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Abnormal miRNA expression has been associated with breast cancer. Knowing miRNA and its target genes gives a better understanding of the biological mechanism behind the development of breast cancer. Here, we evaluated the potential prognostic and predictive values of miRNAs in breast cancer development by analyzing Malay women with breast cancer expression profiles. Seven differentially expressed miRNAs (DEMs) were subjected to miRNA‒target interaction network analysis (MTIN). A comprehensive MTIN was developed by integrating the information on miRNA and target gene interactions from five independent databases, including DIANA-TarBase, miRTarBase, miRNet, miRDB, and DIANA-microT. To understand the role of miRNAs in the progress of breast cancer, functional enrichment analysis of the miRNA target genes was conducted, followed by survival analysis to assess the prognostic values of the miRNAs and their target genes. In total, 1416 interactions were discovered among seven DEMs and 1274 target genes with a confidence score (CS) > 0.8. The overall survival analysis of the three most DEMs revealed a significant association of miR-27b-3p with poor prognosis in the TCGA breast cancer patient cohort. Further functional analysis of 606 miR-27b-3p target genes revealed their involvement in cancer-related processes and pathways, including the progesterone receptor signaling pathway, PI3K-Akt pathway, and EGFR transactivation. Notably, six high-confidence target genes (BTG2, DNAJC13, GRB2, GSK3B, KRAS, and UBR5) were discovered to be associated with worse overall survival in breast cancer patients, underscoring their essential roles in breast cancer development. Thus, we suggest that miR-27b-3p has significant potential as a biomarker for detecting breast cancer and can provide valuable understanding regarding the molecular mechanisms of the disease., (© The Author(s).)

Objective: This study aimed to characterize the miRNA expression profiles from plasma samples of our local breast cancer patients in comparison to healthy control by using miRNA PCR Array., Methods: In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control., Results: Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95., Conclusion: miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing., .