays a role in the molecular biological mechanisms related to the occurrence and development of cancer. However, the effect of the ceRNA network on breast cancer, especially the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network, has not been fully studied.

Methods: To explore potential prognostic markers of breast cancer under ceRNA network, we first extracted the breast cancer expression profiles of lncRNAs, miRNAs and mRNAs and their corresponding clinical data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) database. Next, we selected breast cancer-related candidate genes by intersection of the differential expression analysis and the weighted gene coexpression network analysis (WGCNA). Then, we studied the interactions among lncRNAs, miRNAs, and mRNAs by means of multiMiR and starBase and then constructed a ceRNA network of 9 lncRNAs, 26 miRNAs, and 110 mRNAs. We established a prognostic risk formula by means of multivariable Cox regression analysis.

Results: Based on public databases and evaluated via modeling, we identified the HOX antisense intergenic RNA ()-miR-130a-3p-high mobility group-box 3 (HMGB3) axis as a potential prognostic marker in breast cancer through a prognostic risk model we established using multivariable Cox analysis.

Conclusions: For the first time, the potential interactions among , miR-130a-3p, and HMGB3 in the tumorigenesis were clarified, and these may provide novel prognostic value for breast cancer treatment.