ArticleFrontiers in microbiology2025
Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients.
Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Metabolism-Driven Modulation by the Human Microbiota: Implications for Cancer Therapy and Emerging Strategies.Advances in experimental medicine and biology · 2026Review
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5 authors.
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Abstract
Background: Lung cancer is a leading cause of cancer-related mortality worldwide, with chemotherapy response varying significantly among patients. Emerging evidence suggests that the pulmonary microbiota and metabolome may influence treatment outcomes, but their roles remain unclear. Methods: This study enrolled 25 lung cancer patients undergoing chemotherapy, categorized into chemotherapy-sensitive ( Results: The study identified 92 significantly altered metabolites in BALF between the two groups. Trans-urocanate showed the highest increase, while phenylalanylphenylalanine exhibited the greatest decrease in sensitive patients. Key metabolic pathways, including ABC transporters, glutathione metabolism, and bile acid biosynthesis, were enriched. Microbiome analysis revealed differential abundances of specific bacterial genera, particularly increased Caulobacter and decreased Acinetobacter in sensitive patients. Notably, serum levels of four bile acids (chenodeoxycholic acid, cholic acid, deoxycholic acid, and ursodeoxycholic acid) were significantly elevated in chemotherapy-sensitive patients, demonstrating good predictive value with AUCs ranging from 0.633 to 0.830. Conclusion: The study highlights distinct microbial and metabolic signatures associated with chemotherapy response, suggesting potential biomarkers for personalized therapy.
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