Identification of Novel Biomarkers Associated With the Prognosis and Potential Pathogenesis of Breast Cancer via Integrated Bioinformatics Analysis

Background: Breast cancer is the most commonly diagnosed malignancy and a major cause of cancer-related deaths in women globally. Identification of novel prognostic and pathogenesis biomarkers play a pivotal role in the management of the disease. Methods: Three data sets from the GEO database were used to identify differentially expressed genes (DEGs) in breast cancer. Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes pathway analyses were performed to elucidate the functional roles of the DEGs. Besides, we investigated the translational and protein expression levels and survival data of the DEGs in patients with breast cancer from the Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine, Human Protein Atlas, and Kaplan Meier plotter tool databases. The corresponding change in the expression level of microRNAs in the DEGs was also predicted using miRWalk and TargetScan, and the expression profiles were analyzed using OncomiR. Finally, the expression of novel DEGs were validated in Chinese breast cancer tissues by RT-qPCR. Results: A total of 46 DEGs were identified, and GO analysis revealed that these genes were mainly associated with biological processes involved in fatty acid, lipid localization, and regulation of lipid metabolism. Two novel biomarkers, ADH1A and IGSF10, and 4 other genes (APOD, KIT, RBP4, and SFRP1) that were implicated in the prognosis and pathogenesis of breast cancer, exhibited low expression levels in breast cancer tissues. Besides, 14/25 microRNAs targeting 6 genes were first predicted to be associated with breast cancer prognosis. RT-qPCR results of ADH1A and IGSF10 expression in Chinese breast cancer tissues were consistent with the database analysis and showed significant down-regulation. Conclusion: ADH1A, IGSF10, and the 14 microRNAs were found to be potential novel biomarkers for the diagnosis, treatment, and prognosis of breast cancer.

Automated summary

Novel biomarkers such as ADH1A and IGSF10, as well as 14 microRNAs associated with breast cancer prognosis, were identified through gene expression analysis. These findings have the potential to improve diagnostic, treatment, and prognostic strategies for breast cancer.