Hsa-miR-662 as a New Prognostic Biomarker in Patients with Breast Cancer; In-silico and Experimental Study

Breast cancer (BC) is a complex genetic disease that has an average annual incidence of one million people and is the second leading cause of death among women in the world. Therefore, a better understanding of tumor biology and the determination of biomarkers for early diagnosis of disease is essential. MicroRNAs and long non-coding RNAs are novel gene regulators that play key roles in tumor initiation and progression. The current study was performed to assess the biomarker potential. This study performed a combination of in-silico and experimental investigations of altered miRNAs in BC to assess the use of miRNAs as novel biomarkers for early detection and prognosis prediction of patients with BC.

We searched the miRNA expression patterns of BC from three expression arrays (GSE58606, GSE38867, and GSE40525,) from the Gene Expression Omnibus (GEO) database to recognize differentially expressed miRNAs (DEMs) between BC tissues and normal adjacent samples. Using “Limma" package's Quantile Normalization function and INMEX bioinformatic tool, hub DEMs were identified. MiRNAs targeted genes were found and visualized via the miRWalk and miRTargetLink databases and their Enrichment analysis was performed for identified genes. Due to more validation of DEGs, GSE70951, an independent expression array dataset, was analyzed. By merging DEMs and DEGs, miRNA-mRNA network was constructed. After elucidation of hub miRNAs, the capacity of detected miRNAs to differentiate BC from adjacent controls was estimated by Kaplan-Meier analysis.  Furthermore, RT-qPCR on 100 BC samples and 100 adjacent non-tumor tissues was performed to validate the in-silico results.

According to our study, in BC samples, miR-662 was differentially downregulated in comparison with normal adjacent tissues.

Altogether, miR-662 can be considered as a viable target for BC diagnostics and treatment.