This work focused on investigating the relation of centromeric protein A (CENPA) gene expression with prognosis of papillary renal cell carcinoma (PRCC). We obtained data from PRCC cases in TCGA. Thereafter, CENPA levels between the paired PRCC and matched non-carcinoma samples were analyzed by Wilcoxon rank-sum test, while the relations of clinicopathological characteristics with CENPA level were examined by logistic regression and Wilcoxon rank-sum test. The prognostic value of CENPA was assessed by plotting the receiver operating feature curve (ROC) and calculating the value of area under curve (AUC). In addition, relations between clinicopathological characteristics and PRCC survival were analyzed through Kaplan–Meier (KM) and Cox regression analyses. After dividing the total number of patients into the trial cohort and the validation cohort in a ratio of 7:3, we constructed a nomogram in trial cohort according to multivariate Cox regression results for predicting how CENPA affected patient survival and used the calibration curve to verify its accuracy in both cohorts. We also determined CENPA levels within cancer and matched non-carcinoma samples through immunohistochemistry (IHC). Finally, we utilized functional enrichment for identifying key pathways related to differentially expressed genes (DEGs) between PRCC cases with CENPA up-regulation and down-regulation. CENPA expression enhanced in PRCC tissues compared with healthy counterparts (P < 0.001). CENPA up-regulation was related to pathological TNM stage and clinical stage (P < 0.05). Meanwhile, the ROC curves indicated that CENPA had a remarkable diagnostic capacity for PRCC, and the expression of CENPA can significantly improve the predictive accuracy of pathological TNM stage and clinical stage for PRCC. As revealed by KM curves, PRCC cases with CENPA up-regulation were associated with poor survival compared with those with CENPA down-regulation (Risk ratio, RR = 3.07, 95% CI: 1.58–5.97, P = 0.001). In the meantime, univariate as well as multivariate analysis showed an independent association of CENPA with overall survival (OS, P < 0.05) and the nomogram demonstrated superior predictive ability in both cohorts. IHC analysis indicated that PRCC cases showed an increased CENPA positive rate compared with controls. As revealed by functional annotations, CENPA was enriched into pathways associated with neuroactive ligand receptor interactions, cytokine receptor interactions, extracellular matrix regulators, extracellular matrix glycoproteins and nuclear matrisome. CENPA expression increases within PRCC samples, which predicts dismal PRCC survival. CENPA may become a molecular prognostic marker and therapeutic target for PRCC patients.

Objective: This work focused on investigating the relation of centromeric protein A (CENPA) gene expression with prognosis of papillary renal cell carcinoma (PRCC). Methods: We obtained data from PRCC cases in TCGA. Thereafter, CENPA levels between the paired PRCC and matched non-carcinoma samples were analyzed by Wilcoxon rank-and-sum test, while the relations of clinicopathological characteristics with CENPA level were examined by logistic regression and Wilcoxon rank-sum test. The prognostic value of CENPA was assessed by plotting the receiver operating feature curve (ROC) and calculating the value of area under curve (AUC). In addition, relations between clinicopathological features and PRCC survival were analyzed through Kaplan-Meier (KM) and Cox regression analyses. Additionally, we constructed a nomogram according to multivariate Cox regression results for predicting how CENPA affected patient survival. We also determined CENPA levels within cancer and matched non-carcinoma samples through immunohistochemistry (IHC). Finally, we utilized functional enrichment for identifying key pathways related to differentially expressed genes (DEGs) between PRCC cases with CENPA up-regulation and down-regulation. Results: CENPA expression enhanced in PRCC tissues compared with healthy counterparts (P <0.001). CENPA up-regulation was related to clinical stage and pathological TNM stage (P<0.05). Meanwhile, the ROC curve indicated that CENPA had a remarkable diagnostic capacity for PRCC (AUC=0.936). As revealed by KM curve, PRCC cases with CENPA up-regulation were associated with poor survival compared with those with CENPA down-regulation (risk ratio, RR=3.07, 95% CI: 1.58-5.97, P=0.001). In the meantime, univariate as well as multivariate analysis showed an independent association of CENPA with overall survival (OS, P <0.001). IHC analysis indicated that PRCC cases showed an increased CENPA positive rate compared with controls. As revealed by functional annotations, CENPA was enriched into pathways associated with KEGG - NEUROACTIVE - LIGAND - RECEPTOR - INTERACTION, KEGG - CYTOKINE - CYTOKINE - RECEPTOR INTERACTION, NABA - ECM - REGULATORS, NABA - ECM - GLYCOPROTEINS, and NABA - CORE - MATRISOME pathways. Conclusion: CENPA expression increases within PRCC samples, which predicts dismal PRCC survival. CENPA may become a molecular prognostic marker and therapeutic target for PRCC patients.