Cheng Jing, Zheng Guangyong, Jin Hai, Gao Xianfu
Department of Medical Instrument, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China.
Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Comb Chem High Throughput Screen. 2017;20(2):133-139. doi: 10.2174/1386207319666161220115409.
Esophageal Squamous Cell Carcinoma (ESCC) is a common malignant tumor in China, which causes about 200,000 deaths each year. Sensitive biomarkers are helpful to diagnose the disease in early stage.
To identify biomarkers of ESCC and elucidate underlying mechanism of the disease, a targeted metabolomics strategy based on liquid chromatography-tandem mass spectrometry (LCMS/ MS) has been implemented to explore tyrosine metabolism from 40 ESCC patients and 27 healthy controls.
Four metabolites, i.e. phenylalanine, 4-hydroxyphenyllactic acid, 3,4-dihydroxyphenylalanine, and 3,4-dihydroxyphenylacetic acid were identified as diagnostic biomarkers for ESCC patients. Based on these biomarkers, a prediction model was constructed for ESCC diagnosis. The analysis of receiver operating characteristic (ROC) curve confirmed its effectiveness of the model.
Our results reveal that tyrosine metabolism is disturbed in ESCC patients and the metabolites involved in tyrosine pathway can be used as diagnostic biomarkers of the disease. Findings of this study can help investigate pathogenesis of ESCC and facilitate understanding mechanism of the disease.
食管鳞状细胞癌（ESCC）是中国常见的恶性肿瘤，每年导致约20万人死亡。敏感的生物标志物有助于早期诊断该疾病。
为了鉴定ESCC的生物标志物并阐明该疾病的潜在机制，基于液相色谱-串联质谱（LCMS/MS）的靶向代谢组学策略已被用于探索40例ESCC患者和27例健康对照的酪氨酸代谢。
四种代谢物，即苯丙氨酸、4-羟基苯乳酸、3,4-二羟基苯丙氨酸和3,4-二羟基苯乙酸被鉴定为ESCC患者的诊断生物标志物。基于这些生物标志物，构建了ESCC诊断预测模型。受试者工作特征（ROC）曲线分析证实了该模型的有效性。
我们的结果表明ESCC患者的酪氨酸代谢受到干扰，酪氨酸途径中涉及的代谢物可作为该疾病的诊断生物标志物。本研究结果有助于探讨ESCC的发病机制，并促进对该疾病机制的理解。
