使用非靶向代谢组学分析的胰腺导管腺癌诊断生物标志物
Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma Using Non-Targeted Metabolomic Analysis.
摘要(中文译文)
利用体液进行的液体活检能够无创获取多种肿瘤来源分子，从而全面表征肿瘤特征。其中，代谢组学分析可能准确反映疾病发病机制，并在临床诊断应用中具有前景。本研究通过对胰液进行非靶向代谢组学分析，探索与胰腺导管腺癌（PDAC）相关的代谢改变，并基于所选代谢物构建初步诊断模型。胰液样本采集自因PDAC接受胰十二指肠切除术的患者（=11）以及患有非PDAC疾病的患者（=14），后者包括慢性胰腺炎等良性疾病以及远端胆管腺癌和壶腹腺癌等非胰腺恶性肿瘤，样本于术中及术后收集。采用LC-QTOF-MS进行非靶向代谢组学分析。使用MS-DIAL和MetaboAnalyst处理数据，并通过PLS-DA筛选组间差异成分。基于注释的代谢物，采用逻辑回归构建诊断模型。PLS-DA识别出56个具有判别力的成分，其中19个成功注释。在PDAC患者胰液中，1种代谢物显著升高，22种相对降低。趋于降低的已知代谢物包括异柠檬酸、柠檬酸及若干氧化脂肪酸。使用这些所选代谢物构建的初步逻辑回归诊断模型显示出中等判别性能。柠檬酸被纳入最终的三变量模型，提示其作为PDAC判别候选标志物的潜力。胰液反映了PDAC相关的代谢变化，可能含有候选诊断生物标志物。本研究中注释的代谢物可能具有作为新型标志物的潜力，对未知成分的进一步研究可能有助于推进PDAC的诊断和治疗。
Abstract
: Liquid biopsy using bodily fluids enables noninvasive acquisition of diverse tumor-derived molecules for comprehensive characterization of tumor profiles. Metabolomic analysis, in particular, may accurately reflect disease pathogenesis and holds promise for clinical diagnostic applications. This study explored metabolic alterations associated with pancreatic ductal adenocarcinoma (PDAC) using non-targeted metabolomic analysis of pancreatic juice to construct a preliminary diagnostic model based on selected metabolites. Pancreatic juice samples were collected intraoperatively and postoperatively from patients undergoing pancreaticoduodenectomy for PDAC ( = 11) and from those who had non-PDAC diseases, including benign conditions such as chronic pancreatitis and non-pancreatic malignancies such as distal bile duct adenocarcinoma and ampullary adenocarcinoma ( = 14). Non-targeted metabolomic analysis was performed using LC-QTOF-MS. Data were processed using MS-DIAL and MetaboAnalyst, and components showing intergroup differences were selected via PLS-DA. A diagnostic model was constructed using logistic regression based on annotated metabolites. PLS-DA identified 56 discriminative components, of which 19 were successfully annotated. One metabolite was notably increased and 22 were relatively decreased in pancreatic juice of patients with PDAC. Among known metabolites that tended to decrease were isocitric acid, citric acid, and several oxidized fatty acids. A tentative logistic regression-based diagnostic model using these selected metabolites showed moderate discriminative performance. Citric acid was included in the final three-variable model, suggesting its potential as a candidate marker for PDAC discrimination. Pancreatic juice reflects PDAC-associated metabolic changes and may contain candidate diagnostic biomarkers. Metabolites annotated in this study may have potential as novel markers, and further studies on unknown components could help advance PDAC diagnosis and treatment.
如何引用
AMA
Hirofumi Sonoda, Hideo Ogiso, Yuichi Aoki, Kazue Morishima, Hideki Sasanuma, Naohiro Sata, et al. Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma Using Non-Targeted Metabolomic Analysis.. Cancers. 2026; doi:10.3390/cancers18040684.
APA
Hirofumi Sonoda, Hideo Ogiso, Yuichi Aoki, Kazue Morishima, Hideki Sasanuma, Naohiro Sata, et al (2026). Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma Using Non-Targeted Metabolomic Analysis.. Cancers. https://doi.org/10.3390/cancers18040684
GB/T 7714
Hirofumi Sonoda, Hideo Ogiso, Yuichi Aoki, Kazue Morishima, Hideki Sasanuma, Naohiro Sata, et al. Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma Using Non-Targeted Metabolomic Analysis.[J]. Cancers, 2026 doi:10.3390/cancers18040684.
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