Combined Metabolomic Analysis of Plasma and Tissue Reveals a Prognostic Risk Score System and Metabolic Dysregulation in Esophageal Squamous Cell Carcinoma

Background: Esophageal squamous cell carcinoma (ESCC) is a gastrointestinal malignancy with poor prognosis. Although studies have shown that metabolic reprogramming is linked to ESCC development, no prognostic metabolic biomarkers or potential therapeutic metabolic targets have been found yet. Method: The present study investigated some circulating metabolites associated with overall survival in 276 curatively ESCC patients using liquid chromatography/mass spectrometry (LC/MS) metabolomics and Kaplan-Meier analysis. Tissue metabolomics analysis of 23 paired ESCC tissue samples was performed to discover metabolic dysregulation in ESCC cancerous tissues. A method consisting of Support Vector Machine based on Recursive Feature Elimination (SVM-RFE) and LIMMA differential expression analysis was utilized to select promising feature genes in transcriptomic data from 179 paired ESCC tissue samples. A joint pathway analysis with genes and metabolite was further conducted to reveal the most potential metabolic pathway or targets in ESCC. Results: Our study identified four metabolites - kynurenine, the lysophosphatidylcholine 1-myristoyl-sn-glycero-3-phosphocholine (LPC(14:0)sn-1), 2-piperidinone, and hippuric acid - as prognostic factors in the preoperative plasma from ESCC patients. A risk score consisting of kynurenine and LPC(14:0)sn-1 significantly improved the prognostic performance of the TNM staging system and was able to further stratify the risk of ESCC. Combined tissue metabolomics analysis and SVM-RFE gene selection revealed dysregulated tryptophan-kynurenine metabolism as an important metabolic feature in ESCC, including accumulation of tryptophan, formylkynurenine, and kynurenine, as well as up-regulated indoleamine 2,3-dioxygenase 1 (IDO1) in ESCC cancerous tissues. Conclusions: Our work identified for the first time four potential prognostic circulating metabolites, and further revealed up-regulated tryptophan-kynurenine metabolism in ESCC. Our results not only provide a metabolite-based risk score system as a useful prognostic tool, but also improve the understanding in molecular mechanisms of ESCC onset/progression, and offer novel potential therapeutic targets.