ReviewJournal of ovarian research2026
Clinical landscape of therapeutic vaccines for ovarian cancer: current status, challenges, and future directions.
Review in Journal of ovarian research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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5 authors.
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Abstract
backgroundTherapeutic cancer vaccines have emerged as a promising immunotherapeutic strategy for ovarian cancer by stimulating tumor-specific immune responses and establishing long-term immune memory. Despite decades of clinical investigation, the overall development landscape, translatform characteristics, and research trends of ovarian cancer vaccines remain incompletely understood.
methodsClinical trials related to ovarian cancer vaccines were retrieved from the ClinicalTrials.gov database. A total of 136 unique studies registered between 1996 and June 2026 were included. Information regarding study phase, recruitment status, enrollment size, geographic distribution, funding source, vaccine platform, combination strategy, clinical application context, and endpoint selection was extracted and descriptively analyzed. Relationships among vaccine platforms, combination strategies, clinical phases, and endpoint categories were further visualized. Immune monitoring outcomes were further coded according to reporting specificity, assay-method class, and biological domain.
resultsA total of 136 clinical studies involving 4,180 participants were identified. Most studies were early-phase trials, including Phase I (48.53%), Phase II (23.53%), and Phase I/II (21.32%), whereas only 2 Phase III studies were found. Completed studies accounted for 55.88%, while only 22.79% had publicly posted results. The United States dominated the research landscape, participating in 105 studies. Major vaccine platforms included peptide/antigen vaccines, dendritic-cell vaccines, whole tumor cell or lysate vaccines, DNA/RNA vaccines, and viral/vector vaccines. Current development trends indicate a transition from single-vaccine approaches toward combination strategies involving immune checkpoint inhibitors, chemotherapy, and immune adjuvants. Most studies focused on advanced, metastatic, or recurrent ovarian cancer. Safety/toxicity and immunogenicity were the most frequently used endpoints, whereas progression-free survival, overall survival, quality of life, and biomarker-based outcomes were comparatively underrepresented. Immune monitoring or immune-response outcomes were reported in 92 trials (67.65%), but only 58 trials (42.65%) specified an assay method; 34 trials (25.00%) described an immune domain without a named assay.
conclusionsTherapeutic vaccine development for ovarian cancer has shown sustained progress over the past three decades but remains largely in an early exploratory stage. Although diverse vaccine platforms and combination immunotherapy strategies demonstrate substantial translational potential, confirmatory evidence remains limited. Future efforts should prioritize biomarker-guided patient selection, personalized vaccine development, standardized immune monitoring, clinically meaningful endpoints, and large-scale multicenter randomized Phase II/III trials to facilitate the translation of vaccine-induced immune responses into tangible clinical benefits. The observed heterogeneity in immune-response reporting further highlights the need for prespecified, harmonized, and vaccine-specific immune monitoring frameworks in future vaccine trials.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.