1H-NMR based metabonomic profiling of human esophageal cancer tissue
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- 作者：Liang Wang (1)
Jie Chen (1)
Longqi Chen (2)
Pengchi Deng (3)
Qian bu (1)
Pu Xiang (1)
Manli Li (1)
Wenjie Lu (1)
Youzhi Xu (1)
Hongjun Lin (1)
Tianming Wu (1)
Huijuan Wang (1)
Jing Hu (1)
Xiaoni Shao (1)
Xiaobo Cen (1)
Ying-Lan Zhao (1) - 关键词：Metabonomic profiling ; Human esophageal cancer ; 1H ; NMR
- 刊名：Molecular Cancer
- 出版年：2013
- 出版时间：December 2013
- 年：2013
- 卷：12
- 期：1
- 全文大小：794KB
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Jie Chen (1)
Longqi Chen (2)
Pengchi Deng (3)
Qian bu (1)
Pu Xiang (1)
Manli Li (1)
Wenjie Lu (1)
Youzhi Xu (1)
Hongjun Lin (1)
Tianming Wu (1)
Huijuan Wang (1)
Jing Hu (1)
Xiaoni Shao (1)
Xiaobo Cen (1)
Ying-Lan Zhao (1)
1. State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China
2. Department of thoracic surgery, West China Hospital, West China Medical School, Sichuan University, Chengdu, 610041, China
3. Analytical & Testing Center, Sichuan University, Chengdu, 610041, China - ISSN：1476-4598
文摘
Background The biomarker identification of human esophageal cancer is critical for its early diagnosis and therapeutic approaches that will significantly improve patient survival. Specially, those that involves in progression of disease would be helpful to mechanism research. Methods In the present study, we investigated the distinguishing metabolites in human esophageal cancer tissues (n--9) and normal esophageal mucosae (n--6) using a 1H nuclear magnetic resonance (1H-NMR) based assay, which is a highly sensitive and non-destructive method for biomarker identification in biological systems. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least-squares-discriminant anlaysis (OPLS-DA) were applied to analyse 1H-NMR profiling data to identify potential biomarkers. Results The constructed OPLS-DA model achieved an excellent separation of the esophageal cancer tissues and normal mucosae. Excellent separation was obtained between the different stages of esophageal cancer tissues (stage II--8; stage III--5 and stage IV--6) and normal mucosae. A total of 45 metabolites were identified, and 12 of them were closely correlated with the stage of esophageal cancer. The downregulation of glucose, AMP and NAD, upregulation of formate indicated the large energy requirement due to accelerated cell proliferation in esophageal cancer. The increases in acetate, short-chain fatty acid and GABA in esophageal cancer tissue revealed the activation of fatty acids metabolism, which could satisfy the need for cellular membrane formation. Other modified metabolites were involved in choline metabolic pathway, including creatinine, creatine, DMG, DMA and TMA. These 12 metabolites, which are involved in energy, fatty acids and choline metabolism, may be associated with the progression of human esophageal cancer. Conclusion Our findings firstly identify the distinguishing metabolites in different stages of esophageal cancer tissues, indicating the attribution of metabolites disturbance to the progression of esophageal cancer. The potential biomarkers provide a promising molecular diagnostic approach for clinical diagnosis of human esophageal cancer and a new direction for the mechanism study.