Evidence map›Paper›PMID 39794303›Full record

ArticleClinical and translational medicine2025

Lower respiratory tract microbiome dysbiosis impairs clinical responses to immune checkpoint blockade in advanced non-small-cell lung cancer.

Yong Zhang, Xiang-Xiang Chen, Ruo Chen, Ling Li, Qing Ju, Dan Qiu, Yuan Wang, Peng-Yu Jing, Ning Chang, Min Wang and 3 more

Abstract read
In one paragraph

Article in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. The Immune Checkpoint Inhibitors Journey: From Early Promise to Lasting Impact.Journal of immunotherapy and precision oncology · 2026
    Review
  2. Microbiome and cancer immunotherapy: a bibliometric analysis.Journal of the Egyptian National Cancer Institute · 2026
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yong Zhang *Department of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Xiang-Xiang Chen *Department of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Ruo Chen *Department of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Ling LiDepartment of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Qing JuDepartment of Pulmonary and Critical Care of Medicine, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Dan QiuDepartment of Pulmonary and Critical Care of Medicine, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Yuan WangDepartment of Microbiology, School of Basic Medicine, Fourth Military Medical University, Xi'an, China.
Peng-Yu JingDepartment of Thoracic Surgery, The Second Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Ning ChangDepartment of Pulmonary and Critical Care of Medicine, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Min WangDepartment of Pulmonary and Critical Care of Medicine, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Jian ZhangDepartment of Pulmonary and Critical Care of Medicine, The First Affiliated Hospital of Fourth Military Medical University, Xi'an, China.
Zhi-Nan ChenDepartment of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Ke WangDepartment of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.ORCID 0000-0001-8913-7115

Funding

Clinical Booster Project of Fourth Military Medical University 2021LC2115National Natural Science Foundation of China 82273226National Natural Science Foundation of China 82473215Young Elite Scientist Sponsorship Program by China Association for Science and Technology 2020QNRC001
6 · The paper itself

Abstract

backgroundGut microbiome on predicting clinical responses to immune checkpoint inhibitors (ICIs) has been discussed in detail for decades, while microecological features of the lower respiratory tract within advanced non-small-cell lung cancer (NSCLC) are still relatively vague.

methodsDuring this study, 26 bronchoalveolar lavage fluids (BALF) from advanced NSCLC participants who received immune checkpoint inhibitor monotherapy were performed 16S rRNA sequencing and untargeted metabolome sequencing to identify differentially abundant microbes and metabolic characteristics. Additionally, inflammatory cytokines and chemokines were also launched in paired BALF and serum samples by immunoassays to uncover their underlying correlations. The omics data were separately analyzed and integrated by using multiple correlation coefficients. Multiplex immunohistochemical staining was then used to assess the immune cell infiltration after immune checkpoint blockade therapy.

resultsLower respiratory tract microbiome diversity favoured preferred responses to ICIs. Microbial markers demonstrated microbial diversity overweight a single strain in favoured response to ICI therapy, where Bacillus matters. Sphingomonas and Sediminibacterium were liable to remodulate lipid and essential amino acid degradations to embrace progression after immunotherapies. Microbiome-derived metabolites reshaped the immune microenvironment in the lower respiratory tract by releasing inflammatory cytokines and chemokines, which was partially achieved by metabolite-mediated tumoral inflammatory products and reduction of CD8

conclusionsThis study provided a microecological landscape of the lower respiratory tract with advanced NSCLC to ICI interventions and presented a multidimensional perspective with favoured outcomes that may improve the predictive capacity of the localized microbiome in clinical practices. HIGHLIGHTS: Alterations of the lower respiratory tract microbiome indicate different clinical responses to ICB within advanced NSCLC. Reduced microbial diversity of lower respiratory tracts impairs anti-tumoral performances. Microbe-derived metabolites perform as a dominant regulator to remodify the microecological environment in lower respiratory tracts. Multi-omics sequencings of the lower respiratory tract possess the potential to predict the long-term clinical responses to ICB among advanced NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungDysbiosisImmune Checkpoint InhibitorsLung NeoplasmsAgedBronchoalveolar Lavage FluidFemaleHumansMaleMicrobiotaMiddle AgedImmune Checkpoint Inhibitorsadvanced non‐small‐cell lung cancerclinical outcomesimmune checkpoint blockade therapylower respiratory tract microbiomemulti‐omics analysis

Identifiers

PMID39794303
PMCPMC11726686

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.