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Background <p>Recent studies suggest that intratumoral microbiome and altered metabolic networks play crucial roles in pancreatic cancer (PC) progression. However, the precise interplay between microbial communities and tumor metabolism in PC remains poorly understood. This study aims to investigate the impact of the intratumoral microbiome, the metabolic landscape, and their interactions on PC development.</p> Methods <p>16S rDNA sequencing and Untargeted metabolomic profiling were performed on 47 paired pancreatic cancer and adjacent normal tissues to analyze their intratumoral microbiome and metabolic landscapes. Bioinformatics tools were used to conduct differential microbiome abundance analysis and pathway enrichment. A correlation analysis was performed to identify key microbiota-metabolite interactions.</p> Results <p>16S rDNA sequencing revealed significant differences in the abundance and diversity (α-diversity and β-diversity) of the intratumoral microbiome in PC. The predominant species in pancreatic cancer were <i>Pseudomonas</i>. Enrichment analysis showed that amino acid metabolic pathways, including Arginine and Proline Metabolism, Arginine Biosynthesis, were significantly enriched in PC. Untargeted metabolomics identified 298 metabolites that were significantly altered in PC (fold change &gt; 1.5, <i>P</i>-value &lt; 0.05). These included amino acid metabolites such as Lys-Leu, Pro-Leu, Arg-Leu, Lys-Val, His-Lys, and others. Functional enrichment analysis highlighted several metabolic pathways that play important roles in pancreatic cancer, including Glycine, Serine, and Threonine Metabolism, Amino Acid Biosynthesis, Metabolic Pathways and Cysteine and Methionine Metabolism. Correlation analysis between microbiome and metabolic data revealed significant associations between Pseudomonas and several metabolites, including Alpha-ketoisovaleric acid, 16-hydroxyhexadecanoic acid, Myristic acid, Nonanoic acid (the Spearman correlation coefficient <i>r</i>, 0.5 ≤|<i>r</i>|≤ 1 and <i>P</i>-value &lt; 0.05).</p> Conclusion <p>This study suggests a relationship between the microbiome and metabolism in pancreatic cancer. We observed that Pseudomonas contributes to altered amino acid metabolism, but whether this interaction is causal and the mechanisms underlying it remain unclear. Further experimental validation is required before considering microbiome-targeted metabolic interventions as viable therapeutic strategies.</p>

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Microbiome-metabolome interplay in pancreatic cancer progression: insights from multi-omics analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月2日

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  • Dong Luo,
  • Qizhen Chen,
  • Yixiong Li,
  • Jianbo Yang,
  • Yongguang Tao,
  • Liandong Ji,
  • Xuejun Gong

摘要

Background

Recent studies suggest that intratumoral microbiome and altered metabolic networks play crucial roles in pancreatic cancer (PC) progression. However, the precise interplay between microbial communities and tumor metabolism in PC remains poorly understood. This study aims to investigate the impact of the intratumoral microbiome, the metabolic landscape, and their interactions on PC development.

Methods

16S rDNA sequencing and Untargeted metabolomic profiling were performed on 47 paired pancreatic cancer and adjacent normal tissues to analyze their intratumoral microbiome and metabolic landscapes. Bioinformatics tools were used to conduct differential microbiome abundance analysis and pathway enrichment. A correlation analysis was performed to identify key microbiota-metabolite interactions.

Results

16S rDNA sequencing revealed significant differences in the abundance and diversity (α-diversity and β-diversity) of the intratumoral microbiome in PC. The predominant species in pancreatic cancer were Pseudomonas. Enrichment analysis showed that amino acid metabolic pathways, including Arginine and Proline Metabolism, Arginine Biosynthesis, were significantly enriched in PC. Untargeted metabolomics identified 298 metabolites that were significantly altered in PC (fold change > 1.5, P-value < 0.05). These included amino acid metabolites such as Lys-Leu, Pro-Leu, Arg-Leu, Lys-Val, His-Lys, and others. Functional enrichment analysis highlighted several metabolic pathways that play important roles in pancreatic cancer, including Glycine, Serine, and Threonine Metabolism, Amino Acid Biosynthesis, Metabolic Pathways and Cysteine and Methionine Metabolism. Correlation analysis between microbiome and metabolic data revealed significant associations between Pseudomonas and several metabolites, including Alpha-ketoisovaleric acid, 16-hydroxyhexadecanoic acid, Myristic acid, Nonanoic acid (the Spearman correlation coefficient r, 0.5 ≤|r|≤ 1 and P-value < 0.05).

Conclusion

This study suggests a relationship between the microbiome and metabolism in pancreatic cancer. We observed that Pseudomonas contributes to altered amino acid metabolism, but whether this interaction is causal and the mechanisms underlying it remain unclear. Further experimental validation is required before considering microbiome-targeted metabolic interventions as viable therapeutic strategies.