Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.
Int J Cancer. 2022 Apr 1;150(7):1091-1100. doi: 10.1002/ijc.33877. Epub 2021 Dec 9.
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.
用于早期检测胰腺癌的生物标志物仍亟待探索。为了在未来的中国队列中研究系统性循环代谢物失衡,并鉴定出胰腺癌的潜在生物标志物,我们对中国心血管代谢疾病与癌症队列研究(China Cardiometabolic Disease and Cancer Cohort Study,4C)中的新发胰腺癌患者和匹配对照(n=192)进行了一项非靶向代谢组学研究。我们在基线血清中对 998 种代谢物进行了特征描述,并基于 KEGG 数据库计算了 156 种产物与前体的比率。鉴定出的代谢特征图谱揭示了在胰腺癌诊断之前存在系统性代谢网络紊乱。45 种代谢物或产物与前体的比率与胰腺癌显著相关(P<0.05, FDR<0.1),提示氨基酸(特别是丙氨酸、天冬氨酸和谷氨酸)、脂质(特别是甾体激素)、维生素、核苷酸和肽类的代谢异常。一个包含天冬氨酸/丙氨酸(比值比[95%置信区间]:1.97[1.31-2.94])、雄烯二酮单硫酸盐(0.69[0.49-0.97])和甘氨酰缬氨酸(1.68[1.04-2.70])的新型代谢物组合与胰腺癌风险显著相关。接受者操作特征曲线下面积(area under the receiver operating characteristic curve,AUC)从参考模型 CA 19-9 的 0.573 提高到了 0.721。该新型代谢物组合在独立队列中得到了验证,AUC 从 0.529 提高到了 0.661。这些生物标志物可能在胰腺癌的早期检测中具有潜在价值。