A recent study investigated associations between gut microbiota, fecal metabolic alterations, and esophageal cancer using advanced metabolomic and 16S ribosomal RNA (rRNA) gene sequencing approaches.
Study
A total of 34 patients with esophageal cancer (stages I–IV) and 29 age-, gender-, and diet-matched healthy controls were enrolled at HuLunBuir People’s Hospital in 2024. Individuals with prior malignancy, recent gastrointestinal inflammation, relevant medication use, chronic digestive disorders, or significant metabolic and cardiopulmonary disease were excluded. The cancer patients had previously received palliative anti-tumor treatment, including radiotherapy, systemic chemotherapy, chemoradiotherapy, or combination regimens.
Fecal samples were collected for microbiome and metabolomic analyses, while serum tumor biomarkers were also measured. DNA from fecal samples was amplified for the 16S rRNA V3–V4 region with barcoded primers and sequenced using the Illumina NovaSeq platform. Microbial diversity was evaluated with established indices and statistical analyses.
Metabolomic profiling was conducted by extracting compounds from fecal samples and analyzing them via liquid chromatography–mass spectrometry (LC-MS/MS). Differential metabolites were identified based on variable importance in projection (VIP) scores, t-tests, and false discovery rate (FDR) adjustment. Metabolite–microbiome correlations were assessed with Spearman’s rank correlation and visualized in Cytoscape. Esophageal tissue underwent histological analysis with hematoxylin and eosin staining.
Findings
Biomarkers SCC, CYFRA21-1, and CA72-4 were significantly elevated in esophageal cancer patients, while CEA and CA19-9 showed no significant difference. Histological analysis revealed progressive cancer tissue infiltration from Stage I to Stage IV, with advanced stages displaying extensive squamous cell involvement and a transition from squamous epithelial hyperplasia to atypical hyperplasia in adjacent tissues.
16S rRNA gene sequencing identified 9 phyla, 13 classes, 27 orders, 45 families, 100 genera, and 147 species, with 6,513,919 valid reads (average 103,396 reads/sample). Several measures of alpha diversity differed significantly between esophageal cancer patients and controls, including Observed Features, Chao1, Faith PD, and Pielou Evenness, while Shannon and Simpson indices did not differ significantly. Beta diversity also differed significantly in overall microbial community structure between the groups.
The most abundant gut microbial phyla in esophageal cancer were Firmicutes (49.5%), Proteobacteria (17.1%), Verrucomicrobiota (12.6%), and Bacteroidota (10.0%). At the genus level, notable taxa included Akkermansia (12.6%), Escherichia-Shigella (8.9%), Subdoligranulum (5.8%), Blautia (5.1%), and Bacteroides (4.31%).
Compared to controls, esophageal cancer patients had higher abundances of Verrucomicrobiota, Actinobacteriota, Euryarchaeota, and Desulfobacterota, while Bacteroidota and Firmicutes were more prevalent in controls. Genera such as Akkermansia, Dialister, and Prevotella were enriched in cancer, whereas Bacteroides, Romboutsia, and Fusicatenibacter were higher in controls.
Metabolomic profiling revealed 792 differential metabolites, primarily involved in fatty acid, amino acid, and nucleic acid metabolism. Functional prediction using PICRUSt2 identified 30 differential predicted KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, mainly associated with steroid biosynthesis, fatty acid biosynthesis, glycerolipid metabolism, and amino sugar and nucleotide sugar metabolism. Metabolomics also indicated enrichment in lipid metabolism pathways, including fatty acid transport, linoleic acid metabolism, and PPARA-mediated regulation of lipid metabolism.
Association analysis identified significant correlations between gut microorganisms and metabolites. Key bacterial clusters (Clostridia, Bacilli, Bacteroidota, Coriobacteriia) were linked with metabolites involved in GPCR (G protein-coupled receptor) signaling, vitamin transport, nucleoside metabolism, purine metabolism, and linolenic acid metabolism. Both positive and negative correlations were observed.
In an exploratory cross-sectional analysis stratified by cancer stage, the relative abundance of certain genera, particularly Prevotella and Alistipes, was higher in later-stage groups. However, the small number of patients within each stage, particularly the three patients with stage I disease, means these findings should be interpreted cautiously. Metabolites showing stage-associated patterns were mainly enriched in lipid metabolism pathways, especially glycerolipid and fatty acid metabolism.
Conclusion
The current study identified distinct differences in serum biomarkers, gut microbiota composition, and metabolic profiles between people with esophageal cancer and healthy controls. Notably, significant dysregulation in lipid and amino acid metabolism, along with specific microbial and metabolic signatures, was associated with esophageal cancer and disease stage.
However, the researchers noted that the retrospective cross-sectional design, small sample size, prior anti-tumor treatment, and absence of standardized dietary control could have influenced the results. Dietary changes associated with advanced esophageal cancer, including shifts from solid to liquid diets, nutritional support, and reduced energy intake caused by progressive dysphagia, could also contribute to observed microbiome and metabolic differences.
Source:
https://www.news-medical.net/news/20261001/Esophageal-cancer-leaves-a-distinct-metabolic-signature-in-the-gut.aspx