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. ¹ Epithelial carcinoma is the predominant histological subtype, followed by malignant germ cell tumors. ² The pathophysiology of OC remains incompletely understood. Epidemiological evidence indicates reduced OC risk with oral contraceptive use, ³ multiparity, ⁴ and prolonged breastfeeding, ⁵ whereas nulliparity, ⁶ early menarche, ⁷ and late menopause ⁸ 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. ⁹ 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, ¹⁰ with Bacteroidetes and Firmicutes constituting approximately 90% of the total population. ¹¹ GM homeostasis maintains intestinal barrier integrity, internal environmental stability, immune-endocrine modulation, and pathogen defense, thereby supporting host physiology. ¹² Dysbiosis has been linked to numerous diseases, including obesity, ¹³ diabetes, ¹⁴ and inflammatory bowel disease. ¹⁵ 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. ¹⁶ 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.

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Figure 1.

Schematic of GM-mediated OC development. It depicts interactions among GM, estrogen metabolism, immunity, obesity, inflammation, and microbial metabolites. Key aspects include: risk/protective factors (eg, nulliparity, oral contraceptives); GM regulating estrogen via glucuronidase (β-GUS); microbial metabolites activating NF-κB/PI3 K/MAPK pathways for tumorigenesis; tumor microenvironment immune cells; obesity-induced dysbiosis (intestinal barrier failure, altered cell migration/apoptosis); and inflammation-driven IL-6/TNF-α upregulation and Hedgehog (Hh) pathway activation promoting OC.

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. ¹⁷ Specific Firmicutes genera, including Abiotrophia, Bacillus, Enterococcus, Erysipelothrix, Geobacillus, Lactobacillus, Lactococcus, Listeria, Pediococcus, Peptoniphilus, and Staphylococcus, are enriched in tumor samples. ¹⁸ 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. ¹⁹ 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. ²⁰

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Table 1.

Dysbiosis of Gut Microbiota in Ovarian Cancer Patients.

Changes in GM	Method	References
Increase: Proteobacteria and Firmicute	PathoChip Array	17
Increase: Bacteroides and Prevotella	16S rRNA sequencing	20
Decrease: Ruminococcaceae_Ruminococcus and Bifidobacterium
Increase: Escherichia_Shigella and Ruminococcus gnavus	16S rRNA sequencing	21
Decrease: Coprococcus and Fusicatenibacter
Increase: Escherichia and Shigella	16S rRNA sequencing	22
Decrease: Bilophila and Bifidobacterium

Abbreviations: GM, gut microbiota.

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. ²¹ 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 ²² 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, ²³ 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

Regulation of Estrogen Bioavailability

Sustained estrogen exposure is a well-established OC risk factor. ³⁴ 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. ³⁵

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. ³⁶ Reactivated estrogens bind estrogen receptors α (ERα) and β (ERβ) ³⁷ ; (Figure 2). Excessive β-GUS activity may promote carcinogenesis via genotoxin production. ³⁸ 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. ³⁹ Thus, microbial estrogen recycling positions the GM as a pivotal regulator of systemic estrogen levels influencing OC risk.

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Figure 2.

GM contributes to OC initiation and progression by modulating estrogen levels. The main mechanisms are as follows: (1) The GM disrupts the enterohepatic circulation of estrogen; (2) The GM increases estrogen activity by upregulating β-GUS production.

Therapeutic Strategies Targeting the Gut Microbiota in Ovarian Cancer

Gut Microbiota's Effect on Targeted Therapy

Combining chemotherapy with bevacizumab extends progression-free survival (PFS). ⁷⁴ PARP inhibitors (olaparib, rucaparib, niraparib) are effective in BRCA1/2-mutated platinum-sensitive recurrent OC. ⁷⁵ Olaparib-ICI combinations increased objective response rates (ORR). ⁷⁶ Baseline Phascolarctobacterium abundance correlates with longer PFS in BRCA1/2-negative patients on PARPi maintenance ⁷⁷ (Table 2).

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Table 2.

Role of Microorganisms in Ovarian Cancer Therapy.

Therapeutic Modality	Key Drug	Impact of/on GM	Reference
Chemotherapy	​Oxaliplatin​​	GM can influence the antitumor effects of oxaliplatin by producing ROS.	59
	Cisplatin	The perturbation of GM by antibiotics promotes tumor growth and inhibits cisplatin sensitivity; FMT can restore the intestinal barrier damaged by chemotherapy drugs.	60,67
	Cisplatin/Carboplatin /Paclitaxel	The abundance of the Bacteroidetes and Firmicutes increases after chemotherapy, while the abundance of the Proteobacteria decreases.	61
	Paclitaxel	S.typhimurium A1-R overcomes tumor cell resistance; Induces intestinal dysfunction and inflammation.	64,69
	Cyclophosphamide	Enterococcus hirae and Bacteroides intestinalis enhance the antitumor efficacy of cyclophosphamide; Supplementing probiotics can improve adverse outcomes induced by cyclophosphamide treatment.​	65,68
Immunotherapy	Immune checkpoint inhibitors	Enhanced antitumor immune responses	70
	Chimeric antigen receptor	Clinical outcomes of CD19 CAR-T therapy may affect GM abundance	73
Targeted therapy	Parp-inhibitors	Microbiota-mediated immune activation may create a permissive environment for PARPi sensitivity.	77

Abbreviations: GM, gut microbiota; ROS, Reactive Oxygen Species; FMT, fecal microbiota transplantation; CAR-T, chimeric antigen receptor T-cell immunotherapy; PARPi, poly(ADP-ribose) polymerase inhibitor.

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. ⁷⁸ 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. ⁷⁹

Nevertheless, the involvement of GM opens new avenues for precision medicine in OC. Microbiota-derived biomarkers could aid in early cancer detection, ⁸⁰ 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.