Evidence map›Paper›PMID 39237877›Full record

ArticleCellular & molecular biology letters2024

Inverse correlation between TP53 gene status and PD-L1 protein levels in a melanoma cell model depends on an IRF1/SOX10 regulatory axis.

Lucia Martinkova, Pavlina Zatloukalova, Martina Kucerikova, Nela Friedlova, Zuzana Tylichova, Filip Zavadil-Kokas, Ted Robert Hupp, Philip John Coates, Borivoj Vojtesek

Abstract read
In one paragraph

Article in Cellular & molecular biology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Mapping of the hSOX10 protein interactome in human melanoma.bioRxiv : the preprint server for biology · 2025
    Article
  12. 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

9 authors.

Lucia MartinkovaRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic. lucia.haronikova@mou.cz.
Pavlina ZatloukalovaRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Martina KucerikovaRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Nela FriedlovaRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Zuzana TylichovaRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Filip Zavadil-KokasRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Ted Robert HuppRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Philip John CoatesRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic.
Borivoj VojtesekRECAMO, Masaryk Memorial Cancer Institute, 602 00, Brno, Czech Republic. vojtesek@mou.cz.ORCID http://orcid.org/0000-0001-6194-3705

Funding

Grantová Agentura České Republiky 19-18177YGrantová Agentura České Republiky 22-02940SMinisterstvo Zdravotnictví Ceské Republiky 00209805)Ministerstvo Zdravotnictví Ceské Republiky DRO (MMCISALVAGE (P JAC) CZ.02.01.01/00/22_008/0004644
6 · The paper itself

Abstract

backgroundPD-L1 expression on cancer cells is an important mechanism of tumor immune escape, and immunotherapy targeting the PD-L1/PD1 interaction is a common treatment option for patients with melanoma. However, many patients do not respond to treatment and novel predictors of response are emerging. One suggested modifier of PD-L1 is the p53 pathway, although the relationship of p53 pathway function and activation is poorly understood.

methodsThe study was performed on human melanoma cell lines with various p53 status. We investigated PD-L1 and proteins involved in IFNγ signaling by immunoblotting and mRNA expression, as well as membrane expression of PD-L1 by flow cytometry. We evaluated differences in the ability of NK cells to recognize and kill target tumor cells on the basis of p53 status. We also investigated the influence of proteasomal degradation and protein half-life, IFNγ signaling and p53 activation on biological outcomes, and performed bioinformatic analysis using available data for melanoma cell lines and melanoma patients.

resultsWe demonstrate that p53 status changes the level of membrane and total PD-L1 protein through IRF1 regulation and show that p53 loss influences the recently discovered SOX10/IRF1 regulatory axis. Bioinformatic analysis identified a dependency of SOX10 on p53 status in melanoma, and a co-regulation of immune signaling by both transcription factors. However, IRF1/PD-L1 regulation by p53 activation revealed complicated regulatory mechanisms that alter IRF1 mRNA but not protein levels. IFNγ activation revealed no dramatic differences based on TP53 status, although dual p53 activation and IFNγ treatment confirmed a complex regulatory loop between p53 and the IRF1/PD-L1 axis.

conclusionsWe show that p53 loss influences the level of PD-L1 through IRF1 and SOX10 in an isogenic melanoma cell model, and that p53 loss affects NK-cell cytotoxicity toward tumor cells. Moreover, activation of p53 by MDM2 inhibition has a complex effect on IRF1/PD-L1 activation. These findings indicate that evaluation of p53 status in patients with melanoma will be important for predicting the response to PD-L1 monotherapy and/or dual treatments where p53 pathways participate in the overall response.

Indexed as

B7-H1 AntigenInterferon Regulatory Factor-1MelanomaSignal TransductionSOXE Transcription FactorsTumor Suppressor Protein p53Cell Line, TumorGene Expression Regulation, NeoplasticHumansInterferon-gammaKiller Cells, NaturalB7-H1 AntigenCD274 protein, humanInterferon-gammaInterferon Regulatory Factor-1IRF1 protein, humanSOX10 protein, humanSOXE Transcription FactorsTP53 protein, humanTumor Suppressor Protein p53IFNγIRF1p53PD-L1SOX10

Identifiers

PMID39237877
PMCPMC11378555

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Registered trials

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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.