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Background <p>Dysbiosis of the oral microbiota has been shown to be associated with the development of esophageal and gastric cancer. Nevertheless, little research explores how oral microbiota might contribute to the occurrence and progression of adenocarcinoma of the esophagogastric junction (AEG).</p> Method <p>16&#xa0;S rRNA V3-V4 amplicon sequencing was performed on 106 oral microbiota samples from 55 AEG patients and 51 controls. To determine key microbial indicators, Linear Discriminant Analysis Effect Size (LEfSe) analysis, Random Forest model, and species composition heatmaps were utilised. Spearman correlation analysis assessed the relationship between oral microbiota and clinicopathological variables. PICRUSt2 was employed to predict microbial functions and investigate the association with KEGG metabolic pathways.</p> Results <p>A total of 584 oral genera and 647 oral species were observed in AEG and controls, excluding unidentified species. The abundance of 24 oral genera significantly increased in AEG patients, with Neisseria, Streptococcus, Rothia, Gemella, and Capnocytophaga being the five most abundant. Lefse, RF model and Species composition heatmap identified that genera enriched in the AEG group including Streptococcus, Neisseria, Rothia, Gemella, and genera depleted including Prevotella, Veillonella, Centipeda, Nanosynbacter were determined as biological markers to distinguish AEG from healthy controls. The genera with decreased abundance in AEG patients showed a positive association with WBC levels, neutrophil levels, and CA724 levels in the Mantel correlation test. PICRUSt analysis revealed significant differences in the abundance of 12 KEGG pathways. Carbohydrate metabolism, drug resistance, infectious diseases, lipid metabolism, nucleotide metabolism, and membrane transport pathways were positively correlated with genera enriched in the AEG group such as Streptococcus and Rothia, while negatively correlated with depleted genera like Prevotella.</p> Conclusion <p>Our research may suggest that dysbiosis of the oral microbiota and alterations in the KEGG metabolic pathway are linked to the development of AEG. In the future, we will conduct comprehensive verification through animal experiments and large-scale multicentre studies.</p>

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Oral microbial profile polymorphisms predict early Siewert II adenocarcinoma of esophagogastric junction

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月19日

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  • Fangrui Zou,
  • Han Chen,
  • Xin Yu,
  • Die Hu,
  • Yu Dong,
  • Xiaoying Zhou,
  • Xinmin Si

摘要

Background

Dysbiosis of the oral microbiota has been shown to be associated with the development of esophageal and gastric cancer. Nevertheless, little research explores how oral microbiota might contribute to the occurrence and progression of adenocarcinoma of the esophagogastric junction (AEG).

Method

16 S rRNA V3-V4 amplicon sequencing was performed on 106 oral microbiota samples from 55 AEG patients and 51 controls. To determine key microbial indicators, Linear Discriminant Analysis Effect Size (LEfSe) analysis, Random Forest model, and species composition heatmaps were utilised. Spearman correlation analysis assessed the relationship between oral microbiota and clinicopathological variables. PICRUSt2 was employed to predict microbial functions and investigate the association with KEGG metabolic pathways.

Results

A total of 584 oral genera and 647 oral species were observed in AEG and controls, excluding unidentified species. The abundance of 24 oral genera significantly increased in AEG patients, with Neisseria, Streptococcus, Rothia, Gemella, and Capnocytophaga being the five most abundant. Lefse, RF model and Species composition heatmap identified that genera enriched in the AEG group including Streptococcus, Neisseria, Rothia, Gemella, and genera depleted including Prevotella, Veillonella, Centipeda, Nanosynbacter were determined as biological markers to distinguish AEG from healthy controls. The genera with decreased abundance in AEG patients showed a positive association with WBC levels, neutrophil levels, and CA724 levels in the Mantel correlation test. PICRUSt analysis revealed significant differences in the abundance of 12 KEGG pathways. Carbohydrate metabolism, drug resistance, infectious diseases, lipid metabolism, nucleotide metabolism, and membrane transport pathways were positively correlated with genera enriched in the AEG group such as Streptococcus and Rothia, while negatively correlated with depleted genera like Prevotella.

Conclusion

Our research may suggest that dysbiosis of the oral microbiota and alterations in the KEGG metabolic pathway are linked to the development of AEG. In the future, we will conduct comprehensive verification through animal experiments and large-scale multicentre studies.