Abstract
Clinical diagnosis of esophageal cancer (EC) at early stage is rather difficult. This study aimed to profile the molecules in serum and tissue and identify potential biomarkers in patients with EC. A total of 64 volunteers were recruited, and 83 samples (24 EC serum samples, 21 serum controls, 19 paired EC tissues, and corresponding tumor-adjacent tissues) were analyzed. The gas chromatography time-of-flight mass spectrometry (GC/TOF-MS) was employed, and principal component analysis was used to reveal the discriminatory metabolites and identify the candidate markers of EC. A total of 41 in serum and 36 identified compounds in tissues were relevant to the malignant prognosis. A marked metabolic reprogramming of EC was observed, including enhanced anaerobic glycolysis and glutaminolysis, inhibited tricarboxylic acid (TCA) cycle, and altered lipid metabolism and amino acid turnover. Based on the potential markers of glucose, glutamic acid, lactic acid, and cholesterol, the receiver operating characteristic (ROC) curves indicated good diagnosis and prognosis of EC. EC patients showed distinct reprogrammed metabolism involved in glycolysis, TCA cycle, glutaminolysis, and fatty acid metabolism. The pivotal molecules in the metabolic pathways were suggested as the potential markers to facilitate the early diagnosis of human EC.
Highlights
Esophageal cancer (EC) is the eighth most common malignancy globally and the fourth leading cause of cancer mortality in China [1]
Metabolomic analysis is a systemic tool focusing on endogenous low molecular weight compounds to quantitatively assess metabolic features and has been shown to be effective for elucidation of biomarkers, metabolic pathways, and disease diagnosis [4,5,6,7]
It is well documented that metabolism reprogramming occurs in various cancer cells [8, 20, 21]
Summary
Esophageal cancer (EC) is the eighth most common malignancy globally and the fourth leading cause of cancer mortality in China [1]. More accurate and robust biomarkers are in great demand for early screening and diagnosis of EC. Metabolomic analysis is a systemic tool focusing on endogenous low molecular weight compounds to quantitatively assess metabolic features and has been shown to be effective for elucidation of biomarkers, metabolic pathways, and disease diagnosis [4,5,6,7]. Metabolomics increases the possibility of validation of candidate biomarkers in the prospective studies through an accurate screening process for marker identification [12,13,14]. This approach enhances the ability of researchers to analyze metabolomic data of specific biomarkers to gain insight into disease biology [15].
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