{"doi":"10.3389/fonc.2023.1234242","title":"Editorial: Metabolome in gastrointestinal cancer","abstract":"Gastrointestinal (GI) cancers, which include the cancer of organs and glandules of the digestive tract such as the esophagus, stomach, intestine, liver, bile ducts and pancreas, are one of the leading causes of cancer deaths worldwide, accounting for nearly 780,000 deaths a year (1). Lifestyle factors, such as smoking, alcohol abuse, and unhealthy diet, along with family genetic predisposition, play a role in many GI cancer types (2,3). Bacteria, virus and parasitic infections and the gut microbiota also play a role, and certain metabolites have been shown to affect infection, the immune response, and the composition of the gut microbiota (2,4,5). This points to the relevance of the metabolism in GI development and the importance of profiling the GI metabolome to understand the mechanisms underlying cancerogenesis and, even more, the progression (6,7). Metabolites are proven to play an increasingly versatile role in biological interactions, not only as substrates and products of enzyme-driven reactions but also as crucial system regulators (8). Cancer cells can repurpose these systems to drive unwanted proliferation, survival, and growth in cancer, and they can alter their metabolism during progression because of the dynamic interaction with the tumor microenvironment and the availability of metabolic factors such as glucose, amino acids and oxygen (9). This special issue collects original and review articles that provide an update on the current knowledge of the metabolomic signature associated with GI cancers, the interactions between metabolites and the GI tumor microenvironment including the microbiota, and the potential of metabolomic studies to develop predictive models and identify biomarkers of GI cancer that could serve for monitoring the progression and, possibly, as targets for a personalized therapy.Cancer cells have a distinct energy metabolism that is different from that of normal, healthy cells. The unique metabolic profile of pancreatic cancer cells has led researchers to investigate the potential of targeting these pathways as a strategy for treating the disease. Chen and colleagues obtained 22 metabolism-related genes (MRGs) from the MSigDB and gene sequence data in TCGA databases, and ultimately established the prognostic signature for pancreatic cancer based on these MRGs (10). They highlight that NT5E, a gene encoding the cell surface enzyme CD73, which is involved in the production of extracellular adenosine, is critical for acquiring more aggressive properties of pancreatic cancer by altering its metabolic pattern. Their study could be used to guide survival risk stratification of pancreatic cancer for more precise management of patients. Esophageal squamous cell carcinoma (ESCC) is a type of cancer that arises from the cells lining the esophagus.One of the major challenges in the early detection of ESCC is the absence of specific symptoms or biomarkers.Symptoms of the disease may not appear until the cancer has progressed to an advanced stage, which can limit treatment options and reduce the chances of survival. Wang's group performed UPLC-MS/MS on 450 ESCC patients and 588 controls, consisting of a discovery group and two validation groups, to identify biomarkers for early detection and prognosis (11). Through metabolite profiling, they found that dysregulated amino acids and lipid metabolism are critical metabolic signatures of ESCC and targeting the retinol and linoleic acid pathways may be a way to develop new mechanism-based therapeutic approaches. Their work provides novel insights for early detection and risk stratification to advance treatment options that contribute to improved outcomes for ESCC patients.It's noteworthy that metabolite profiling of serum and urine can provide insight into the metabolic changes that occur during cancer development and progression. For example, cancer cells often exhibit altered energy metabolism, including increased glycolysis and altered amino acid metabolism. 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