The Gut Microbiota-Ovarian Cancer Axis: Mechanisms of Influence and Therapeutic Implications.

Introduction
Ovarian cancer (OC) is a leading cause of gynecological cancer mortality, with an incidence second only to cervical cancer and accounting for approximately 200,000 annual deaths globally.
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Epithelial carcinoma is the predominant histological subtype, followed by malignant germ cell tumors.
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The pathophysiology of OC remains incompletely understood. Epidemiological evidence indicates reduced OC risk with oral contraceptive use,
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multiparity,
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and prolonged breastfeeding,
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whereas nulliparity,
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early menarche,
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and late menopause
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are associated with elevated incidence. This pattern suggests a positive correlation between lifetime ovulatory cycles and OC risk. Additional risk factors include genetic predisposition, chronic inflammation, estrogen exposure, epigenetic modifications, and obesity (Figure 1). Alarmingly, approximately 70% of patients experience recurrence or metastasis within three years of initial treatment, contributing to a five-year survival rate below 50% and severely compromised quality of life.
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In response, researchers are actively exploring novel avenues for intervention. The human gut harbors an immensely complex ecosystem—the GM—comprising bacteria, fungi, archaea, protists, and viruses. This community encompasses up to 100 trillion microorganisms,
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with Bacteroidetes and Firmicutes constituting approximately 90% of the total population.
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GM homeostasis maintains intestinal barrier integrity, internal environmental stability, immune-endocrine modulation, and pathogen defense, thereby supporting host physiology.
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Dysbiosis has been linked to numerous diseases, including obesity,
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diabetes,
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and inflammatory bowel disease.
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The potential association between GM dysregulation and carcinogenesis has emerged as a major research focus. Advances in sequencing technologies have facilitated deeper investigation into this relationship. Probiotics and specific OC-associated microbes are now considered promising candidates for novel OC prevention and treatment strategies. Dysbiosis disrupts intestinal epithelial homeostasis, potentially promoting carcinogenesis.
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Substantial evidence indicates that GM influences the TME via microbial metabolites, immunomodulation, and inflammatory responses. Thus, elucidating GM-OC interactions is crucial for understanding disease pathophysiology and identifying new therapeutic targets and diagnostic biomarkers.
This review provides a comprehensive overview of the pivotal role of the GM in the pathogenesis, progression, and treatment of OC. First, we delineate the mechanisms through which the GM influences OC development via three primary pathways: modulation of the tumor microenvironment, interference with estrogen metabolism, and production of specific microbial metabolites. Next, we systematically consolidate evidence on how the GM affects the efficacy of chemotherapy, immunotherapy, and targeted therapy. Finally, we critically discuss current challenges and future directions in developing microbiota-based precision medicine strategies, with the aim of translating these approaches from bench to bedside.

Alterations in Gut Microbiota in Ovarian Cancer
The GM of OC patients exhibits significant dysbiosis, with compositional and functional changes reflecting tumor progression (Table 1). PathoChip analysis detected elevated Proteobacteria and Firmicutes in OC tissues.
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Specific Firmicutes genera, including Abiotrophia, Bacillus, Enterococcus, Erysipelothrix, Geobacillus, Lactobacillus, Lactococcus, Listeria, Pediococcus, Peptoniphilus, and Staphylococcus, are enriched in tumor samples.
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Alpha, beta, and gamma diversity metrics are commonly used in microbiome studies. At the population level, GM composition exhibits sex-specific differences. Females demonstrate higher alpha diversity indices (Chao and Shannon) due to interactions between sex hormones and the microbiota.
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High-throughput sequencing revealed significantly reduced alpha diversity in OC patients versus healthy controls (n = 20), measured by Chao1 (community richness; p = 0.0028) and Shannon (species diversity; p = 0.026) indices. The genus-level analysis suggested that EOC decreased the relative abundance of the beneficial bacteria Bifidobacterium and Ruminococcaceae_Ruminococcus and increased the relative abundance of Bacteroides and Prevotella in the OC tissues.
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These alterations manifest as reduced microbial diversity, enrichment of pathogenic genera, and depletion of beneficial taxa. For example, 16S rRNA sequencing revealed increased Escherichia-Shigella abundance and decreased Coprococcus and Faecalibacterium in OC patients, alongside elevated pro-inflammatory bacteria such as Ruminococcus gnavus.
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These findings highlight the GM's potential as a cancer biomarker and offer new perspectives for OC diagnosis. Dynamic GM changes may serve as prognostic indicators, and diagnostic models based on microbial signatures show clinical promise. This stems from complex inter-microbial interactions that correlate microbiota profiles with clinical traits. Chen et al
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employed machine learning to identify differentially abundant gut taxa in OC patients, integrating clinical indicators into a non-invasive diagnostic model.
Although multiple studies have sought to characterize GM features associated with OC, the reported findings remain inconsistent. For example, while one study noted a significant decrease in Firmicutes,
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others have observed an increase in its abundance. These discrepancies may stem from geographical and dietary differences across cohorts, limited sample sizes that reduce statistical power, and a lack of methodological standardization. Methodologically, most studies have employed 16S rRNA gene sequencing, which provides resolution only to the genus level and may miss species- or strain-specific effects that could exert opposing roles in cancer progression. Moreover, while many studies assess the potential benefit of GM by comparing relative abundance between healthy individuals and patients, mechanistic investigations are required to reliably determine the role of GM in OC development. Thus, current evidence points to a state of GM dysbiosis rather than consistent taxonomic shifts, underscoring the need for larger, multi-center studies with standardized protocols.

Mechanistic Influence of Gut Microbiota on Ovarian Cancer Pathogenesis

Modulation of the Tumor Microenvironment (TME)
The TME is a hypoxic, acidic niche surrounding tumor cells, optimized for their survival. It comprises the extracellular matrix (ECM), stromal cells, vascular endothelium, mesenchymal cells, adipocytes, and immune infiltrates.
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Substantial evidence indicates that the TME critically regulates tumor proliferation, migration, and apoptosis.25,26 Infiltrating immune cells constitute the predominant non-tumor component, whose function—modulated by diverse factors—can shift from anti-tumor to pro-tumor activity, facilitating migration, invasion, and angiogenesis.
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Targeting these cells represents a promising therapeutic strategy. As the body's largest immunological organ, the gut is intricately linked to immune regulation and microbiota-mediated TME modification.
Gut dysbiosis promotes polarization of tumor-associated macrophages (TAMs) toward the immunosuppressive M2 phenotype,28,29 associated with poor OC prognosis. M2 TAM activation elevates systemic IL-6 and TNF-α levels, facilitating epithelial-mesenchymal transition (EMT) in OC.
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Fusobacterium nucleatum impairs NK cell cytotoxicity via TIGIT receptor binding, enabling immune evasion.
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Additionally, Clostridium induces regulatory T-cell accumulation and modulates immune homeostasis in murine models.
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OC patients exhibit reduced Akkermansia abundance—a commensal bacterium critical for intestinal barrier integrity—associated with increased intestinal permeability and impaired immune surveillance. Remarkably, Akkermansia supplementation reversed tumor progression in OC-bearing mice by enhancing gut barrier function and activating CD8+ T cells.
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However, critical limitations of these models must be considered when translating these findings to humans. The murine immune system and gut physiology differ substantially from humans, and the simplified, controlled conditions of laboratory settings cannot fully replicate the complex human exposome. Therefore, while these models offer valuable proof-of-concept insights, their ability to predict therapeutic responses in humans must be validated in clinical studies.

Regulation of Estrogen Bioavailability
Sustained estrogen exposure is a well-established OC risk factor.
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Women with the highest circulating estradiol levels exhibit a threefold increased OC risk versus those with the lowest levels. Menopausal estrogen therapy (≥5 years) confers sustained risk elevation even after cessation.
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The GM functions as an endocrine regulatory organ, modulating estrogen bioavailability via enzymatic systems. A key mechanism is β-glucuronidase (β-GUS)-dependent enterohepatic recirculation: Liver-conjugated estrogen glucuronides are excreted into the gut, where bacterial β-GUS (Bacteroides, Clostridium, and Lactobacillus spp.) hydrolyzes them, releasing bioactive estrogens (eg, estradiol/E2) for systemic reabsorption.
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Reactivated estrogens bind estrogen receptors α (ERα) and β (ERβ)
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; (Figure 2). Excessive β-GUS activity may promote carcinogenesis via genotoxin production.
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Probiotics and prebiotics may reduce estrogen levels and prevent OC by inhibiting intestinal β-GUS; specific Lactobacillus strains reduced β-GUS expression and mitigated irinotecan toxicity in mice.
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Thus, microbial estrogen recycling positions the GM as a pivotal regulator of systemic estrogen levels influencing OC risk.

Impact of Gut Microbiota Metabolites on Ovarian Cancer
Gut microbial components and metabolites enter systemic circulation, inducing local and distant effects that alter the host microenvironment.
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The GM regulates OC through metabolite networks. Gut-derived lipopolysaccharide (LPS) binds Toll-like receptor 4 (TLR4), triggering NF-κB activation and pro-inflammatory cytokine release (eg, TNFα, IL-1, IL-6).
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LPS also stimulates matrix metalloproteinase (MMP) production and PI3 K signaling, activating TAMs and inducing EMT.
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MAPK pathway activation by LPS enhances OC cell proliferation, migration, and invasion.
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Tryptophan metabolites (indole derivatives) primarily activate the aryl hydrocarbon receptor (AHR) and pregnane X receptor (PXR).44,45 In OC models, AHR triggers the pro-tumorigenic PI3 K/Akt pathway.
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Co-expression of AHR and follicle-stimulating hormone receptor (FSHR) correlates with poor OC prognosis.
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Ascites-enriched lysophosphatidylinositol sustains pro-survival PI3 K/Akt/mTOR signaling. Elevated Firmicutes- and Bacteroidetes-derived lysophosphatidylcholine (LPC 18:1) in OC ascites suggests its role in progression.
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Dietary fiber fermentation yields short-chain fatty acids (SCFAs: acetate ≈ 60%, propionate ≈ 25%, butyrate ≈ 15%), key host energy sources.49,50 SCFAs modulate inflammation through G protein-coupled receptors (GPR41/43/109A) and histone deacetylase (HDAC) inhibition. Receptor activation suppresses NF-κB and MAPK signaling, reducing pro-inflammatory cytokines.
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Butyrate inhibits tumor growth via HDAC inhibition, enhancing histone acetylation at the ID2 locus and upregulating CD8+ T cells in murine models.
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Thus, butyrate supplementation potentiates anti-tumor efficacy.
Obesity increases OC risk.
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Adipocytes within the TME promote omental metastasis and fuel tumor proliferation.
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The GM-adipocyte axis is experimentally validated: fecal microbiota transplantation (FMT) from normal to germ-free mice increased adiposity via enhanced monosaccharide absorption and lipogenesis.
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SCFAs activate GPR41/43, suppressing fat accumulation and maintaining metabolic homeostasis.
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However, in contrast to these beneficial roles, butyrate has also been shown to exert immunosuppressive effects by inhibiting dendritic cell maturation.
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This functional divergence likely depends on factors such as metabolite concentration, localization, and the specific immune context of the tumor microenvironment. Since microbial metabolites frequently act through multiple and interconnected signaling pathways, precisely determining the net effect of a single molecule in vivo remains challenging—a significant obstacle for developing metabolite-targeted therapies.

Therapeutic Strategies Targeting the Gut Microbiota in Ovarian Cancer

Gut Microbiota's Effect on Chemotherapy
Platinum agents (cisplatin, carboplatin) are first-line OC chemotherapeutics. Primary platinum resistance affects ∼25% of patients, leading to treatment failure.
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Antibiotics or bowel preparations may disrupt GM and compromise efficacy. In germ-free mice, oxaliplatin's anti-tumor activity was suppressed due to reduced myeloid cell ROS production.
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Similarly, antibiotic-treated OC-bearing mice exhibited accelerated tumor growth and diminished cisplatin sensitivity.
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Post-chemotherapy fecal 16S rRNA sequencing showed decreased Proteobacteria and increased Bacteroidetes/Firmicutes.
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Paclitaxel stabilizes microtubules, arresting cells in G2/M phase.
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It also binds TLR4, inducing c-Jun/NF-κB activation and contributing to chemoresistance.
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Salmonella typhimurium enhances paclitaxel efficacy in models.
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Cyclophosphamide efficacy is modulated by GM; Enterococcus hirae and Lactobacillus murinus potentiate its effects via systemic pTh17 responses and elevated CTL/Treg ratios.
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Probiotics and FMT improve outcomes: naringin and Bifidobacterium animalis reversed platinum resistance
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; FMT with triptolide glycoside (GTW) reduced CA125 levels and mitigated colonic damage.
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GM modulation alleviates chemotherapy-induced toxicity (eg, Lactobacillus plantarum reduced nausea/vomiting
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; sodium butyrate attenuated paclitaxel-induced dysbiosis
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).

Gut Microbiota's Effect on Immunotherapy
Immune checkpoint inhibitors (ICIs; anti-PD-1/CTLA-4) and adoptive cell therapy (ACT) are key immunotherapies. GM influences ICI efficacy: murine combination therapy increased tumor regression by 40% and doubled survival via Tpex cell differentiation into an intermediate exhausted state (Tex-int).
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ACT faces limitations in OC due to immunosuppression. Mesothelin-targeted CAR-T cells showed transient efficacy in advanced OC,
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while MISIIR-targeted CAR-T cells induced potent lysis in vitro.
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Reduced Ruminococcus, Bacteroides, and Faecalibacterium correlate with worse survival and increased toxicity in CAR-T recipients.
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Gut Microbiota's Effect on Targeted Therapy
Combining chemotherapy with bevacizumab extends progression-free survival (PFS).
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PARP inhibitors (olaparib, rucaparib, niraparib) are effective in BRCA1/2-mutated platinum-sensitive recurrent OC.
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Olaparib-ICI combinations increased objective response rates (ORR).
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Baseline Phascolarctobacterium abundance correlates with longer PFS in BRCA1/2-negative patients on PARPi maintenance
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(Table 2).

Challenges and Future Directions
Research on the GM-OC axis has advanced, though its complexity continues to pose challenges. First, beyond the GM, local microbial communities in the upper reproductive tract (eg, fallopian tubes and ovaries) and microbes in peritoneal fluid may also influence OC through local immunomodulation.
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Microbiota from different anatomical sites constitute interconnected ecosystems whose functional interactions remain poorly understood. Moreover, while most studies still focus primarily on the GM itself, research integrating microbial alterations, infections, chemotherapy, and OC across multiple dimensions remains limited. Although associations among these factors have been identified, establishing causality has been difficult. Thus, there is a need to combine robust clinical data with experimental models to clarify how microbiota affect human homeostasis and disease progression.
Second, several obstacles hinder clinical translation: significant inter-individual variation in GM composition, along with key confounders such as antibiotic use, diet, and menopausal status, has not been adequately controlled in most studies. Furthermore, microbiome research lacks standardization in sample processing, sequencing, and data normalization, complicating cross-study comparisons. The long-term safety and ethical implications of microbiota-based interventions (eg, FMT) also require thorough evaluation.
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Nevertheless, the involvement of GM opens new avenues for precision medicine in OC. Microbiota-derived biomarkers could aid in early cancer detection,
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while GM modulation may help reverse chemoresistance and enhance immunotherapy. Future work should prioritize large-scale, multi-center prospective cohorts and integrate multi-omics approaches—such as metagenomics, metabolomics, and transcriptomics—for comprehensive analysis. The development of personalized diagnostic frameworks should also be emphasized. Through these efforts, GM research can be translated into clinical practice, potentially reducing OC mortality and healthcare burdens, and ultimately improving patients’ quality of life.

Conclusion
In summary, GM critically influences the pathogenesis, progression, and treatment of OC. Research in this field, however, is still in its early stages. To advance the translation of GM insights into clinical practice, future efforts should prioritize conducting large-scale, multi-center studies and integrating multi-omics technologies. Overcoming current methodological and translational barriers is essential to realizing the promise of microbiota-based strategies for early detection and personalized therapy, ultimately improving outcomes for OC patients.