Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients

BackgroundLung 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.MethodsThis study...

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Main Authors: Xuehang Jin, Lvjun Zhang, Chiqing Ying, Kailing Pan, Dan Zhu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Microbiology
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Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2025.1604999/full
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author Xuehang Jin
Lvjun Zhang
Chiqing Ying
Kailing Pan
Dan Zhu
author_facet Xuehang Jin
Lvjun Zhang
Chiqing Ying
Kailing Pan
Dan Zhu
author_sort Xuehang Jin
collection DOAJ
description BackgroundLung 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.MethodsThis study enrolled 25 lung cancer patients undergoing chemotherapy, categorized into chemotherapy-sensitive (n = 15) and chemotherapy-insensitive (n = 10) groups. Bronchoalveolar lavage fluid (BALF) was collected for 16S rDNA sequencing and untargeted metabolomics (LC-MS). Serum bile acids were also analyzed.ResultsThe 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.ConclusionThe study highlights distinct microbial and metabolic signatures associated with chemotherapy response, suggesting potential biomarkers for personalized therapy.
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spelling doaj-art-8b7cd6eb377a4a71be10dbc1a7f2287b2025-08-20T02:23:51ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2025-06-011610.3389/fmicb.2025.16049991604999Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patientsXuehang Jin0Lvjun Zhang1Chiqing Ying2Kailing Pan3Dan Zhu4Department of Respiratory and Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, ChinaDepartment of Respiratory and Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, ChinaDepartment of Respiratory and Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, ChinaDepartment of Central Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, ChinaDepartment of Respiratory and Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, ChinaBackgroundLung 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.MethodsThis study enrolled 25 lung cancer patients undergoing chemotherapy, categorized into chemotherapy-sensitive (n = 15) and chemotherapy-insensitive (n = 10) groups. Bronchoalveolar lavage fluid (BALF) was collected for 16S rDNA sequencing and untargeted metabolomics (LC-MS). Serum bile acids were also analyzed.ResultsThe 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.ConclusionThe study highlights distinct microbial and metabolic signatures associated with chemotherapy response, suggesting potential biomarkers for personalized therapy.https://www.frontiersin.org/articles/10.3389/fmicb.2025.1604999/fulllung cancermetabolitemicrobiotachemotherapybiomarker
spellingShingle Xuehang Jin
Lvjun Zhang
Chiqing Ying
Kailing Pan
Dan Zhu
Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
Frontiers in Microbiology
lung cancer
metabolite
microbiota
chemotherapy
biomarker
title Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
title_full Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
title_fullStr Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
title_full_unstemmed Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
title_short Pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
title_sort pulmonary microbiome and metabolome signatures associate with chemotherapy response in lung cancer patients
topic lung cancer
metabolite
microbiota
chemotherapy
biomarker
url https://www.frontiersin.org/articles/10.3389/fmicb.2025.1604999/full
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