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Abstract Objectives Breast cancer (BC) is one of the most common cancers with a high mortality rate in women worldwide. The advantages of early cancer diagnosis are apparent, and it is a critical factor in increasing the patient’s life and survival. According to mounting evidence, microRNAs (miRNAs) may be crucial regulators of critical biological processes. miRNA dysregulation has been linked to the beginning and progression of various human malignancies, including BC, and can operate as tumor suppressors or oncomiRs. This study aimed to identify novel miRNA biomarkers in BC tissues and non-tumor adjacent tissues of patients with BC. Microarray datasets GSE15852 and GSE42568 for differentially expressed genes (DEGs) and GSE45666, GSE57897, and GSE40525 for differentially expressed miRNAs (DEMs) retrieved from the Gene Expression Omnibus (GEO) database were analyzed using “R” software. A protein-protein interaction (PPI) network was created to identify the hub genes. MirNet, miRTarBase, and MirPathDB databases were used to predict DEMs targeted genes. Functional enrichment analysis was used to demonstrate the topmost classifications of molecular pathways. The prognostic capability of selected DEMs was evaluated through a Kaplan-Meier plot. Moreover, the specificity and sensitivity of detected miRNAs to discriminate BC from adjacent controls were assessed by area under the curve (AUC) using the ROC curve analysis. In the last phase of this study, gene expression on 100 BC tissues and 100 healthy adjacent tissues were analyzed and calculated by using the Real-Time PCR method. Results This study declared that miR-583 and miR-877-5p were downregulated in tumor samples in comparison to adjacent non-tumor samples (|logFC|< 0 and P ≤ 0.05). Accordingly, ROC curve analysis demonstrated the biomarker potential of miR-877-5p (AUC = 0.63) and miR-583 (AUC = 0.69). Our results showed that has-miR-583 and has-miR-877-5p could be potential biomarkers in BC.

Background & Objective: 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. Materials & Methods: 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. Results: According to our study, in BC samples, miR-662 was differentially downregulated in comparison with normal adjacent tissues. Conclusion: Altogether, miR-662 can be considered as a viable target for BC diagnostics and treatment.

Bipolar disorder (BD) is a severe psychiatric disorder and among the leading causes of disability worldwide that has a significant genetic component with high heritability. The prognosis for BD patients remains poor because of the lack of reliable biomarkers and also pathogenesis and diagnostic methods remain limited. The purpose of this study was the elucidation potential candidate hub miRNAs related to BD. We searched the gene and miRNA expression patterns of BD from five expression arrays (GSE74358, GSE69486, GSE12654, GSE46416 for gene expression, and GSE152267 for miRNA expression) from the Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between normal and BD samples. Using limma package, 87 DEGs were identified and Enrichment analysis for identified genes was performed. Due to more validation of DEGs, their expression was evaluated by 8 independent expression arrays including GSE12649, GSE23848, GSE39653, GSE46449, GSE5388, GSE5389, GSE53987, and GSE62191. By merging DEMs and DEGs, miRNA-mRNA network was constructed. After elucidation of hub miRNAs, the ability of detected miRNAs to discriminate BD from healthy controls was assessed by area under the curve (AUC) using the ROC curve analysis. Furthermore, RT-qPCR on 50 BD samples and 50 healthy controls was performed to validate the in silico results. Our results showed that hsa-miR-19b-3p and hsa-miR-23b-3P could be potential biomarkers of BD.