Metabolomic analysis of exosomal-markers in esophageal squamous cell carcinoma

Abstract

machine learning from patients with recrudescence and patients without recrudescence and demonstrated a marker set consisting of 3'-UMP, palmitoleic acid, palmitaldehyde, and isobutyl decanoate for predicting ESCC recurrence with an AUC of 98%. These metabolome signatures of exosomes retained a high absolute fold change value at all ESCC stages and were very likely associated with cancer metabolism, which could be potentially applied as novel biomarkers for diagnosis and prognosis of ESCC.