Introduction

Although gastric microbiome is suspected to have certain roles in gastric cancer development, the causal relationship is unclear. In particular, there are limited studies focusing on the association between oral and gastric microbiome. We aimed to investigate the association between the oral and gastric microbiome at each stage of gastric carcinogenesis.

Aims & Methods

Saliva, gastric juice, gastric tissue, serum, urine, and feces samples were obtained from 9 healthy adults, 46 low-grade dysplasia (LGD), 25 high-grade dysplasia (HGD), and 27 gastric cancer (GC) patients. Bacteria and bacteria-derived vesicles were extracted from the sample, and metagenome analysis was performed through NGS analysis using the 16S rRNA gene. The similarity between each sample at the stage of disease progression was analyzed using Spearman's rank correlation.

Results

In bacteria extracted from samples, the similarity of microbial composition between saliva and gastric juice increased from 0.18 in the normal group to 0.58, 0.60, and 0.58 in LGD, HGD, and GC group, respectively. Additionally, the similarity of microbial composition between gastric juice and gastric antral tissue increased from 0.30 in the normal group to 0.47 (LGD), 0.48 (HGD), and 0.34 (GC). In the saliva and gastric antral tissue, the similarity between samples also increased in the patient group compared to the normal group. In bacteria-derived vesicle samples, however, this trend of increasing similarity was less pronounced.

Conclusion

As gastric cancer progresses, the similarity of microbiome composition between saliva, gastric juice, and gastric tissue increases. This suggests the possible role of oral commensals in gastric cancer development through interaction with the gastric microbiome.

Introduction

The dysbiosis of the gastric microbiota has been implicated in gastric carcinogenesis. However, previous studies showed a large heterogeneity of the gastric microbiota profiles in various sampling methods which impacted the diagnostic yield. Currently, the specific method for assessing non-Helicobacter pylori microbiota associated with gastric cancer remain unidentified. This study aimed to compare the diagnostic yield of gastric mucosal brushing and conventional biopsy sampling methods to identify gastric microbiota in patients with gastric cancer and controls.

Aims & Methods

This study, conducted from February 2024 to January 2025, included patients with treatment-naive gastric cancer and asymptomatic controls with normal esophagogastroduodenoscopy findings. Paired brushing and biopsy specimens from the non-tumoral area located at the gastric body were analyzed using 16S rRNA sequencing of the V1-V2 region. Microbiota analysis accessed α-diversity (Richness and Shannon index) and β-diversity (Bray-Curtis dissimilarity) between gastric cancer and control groups, and between sampling methods. Differences in α-diversity were tested with the Mann-Whitney U test. The microbial associations with gastric cancer were evaluated with mixed generalized linear mixed models, adjusted for age and sex.

Results

Fifty-eight samples were analyzed, including 18 from the gastric cancer and 40 from the control group. When comparing sampling methods, overall brushing samples showed significantly higher α-diversity than biopsy samples (genus richness 68±54 VS 26±15, p < 0.0001; Shannon index 3.51±0.56 vs. 2.83±0.77, p < 0.0001, respectively). β-diversity of bacterial genera was also significantly different in overall brushing and biopsy samples (PERMANOVA R² = 0.08, p = 0.001). In brush sampling analysis, the gastric cancer group had statistically significant depleted genus richness and Shannon index than controls (45±26 VS 82±51.8, p = 0.01 and 3.22±0.60 VS 3.78±0.52, p = 0.002). β-diversity of bacterial genera significantly differed between the gastric cancer and control groups (PERMANOVA R² = 0.072, p = 0.02). Twenty-two genera, including Veillonella and Propionibacterium exhibited significant differences in abundance.

Conclusion

Gastric mucosal brushing yielded higher bacterial diversity and provided a more comprehensive profile of the gastric microbiota compared to biopsy. The gastric cancer group had a distinct microbiota structure characterized by less diversity and a significantly lower abundance of genus Veillonella which potentially contributed to the gastric cancer-associated microbiota in low prevalence of gastric cancer area.

Introduction

For gastric neoplasms, endoscopic submucosal dissection (ESD) is a well-known therapeutic option. Our study aimed to investigate the influence of procedural volume on the outcome of gastric ESD.

Aims & Methods

Patients who received ESD for gastric cancer or adenoma from November 2011 to December 2017 were identified using the Korean National Health Insurance Service database. The diagnostic and procedure codes were combined to develop operational definitions, which were validated using individual hospital medical record data. Outcomes included bleeding, perforation, pneumonia, 30-day mortality, composite outcome comprising all these adverse outcomes, and additional resection. Hospital volume was categorized into four groups: very high-, high-, low-, very low-volume hospitals (VHVH, HVH, LVH, VLVH). The outcomes of ESD were compared in relation to hospital volume.

Results

A total of 89,780 patients underwent 95,411 procedures during the research period. There were 5,607 composite events, which included 5,098 bleeding, 601 perforation, and 712 pneumonia cases, respectively. Additional resection occurred within 180days in 7,900 cases. There were significant differences in ESD-related adverse outcomes among the four hospital volume categories. Multiple logistic regression revealed that VHVH, HVH, and LVH were associated with lower risk of a composite outcome, when compared to VLVH (OR, 0.627, 95% CI, 0.445-0.885, p=0.008; OR, 0.542, 95% CI, 0.406-0.722, p<0.001; OR, 0.697, 95% CI, 0.548-0.886, p=0.003). Similar tendencies were also shown for bleeding, perforation, and pneumonia, although this was not evident in additional resection.

Conclusion

The procedural volume at an institutional level was closely associated with clinical outcomes, such as bleeding, perforation, pneumonia, and a composite outcome, in patients with ESD for gastric cancer or adenoma. The outcomes of gastric ESD should be closely and systemically monitored in a nationwide level, to ensure the quality of procedures and the safety of patients.

Introduction

Autoimmune atrophic gastritis (AAG) is an immune-mediated disorder characterized by corpus oxyntic mucosa atrophy and impaired gastric acid secretion(1,2). The increased gastric cancer (GC) risk in AAG is still debated. One mechanism favoring gastric carcinogenesis may be increased intragastric pH leading to intragastric microenvironment changes and facilitating bacterial dysbiosis(3-5). Oral microbiota and periodontal-dental disorders alterations have been linked to increased GC risk as well(6-8). In AAG, the increased intragastric pH may lead to survival of swallowed bacteria, possibly further contributing to the increased GC risk. The oral and gastric microbiota composition together have not been investigated so far in AAG patients.

Aims & Methods

The aim of the study was to investigate the oral and gastric microbiota composition in AAGpts in order to clarify the role of oral bacteria in gastric dysbiosis.
We conducted a case-control study: n=20 histologically diagnosed AAGpts(F75%,age 64 yrs) and n=20 ctrs with healthy stomach(HS)(F45%,age 56 yrs). From all pts and ctrs a sputum sample was obtained in the morning fasting without tooth brushing. Within 1 hour after sputum collection, pts and ctrs underwent gastroscopy with biopsies (updated Sydney system) for histopathological assessment and one further corpus biopsy for DNA extraction. Sputum(n=40) and biopsy(n=40) samples were collected in vials with DNA shield and frozen at -20°C since processing. DNA was extracted (QIAmp DNA kit) and prepared (Illumina Nextera XT DNA Library Preparation Kit). Paired-end sequencing was performed (Illumina MiSeq sequencer,MiSeq Reagent Kit v3). Fastq files were filtered to remove low-quality reads; filtered reads were taxonomically classified and subjected to Homo sapiens filtering (METAnnotatorX2 pipeline, up-to-date RefSeq database, NCBI).

Results

AAGpts and ctrs were similar with regard to clinical features, oral hygiene and paraodontal-dental disorders. Bacterial abundance in biopsies was higher in AAGpts than in ctrs (403 vs 223,p=0.06), but not different in sputum (27,728 vs 31,544,p=0.54). On biopsies, AAGpts showed a lower Shannon Index than ctrs (2.553 vs 2.617, p=0.001). On sputum, AAGpts showed a higher Shannon Index than ctrs (2.828 vs 2.738, p=0.0). Beta-diversity (Bray-Curtis dissimilarity) was not different between pts and ctrs, neither in sputum nor biopsies.
At the taxa level, in biopsies Streptococcus oralis, Fusobacterium pseudoperiodonticum, Veillonella rogosae, and Gemella sanguinis were significantly associated with pts(p<0.03); while in sputum the most significant associations were G.sanguinis, Prevotella multisaccharivorax, F.nucleatum, and F.peridonticum(p<0.03). The most abundantly shared taxa between sputum and biopsy were S.oralis and P.histicola, while G.sanguinis, F.pseudoperidonticum, and V.rogosae were shared in pts only.

Conclusion

This study confirmed gastric dysbiosis in AAG as shown by lower biodiversity and evenness. Gastric bacterial abundance was higher in AAG, probably due to non-acidic gastric pH permitting overgrowth of gastric bacteria. Oral bacterial abundance was similar in AAG and ctr with higher biodiversity-evenness in AAG pts, probably due to upstream passage of unactivated bacteria from stomach to mouth. Oral taxa related to increased GC risk were more commonly associated to AAG and shared between mouth and stomach. In AAG these findings show the role of oral microbiota in gastric dysbiosis, possibly contributing to increased GC risk.

References

1) Lenti MV,Rugge M,Lahner E,Miceli E,Toh BH,Genta RM,De Block C,Hershko C,Di Sabatino A. “Autoimmune gastritis” Nat Rev Dis Primers. 2020 Jul 9;6(1):56.
2) Rugge M,Genta RM,Malfertheiner P,Dinis-Ribeiro M,El-Serag H,Graham DY,Kuipers EJ,Leung WK,Park JY,Rokkas T,Schulz C,El-Omar EM;RE.GA.IN;the Real-world Gastritis Initiative-updating the updates. Gut. 2024 Feb 23;73(3):407-441. doi: 10.1136/gutjnl-2023-331164. PMID: 38383142.
3) Conti L, Annibale B, Lahner E. Autoimmune Gastritis and Gastric Microbiota. Microorganisms. 2020;8(11):1827. Published 2020 Nov 19. doi:10.3390/microorganisms8111827
4) Lin L, Li W, Yan L, et al. Comparison of gastric microbiota in patients with different gastric lesions in high and low risk areas of gastric cancer. BMC Microbiol. 2025;25(1):202. Published 2025 Apr 9. doi:10.1186/s12866-025-03926-4
5) Conti L, Borro M, Milani C, et al. Gastric microbiota composition in patients with corpus atrophic gastritis. Dig Liver Dis. 2021;53(12):1580-1587. doi:10.1016/j.dld.2021.05.005
6) Huang C, Li Y, He C. Oral microbes and gastrointestinal cancers: new strategies and insights. Clin Transl Oncol. Published online April 5, 2025. doi:10.1007/s12094-025-03891-4
7) Xia R, Jiang Z, Zhou Y, et al. Oral microbiota and gastric cancer: recent highlights and knowledge gaps. J Oral Microbiol. 2024;16(1):2391640. Published 2024 Aug 16. doi:10.1080/20002297.2024.2391640
8) Aguiar FJN, Menezes FDS, Fagundes MA, et al. Gastric adenocarcinoma and periodontal disease: A systematic review and meta-analysis. Clinics (Sao Paulo). 2024;79:100321. Published 2024 Jan 31. doi:10.1016/j.clinsp.2023.100321

Introduction

Microbiome analysis is a promising approach for the application of findings from basic research in the clinical field. However, there is an ongoing debate about the consistency of different bioinformatics analysis platforms. The lack of established standards affects the implementation of research findings.

Aims & Methods

In our study, we demonstrated that the results on the microbial composition of gastric mucosal biopsies are only slightly influenced by the efficacy of different microbiome analysis platforms. Furthermore, we investigated whether recent revisions to the International Code of Nomenclature for Prokaryotes and consequent alterations in taxonomic classification influenced the findings.
Gastric biopsy specimens were obtained from gastric cancer patients with well-defined clinical profiles (n=40), including individuals with and without Helicobacter pylori (H. pylori) infection, and from control subjects (n=39) with and without H. pylori infection. DNA extraction and 16S rRNA gene sequencing (V1-V2) was performed at one site, and the resulting fastQ files were distributed to five expert teams for independent analysis. Three widely used bioinformatics pipelines for microbiome analysis, namely DADA2, MOTHUR and QIIME2, were used for the analysis.

Results

The generated fastQ files exhibited no platform-dependent clustering, indicating the comparability of the sequences. Microbial diversity was slightly reduced in both GC groups and significantly reduced in the H. pylori positive controls. This is due to an extreme increase in the relative abundance of H. pylori in this group. It also follows that the samples of the H. pylori positive control group have a very high similarity and form the clearest cluster in the corresponding analysis. Regardless of the protocol used, H. pylori status, microbial diversity and relative bacterial abundance were reproducible on all platforms. Although minor differences in performance were detected and assessed, similarity analysis and bacterial enrichment assessment also yielded consistent results. The introduction of the new taxonomy only had a major impact on the Proteobacteria phylum, as it originally also included H. pylori according to the old taxonomy, but this is now assigned to the new Campilobacterota phylum.

Conclusion

In summary, our findings demonstrate that disparate microbiome analysis methodologies employed by independent research teams can yield comparable results from identical datasets.

Introduction

Although an effective and relatively safe procedure, bleeding complications often occur after gastric endoscopic submucosal dissection (ESD). We aimed to comprehensively evaluate the risk factors of post-procedural bleeding following gastric ESD.

Aims & Methods

This study was designed as a nationwide, population-based, retrospective study utilizing the Korean National Health Insurance Service database, comprising patients who underwent gastric ESD for gastric cancer or adenoma from November 2011 to December 2022. Operational definitions were created to identify the target population and post-procedural bleeding using the diagnosis and procedure code, which underwent validation. We established operational definitions to identify the target population and post-procedural bleeding by utilizing diagnosis and procedure codes, which underwent validation. The risk factors analyzed included age, sex, hospital volume, socioeconomic status (SES), histology, lesion numbers, comorbidities, and medication usage.

Results

During the study period, there were 191,932 procedures conducted on 175,779 patients, resulting in 9921 cases of bleeding events. Several factors were associated with increased post-ESD bleeding risk. Following multiple logistic regression, relevant factors with adjusted odds ratios (aORs) were identified. These factors included young age (aOR: 0.990, 95% CI 0.987-0.992), male sex (aOR: 1.377, 95% CI 1.311-1.448), low-volume center compared to high-volume center (aOR: 1.289, 95% CI 1.022-1.621), medical aid compared to the top 25% SES (aOR: 1.307, 95% CI 1.188-1.440), higher Charlson comorbidity index (aOR: 1.040, 95% CI 1.026-1.054), gastric cancer (aOR: 1.369, 95% CI 1.307-1.434), and multiple lesions (aOR: 1.144, 95% CI 1.032-1.267). Furthermore, bleeding risk was significantly higher in groups with several comorbidities and antithrombotic agent users, particularly showing Notably high aORs in groups with renal failure (aOR: 2.086, 95% CI 1.909-2.278), warfarin (aOR: 2.641, 95% CI 2.219-3.143), direct oral anticoagulants (aOR: 2.519, 95% CI 2.220-2.859), and antiplatelet combinations (aOR: 2.073, 95% CI 1.783-2.410).

Conclusion

This study revealed various factors associated with increased bleeding risk after gastric ESD using a large cohort, which could be an important issue in terms of risk stratification and personalized treatment.