High Centromere Protein-A (CENP-A) Expression Correlates with Progression and Prognosis in Gastric Cancer

Abstract

Purpose: Recent studies have established the ability of centromere protein-A (CENP-A) to perform as an oncogene, regulating tumor progression. The aim of this research was to explore the relationship between CENP-A expression and clinical significance in gastric cancer (GC) patients. Materials and Methods: Experiments with a microarray were conducted using the Affymetrix U133 plus 2.0 GeneChip Array. Upregulated differentially expressed genes (DEGs) were identified via the GEO2R and intersected using a Venn diagram. Bioinformatic databases Omcomine, GEPIA, and Ualcan were applied to investigate the expression level of CENP-A in GC. The real-time quantitative RT-PCR (qRT-PCR) was used to validate the level of CENP-A mRNA in GC. Immunohistochemistry (IHC) was employed to verify the protein levels of CENP-A, while the relationship between CENP-A expression and patients’ clinical parameters in GC was explored through the use of IHC. Kaplan-Meier analysis was conducted to evaluate the prognostic significance of CENP-A. Additionally, the Kaplan-Meier plotter database (KM plotter) was used to verify the prognostic function of CENP-A in GC patients. Results: The results indicated that CENP-A was significantly overexpressed, both in protein and mRNA levels of GC tissues, compared to adjacent noncancerous tissues (P< 0.05). Furthermore, we observed that CENP-A expression was positively associated with TNM stage, tumor classification, lymph node metastasis, distant metastasis, and Lauren type (P< 0.05). Kaplan-Meier analysis showed that patients with an overexpression of CENP-A had significantly poorer overall survival (OS) times (P< 0.05). Multivariate analysis suggested CENP-A may serve as an independent predicting factor for the poor outcome of GC patients. Conclusion: Our results show that CENP-A upregulation is significantly correlated with advanced tumor progression and poor prognosis. CENP-A may function as a novel potential biomarker for predicting the clinical outcomes of GC patients.