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Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with esophageal cancer.
Yang, Xiao-Li; Wang, Peng; Ye, Hua; Jiang, Ming; Su, Yu-Bin; Peng, Xuan-Xian; Li, Hui; Zhang, Jian-Ying.
Affiliation
  • Yang XL; State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.
  • Wang P; State Key Laboratory of Bio-Control, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, University City, Guangzhou, China.
  • Ye H; State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.
  • Jiang M; Henan Key Laboratory of Tumor Epidemiology and College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Su YB; State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.
  • Peng XX; Henan Key Laboratory of Tumor Epidemiology and College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Li H; State Key Laboratory of Bio-Control, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, University City, Guangzhou, China.
  • Zhang JY; Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Department of Biotechnology, College of Life Science and Technology, Jinan University, Guangzhou, China.
Front Oncol ; 12: 938234, 2022.
Article in En | MEDLINE | ID: mdl-36176418
Metabolomics has been reported as an efficient tool to screen biomarkers that are related to esophageal cancer. However, the metabolic biomarkers identifying malignant degrees and therapeutic efficacy are still largely unknown in the disease. Here, GC-MS-based metabolomics was used to understand metabolic alteration in 137 serum specimens from patients with esophageal cancer, which is approximately two- to fivefold as many plasma specimens as the previous reports. The elevated amino acid metabolism is in sharp contrast to the reduced carbohydrate as a characteristic feature of esophageal cancer. Comparative metabolomics showed that most metabolic differences were determined between the early stage (0-II) and the late stage (III and IV) among the 0-IV stages of esophageal cancer and between patients who received treatment and those who did not receive treatment. Glycine, serine, and threonine metabolism and glycine were identified as the potentially overlapped metabolic pathway and metabolite, respectively, in both disease progress and treatment effect. Glycine, fructose, ornithine, and threonine can be a potential array for the evaluation of disease prognosis and therapy in esophageal cancer. These results highlight the means of identifying previously unknown biomarkers related to esophageal cancer by a metabolomics approach.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Oncol Year: 2022 Document type: Article Affiliation country: China Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Oncol Year: 2022 Document type: Article Affiliation country: China Country of publication: Switzerland