Liu Mengfei, Tian Hongrui, Wang Minmin, Guo Chuanhai, Xu Ruiping, Li Fenglei, Liu Anxiang, Yang Haijun, Duan Liping, Shen Lin, Wu Qi, Liu Zhen, Liu Ying, Liu Fangfang, Pan Yaqi, Hu Zhe, Chen Huanyu, Cai Hong, He Zhonghu, Ke Yang
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Genetics, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Department of Global Health, School of Public Health, Peking University, Beijing 100191, China.
iScience. 2024 May 11;27(6):109965. doi: 10.1016/j.isci.2024.109965. eCollection 2024 Jun 21.
Using noninvasive biomarkers to identify high-risk individuals prior to endoscopic examination is crucial for optimization of screening strategies for esophageal squamous cell carcinoma (ESCC). We conducted a nested case-control study based on two community-based screening cohorts to evaluate the warning value of serum metabolites for esophageal malignancy. The serum samples were collected at enrollment when the cases had not been diagnosed. We identified 74 differential metabolites and two prominent perturbed metabolic pathways, and constructed Metabolic Risk Score (MRS) based on 22 selected metabolic predictors. The MRS generated an area under the receiver operating characteristics curve (AUC) of 0.815. The model performed well for the within-1-year interval (AUC: 0.868) and 1-to-5-year interval (AUC: 0.845) from blood draw to diagnosis, but showed limited ability in predicting long-term cases (>5 years). In summary, the MRS could serve as a potential early warning and risk stratification tool for establishing a precision strategy of ESCC screening.
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