Abstract
Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)(1) analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated over the treatment course. The results suggest that these biomarkers may be useful in diagnosis, as well as in monitoring therapeutic responses and predicting outcomes of the ESCC.
Highlights
From the ‡State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, P
A nontargeted metabolomics approach based on rapid resolution liquid chromatography-mass spectrometry (RRLC-MS) in conjunction with multivariate statistical data analyses (MVDA) was employed to determine global alterations in the metabolic profiles of healthy controls and esophageal squamous cell carcinoma (ESCC) patients before, during, and after cisplatin-based CRT
The retention time deviation profiles (R-software) of all plasma samples generated values of less than Ϯ 40 s and Ϯ 20 s for the majority of RRLC-MS analysis by ESI in positive ion mode (RRLC-(ϩ)ESIMS) and in negative ion mode (RRLC-(-)ESI-MS) analyses, respectively, indicating high reproducibility. These results confirm that the significant differences observed between groups by multivariate statistical analysis were more likely to be a result of genuine subtle changes in metabolites, rather than products of artifacts arising from technical errors
Summary
Chemicals—ACN (HPLC grade) and formic acid (FA, HPLC grade) were purchased from Merck (Darmstadt, Germany). Sample Collection—All of the fasting samples were recruited from the Cancer Institute and Hospital of the Chinese Academy of Medical Sciences (Beijing, China). The cancer hospital had the standard sample collection protocols. Fasting blood samples were collected into K2 EDTA vacutainer tubes and cooled down in freezer (4 °C) at once. They were centrifuged within 2 h at 3000 ϫ g for 10 min at 4 °C. For RRLC-MS/MS based validation test, plasma samples containing internal standards (levofloxacin, hesperidin, and rhein, 5 g/ml) were prepared as described here.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
