A nomogram based on CENPP expression for survival prediction in breast cancer

In recent years, it has been found that the expression of 17 centromere proteins (CENPs) was closely related to malignant tumors, however, the role of CENPs in breast cancer (BC) has not been fully investigated. This study intends to investigate the prognostic value of CENPs in BC and establish nomogram based on expression of CENPs to predict BC patients' prognosis.

A total of 800 BC patients with complete relevant data were included from the TCGA database and were further randomly divided into training set (N=480) and validation set (N=320). Univariate and multivariate Cox regression analysis were used to screen independent factors for overall survival (OS) prediction of BC patients in the training set. Then, the nomogram was established based on these independent predictors and further validated by receiver-operating characteristic (ROC) curves and calibration plots. The GEPIA and bcGenExMiner v4.4 databases were utilized to analyze mRNA expression of candidate gene in BC patients with different clinicopathological features, respectively.

Multivariate Cox regression analysis showed that age, Her2 status, pathologic_T stage, pathologic_M stage and CENPP expression were of independent prognostic value for BC. CENPP was overexpressed in BC tissues (P<0.01) and lower expression of CENPP was associated with worse OS (P=0.005, HR =2.35; 95% CI: 1.30-4.23). 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 AUCs of 3- and 5-year survival were 0.757 and 0.797, respectively. In the validation set, the AUCs of 3- and 5-year survival were 0.727 and 0.71, respectively.

Our study showed that CENPP was a novel prognostic factor for patients with BC, and the established nomogram could provide valuable information on prognostic prediction for patients with BC.