Background: To summarize the regulatory role of mRNA-miRNA-lncRNA network associated with endocrine therapy resistance (ETR) in breast cancer.
Methods: We analyzed the differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) in long-term estrogen-deprived (LTED) estrogen receptor (ER)-positive breast cancer cells (LTED MCF7) (modeling relapse on endocrine therapy) and MCF7 cells in the presence of estrogen (E2) (modeling a patient at primary diagnosis) by mining GSE120929 and GSE120930 datasets. The mRNA-miRNA-lncRNA network was constructed by multiple bioinformatic tools. The prognosis of genes from the network was validated in breast cancer patients with following systemic treatment (endocrine therapy) by GEPIA, Kaplan–Meier plotter and UALCAN database.
Results: Totally, 769 DEGs, 33 DEMs, and 10 DELs were selected. The mRNA-miRNA-lncRNA network was established including 60 mRNA nodes, 6 miRNA nodes and 3 lncRNA nodes. A significant module containing 3 nodes and 3 edges was calculated based on the mRNA-miRNA-lncRNA network. The hub genes in the network are ABCG2, ESR1  and GJA1 . ESR1/miR-130b-3p/HOTAIR  are significantly correlated with the prognosis of breast cancer patients with endocrine therapy.
Conclusion: This study provides a novel ETR-related mRNA-miRNA-lncRNA network. Further, we suggest that ESR1/miR-130b-3p/HOTAIR  may be promising targets for clinical treatment of endocrine therapy-resistant breast cancer.
Keywords: endocrine therapy resistance, breast cancer, bioinformatic analysis, mRNA-miRNA-lncRNA network, GEO