| Popis: |
Shengyan Huang,1,* Xirong Tan,1,* Ping Feng,1,2,* Sha Gong,1 Qingmei He,1 Xunhua Zhu,1 Na Liu,1 Yingqing Li1 1State Key Laboratory of Oncology in South China; Collaborative Innovation Center of Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy; Sun Yat-sen University Cancer Center, Guangzhou, 510060, Peopleâs Republic of China; 2The Affiliated Nanhua Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Yingqing Li; Na Liu Tel +86-20-87343255; +86-20-87342370Fax +86-20-87342370Email liyingq1@sysucc.org.cn; liun1@sysucc.org.cnObjective: Metabolic syndrome has been identified as a prognostic predictor in multiple cancers. This study aimed to evaluate the impact of metabolic syndrome on the clinical outcome of patients with nasopharyngeal carcinoma (NPC) and its mechanism.Methods: A cohort of 2003 NPC patients with a median follow-up time of 96.3 months (range: 4.1â 120.0 months) were enrolled in this analysis. KaplanâMeier curves and the Log rank test were used to determine the differences in progression-free survival (PFS), cancer specific survival (CSS) and overall survival (OS). Univariate and multivariable analyses were used to identify independent prognostic predictors. Untargeted metabolomics (LC-HRMS) was used to detect the serum metabolic profiles of 10 well-matched patients with or without metabolic syndrome. Differential metabolite-based enrichment analysis and pathway analysis were performed to identify the potential mechanism of metabolic syndrome in NPC.Results: A total of 171/2003 (8.5%) patients were diagnosed with metabolic syndrome, and these patients tended to be male (P < 0.001) and older (P = 0.003). Patients with metabolic syndrome had poorer PFS (P = 0.011), CSS (P = 0.003) and OS (P = 0.001) than those without metabolic syndrome. Univariate and multivariable analyses showed that metabolic syndrome was a statistically significant and independent predictor for PFS (HR: 1.34, 95% CI: 1.03â 1.75, P = 0.032), CSS (HR: 1.53, 95% CI: 1.12â 2.08, P = 0.008), and OS (HR: 1.50, 95% CI: 1.13â 2.00, P = 0.006). The serum metabolic profile of patients with metabolic syndrome was distinct from that of patients without metabolic syndrome. A total of 319 differential metabolites [log2(FC)> 1 or log2 (FC) |
