Gastric Cancer and Microbiota: Exploring the Microbiome’s Role in Carcinogenesis and Treatment Strategies
Abstract
1. Introduction
2. Helicobacter Pylori and the Gastric Microbiome
2.1. Role of H. Pylori in Gastric Carcinogenesis and the Microbial Dysbiosis Triggered by This Bacterium
2.2. Synergistic and Antagonistic Interactions with Other Microbes
3. Gastric Microbiota Alterations in Carcinogenesis
3.1. Microbiota Composition in Precancerous and Cancerous Lesions
3.2. Fungal Microbiota and Bacterial–Fungal Interactions
4. Microbial Metabolites and Oncogenic Pathways
4.1. Key Microbial Metabolites
4.2. Metabolite-Induced Signaling in Cancer Cell Proliferation and Inflammation–the Role of Specific Metabolites as Diagnostic and Prognostic Markers
5. Oral and Gut Microbiota: Peripheral Players with Central Roles
5.1. Impact of Oral Microbiota Translocation to the Stomach
5.2. The Salivary Microbiota as a Diagnostic Avenue
5.3. The Digestive Tract Microbiota’s Systemic Immunoregulatory Effects
6. Microbiota, Immunity, and Therapy Response
6.1. Impact of Microbiota on Immunotherapy Outcomes
6.2. Strategies to Modulate Microbiota to Enhance Therapeutic Response
7. Clinical Perspectives and Future Directions
7.1. Clinical Aspects
7.2. Future Perspectives
7.3. Microbiome-Based Clinical Trials
8. Conclusions
- Longitudinal studies tracking microbiota changes from precancerous lesions to advanced GC to establish causal relationships and microbial signatures predictive of progression;
- Functional microbiome analyses (metatranscriptomics, metabolomics) to elucidate the active metabolic pathways driving carcinogenesis;
- Identification of microbial-derived biomarkers for early diagnosis, prognosis, and treatment stratification;
- Integration of microbiome data into personalized medicine frameworks, particularly for immunotherapy responsiveness prediction;
- Investigation of microbial–host immune interactions, including the role of microbiota in programming tissue-resident memory T cells and shaping the tumor immune landscape.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
GC | Gastric cancer |
WHO | World Health Organization |
IARC | International Agency for Research on Cancer |
CNS | Central nervous system |
FMT | Fecal microbiota transplantation |
MDIs | Microbial dysbiosis indices |
CAG | Chronic atrophic gastritis |
ROS | Reactive oxygen species |
RNS | Reactive nitrogen species |
PTEN | Phosphatase and tensin homologue |
VEGF | Vascular endothelial growth factor |
MNU | N-Methyl-N-nitrosoureas |
SCFAs | Short-chain fatty acids |
HDAC | Histone deacetylase |
TME | Tumor microenvironment |
NK | Natural killer cells |
DCA | Deoxycholic acid |
COX | Cyclooxygenase |
DFMO | α-difluoromethylornithine |
PUFAs | ω-6 polyunsaturated fatty acids |
PGE2 | Prostaglandin E2 |
LPS | Lipopolysaccharide |
PAMPs | Pathogen-associated molecular patterns |
TLRs | Toll-like receptors |
GPCRs | G-protein-coupled receptors |
GC/MS | Gas chromatography/mass spectrometry |
LC-MS | Liquid chromatography/mass spectrometry |
NMR | Nuclear magnetic resonance spectroscopy |
TCA | Tricarboxylic acid |
GI | Gastrointestinal |
PPIs | Proton pump inhibitors |
OSCC | Oral squamous cell carcinoma |
IBD | Inflammatory bowel disease |
PRRs | Pathogen recognition receptors |
TAMs | Tumor-associated macrophages |
MDSCs | Myeloid-derived suppressor cells |
Tregs | Regulatory T cells |
pDCs | Plasmacytoid dendritic cells |
ICIs | Immune checkpoint inhibitors |
IECs | Intestinal epithelial cells |
MHC | Major histocompatibility complex class II molecules |
TRM | Tissue-resident memory T cells |
NAFLD | Nonalcoholic fatty liver disease |
ESMO | European Society of Medical Oncology |
CSCO | Chinese Society of Clinical Oncology |
MSI-H | Microsatellite instability-high |
EMA | European Medicines Agency |
FDA | Food and Drug Administration |
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Model | Biological System | Study Objective | Key Findings | Ref. |
---|---|---|---|---|
Human clinical observational study | Human gastric mucosal biopsies obtained via endoscopic procedures from 47 patients at various stages of gastric disease: SG (superficial gastritis), AG (atrophic gastritis), GIN (gastric intraepithelial neoplasia), GC (gastric cancer). Human gastric microbiota analyzed using 16S rRNA gene sequencing (targeting regions V3–V4). | To characterize alterations in gastric microbiota associated with different stages of gastric carcinogenesis, identify potential biomarkers, and compare microbiota profiles between cardia and non-cardia gastric cancers. | The study suggested potential microbial biomarkers for early detection. No significant trend in overall microbial richness or diversity across stages. The Shannon index was higher in GIN compared to other groups. The top dominant phyla included Firmicutes, Proteobacteria, Bacteroidetes, Fusobacteria, and Actinobacteria. Enrichment of oral bacteria (e.g., Slackia, Selenomonas) increased progressively from gastritis to GC, which may suggest oral flora involvement. Microbiota profiles differed significantly in cardia vs. non-cardia gastric cancer, with higher Helicobacter abundance in cardia cancers. | [38] |
Human clinical comparative study | Gastric non-malignant and tumor tissue samples from GC patients in China (cardia) and Mexico (non-cardia). | To characterize the human stomach microbiota in gastric cancer patients, compare microbiota between non-malignant and tumor tissues, and assess microbial differences across populations and tissue types. | Microbial diversity and richness were significantly higher in tumor tissues compared to non-tumor tissues. Helicobacter was enriched in non-tumor tissues; Lactobacillus, Streptococcus, Acinetobacter, Prevotella, and six additional genera were enriched in tumor tissues. Untargeted metabolomics identified 150 discriminative metabolites with higher relative abundance of amino acids, carbohydrates and carbohydrate conjugates, glycerophospholipids, and nucleosides in tumor tissues. Targeted metabolomics revealed that 1-methylnicotinamide and N-acetyl-D-glucosamine-6-phosphate combined serve as robust biomarkers for distinguishing tumor from non-tumor tissue. Correlations suggest that specific bacteria like Helicobacter and Lactobacillus influence the tumor metabolome, potentially promoting gastric cancer development. | [267] |
Human clinical study | Human salivary microbiota characterized through 16S rRNA gene sequencing; a total of 293 patients undergoing endoscopic examination grouped into superficial gastritis (SG), atrophic gastritis (AG), and gastric cancer (GC) stages. | To characterize salivary microbiota changes across progressive stages of gastric carcinogenesis and identify saliva bacterial markers that can be used to detect gastric cancer. | Distinct salivary microbiota profile observed in GC patients with enrichment of proinflammatory taxa, such as Corynebacterium and Streptococcus. Reduction of bacteria that reduce carcinogenic N-nitroso compounds (e.g., Haemophilus, Neisseria) in GC. Salivary microbiota profiles distinguished GC from SG and AG with high accuracy (AUC = 0.91). Potential diagnostic biomarkers identified among taxa like unclassified Streptophyta and Streptococcus. Proposed mechanisms include the accumulation of proinflammatory bacteria and a decline in bacteria that reduce carcinogens, contributing to gastric carcinogenesis. | [150] |
Human clinical study (retrospective cohort study) | Gastric mucosal microbiota from patients with gastric cancer (tissues: normal, peritumoral, tumoral). | To investigate the prognostic value of gastric mucosal microbiota in different stomach microhabitats of gastric cancer patients. | Patients with different prognoses showed distinct gastric microbiota compositions and diversity. In peritumoral microhabitats, Helicobacter abundance was higher in patients with good prognoses, while Halomonas and Shewanella were lower. The gastric microbiota association network was more complex in patients with poor prognoses. Predicted microbiota functions varied by microhabitat, notably in peritumoral tissues. Gastric mucosal microbiota alterations may serve as prognostic biomarkers for clinical outcomes in gastric cancer. | [268] |
Human clinical study | Human gastric mucosa biopsy samples from 18 gastric cancer (GC) patients and 32 superficial gastritis (SG) patients. Paired tumor and paracancerous tissue samples were collected from GC patients. 16S rRNA gene sequencing for bacterial profiling. | To investigate and compare the gastric mucosal microbiome composition in GC patients and SG patients, assessing differences in bacterial diversity, specific taxa abundance, and predictive functional profiles. To evaluate the microbial dysbiosis index (MDI) as a discriminant metric for gastric-cancer-associated dysbiosis. | GC patients exhibit distinct gastric microbiome profiles compared to SG patients, with significant microbial dysbiosis evident in both tumor and paracancerous tissues. Six bacterial genera were enriched and eighteen were depleted in GC tissues relative to SG. The microbial dysbiosis index (MDI) was significantly higher in GC patients, negatively correlated with microbial diversity (Shannon index), and positively correlated with Helicobacter spp. abundance. Functional predictions suggest nitrosating microbial community enrichment in GC patients, implicating microbial metabolism in carcinogenesis. The microbiome differences in GC patients are not limited to tumor sites but also present in adjacent normal tissue, suggesting early microbiome changes in gastric carcinogenesis. | [269] |
Human clinical study (case-control study) | Human stomach gastric microbiota in a Korean population involving 556 participants (268 gastric cancer patients and 288 controls). DNA extracted from gastric biopsy samples was analyzed using 16S rRNA gene sequencing to characterize gastric microbiota composition. | The study focused on identifying the relative abundance of specific bacterial species in the gastric mucosa and their association with gastric cancer risk. | Higher relative abundance of Helicobacter pylori, Propionibacterium acnes, and Prevotella copri was significantly associated with increased gastric cancer risk. Higher relative abundance of Lactococcus lactis was associated with decreased gastric cancer risk. These bacterial species combined predicted gastric cancer with about 79.7% sensitivity. The study supports microbial profiles as potential diagnostic markers for gastric cancer risk in Koreans. | [270] |
Human clinical study | The study involved 227 participants, including 83 gastric cancer patients, 54 gastritis patients, 29 colorectal cancer patients, and 61 healthy controls. Human gut microbiota analyzed via 16S rRNA gene sequencing of fecal samples. | To investigate alterations in gut microbiota composition during gastric cancer progression and evaluate the gut microbiome as a non-invasive predictive marker for gastric cancer diagnosis. | Gut microbiota composition and diversity significantly differ between gastric cancer patients and healthy controls. Random forest model using microbial taxa classified gastric cancer with an AUC of 0.91 and a true positive rate of 0.83 in validation. Gastritis shares some microbiome features with gastric cancer. Chemotherapy reduces microbial abundance and diversity in gastric cancer patients. The genera Lactobacillus and Megasphaera are significantly associated with gastric cancer and serve as predictive markers. | [271] |
Retrospective clinical cohort study | Human gastric cancer patients were classified by body mass index (BMI), specifically low BMI (LBMI) and non-low BMI (NLBMI) groups. Tumor tissues and adjacent normal tissues from these patients were analyzed for intratumoral microbiota, immune cell infiltration, gene expression, and metabolite profiling. | To investigate how BMI relates to intratumoral microbiota and the tumor microenvironment in gastric cancer patients and to identify specific microbial features associated with prognosis in low-BMI patients. | GC patients with low BMI had poorer clinical outcomes and pathological features, and low BMI was an independent risk factor for poor prognosis. 16S rRNA microbial diversity was similar between BMI groups, but 32 bacterial taxa differed, with the genus Abiotrophia significantly enriched in LBMI tumors. Abiotrophia was negatively correlated with eosinophils and certain genes and positively correlated with others in LBMI tumors. LBMI was linked with increased purine metabolites (guanine, IDP). Low BMI may suppress immune responses and affect chemotherapy efficacy, possibly via changes in intratumoral microbiota and metabolism. | [272] |
Human clinical study | Human gastric tissue biopsies from patients with gastritis, intestinal metaplasia, and gastric cancer. | To profile and compare the gastric-epithelium-associated bacterial species among patients with gastritis, intestinal metaplasia, and gastric cancer, aiming to identify additional potential pathogenic bacteria beyond Helicobacter pylori. | Helicobacter pylori abundance significantly decreased in gastric cancer patients compared to non-cancer patients. Clostridium (notably Clostridium colicanis), Fusobacterium (notably Fusobacterium nucleatum), and Lactobacillus species were enriched in gastric cancer tissues. Clostridium and Fusobacterium may serve as diagnostic markers for gastric cancer. The gastric microbiota’s composition differs significantly between cancer and non-cancer groups, suggesting a cancer-specific bacterial signature. | [273] |
Human subjects: 30 gastric cancer patients and 30 healthy controls. Intestinal microbiota analyzed through fecal samples using 16S rRNA gene sequencing technology. | To explore and analyze the composition and characteristics of intestinal microbiota differences between gastric cancer patients and healthy people and to identify specific bacteria associated with gastric cancer. | No significant difference in overall diversity and abundance of intestinal flora between groups. Significant decrease in Faecalibacterium, Bifidobacterium, and Subdoligranulum in gastric cancer patients. Significant increase in Enterococcus, Streptococcus, and Bacteroides in gastric cancer patients. Identified six key intestinal bacterial genera closely related to gastric cancer. Functional pathways enriched in gastric cancer patients’ gut flora include two-component systems, glycolysis/gluconeogenesis, transporters, and others. | [274] |
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Lazăr, D.-C.; Chiriac, S.-D.; Drăghici, G.-A.; Moacă, E.-A.; Faur, A.C.; Avram, M.-F.; Turi, V.-R.; Nicolin, M.-R.; Goldiș, A.; Salehi, M.A.; et al. Gastric Cancer and Microbiota: Exploring the Microbiome’s Role in Carcinogenesis and Treatment Strategies. Life 2025, 15, 999. https://doi.org/10.3390/life15070999
Lazăr D-C, Chiriac S-D, Drăghici G-A, Moacă E-A, Faur AC, Avram M-F, Turi V-R, Nicolin M-R, Goldiș A, Salehi MA, et al. Gastric Cancer and Microbiota: Exploring the Microbiome’s Role in Carcinogenesis and Treatment Strategies. Life. 2025; 15(7):999. https://doi.org/10.3390/life15070999
Chicago/Turabian StyleLazăr, Daniela-Cornelia, Sorin-Dan Chiriac, George-Andrei Drăghici, Elena-Alina Moacă, Alexandra Corina Faur, Mihaela-Flavia Avram, Vladiana-Romina Turi, Mihaela-Roxana Nicolin, Adrian Goldiș, Matin Asad Salehi, and et al. 2025. "Gastric Cancer and Microbiota: Exploring the Microbiome’s Role in Carcinogenesis and Treatment Strategies" Life 15, no. 7: 999. https://doi.org/10.3390/life15070999
APA StyleLazăr, D.-C., Chiriac, S.-D., Drăghici, G.-A., Moacă, E.-A., Faur, A. C., Avram, M.-F., Turi, V.-R., Nicolin, M.-R., Goldiș, A., Salehi, M. A., & Jipa, R. (2025). Gastric Cancer and Microbiota: Exploring the Microbiome’s Role in Carcinogenesis and Treatment Strategies. Life, 15(7), 999. https://doi.org/10.3390/life15070999