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. 2022 Aug 29:13:931222.
doi: 10.3389/fgene.2022.931222. eCollection 2022.

CENP-A is a potential prognostic biomarker and correlated with immune infiltration levels in glioma patients

Yuan Yang  1 , Mengyun Duan  2 , Yunfei Zha  1 , Zijun Wu  1
Affiliations

CENP-A is a potential prognostic biomarker and correlated with immune infiltration levels in glioma patients

Yuan Yang et al. Front Genet. .

Abstract

Background: Centromeric protein A (CENP-A), an essential protein involved in chromosomal segregation during cell division, is associated with several cancer types. However, its role in gliomas remains unclear. This study examined the clinical and prognostic significance of CENP-A in gliomas. Methods: Data of patients with glioma were collected from the Cancer Genome Atlas. Logistic regression, the Kruskal-Wallis test, and the Wilcoxon signed-rank test were performed to assess the relationship between CENP-A expression and clinicopathological parameters. The Cox regression model and Kaplan-Meier curve were used to analyze the association between CENP-A and survival outcomes. A prognostic nomogram was constructed based on Cox multivariate analysis. Gene set enrichment analysis (GSEA) was conducted to identify key CENP-A-related pathways and biological processes. Results: CENP-A was upregulated in glioma samples. Increased CENP-A levels were significantly associated with the world health organization (WHO) grade [Odds ratio (OR) = 49.88 (23.52-129.06) for grade 4 vs. grades 2 and 3], primary therapy outcome [OR = 2.44 (1.64-3.68) for progressive disease (PD) and stable disease (SD) vs. partial response (PR) and complete response (CR)], isocitrate dehydrogenase (IDH) status [OR = 13.76 (9.25-20.96) for wild-type vs. mutant], 1p/19q co-deletion [OR = 5.91 (3.95-9.06) for no codeletion vs. co-deletion], and age [OR = 4.02 (2.68-6.18) for > 60 vs. ≤ 60]. Elevated CENP-A expression was correlated with shorter overall survival in both univariate [hazard ratio (HR): 5.422; 95% confidence interval (CI): 4.044-7.271; p < 0.001] and multivariate analyses (HR: 1.967; 95% CI: 1.280-3.025; p < 0.002). GSEA showed enrichment of numerous cell cycle-and tumor-related pathways in the CENP-A high expression phenotype. The calibration plot and C-index indicated the favorable performance of our nomogram for prognostic prediction in patients with glioma. Conclusion: We propose a role for CENP-A in glioma progression and its potential as a biomarker for glioma diagnosis and prognosis.

Keywords: CENP-A; biomarker; glioma; microenvironment; prognosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
High CENP-A expression in tumor tissues. (A) CENP-A expression levels in glioma tissues compared with normal tissues (control). (B) ROC analysis of CENP-A expression showing its excellent ability in distinguishing tumors from normal tissues. (C) Pan-cancer analysis of CENP-A expression across different cancers based on TCGA data. ns, no significance, p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001.
FIGURE 2
FIGURE 2
Clinical correlation analysis of CENP-A expression with clinicopathologic features. (A) WHO grade, (B) Primary therapy outcome, (C) Age, (D) IDH status, and (E) 1p/19q co-deletion. WHO, World health organization; IDH, isocitrate dehydrogenase; WT, wild type; MUT, mutated.
FIGURE 3
FIGURE 3
Survival analyses and prognostic nomogram. (A–C) Impact of CENP-A on the overall, progression-free, and disease-specific survival rates in glioma according to TCGA. (D,E) Development and verification of a glioma predictive nomogram based on CENP-A expression levels and independent prognostic factors.
FIGURE 4
FIGURE 4
The correlation of CENP-A expression with glioma prognosis among patients with various clinicopathological characteristics. (A) Forest plots showing the subgroup analysis of overall survival. (B–I) Kaplan–Meier survival curves of each patient subgroup.
FIGURE 5
FIGURE 5
Differentially expressed genes (DEGs) between high and low CENP-A expression glioma groups in TCGA dataset. (A) Heatmap of the top five upregulated and downregulated DEGs. (B) Volcano plot of DEGs expression profiles. (C–E) Scatter plot showing the correlation between CENP-A expression and UBE2C (C), BIRC5 (D), and CCNB2 (E) expression.
FIGURE 6
FIGURE 6
Functional enrichment and protein-protein interaction (PPI) enrichment analyses of CENP-A-related DEGs. (A) Heatmap showing Gene Ontology (GO) functional enrichment analysis. (B,C) Visualized network of top 20 GO enriched terms. (D,E) PPI networks and the most significant Molecular Complex Detection (MCODE) sub-networks.
FIGURE 7
FIGURE 7
Gene set enrichment analysis (GSEA) enrichment plots including (A) cell cycle, (B) DNA conformation change, (C) chromosome condensation, (D) chromosome segregation, (E) G2M checkpoint, (F) IL6-JAK-STAT3 signaling, (G) apoptosis, (H) nucleosome assembly and (I) histone modifications.
FIGURE 8
FIGURE 8
The role of CENP-A in tumor immune responses. (A) A forest plot showing the association between CENP-A expression and immune infiltration level. (B,C) The abundances of Th2 cells and pDC cells among low- and high-CENP-A expression groups. (D,E) The correlation between CENP-A expression levels and the relative enrichment levels of Th2 and pDC cells.
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