An integrated bioinformatics analysis to investigate the targets of miR-133a-1 in breast cancer.

BACKGROUND

The microRNA (miRNA) miR-133a-1 has been identified as a tumor suppressor in breast cancer. However, the underlying mechanisms of miR-133a-1 in breast cancer have not been fully elucidated. This study aimed to explore the targets of miR-133a-1 in breast cancer using an integrated bioinformatics approach.

METHODS

Human SKBR3 breast cancer cells were transfected with miR-133a-1 or a miRNA negative control (miRNA-NC) for 48 hours. The RNA-seq sequencing technique was performed to identify the differential expression of genes induced by miR-133a-1 overexpression. Functional enrichment analysis was conducted to determine the target genes and pathways involved in breast cancer.

RESULTS

Breast cancer patients with high levels of miR-133a-1 expression commonly showed longer overall survival compared to patients with a low level of miR-133a-1 expression. Using Cuffdiff, we identified 1,216 differentially expressed genes induced by miR-133a-1 overexpression, including 653 upregulated and 563 downregulated genes. was the most upregulated gene and was the most downregulated gene. The top 10 pathways related to the differentially expressed genes were identified through Gene Ontology (GO) enrichment analysis. Sex-determining region Y-box 9 () demonstrated the highest semantic similarities among the differentially expressed genes. Since and were hub nodes in the protein-protein interaction network, the gene may be a target of miR-133a-1 in breast cancer.

CONCLUSIONS

This report provides useful insights for understanding the underlying mechanisms in the pathogenesis of breast cancer.