Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 245

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Targeting Tumor Suppressor p53 for Cancer Therapy: Strategies, Challenges and Opportunities

Hong, Bo, Heuvel, A., Prabhu, Varun, Zhang, Shengliang, El-Deiry, Wafik·2014·Current Drug Targets

Abstract

p53 is one of the most important tumor suppressor genes that is frequently mutated in human cancers. Generally, p53 functions as a transcription factor that is stabilized and activated by various genotoxic and cellular stress signals, such as DNA damage, hypoxia, oncogene activation and nutrient deprivation, consequently leading to cell cycle arrest, apoptosis, senescence and metabolic adaptation. p53 not only becomes functionally deficient in most cancers, but not infrequently mutant p53 also acquires dominant negative activity and oncogenic properties. p53 has remained an attractive target for cancer therapy. Strategies targeting p53 have been developed including gene therapy to restore p53 function, inhibition of p53-MDM2 interaction, restoration of mutant p53 to wild-type p53, targeting p53 family proteins, eliminating mutant p53, as well as p53-based vaccines. Some of these p53-targeted therapies have entered clinical trials. We discuss the therapeutic potential of p53, with particular focus on the therapeutic strategies to rescue p53 inactivation in human cancers. In addition, we discuss the challenges of p53-targeted therapy and new opportunities for the future.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2174/1389450114666140106101412

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 22 references

Cited by

See all 245

Metadata

Authors
Hong, B., Heuvel, A., Prabhu, V., Zhang, S., & El-Deiry, W.
Venue
Current Drug Targets
Published
2014-01-31
Volume
15
Issue
1
Pages
80-89
ISSN
1389-4501 (ISSN-L)
OpenAlex
W2129141930
Cited by
245
References
22
FWCI
9.48
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Targeting Tumor Suppressor p53 for Cancer Therapy: Strategies, Challenges and Opportunities. https://app.cochat.ai/papers/10.2174/1389450114666140106101412
The paper
Hong, B., Heuvel, A., Prabhu, V., Zhang, S., & El-Deiry, W. (2014). Targeting Tumor Suppressor p53 for Cancer Therapy: Strategies, Challenges and Opportunities. Current Drug Targets. https://doi.org/10.2174/1389450114666140106101412

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.