ArticleJournal of ovarian research2024
The intratumoral microbiota biomarkers for predicting survival and efficacy of immunotherapy in patients with ovarian serous cystadenocarcinoma.
Article in Journal of ovarian research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Malassezia restricta-Derived Extracellular Vesicles Drive Ovarian Cancer Progression Through JAK2/STAT3-Mediated M2 Macrophage Polarisation.Microbial biotechnology · 2026Article
- Intratumoral microbiota in cancer: molecular mechanism and therapeutic strategies.Molecular biomedicine · 2026Review
- The intratumoral microbiome: a review of the tumor microenvironment's fourth axis shaping anti-tumor immunity, cancer prognosis, and therapeutic response.Frontiers in immunology · 2026Review
- Tumor-resident microbiota in gynecologic malignancies: Molecular mechanisms, clinical correlations, and translational potential.iScience · 2025Review
- Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.mSystems · 2025Article
- Decoding the Tumor-Associated Microbiota: From Origins to Nanomedicine Applications in Cancer Therapy.Biology · 2025Review
- Oncolytic virus therapy in the elderly: immune frailty, challenges, and perspectives.Frontiers in immunology · 2025Review
- Intratumoral Microbiota: Insights from Anatomical, Molecular, and Clinical Perspectives.Journal of personalized medicine · 2024Review
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Authors and funding
6 authors.
Funding
Abstract
backgroundOvarian serous cystadenocarcinoma, accounting for about 90% of ovarian cancers, is frequently diagnosed at advanced stages, leading to suboptimal treatment outcomes. Given the malignant nature of the disease, effective biomarkers for accurate prediction and personalized treatment remain an urgent clinical need.
methodsIn this study, we analyzed the microbial contents of 453 ovarian serous cystadenocarcinoma and 68 adjacent non-cancerous samples. A univariate Cox regression model was used to identify microorganisms significantly associated with survival and a prognostic risk score model constructed using LASSO Cox regression analysis. Patients were subsequently categorized into high-risk and low-risk groups based on their risk scores.
resultsSurvival analysis revealed that patients in the low-risk group had a higher overall survival rate. A nomogram was constructed for easy visualization of the prognostic model. Analysis of immune cell infiltration and immune checkpoint gene expression in both groups showed that both parameters were positively correlated with the risk level, indicating an increased immune response in higher risk groups.
conclusionOur findings suggest that microbial profiles in ovarian serous cystadenocarcinoma may serve as viable clinical prognostic indicators. This study provides novel insights into the potential impact of intratumoral microbial communities on disease prognosis and opens avenues for future therapeutic interventions targeting these microorganisms.
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