Department of Hepatobiliary & Pancreatic Surgery Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei, PR China; Clinical Medicine Research Center for Minimally Invasive Procedure of Hepatobiliary & Pancreatic Diseases of Hubei Province, Wuhan 430071, Hubei, PR China.
Department of Clinical Laboratory, Center for Gene Diagnosis, and Program of Clinical Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei, PR China.
Clin Chim Acta. 2024 Feb 1;554:117777. doi: 10.1016/j.cca.2024.117777. Epub 2024 Jan 12.
Due to the difficulty of pathological sampling, the clinical differentiation between benign and malignant biliopancreatic diseases remains challenging. Endoscopic retrograde cholangiopancreatography (ERCP) is used to investigate biliary diseases, enabling the collection of bile. This study assessed potential metabolic alterations in biliopancreatic malignancies by exploring changes in the bile metabolome and the diagnostic potential of bile metabolome analysis.
A total of 264 bile samples were collected from patients who were divided into a discovery cohort (n = 85) and a validation cohort (n = 179). Untargeted metabolomic analysis was used in the discovery cohort, while targeted metabolomic analysis was used in the validation cohort for further investigation of the differentially abundant metabolites.
The untargeted metabolomic analysis revealed that the metabolic changes associated with biliopancreatic malignancies occurred mainly in lipid metabolites, among which fatty acid metabolism was most significantly altered, and differentially abundant metabolites identified in the discovery cohort were mainly enriched in unsaturated fatty acid synthesis and linolenic acid synthesis pathways. Analysis of free fatty acid (FFA) metabolism in the validation cohort revealed that the FFA levels and related indicators verified the abnormal fatty acid metabolism associated with biliopancreatic malignancies. The combined model for biliopancreatic malignancies based on the fatty acid indexes and clinical test results improved the diagnostic performance of current clinical level. Then, we used machine learning to define three different FFA metabolic clusters of biliopancreatic malignancies, and survival analysis showed significant differences in prognostic outcomes among the three clusters.
This study found metabolic alterations in biliopancreatic malignancies based on bile samples, which may provide new insights for the clinical diagnosis and prognostic assessment of biliopancreatic malignancies.
由于病理采样困难，良恶性胆胰疾病的临床鉴别仍然具有挑战性。内镜逆行胰胆管造影术（ERCP）用于研究胆道疾病，能够采集胆汁。本研究通过探索胆汁代谢组学的变化及其对胆汁代谢组学分析的诊断潜力，评估胆胰恶性肿瘤的潜在代谢改变。
共收集 264 例胆汁样本，患者分为发现队列（n=85）和验证队列（n=179）。在发现队列中进行非靶向代谢组学分析，在验证队列中进行靶向代谢组学分析，以进一步研究差异丰度代谢物。
非靶向代谢组学分析显示，与胆胰恶性肿瘤相关的代谢变化主要发生在脂质代谢物中，其中脂肪酸代谢变化最明显，在发现队列中鉴定的差异丰度代谢物主要富集在不饱和脂肪酸合成和亚油酸合成途径中。在验证队列中分析游离脂肪酸（FFA）代谢时，发现 FFA 水平和相关指标验证了与胆胰恶性肿瘤相关的异常脂肪酸代谢。基于脂肪酸指标和临床检验结果的胆胰恶性肿瘤联合模型提高了当前临床水平的诊断性能。然后，我们使用机器学习定义了三种不同的胆胰恶性肿瘤 FFA 代谢簇，生存分析显示这三个簇之间的预后结果存在显著差异。
本研究基于胆汁样本发现了胆胰恶性肿瘤的代谢改变，这可能为胆胰恶性肿瘤的临床诊断和预后评估提供新的见解。
