Evidence map›Paper›PMID 38132123›Full record

ReviewCells2023

The Role of p53 in Nanoparticle-Based Therapy for Cancer.

Olga Szewczyk-Roszczenko, Nikolai A Barlev

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 11% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Growth suppressing effect ofCytotechnology · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Genetic Update and Treatment for Dystonia.International journal of molecular sciences · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 3 countries.

Olga Szewczyk-RoszczenkoDepartment of Synthesis and Technology of Drugs, Medical University of Bialystok, Kilinskiego 1, 15-089 Bialystok, Poland.ORCID 0000-0002-3719-6583
Nikolai A BarlevDepartment of Biomedicine, School of Medicine, Nazarbayev University, Kerey and Zhanibek Khans St., Astana 020000, Kazakhstan.ORCID 0000-0001-7111-2446
Institute of Cytology · RUMedical University of Białystok · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

p53 is arguably one of the most important tumor suppressor genes in humans. Due to the paramount importance of p53 in the onset of cell cycle arrest and apoptosis, the p53 gene is found either silenced or mutated in the vast majority of cancers. Furthermore, activated wild-type p53 exhibits a strong bystander effect, thereby activating apoptosis in surrounding cells without being physically present there. For these reasons, p53-targeted therapy that is designed to restore the function of wild-type p53 in cancer cells seems to be a very appealing therapeutic approach. Systemic delivery of p53-coding DNA or RNA using nanoparticles proved to be feasible both in vitro and in vivo. In fact, one p53-based therapeutic (gendicine) is currently approved for commercial use in China. However, the broad use of p53-based therapy in p53-inactivated cancers is severely restricted by its inadequate efficacy. This review highlights the current state-of-the-art in this area of biomedical research and also discusses novel approaches that may help overcome the shortcomings of p53-targeting nanomedicine.

Indexed as

Antineoplastic AgentsNanoparticlesNeoplasmsGenetic TherapyHumansTumor Suppressor Protein p53Antineoplastic AgentsTumor Suppressor Protein p53apoptosisbystander effectgene therapynanoparticlesp53

Identifiers

PMID38132123
PMCPMC10742014
OpenAlexW4389560287

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.