ReviewInternational journal of molecular sciences2022
Anticancer Therapeutic Strategies Targeting p53 Aggregation.
Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 18 citations in OpenAlex.
- Multi-Site Aggregation of p53: Insights from Self- and Co-Aggregation of Multiple Aggregation-Prone Regions.ACS omega · 2026Article
- p53: from understanding its structure to advances in therapeutic targeting.Signal transduction and targeted therapy · 2026Review
- The Multifaceted Role of p53 in Cancer Molecular Biology: Insights for Precision Diagnosis and Therapeutic Breakthroughs.Biomolecules · 2025Review
- Unveiling vitamin C: A new hope in the treatment of diffuse large B‑cell lymphoma (Review).International journal of oncology · 2025Review
- Designed Cell-Penetrating Peptide Constructs for Inhibition of Pathogenic Protein Self-Assembly.Pharmaceutics · 2024Review
- Oncogenic p53 triggers amyloid aggregation of p63 and p73 liquid droplets.Communications chemistry · 2024Article
- Protein aggregation and biomolecular condensation in hypoxic environments (Review).International journal of molecular medicine · 2024Review
- Review
- p53 amyloid pathology is correlated with higher cancer grade irrespective of the mutant or wild-type form.Journal of cell science · 2023Article
- Big versus small: The impact of aggregate size in disease.Protein science : a publication of the Protein Society · 2023Review
- PRIMA-1 inhibits Y220C p53 amyloid aggregation and synergizes with cisplatin in hepatocellular carcinoma.Frontiers in molecular biosciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
p53 is a tumor suppressor protein that is mutated in more than 50% of cancer cases. When mutated, it frequently results in p53 oncogenic gain of function (GOF), resulting in a greater tendency to aggregate in the phase separation and phase transition pathway. GOFs related to p53 aggregation include chemoresistance, which makes therapy even more difficult. The therapies available for the treatment of cancer are still quite limited, so the study of new molecules and therapeutic targets focusing on p53 aggregates is a promising strategy against cancer. In this review, we classify anticancer molecules with antiaggregation properties into four categories: thiol alkylating agents, designed peptides, agents with chaperone-based mechanisms that inhibit p53 aggregation, and miscellaneous compounds with anti-protein aggregation properties that have been studied in neurodegenerative diseases. Furthermore, we highlight autophagy as a possible degradation pathway for aggregated p53. Here, considering cancer as a protein aggregation disease, we review strategies that have been used to disrupt p53 aggregates, leading to cancer regression.
Indexed as
Identifiers
What Socratic 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 Socratic graph.