作者
Shuangyuan Wang,Mian Li,Yan Li,Meian He,Hong Lin,Yu Xu,Qin Wan,Guijun Qin,Gang Chen,Min Xu,Guixia Wang,Yingfen Qin,Zuojie Luo,Xulei Tang,Tiange Wang,Zhiyun Zhao,Yiping Xu,Yuhong Chen,Yanan Huo,Ruying Hu,Zhen Ye,Meng Dai,Lixin Shi,Zhengnan Gao,Qing Su,Yiming Mu,Jiajun Zhao,Lulu Chen,Tianshu Zeng,Xuefeng Yu,Qiang Li,Feixia Shen,Li Chen,Shouxin Zhang,Youmin Wang,Huacong Deng,Chao Liu,Shengli Wu,Tao Yang,Donghui Li,Guang Ning,Tangchun Wu,Weiqing Wang,Yufang Bi,Jieli Lu
摘要
Biomarkers for early detection of pancreatic cancer are in urgent need. To explore systematic circulating metabolites unbalance and identify potential biomarkers for pancreatic cancer in prospective Chinese cohorts, we conducted an untargeted metabolomics study in subjects with incident pancreatic cancer and matched controls (n = 192) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We characterized 998 metabolites in baseline serum and calculated 156 product-to-precursor ratios based on the KEGG database. The identified metabolic profiling revealed systematic metabolic network disorders before pancreatic cancer diagnosis. Forty-Five metabolites or product-to-precursor ratios showed significant associations with pancreatic cancer (P < .05 and FDR < 0.1), revealing abnormal metabolism of amino acids (especially alanine, aspartate and glutamate), lipids (especially steroid hormones), vitamins, nucleotides and peptides. A novel metabolite panel containing aspartate/alanine (OR [95% CI]: 1.97 [1.31-2.94]), androstenediol monosulfate (0.69 [0.49-0.97]) and glycylvaline (1.68 [1.04-2.70]) was significantly associated with risk of pancreatic cancer. Area under the receiver operating characteristic curves (AUCs) was improved from 0.573 (reference model of CA 19-9) to 0.721. The novel metabolite panel was validated in an independent cohort with AUC improved from 0.529 to 0.661. These biomarkers may have a potential value in early detection of pancreatic cancer.