Abstract
BACKGROUND: Breast cancer is regarded as a highly malignant neoplasm in the female population, posing a significant risk to women's overall well-being. The prevalence of breast cancer has been observed to rise in China, accompanied by an earlier age of onset when compared to Western countries. Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women, primarily due to its limited responsiveness to conventional treatment modalities. The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests. There is a prevailing uncertainty regarding the most effective screening method and target populations, as well as the specificities and execution of screening programs. AIM: To identify diagnostic and prognostic biomarkers for breast cancer. METHODS: Overlapping differentially expressed genes were screened based on Gene Expression Omnibus (GSE36765, GSE10810, and GSE20086) and The Cancer Genome Atlas datasets. A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as gene set enrichment analyses, were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer. For clarification of the diagnostic and prognostic roles of these genes, Kaplan-Meier and Cox proportional hazards analyses were conducted. RESULTS: This study demonstrated that calreticulin, heat shock protein family B member 1, insulin-like growth Factor 1, interleukin-1 receptor 1, Krüppel-like factor 4, suppressor of cytokine signaling 3, and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications. CONCLUSION: The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.