Analyzing lung cancer risks in patients with impaired pulmonary function through characterization of gut microbiome and metabolites

Study information

Reviewed Marked as Reviewed by Svetlana up on 2024-6-20

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

38166904

DOI Digital object identifier for electronic documents.

10.1186/s12890-023-02825-6

URI

Authors

Luan J, Zhang F, Suo L, Zhang W, Li Y, Yu X, Liu B, Cao H

Journal

BMC pulmonary medicine

Year

2024

Keywords:

Biomarkers, Gut microbiota, Lung cancer, Metabolomics, Pulmonary function

BACKGROUND: Lung cancer (LC) is one of the most devastating diseases worldwide, there is growing studies confirm the role of impaired lung function in LC susceptibility. Moreover, gut microbiota dysbiosis is associated with LC severity. Whether alterations in gut microbiota and metabolites are associated with long-term lung dysfunction in LC patients remain unclear. Our study aimed to analyze the risk factors in LC patients with impaired pulmonary function based on the characteristics of the gut microbiome and metabolites. METHODS: Fecal samples from 55 LC patients and 28 benign pulmonary nodules patients were collected. Pulmonary ventilation function was graded according to the American Thoracic Society/ European Respiratory Society (ATS/ERS) method. LC patients were divided into 3 groups, including 20 patients with normal lung ventilation, 23 patients with mild pulmonary ventilation dysfunction and 12 patients with moderate or above pulmonary ventilation dysfunction. The fecal samples were analyzed using 16 S rRNA gene amplicon sequencing and metabolomics. RESULTS: The gut microbiome composition between LC patients and benign pulmonary nodules patients presented clearly differences based on Partial Least Squares Discriminant Analysis (PLS-DA). Pulmonary ventilation function was positively correlated with LC tumor stage, the richness and diversity of the gut microbiota in LC patients with moderate or above pulmonary ventilation dysfunction increased significantly, characterized by increased abundance of Subdoligranulum and Romboutsia. The metabolomics analysis revealed 69 differential metabolites, which were mainly enriched in beta-Alanine metabolism, styrene degradation and pyrimidine metabolism pathway. The area under the curve (AUC) combining the gut microbiome and metabolites was 90% (95% CI: 79-100%), indicating that the two species and four metabolites might regarded as biomarkers to assess the prediction of LC patients with impaired pulmonary function. CONCLUSIONS: Our results showed that microbiome and metabolomics analyses provide important candidate to be used as clinically diagnostic biomarkers and therapeutic targets related to lung cancer with impaired pulmonary function.

Experiment 1

Edit History Delete

Flag for review

Your review change was submittedDuplicate this Experiment Add a new Signature

Reviewed Marked as Reviewed by Svetlana up on 2024-6-20

Curated date: 2024/03/21

Curator: Omojokunoluwatomisin

Revision editor(s): Omojokunoluwatomisin, Scholastica

Subjects

Location of subjects: China

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Lung cancer alveolar cell carcinoma,cancer of lung,lung cancer,lung cancer, protection against,lung neoplasm,malignant lung neoplasm,malignant lung tumor,malignant neoplasm of lung,malignant neoplasm of the lung,malignant tumor of lung,malignant tumor of the lung,Nonsmall cell lung cancer,Lung cancer

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Benign pulmonary diseases (N group)

Group 1 name Corresponds to the case (exposed) group for case-control studies: Lung cancer (L group)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Lung cancer patients graded according to the American Thoracic Society/ European Respiratory Society (ATS/ERS) five level classification method for pulmonary ventilation impairment and divided into 3 groups, including 20 patients with normal lung ventilation, 23 patients with mild pulmonary ventilation dysfunction and 12 patients with moderate or above pulmonary ventilation dysfunction.

Group 0 sample size Number of subjects in the control (unexposed) group: 28

Group 1 sample size Number of subjects in the case (exposed) group: 55

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 3 months

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: No

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 2

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged

Chao1 Abundance-based estimator of species richness: unchanged

Simpson Estimator of species richness and species evenness: more weight on species evenness: unchanged

Richness Number of species: unchanged

Signature 1

Edit History Delete

Flag for review

Your review change was submitted

Reviewed Marked as Reviewed by Svetlana up on 2024-6-20

Curated date: 2024/03/21

Curator: Omojokunoluwatomisin

Revision editor(s): Omojokunoluwatomisin, Scholastica

Source: figure 2b

Description: Differential taxa at the genus level analyzed by linear discriminant analysis (LDA) scores in lung cancer patients (C) versus benign diseases patients(N)

Abundance in Group 1: increased abundance in Lung cancer (L group)

NCBI	Quality Control	Links
Bacteroides
Oscillospiraceae

Revision editor(s): Omojokunoluwatomisin, Scholastica

Signature 2

Edit History Delete

Flag for review

Your review change was submitted

Reviewed Marked as Reviewed by Svetlana up on 2024-6-20

Curated date: 2024/03/21

Curator: Omojokunoluwatomisin

Revision editor(s): Omojokunoluwatomisin, Scholastica

Source: figure 2b

Description: Differential taxa at the genus level analyzed by linear discriminant analysis (LDA) scores in lung cancer patients (C) versus benign diseases patients(N)

Abundance in Group 1: decreased abundance in Lung cancer (L group)

NCBI	Quality Control	Links
Blautia
Carnobacterium
Coprococcus
Fusicatenibacter
Kurthia
Lachnoanaerobaculum
Propionibacterium
Ruminococcus gauvreauii
Subdoligranulum
unclassified Atopobiaceae
CAG:352CAG:352
Lachnospiraceae ND3007Lachnospiraceae ND3007

Revision editor(s): Omojokunoluwatomisin, Scholastica