Circulating Microbial Metabolites Predict Tumor Relapse and Chemotherapy Efficacy in Nasopharyngeal Carcinoma

作者：Jun‐Yan Li, Yao Yao, Xi-Rong Tan, Nan Si, Wei Jiang, Ying‐Qi Lu, Jia‐Hao Dai, Tongyong Yu, Heng Hu, Yu Duan, Sen‐Yu Feng, Sai‐Wei Huang, Ye‐Lin Liang, Sha Gong, Na Liu, Yu‐Min Hu, Ying‐Qing Li · 发表于：MedComm · 年份：2026 · DOI：10.1002/mco2.70687 · 被引用次数：1 · 研究领域：Metabolomics and Mass Spectrometry Studies、Head and Neck Cancer Studies、Ferroptosis and cancer prognosis

ABSTRACT The value of microbial metabolites in prognosis and treatment response prediction in patients with nasopharyngeal carcinoma (NPC) remains unclear. Here, through the untargeted metabolomic analysis of plasma in 48 paired NPC patients with or without tumor relapse, we identified distinct circulating metabolite atlases between NPC patients with different prognoses. We used bootstrap least absolute shrinkage and selection operator (LASSO) on a penalized Cox regression model to select metabolites and constructed a metabolite risk model comprising four microbial metabolites in a training cohort ( n = 202), and validated it in an independent test cohort ( n = 201) and an external validation cohort ( n = 180). The model stratified patients into three risk groups. Patients in the low‐risk group had optimal DFS, DMFS, and OS, compared with those in the intermediate‐risk group. High‐risk patients had poor survival across all clinical endpoints. Furthermore, patients in the intermediate‐risk group could benefit from induction chemotherapy. In addition, we generated a nomogram integrating the risk model, N stage, and plasma EBV‐DNA load, which further enhanced the predictive accuracy of the metabolite risk model. Collectively, we developed and validated a robust predictive model based on serum metabolites, promoting risk stratification and enhancing treatment outcomes in patients with NPC. We identified distinct circulating metabolite atlases between NPC patients with different p...