Microbiome signatures associated with clinical stages of gastric Cancer: whole metagenome shotgun sequencing study

Study information

Needs review

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

38658841

DOI Digital object identifier for electronic documents.

https://doi.org/10.1186/s12866-024-03219-2

URI

https://bmcmicrobiol.biomedcentral.com/articles/10.1186/s12866-024-03219-2

Authors

Jeong S, Liao YT, Tsai MH, Wang YK, Wu IC, Liu CJ, Wu MS, Chan TS, Chen MY, Hu PJ, Kao WY, Liu HC, Tsai MJ, Liu CY, Chang CC, Wu DC, Hsu YH

Journal

BMC microbiology

Year

2024

Keywords:

Bacteroides_caccae, Bifidobacterium_longum, Fusobacteria, GLCMANNANAUT-PWY, Lachnospiraceae_bacterium_5_1_63FAA, Streptococcus_anginosus

BACKGROUND: Gastric cancer is one of the global health concerns. A series of studies on the stomach have confirmed the role of the microbiome in shaping gastrointestinal diseases. Delineation of microbiome signatures to distinguish chronic gastritis from gastric cancer will provide a non-invasive preventative and treatment strategy. In this study, we performed whole metagenome shotgun sequencing of fecal samples to enhance the detection of rare bacterial species and increase genome sequence coverage. Additionally, we employed multiple bioinformatics approaches to investigate the potential targets of the microbiome as an indicator of differentiating gastric cancer from chronic gastritis. RESULTS: A total of 65 patients were enrolled, comprising 33 individuals with chronic gastritis and 32 with gastric cancer. Within each group, the chronic gastritis group was sub-grouped into intestinal metaplasia (n = 15) and non-intestinal metaplasia (n = 18); the gastric cancer group, early stage (stages 1 and 2, n = 13) and late stage (stages 3 and 4, n = 19) cancer. No significant differences in alpha and beta diversities were detected among the patient groups. However, in a two-group univariate comparison, higher Fusobacteria abundance was identified in phylum; Fusobacteria presented higher abundance in gastric cancer (LDA scored 4.27, q = 0.041 in LEfSe). Age and sex-adjusted MaAsLin and Random Forest variable of importance (VIMP) analysis in species provided meaningful features; Bacteria_caccae was the most contributing species toward gastric cancer and late-stage cancer (beta:2.43, se:0.891, p:0.008, VIMP score:2.543). In contrast, Bifidobacterium_longum significantly contributed to chronic gastritis (beta:-1.8, se:0.699, p:0.009, VIMP score:1.988). Age, sex, and BMI-adjusted MasAsLin on metabolic pathway analysis showed that GLCMANNANAUT-PWY degradation was higher in gastric cancer and one of the contributing species was Fusobacterium_varium. CONCLUSION: Microbiomes belonging to the pathogenic phylum Fusobacteria and species Bacteroides_caccae and Streptococcus_anginosus can be significant targets for monitoring the progression of gastric cancer. Whereas Bifidobacterium_longum and Lachnospiraceae_bacterium_5_1_63FAA might be protection biomarkers against gastric cancer.

Experiment 1

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Curated date: 2024/07/17

Curator: Shulamite

Revision editor(s): Shulamite

Subjects

Location of subjects: Taiwan

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: Chronic gastritis , Gastric cancer CG - Chronic gastritis,chronic gastritis,chronic gastritis (disease),Chronic gastritis (disorder),Chronic gastritis NOS,Chronic gastritis NOS (disorder),Chronic gastritis, NOS,Erosive Gastritis,Erosive gastropathy (disorder),gastritis,gastritis (disease), chronic,Gastritis (disorder),Gastritis [Ambiguous],GASTRITIS HEMORRHAGIC,Gastritis unspecified (disorder),Hemorrhagic Gastritis,Idiopathic erosive/hemorrhagic gastritis (disorder),Other specified gastritis,Other specified gastritis (disorder),Other specified gastritis NOS (disorder),Other specified gastritis, without mention of hemorrhage,Chronic gastritis,Ca body - stomach,ca greater curvature of stomach,Ca lesser curvature - stomach,cancer of stomach,gastric cancer,gastric cancer, intestinal,gastric neoplasm,malignant gastric neoplasm,malignant gastric tumor,malignant neoplasm of body of stomach,malignant neoplasm of lesser curve of stomach,malignant neoplasm of stomach,malignant neoplasm of the stomach,malignant stomach neoplasm,malignant tumor of body of stomach,malignant tumor of greater curve of stomach,malignant tumor of lesser curve of stomach,malignant tumor of stomach,malignant tumor of the stomach,stomach cancer,Gastric cancer

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Chronic gastritis

Group 1 name Corresponds to the case (exposed) group for case-control studies: Gastric Cancer

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Gastric cancer is one of the major health problems worldwide, ranking fifth in incidence and third in cancer-related mortality, as reported in the latest published global cancer statistics

Group 0 sample size Number of subjects in the control (unexposed) group: 33

Group 1 sample size Number of subjects in the case (exposed) group: 32

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 6 months

Lab analysis

Sequencing type: WMS

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

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: Mann-Whitney (Wilcoxon); LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.041

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 4.27

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, body mass index, sex

Alpha Diversity

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

Signature 1

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Curated date: 2024/07/21

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Source: Table 1

Description: Differential abundance by Wilcoxon Rank-Sum Test between chronic gastritis and gastric cancer in Phylum

Abundance in Group 1: decreased abundance in Gastric Cancer

NCBI	Quality Control	Links
Actinobacillus sp.

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Signature 2

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Source: Table 1

Description: Differential abundance by Wilcoxon Rank-Sum Test between chronic gastritis and gastric cancer in Phylum

Abundance in Group 1: increased abundance in Gastric Cancer

NCBI	Quality Control	Links
Fusobacterium

Revision editor(s): Shulamite

Experiment 2

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Differences from previous experiment shown

Subjects

Location of subjects: Not specified

Host species Species from which microbiome was sampled. Contact us to have more species added.: Not specified

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Not specified

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Not specified

Group 0 name Corresponds to the control (unexposed) group for case-control studies: LEfSe analysis, for the 2-group comparison

Group 1 name Corresponds to the case (exposed) group for case-control studies: Not specified

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Not specified

Group 0 sample size Number of subjects in the control (unexposed) group: Not specified

Group 1 sample size Number of subjects in the case (exposed) group: Not specified

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): Not specified

Lab analysis

Statistical Analysis

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.014

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, sex, Confounders controlled for: "BMI" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.BMI