Evidence map›Paper›PMID 40696461›Full record

ArticleGenome biology2025

A base editing platform for the correction of cancer driver mutations unmasks conserved p53 transcription programs.

Pascal Wang, Rituparno Sen, Frank Buchholz, Shady Sayed

Abstract read
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
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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

4 authors.

Pascal WangMedical Systems Biology, Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany.ORCID http://orcid.org/0009-0004-0102-8133
Rituparno SenMedical Systems Biology, Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany.ORCID http://orcid.org/0000-0001-5980-5565
Frank BuchholzMedical Systems Biology, Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany. frank.buchholz@tu-dresden.de.ORCID http://orcid.org/0000-0002-4577-3344
Shady SayedMedical Systems Biology, Faculty of Medicine Carl Gustav Carus, TU Dresden, Dresden, Germany. shady.sayed@tu-dresden.de.ORCID http://orcid.org/0000-0002-3209-238X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the role of cancer hotspot mutations is essential for unraveling mechanisms of tumorigenesis and identifying therapeutic vulnerabilities. Correcting cancer mutations with base editing is a novel, yet promising approach for investigating the biology of driver mutations.

resultsHere, we present a versatile platform to investigate the functional impact of cancer hotspot mutations through adenine base editing in combination with transcriptomic profiling. Using this approach, we correct TP53 hotspot mutations in cancer cell lines derived from diverse tissues, followed by mRNA sequencing to evaluate transcriptional changes. Remarkably, correcting these mutations not only reveals the dependency on mutant allele expression but also restores highly conserved tumor-suppressive transcriptional programs, irrespective of tissue origin or co-occurring mutations, highlighting a shared p53-dependent regulatory network. Our findings demonstrate the utility of this base editing platform to systematically interrogate the functional consequences of cancer-associated mutations and their downstream effects on gene expression.

conclusionsThis work establishes a robust framework for studying the transcriptional dynamics of cancer hotspot mutations and sheds light on the conserved biological processes reinstated by p53 correction, offering potential avenues for future targeted therapies.

Indexed as

Gene EditingMutationNeoplasmsTranscription, GeneticTumor Suppressor Protein p53Cell Line, TumorGene Expression Regulation, NeoplasticHumansTP53 protein, humanTumor Suppressor Protein p53Base editingCancerCRISPRDriver mutationP53SMAD4Transcriptomics

Identifiers

PMID40696461
PMCPMC12285138

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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.