Fecal metabolomic and microbiome profiling reveals lipid metabolic dysregulation in esophageal cancer

The aim of this study is to perform metabolomic and 16 S rRNA gene sequencing analyses in fecal sample of patients with esophageal cancer to investigate the impact of gut microbiota dysbiosis-mediated metabolic disorders on esophageal cancer. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 16s rRNA gene sequencing are employed to identify differentially abundant metabolites and gut microbiota in the fecal sample. Differentially abundant metabolites and differential expression profile are further analyzed for their biological functions and potential metabolic pathways through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. At the metabolic level, 792 metabolites exhibited dysregulation, with functional enrichment analyses indicating their involvement in fatty acid metabolism, amino acid metabolism, and nucleic acid metabolism. At the microbial level, based on LEfSe analysis, Prevotella , Faecalibacterium , Lachnoclostridium , and Parasutterella can be identified as representative differential microorganisms, demonstrating significant capability in distinguishing between the two groups. Based on PICRUSt functional enrichment prediction analysis, the significantly enriched pathways were primarily clustered within the steroid biosynthesis, fatty acid biosynthesis, glycerolipid metabolism, and amino sugar and nucleotide sugar metabolism. Lipid metabolism plays a crucial role in numerous physiological processes, including promoting inflammation and signal transduction. The disturbance of lipid metabolism in esophageal cancer provides a new basis for uncovering the occurrence and development of the disease.