ReviewExploration of targeted anti-tumor therapy2025
Bispecific antibodies in the treatment of epithelial ovarian, endometrial, and cervical cancer: an overview of current applications, challenges, and emerging opportunities.
Review in Exploration of targeted anti-tumor therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Targeting VEGF, PARP, and FRα Pathways in Ovarian Cancer: Clinical Advances with Bevacizumab, Rucaparib, and Mirvetuximab Soravtansine.Journal of clinical medicine · 2026Review
- Targeting glucocorticoid receptor signaling in platinum-resistant ovarian cancer: translational rationale and clinical advances following the ROSELLA trial.Oncology reviews · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gynecological cancer remains one of the leading causes of mortality worldwide. Recent advances in genomic and molecular sequencing have significantly enhanced our understanding of the biological pathways that drive tumor progression and resistance to therapy. Targeted therapies, including monoclonal antibodies (mAbs), have revolutionized cancer treatment by selectively interfering with oncogenic proteins expressed on cancer cells. However, the long-term clinical benefit is often limited due to the emergence of drug resistance, frequently mediated by compensatory signaling pathways or immune escape mechanisms. To overcome these limitations, bispecific antibodies (bsAbs) represent an innovative class of therapeutic agents that have shown promising results across various medical fields. They have been developed to engage two distinct targets simultaneously, such as tumor antigens, immune effectors, or immunomodulatory checkpoints, thereby enhancing anti-tumor activity and reducing the risk of resistance. There are 17 bsAbs approved for clinical use in various countries, with numerous others currently in active development and over 600 bsAbs undergoing clinical trials worldwide. Among these, 11 have received FDA approval for the treatment of hematologic malignancies as well as solid tumors, including uveal melanoma, metastatic non-small cell lung cancer, small cell lung cancer, and biliary tract cancers. Although some studies have explored bsAbs in gynecological cancers, this area remains underdeveloped compared to other oncology fields. Most ongoing studies in this area are still in their early phases (phase I or phase II), and there is a need for optimization in terms of antibody design, efficacy, and safety profiles. Therefore, the purpose of this review is to present a comprehensive summary of the current research on bsAbs in gynecological cancers, with a focus on endometrial, cervical, and ovarian cancers. We will highlight ongoing clinical trials, discuss the mechanisms of action of these agents, and explore their potential benefits in enhancing treatment outcomes.
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Registered trials
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 Socratic graph.