A Nomogram Based on CENPP Expression for Survival Prediction in Breast Cancer

Introduction: In recent years, it has been found that the expression of 17 centromere proteins (CENPs) is closely related to malignant tumors. This study intends to investigate the prognostic value of CENPs in breast cancer (BC). Methods: : A total of 800 BC patients were included from the TCGA database. The Cox proportional regression models was used to develop a CENPs-related prognostic signature. Furthermore, the mRNA expression and overall survival (OS) of CENPP (centromere protein P) in BC patients with different clinicopathological featureswas analyzed via GEPIA, bcGenExMiner v4.4 and Kaplan-Meier plotter. Finally, the nomogram was established based on the independent predictors recognized by multivariate Cox regression analysis and further validated by receiver-operating characteristic (ROC) curves and calibration plots internally and externally. Results: : The result shown that age, Her2 status, pathologic_T stage, pathologic_M stage and CENPP expression with independent prognostic values for BC. CENPP was overexpressed in BC tissues and CENPP high expression was associated with better OS. We then established a nomogram based on those independent predictors, and the calibration curve demonstrated good fitness of the nomogram for OS prediction. In the training set, the AUC of 3−year and 5−year survival were 0.757 and 0.797, respectively. In the validation set, the AUC of 3−year and 5−year survival were 0.727 and 0.71. Conclusion: Our study showed that CENPP is a novel prognostic factor for patients with BC, and the established nomogram can provide valuable information on prognostic prediction for patients with BC.