From Dysbiosis to Diagnosis: The Role of Gut Microbiota in Breast Cancer Etiology and Management
Abstract
1. Introduction
2. Gut Microbiota: Composition and Functions
2.1. Microbial Composition in a Healthy Human Gut
2.2. Functional Capacities of the Gut Microbiota
2.3. The Estrobolome: Microbial Gatekeeper of Estrogen Homeostasis
3. Dysbiosis: Definition and Mechanisms
3.1. What Is Dysbiosis?
- ▪
- A loss of microbial diversity;
- ▪
- A reduction in beneficial bacteria (e.g., Lactobacillus, Bifidobacterium);
- ▪
- An overgrowth of potentially pathogenic taxa (e.g., E. coli, C. difficile);
- ▪
- A shift in microbial metabolic activity that leads to the production of deleterious compounds.
3.2. Causes of Gut Dysbiosis
3.2.1. Diet
3.2.2. Antibiotic Use
3.2.3. Environmental Toxins
3.2.4. Psychosocial and Physiological Stress
3.3. Consequences of Dysbiosis on Host Physiology
4. Mechanistic Links Between Gut Microbiota and Breast Cancer
4.1. Estrogen Metabolism and the Estrobolome
4.2. Immune System Modulation
4.3. Microbial Metabolites
4.4. Microbiota–Gut–Brain Axis
5. Microbial Signatures of Breast Cancer: Linking Gut Health to Hormonal and Immune Pathways
6. Role of Biotics in Modulating Gut Microbiota
6.1. Probiotics
6.2. Prebiotics
6.3. Synbiotics
6.4. Postbiotics
7. Preclinical and Clinical Evidence on Biotics in Breast Cancer
7.1. Preclinical Evidence: In Vivo and In Vitro Models
7.2. In Vitro Studies
7.3. In Vivo Studies
8. Clinical Studies: From Pilot Trials to Emerging Translational Evidence
9. Safety, Efficacy, and Clinical Translation
10. Limitations and Future Challenges
- Large-scale longitudinal cohorts integrating metagenomics with metabolomics, epigenomics, and host immune profiling to map temporal host-microbe interactions and identify causal pathways.
- Randomized interventional trials testing dietary modulation, probiotics, prebiotics, synbiotics, and fecal microbiota transplantation (FMT) with well-defined clinical endpoints relevant to tumor burden, recurrence, inflammation, and quality of life.
- Mechanistic studies using gnotobiotic models, CRISPR-engineered microbial strains, and metabolite supplementation to delineate causal roles of specific taxa, enzymes (e.g., β-glucuronidase), and microbial metabolites such as SCFAs, secondary bile acids, and indole derivatives.
- Standardization of sequencing methodologies, biotic strain documentation, dosing strategies, and regulatory pathways to enable reproducible science and safe implementation.
11. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Biotic/Intervention | Major Effects on Gut Microbiota | Breast Cancer Relevant Outcomes | Ref. |
|---|---|---|---|
| Lactobacillus (L.) reuteri supplementation | ↑ Lactobacillus abundance; ↓ pro-inflammatory taxa | Suppressed tumor growth; ↑ NK cell activity | [188] |
| Akkermansia muciniphila administration | ↑ Mucus-associated bacteria; improved epithelial integrity | ↓ tumor volume; ↓ systemic inflammation | [189] |
| L. acidophilus | Restored microbial diversity during chemotherapy | Reduced mucositis; better epithelial repair | [190] |
| Inulin prebiotic | ↑ Faecalibacterium & Roseburia; ↑ butyrate | Butyrate-mediated apoptosis; ↓ proliferation markers | [191] |
| Resistant starch diet | ↑ SCFA-producing taxa | ↓ inflammatory cytokines; ↓ tumor viability | [192] |
| Fructooligosaccharides supplementation | ↑ Bifidobacterium; ↓ LPS-producing bacteria | ↓ systemic inflammation; improved immune tone | [193] |
| Synbiotic (L. casei + inulin) | Synergistic increase in SCFA-producing taxa | ↓ β-glucuronidase; ↓ tumor proliferation | [194] |
| Butyrate (postbiotic) | Does not depend on colonization; elevates luminal SCFAs | HDAC inhibition → apoptosis & reduced tumor growth | [195,196] |
| Cell-wall fragments (postbiotic) | Immune activation without live microbes | ↑ NK cell cytotoxicity and apoptosis; ↓ inflammation and proliferation | [197,198] |
| Urolithin-A | Modulates microbial fermentation of ellagic acid | ↓ oxidative stress; ↓ tumor proliferation; induces apoptosis and autophagy | [199] |
| Engineered Bifidobacterium delivering butyrate | Targeted metabolite production | Inhibited tumor growth; enhanced T-cell response | [200] |
| Fecal microbial transplant | Restored microbial diversity in dysbiotic mice | ↓ tumor progression; improved anti-tumor immunity | [201] |
| Biotic/Intervention | Major Effects on Gut Microbiota | Breast Cancer Relevant Outcomes | Ref. |
|---|---|---|---|
| Probiotic yogurt consumption | ↑ Bifidobacterium and Lactobacillus | Lower β-glucuronidase activity; reduced estrogen reactivation potential | [202] |
| Multi-species Lactobacillus (L.) | ↑ Alpha-diversity; ↑ SCFAs | Reduced fatigue; improved sleep & GI well-being | [203] |
| Synbiotic multi-strain + GOS | ↑ microbial richness; ↑ butyrate and Urolithin A | Improved metabolic profile; reduced GI toxicity | [204] |
| Green tea polyphenols | ↑ SCFA-related taxa | ↓ estrogen metabolites; ↓ inflammatory markers | [205] |
| FMT + Immunotherapy | Microbiome reconstruction; ↑ SCFA pathways | Improved immunotherapy response | [206] |
| Synbiotic (multi-species Lactobacillus), 12 weeks | ↑ α-diversity; ↑ butyrate production | ↓ chemotherapy side effects; ↑ QoL and ↓ fatigue | [207] |
| Multispecies probiotic (L. acidophilus, B. bifidum, S. thermophilus) during chemotherapy | ↑ diversity | ↓ GI toxicity; ↑ peripheral NK activity (immunostimulant) | [208] |
| L. casei Shirota (Yakult) + soy isoflavones | Converse the soy isoflavones to some active metabolites like equol | ↓ systemic inflammation markers; lower neutropenia incidence (related clinical context) | [209] |
| Whole-food, plant-based diet | ↑ SCFA-supporting taxa expected; feasibility data | ↓ body weight, serum insulin, essential and non-essential amino acids and IGF | [210] |
| High dietary fiber intake | Supports SCFA producers | ↓ β-glucuronidase activity (mechanistic rationale) | [211] |
| Baseline gut microbiome and cancer-related fatigue | Microbiota profiles associated with symptom burden | Microbiome mediates dietary quality–fatigue | [212] |
| Baseline α-diversity → chemo GI symptoms | α-diversity predictive of GI symptom severity | Microbiome predicts treatment tolerability | [213] |
| IgA-coated vs non-coated microbiota in postmenopausal BC | Distinct IgA-coating patterns; altered taxa profiles | Links to estrogen milieu in postmenopausal BC | [214] |
| Dietary plant-based intervention in BC survivors | ↑ F. prausnitzii & A. muciniphila; improved estrogen metabolite ratios (↑ 2-OHE1:16α-OHE1) | Suggests enhanced estrogen detoxification & favorable host–microbe shifts | [215] |
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Mishra, P.; Mishra, S.P.; Pattnaik, A.; Singh, S.; Shakri, A.R.; Badhai, J.; Ganguly, S.; Guria, A.; Cheekatla, S.S. From Dysbiosis to Diagnosis: The Role of Gut Microbiota in Breast Cancer Etiology and Management. Appl. Microbiol. 2025, 5, 134. https://doi.org/10.3390/applmicrobiol5040134
Mishra P, Mishra SP, Pattnaik A, Singh S, Shakri AR, Badhai J, Ganguly S, Guria A, Cheekatla SS. From Dysbiosis to Diagnosis: The Role of Gut Microbiota in Breast Cancer Etiology and Management. Applied Microbiology. 2025; 5(4):134. https://doi.org/10.3390/applmicrobiol5040134
Chicago/Turabian StyleMishra, Priyanka, Sidharth P. Mishra, Aryamav Pattnaik, Swoyam Singh, Ahmad R. Shakri, Jhasketan Badhai, Soumyajit Ganguly, Ashirbad Guria, and Satyanarayana S. Cheekatla. 2025. "From Dysbiosis to Diagnosis: The Role of Gut Microbiota in Breast Cancer Etiology and Management" Applied Microbiology 5, no. 4: 134. https://doi.org/10.3390/applmicrobiol5040134
APA StyleMishra, P., Mishra, S. P., Pattnaik, A., Singh, S., Shakri, A. R., Badhai, J., Ganguly, S., Guria, A., & Cheekatla, S. S. (2025). From Dysbiosis to Diagnosis: The Role of Gut Microbiota in Breast Cancer Etiology and Management. Applied Microbiology, 5(4), 134. https://doi.org/10.3390/applmicrobiol5040134

