Significance of centromere protein genes and their associated immune and metabolic differences in the prediction of prognosis and treatment outcome in breast cancer

Abstract

Background: Genes of the centromere protein (CENP) are involved in the kinetochore assembly during mitosis. The expression of some CENPgenes has been associated with various carcinogenesis and development. However, it is unclear whether abnormal expression of CENP genes as a unit affects the clinical outcome, immune cell infiltration, and immunotherapy of breast cancer (BRCA) patients. Methods: We systematically evaluated CENP genes and comprehensively determined the correlation between high and low expression and prognosis, staging, malignant phenotype, and drug sensitivity of BRCA. The correlation between CENP genes and immune cell infiltration was comprehensively determined. Further screening for immune- and metabolic-related hub genes was used to quantify subtypes of patients. Then, we evaluated their value in prognosis prediction and treatment response to BRCA. The correlation between CENP genes and drug resistance was also determined by sequencing the tissues of patients. Single-cell sequencing to further analyze CENP genes expression in metastatic cancer. Results: The CENP genes were significantly differentially expressed in BRCA compared to para-cancer. Highly expressed CENP genes had a poor prognosis, late stage, and a high proportion of malignant phenotypes. We identified high and low CENPclusters and observed that high expression was associated with poor prognosis, high immune escape, and reduced drug sensitivity in patients. Afterward, we screened immune- and metabolic-related hub genes and predicted the prognosis of BRCA patients based on them. Furthermore, CENP genes were elevated in drug-resistant breast cancer tissues and metastatic breast cancer tissues. Conclusion: Collectively, we determined the prognostic impact of the CENP genes on BRCA patients. Furthermore, by further screening the hub genes to subgroup breast cancer patients to predict prognosis and to be able to explore more effective treatment strategies based on the expression of CENP genes.