Serum metabolites of healthy controls and esophageal cancer (EC) patients have previously been compared to predict cancer-specific profiles. However, the association between metabolic alterations in serum samples and esophageal tissues in EC patients remains unclear. Here, we analyzed 50 pairs of EC tissues and distant noncancerous tissues, together with patient-matched serum samples, using 1 H NMR spectroscopy and pattern recognition algorithms. EC patients could be differentiated from the controls based on the metabolic profiles at tissue and serum levels. Some overlapping discriminatory metabolites, including valine, alanine, glucose, acetate, citrate, succinate and glutamate, were identified in both matrices. These results suggested deregulation of metabolic pathways, and potentially revealed the links between EC and several metabolic pathways, such as the tricarboxylic acid cycle, glutaminolysis, short-chain fatty acid metabolism, lipometabolism and pyruvate metabolism. Perturbation of the pyruvate metabolism was most strongly associated with EC progression. Consequently, an optimal serum metabolite biomarker panel comprising acetate and pyruvate was developed, as these two metabolites are involved in pyruvate metabolism, and changes in their serum levels were significantly correlated with alterations in the levels of some other esophageal tissue metabolites. In comparison with individual biomarkers, this panel exhibited better diagnostic efficiency for EC, with an AUC of 0.948 in the test set, and a good predictive ability of 82.5% in the validation set. Analysis of key genes related to pyruvate metabolism in EC patients revealed patterns corresponding to the changes in serum pyruvate and acetate levels. These correlation analyses demonstrate that there were distinct metabolic characteristics and pathway aberrations in the esophageal tumor tissue and in the serum. Changes in the serum metabolic signatures could reflect the alterations in the esophageal tumor profile, thereby emphasizing the importance of distinct serum metabolic profiles as potential noninvasive biomarkers for EC.
Keywords: NMR-based metabolomics; biomarker; esophageal cancer; serum; tumor tissue.
© 2021 John Wiley & Sons, Ltd.