ReviewBiomolecules2023
The Challenges and Prospects of p53-Based Therapies in Ovarian Cancer.
Review in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed, 45 citations in OpenAlex.
- A p53Molecular therapy. Oncology · 2026Article
- Multi-Site Aggregation of p53: Insights from Self- and Co-Aggregation of Multiple Aggregation-Prone Regions.ACS omega · 2026Article
- Genetic Medicine Approaches for Tumor Suppressor Loss: Therapeutic Replacement with Self-Amplifying RNA.Pharmaceutical research · 2026Review
- Review
- Targeting mutant p53 in cancer: from mechanistic insights to therapeutic strategies.Cellular & molecular biology letters · 2026Review
- Dual Targeting of Mutant p53 and SNRPD2 via Engineered Exosomes Modulates Alternative Splicing to Suppress Ovarian Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- miR-340 improves the efficiency of p53 gene therapy in metastatic prostate cancer cells through downregulation of MDM2.Scientific reports · 2026Article
- Repurposing natural compounds: computational evaluation ofFrontiers in bioinformatics · 2026Article
- Natural compounds targeting glycolysis and TME in ovarian cancer: from metabolic crosstalk to therapeutic potential.Frontiers in pharmacology · 2026Review
- Synergistic effects of the curcumin analog HO-3867 and olaparib in transforming fallopian tube epithelial cells.Investigational new drugs · 2025Article
- AAV for ovarian cancer gene therapy.Cancer gene therapy · 2025Review
- Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis.BMC women's health · 2025Article
- Article
- Proteasome Inhibitor MG-132 and PKC-ι-Specific Inhibitor ICA-1S Degrade Mutant p53 and Induce Apoptosis in Ovarian Cancer Cell Lines.International journal of molecular sciences · 2025Article
- Article
- Clinical and molecular analysis of JCPyV and BKPyV infection and associated risk of urothelial carcinoma development in the upper tract.Virology journal · 2025Article
- Promising new drugs and therapeutic approaches for treatment of ovarian cancer-targeting the hallmarks of cancer.BMC medicine · 2025Review
- Unveiling drug resistance pathways in high-grade serous ovarian cancer(HGSOC): recent advances and future perspectives.Frontiers in immunology · 2025Review
- Single-cell transcriptome analysis revealed heterogeneity in glycolysis and identified IGF2 as a therapeutic target for ovarian cancer subtypes.BMC cancer · 2024Article
- Dual‑regulated oncolytic adenovirus carryingMolecular medicine reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
It has been well established that mutations in the tumor suppressor gene, p53, occur readily in a vast majority of cancer tumors, including ovarian cancer. Typically diagnosed in stages three or four, ovarian cancer is the fifth leading cause of death in women, despite accounting for only 2.5% of all female malignancies. The overall 5-year survival rate for ovarian cancer is around 47%; however, this drops to an abysmal 29% for the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC). HGSOC has upwards of 96% of cases expressing mutations in p53. Therefore, wild-type (WT) p53 and p53-based therapies have been explored as treatment options via a plethora of drug delivery vehicles including nanoparticles, viruses, polymers, and liposomes. However, previous p53 therapeutics have faced many challenges, which have resulted in their limited translational success to date. This review highlights a selection of these historical p53-targeted therapeutics for ovarian cancer, why they failed, and what the future could hold for a new generation of this class of therapies.
Indexed as
Identifiers
What OpenQuestion holds
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.