Serum Metabolomic Signatures of Lymph Node Metastasis of Esophageal Squamous Cell Carcinoma
Serum Metabolomic Signatures of Lymph Node Metastasis of Esophageal Squamous Cell Carcinoma
复制标题
食管鳞状细胞癌淋巴结转移的血清代谢组学特征。
DOI：
10.1021/pr500483z
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发表时间：
2014-09-01
影响因子：
4.4
通讯作者：
Gao, Xianfu
中科院分区：
文献类型：
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作者：
Jin, Hai;Qiao, Fan;Gao, Xianfu
食管癌是一种重要的预后不良的恶性肿瘤，淋巴结转移是影响其预后的重要因素。应用整体代谢组学方法研究食管鳞癌淋巴结转移。使用气相色谱/质谱法以及单变量和多变量统计分析进行代谢组学分析。ESCC患者和健康受试者之间存在明显的代谢差异。根据淋巴结转移情况可对食管鳞癌进行分类。我们进一步鉴定了ESCC和淋巴结转移性ESCC患者的一系列差异血清代谢物，表明转移性ESCC患者中癌细胞的增殖（有氧糖酵解、氨基分解、脂肪酸代谢和支链氨基酸消耗）、凋亡、迁移、免疫逃逸和氧化应激中的代谢功能障碍。通过二元逻辑回归分析，总共选择了三种血清代谢物（缬氨酸、γ-氨基丁酸和吡咯-2-羧酸），通过受试者操作特征分析，它们的联合使用导致了对ESCC转移的高诊断能力。目前的代谢组学研究分期食管癌患者的淋巴结转移，结果表明，这种方法在预后预测，定制治疗，并了解预后不良的食管癌患者的病理机制有前途的应用。
Lymph node metastasis was recently proven to be the single most important prognostic factor for esophageal cancer, an important malignant tumor with poor prognosis. A global metabolomics approach was applied to study lymph node metastasis of esophageal squamous cell carcinoma (ESCC). Metabolomics analyses were performed using gas chromatography/mass spectrometry together with univariate and multivariate statistical analyses. There were clear metabolic distinctions between ESCC patients and healthy subjects. ESCC patients could be well-classified according to lymph node metastasis. We further identified a series of differential serum metabolites for ESCC and lymph node metastatic ESCC patients, suggesting metabolic dysfunction in proliferation (aerobic glycolysis, glutaminolysis, fatty acid metabolism, and branched-chain amino acid consumption), apoptosis, migration, immune escape, and oxidative stress of cancer cells in metastatic ESCC patients. In total, three serum metabolites (valine, γ-aminobutyric acid, and pyrrole-2-carboxylic acid) were selected by binary logistic regression analysis, and their combined use resulted in high diagnostic capacity for ESCC metastasis by receiver operating characteristic analysis. The present metabolomics study staged ESCC patients by lymph node metastasis, and the results suggest promising applications of this approach in prognostic prediction, tailored therapeutics, and understanding the pathological mechanisms of poor prognosis of ESCC patients.