NASOPHARYNGEAL carcinoma survival prediction may be significantly improved through the identification of key prognostic genes and a clinically integrated prediction model, according to recent gene expression analysis.
Burden of Nasopharyngeal Carcinoma
Nasopharyngeal carcinoma is a malignancy with a persistently high incidence in southern provinces of China and continues to represent a major public health concern. Despite advances in diagnosis and treatment, biomarkers and prediction models capable of accurately estimating survival outcomes remain limited. Addressing this unmet need, researchers analysed gene expression datasets to identify molecular drivers associated with prognosis in patients with nasopharyngeal carcinoma (NPC).
Using two publicly available gene expression datasets, hub genes central to disease biology were identified. These genes were subsequently evaluated in clinical samples to determine their expression patterns and associations with patient survival. This approach aimed to bridge molecular data with clinically relevant outcomes in nasopharyngeal carcinoma.
Hub Genes Linked to Survival Outcomes
Seven hub genes were identified, namely AURKA, AURKB, BUB1, BUB1B, CCNA2, CCNB2, and CDK1. All were significantly upregulated in tumour tissues compared with non tumour samples. Further analysis demonstrated that expression levels of AURKA, BUB1, and CDK1 were significantly higher in samples from patients in the death group.
Survival analysis using the log rank test showed that patients with high expression levels of AURKA, BUB1, or CDK1 had a significantly reduced overall survival rate. These findings position these genes as potential prognostic biomarkers and suggest a critical role for cell cycle regulation in disease progression.
Nasopharyngeal Carcinoma Prediction Model
Building on these findings, a survival prediction model was developed incorporating gender, age, tumour stage, nodal stage, metastatic stage, and the expression levels of BUB1 and AURKA. Model performance was evaluated using receiver operating characteristic curve analysis, calibration plots, net reclassification index, integrated discrimination improvement index, and decision curve analysis. Collectively, these assessments demonstrated good discriminating ability, predictive accuracy, and clinical utility.
The study concludes that AURKA, BUB1, and CDK1 are promising prognostic biomarkers in nasopharyngeal carcinoma. Importantly, a model integrating molecular and clinical variables may offer clinicians a more robust tool for survival prediction and risk stratification in patients with this disease.
Reference
Zhu J et al. Identification of hub genes and construction of a survival prediction model for patients with nasopharyngeal carcinoma. Sci Rep. 2026; https://doi.org/10.1038/s41598-026-36395-4.
