Clinical Research Papers:

A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis

Yinan Chen, Jun Zhang, Lei Guo, Lei Liu, Jingran Wen, Lu Xu, Min Yan, Zuofeng Li, Xiaoyan Zhang, Peng Nan, Jinling Jiang, Jun Ji, Jianian Zhang, Wei Cai, Huisheng Zhuang, Yan Wang, Zhenggang Zhu and Yingyan Yu _

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Oncotarget. 2016; 7:87496-87510. https://doi.org/10.18632/oncotarget.11754

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Yinan Chen1,*, Jun Zhang1,*, Lei Guo1, Lei Liu1, Jingran Wen2, Lu Xu1, Min Yan1, Zuofeng Li2, Xiaoyan Zhang2, Peng Nan3, Jinling Jiang1, Jun Ji1, Jianian Zhang1, Wei Cai1, Huisheng Zhuang4, Yan Wang5, Zhenggang Zhu1 and Yingyan Yu1

1 Department of Surgery of Ruijin Hospital, and Shanghai Institute of Digestive Surgery, Shanghai Key Laboratory for Gastric Neoplasms, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

2 Tongji University, School of Life Science and Technology, Shanghai, China

3 School of Life Sciences, Fudan University, Shanghai, China

4 School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

5 College of Public Health, Shanghai Jiao Tong University, School of Medicine, Shanghai, China

* These authors have contributed equally to this work


Yingyan Yu, email:

Zhenggang Zhu, email:

Keywords: gastric cancer; urine; metabolomics; biomarkers; GC-MS

Received: March 29, 2016 Accepted: July 19, 2016 Published: August 31, 2016


Early diagnosis of gastric cancer is crucial to improve patient′ outcome. A good biomarker will function in early diagnosis for gastric cancer. In order to find practical and cost-effective biomarkers, we used gas chromatography combined mass spectrometer (GC-MS) to profile urinary metabolites on 293 urine samples. Ninety-four samples are taken as training set, others for validating study. Orthogonal partial least squares discriminant analysis (OPLS-DA), significance analysis of microarray (SAM) and Mann-Whitney U test are used for data analysis. The diagnostic value of urinary metabolites was evaluated by ROC curve. As results, Seventeen metabolites are significantly different between patients and healthy controls in training set. Among them, 14 metabolites show diagnostic value better than classic blood biomarkers by quantitative assay on validation set. Ten of them are amino acids and four are organic metabolites. Importantly, proline, p-cresol and 4-hydroxybenzoic acid disclose outcome-prediction value by means of survival analysis. Therefore, the examination of urinary metabolites is a promising noninvasive strategy for gastric cancer screening.

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