Evidence map›Paper›PMID 33263276›Full record

ArticleeLife2020

Dissecting the DNA binding landscape and gene regulatory network of p63 and p53.

Konstantin Riege, Helene Kretzmer, Arne Sahm, Simon S McDade, Steve Hoffmann, Martin Fischer

Open access · goldAbstract read
In one paragraph

Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.3field-weighted citation impact, top 9% 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

27 citing papers in PubMed, 46 citations in OpenAlex.

  1. Article
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  5. Deletion of p63 exon 13 in mice reveals C-terminal isoform-specific functions in epithelial development.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Article
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  8. p53motifDB: integration of genomic information and tumour suppressor p53 binding motifs.Database : the journal of biological databases and curation · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Context dependent activity of p63-bound gene regulatory elements.bioRxiv : the preprint server for biology · 2024
    Article
  14. Article
  15. Article
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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

6 authors at 3 institutions in 2 countries.

Konstantin RiegeComputational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.
Helene KretzmerDepartment of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany.
Arne SahmComputational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.ORCID 0000-0002-7330-1790
Simon S McDadePatrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, United Kingdom.ORCID 0000-0002-3024-4773
Steve HoffmannComputational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.
Martin FischerComputational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.ORCID 0000-0002-3429-1876
Leibniz Institute on Aging - Fritz Lipmann Institute (FLI) · DEMax Planck Institute for Molecular Genetics · DEQueen's University Belfast · GB

Funding

Bundesministerium für Bildung und Forschung 031L016DDeutsche Forschungsgemeinschaft FI 1993/2-1Leibniz Association Open Access Fund
6 · The paper itself

Abstract

The transcription factor p53 is the best-known tumor suppressor, but its sibling p63 is a master regulator of epidermis development and a key oncogenic driver in squamous cell carcinomas (SCC). Despite multiple gene expression studies becoming available, the limited overlap of reported p63-dependent genes has made it difficult to decipher the p63 gene regulatory network. Particularly, analyses of p63 response elements differed substantially among the studies. To address this intricate data situation, we provide an integrated resource that enables assessing the p63-dependent regulation of any human gene of interest. We use a novel iterative de novo motif search approach in conjunction with extensive ChIP-seq data to achieve a precise global distinction between p53-and p63-binding sites, recognition motifs, and potential co-factors. We integrate these data with enhancer:gene associations to predict p63 target genes and identify those that are commonly de-regulated in SCC representing candidates for prognosis and therapeutic interventions.

Indexed as

Gene Regulatory NetworksBinding SitesBiomarkers, TumorComputational BiologyDatabases, GeneticDNAGene Expression RegulationHead and Neck NeoplasmsHumansPrognosisProtein BindingSquamous Cell Carcinoma of Head and NeckTranscription FactorsTumor Suppressor Protein p53Tumor Suppressor ProteinsBiomarkers, TumorDNATP53 protein, humanTP63 protein, humanTranscription FactorsTumor Suppressor Protein p53Tumor Suppressor ProteinschromosomesDNA binding landscapegene expressiongene regulatory networkgeneticsgenomicshumanp53p63resourcesquamous cell carcinoma

Identifiers

PMID33263276
PMCPMC7735755
OpenAlexW3107422833

What Socratic 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 Socratic graph.