Identification of dysregulated miRNAs and their roles in breast cancer; An in silico meta‐analysis study

Abstract

Background: Breast cancer (BC) is the most frequent malignancy diagnosed globally and the leading cause of cancer-related deaths in women. BC therapy and categorization were transformed by high-throughput screening techniques, which also revealed BC-related microRNAs (miRNAs) as novel candidates for biomarkers. These techniques also aid in defining the etiology and developing therapeutic targets. In this work, Differentially Expressed MiRNAs (DEMs) and their functions in BC were determined using a meta-analysis of microarray data. Methods: Six eligible microarray datasets containing BC tissues and tumor-adjacent normal tissues (GSE45666, GSE40525, and GSE42072), as well as serum sample data (GSE73002, GSE106817, and GSE113486), were obtained from the NCBI Gene Expression Omnibus (GEO) database. Following that, a meta-analysis was conducted using the SVA and LIMMA packages. The Cancer Genome Atlas (TCGA) RNA-seq data were utilized to validate DEMs. Subsequently, experimentally and predicted targets of verified DEMs were identified, and Protein-Protein Interactions (PPIs) displayed hub genes. Finally, Gene Ontology (GO) biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were examined to reveal affected pathways. Additionally, the clinical diagnostic and prognostic significance of verified DEMs was illustrated using receiver operating characteristic (ROC) curves and Kaplan-Meier plots. Results: MiR-142-3p, miR-142-5p, miR-429, and miR-107 were reported as verified DEMs in BC. During the enrichment analysis, ATXN1, PTEN, MKLN1, ASH1L, SUZ12, HIF1A, AFF4, CDCA4, IPO7, TWF1, and CLOCK exhibited the highest number of linkages with the listed DEMs. Furthermore, NRIP1, ESR1, PTEN, HIF1A, VEGFA, YWHAH, and RAC1 were recognized as hub genes within the PPIs. Finally, significant cellular pathways such as cellular senescence, the PI3K-Akt signaling pathway, and human cytomegalovirus (HCMV) infection were highlighted by the genes that were associated with several DEMs. CDKN1B, PTEN, HIF1A, ESR1, VEGFA, IL6, CCNT2, HMGA2, HIPK2, and MYB were the most common genes in the highlighted pathways. Conclusion: Our research indicated that miR-142-3p, miR-142-5p, miR-429, and miR-107 have the potential to serve as biomarkers for BC. Additionally, the identification of their targets unveiled their crucial roles in the molecular and cellular functions of BC.

Keywords

• Breast cancer
• Microarray GEO dataset
• High-throughput data
• Bioinformatic
• In silico meta-analysis
• miR-142-3p