ReviewJournal of experimental & clinical cancer research : CR2021
Patient-derived organoids and high grade serous ovarian cancer: from disease modeling to personalized medicine.
Review in Journal of experimental & clinical cancer research : CR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Molecular targeted therapy in combination with chemotherapy for the treatment of platinum-resistant/refractory ovarian cancer (PROC): a systematic review and network meta-analysis.Annals of medicine · 2026Pooled it
- Evaluating carboplatin and PARP inhibitor combination efficacy using high-grade serous carcinoma spheroids and organoids.Cancer biology & therapy · 2026Article
- Protocol for generating and culturing high-grade serous ovarian carcinoma organoids from fresh or cryopreserved patient samples.STAR protocols · 2026Article
- Natural Product Target Identification of Wheldone, a Fungal Metabolite, as a KIF11 Inhibitor in Ovarian Cancer Using the DiffPOP (Differential Protein Precipitation) Method.Molecular & cellular proteomics : MCP · 2026Article
- Stem Cell-Derived Organoids for Cancer Therapy: Precision Medicine and Drug Selection.International journal of molecular sciences · 2026Review
- Targeting cancer stem cells predicts response and reverses chemoresistance in ascites-derived ovarian cancer organoids.BMC medicine · 2026Article
- zAvatar-test-A functional precision model to personalize ovarian cancer treatments: Results from a co-clinical study.Cell reports. Medicine · 2026Article
- Integrative Multi-Omics Analysis Reveals Molecular Signatures of Recurrence in Paired Primary and Recurrent High-Grade Serous Ovarian Cancer.International journal of molecular sciences · 2026Article
- Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2025Article
- Therapeutic Effects of Lurbinectedin in PARP Inhibitor-Resistant High-Grade Serous Ovarian Cancer Using Patient-Derived Cell Lines and Organoid Models.International journal of molecular sciences · 2025Article
- Patient-derived organoids as a model to study tubo-ovarian carcinoma: a pathologist's perspective.Journal of ovarian research · 2025Article
- Prospects and challenges of ovarian cancer organoids in chemotherapy research (Review).Oncology letters · 2025Review
- Article
- Multifaceted cancer alleviation by cowpea mosaic virus in a bioprinted ovarian cancer peritoneal spheroid model.Biomaterials · 2024Article
- Review
- Patient-derived ovarian cancer organoid carries immune microenvironment and blood vessel keeping high response to cisplatin.MedComm · 2024Article
- Aulosirazole Stimulates FOXO3a Nuclear Translocation to Regulate Apoptosis and Cell-Cycle Progression in High-Grade Serous Ovarian Cancer (HGSOC) Cells.Molecular pharmacology · 2024Article
- Patient-derived organoids in human cancer: a platform for fundamental research and precision medicine.Molecular biomedicine · 2024Review
- How BRCA and homologous recombination deficiency change therapeutic strategies in ovarian cancer: a review of literature.Frontiers in oncology · 2024Review
- Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundHigh grade serous ovarian cancer (HGSOC) is among the deadliest human cancers and its prognosis remains extremely poor. Tumor heterogeneity and rapid acquisition of resistance to conventional chemotherapeutic approaches strongly contribute to poor outcome of patients. The clinical landscape of HGSOC has been radically transformed since the advent of targeted therapies in the last decade. Nevertheless, the lack of predictive biomarkers informing on the differential clinical benefit in select subgroups, and allowing patient-centric approaches, currently limits the efficacy of these novel therapies. Thus, rational selection of the best possible treatment for each patient represents a clinical priority in order to improve outcome, while limiting undesirable effects. MAIN BODY: In this review, we describe the state of the art and the unmet needs in HGSOC management, illustrate the treatment options that are available and the biomarkers that are currently employed to orient clinical decisions. We also describe the ongoing clinical trials that are testing new therapeutic approaches for HGSOC. Next, we introduce the organoid technology as a promising, expanding strategy to study cancer and to develop personalized therapeutic approaches. In particular, we discuss recent studies that have characterized the translational potential of Patient's Derived Organoids (PDOs) to inform on drug sensitivity of HGSOC patients.
conclusionsPDOs can predict the response of patients to treatments and may therefore guide therapeutic decisions. Although preliminary results appear encouraging, organoids still need to be generated and expanded efficiently to enable drug screening in a clinically meaningful time window. A new generation of clinical trials based on the organoid technology should guarantee tailored approaches to ovarian cancer management, as it is now clear that the one-size-fits-all approach cannot lead to efficient and meaningful therapeutic advancements.
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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 OpenQuestion graph.