Identification of early diagnostic biomarkers for breast cancer through bioinformatics analysis

In the realm of clinical practice, there is currently an insufficiency of distinct biomarkers available for the detection of breast cancer. It is of utmost importance to promptly employ bioinformatics methodologies to investigate prospective biomarkers for breast cancer, with the ultimate goal of achieving early diagnosis of the disease. The initial phase of this investigation involved the identification of 2 breast cancer gene chips meeting the specified criteria within the gene expression omnibus database. Subsequently, paired data analysis was conducted on these datasets, leading to the identification of differentially expressed genes (DEGs). In addition, this study executed Gene Ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. The subsequent stage involved the construction of a protein-protein interaction network graph using the STRING website and Cytoscape software, facilitating the calculation of Hub genes. Lastly, the UALCAN database and Kaplan–Meier survival plots were utilized to perform differential expression and survival analysis on the selected Hub genes. A total of 733 DEGs were identified from the combined analysis of 2 datasets. Among these DEGs, 441 genes were found to be downregulated, while 292 genes were upregulated. The selected DEGs underwent comprehensive analysis, including gene ontology enrichment analysis, Kyoto encyclopedia of genes and genomes pathway enrichment analysis, and establishing a protein-protein interaction network. As a result, 10 Hub genes closely associated with early diagnosis of breast cancer were identified: PDZ-binding kinase, cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, BIRC5, cell cycle protein B2, hyaluronan-mediated motility receptor, mitotic arrest deficient 2-like 1, and protein regulator of cytokinesis 1. The findings of this study unveiled the significant involvement of the identified 10 Hub genes in facilitating the growth and proliferation of cancer cells, particularly cell cycle protein A2, cell division cycle-associated protein 8, maternal embryonic leucine zipper kinase, nucleolar and spindle-associated protein 1, hyaluronan-mediated motility receptor, and protein regulator of cytokinesis 1, which demonstrated a more pronounced connection with the onset and progression of breast cancer. Further analysis through differential expression and survival analysis reaffirmed their strong correlation with the incidence of breast cancer. Consequently, the investigation of these 10 pertinent Hub genes presents novel prospects for potential biomarkers and valuable insights into the early diagnosis of breast cancer.