Evidence map›Paper›PMID 34000624›Full record

ArticleEBioMedicine2021

Clinically relevant aberrant Filip1l DNA methylation detected in a murine model of cutaneous squamous cell carcinoma.

Kevin Roth, Louis Coussement, Elena V Knatko, Maureen Higgins, Sandra Steyaert, Charlotte M Proby, Tim de Meyer, Albena T Dinkova-Kostova

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 39% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

8 authors at 3 institutions in 3 countries.

Kevin RothJacqui Wood Cancer Centre, Division of Cellular Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, United Kingdom.
Louis CoussementBiobix, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000, Ghent, Belgium; CRIG, Cancer Research Institute Ghent, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium.
Elena V KnatkoJacqui Wood Cancer Centre, Division of Cellular Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, United Kingdom.
Maureen HigginsJacqui Wood Cancer Centre, Division of Cellular Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, United Kingdom.
Sandra SteyaertBiobix, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.
Charlotte M ProbyJacqui Wood Cancer Centre, Division of Cellular Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, United Kingdom.
Tim de MeyerBiobix, Department of Data Analysis and Mathematical Modelling, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000, Ghent, Belgium; CRIG, Cancer Research Institute Ghent, Sint-Pietersnieuwstraat 25, 9000, Ghent, Belgium.
Albena T Dinkova-KostovaJacqui Wood Cancer Centre, Division of Cellular Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee DD1 9SY, United Kingdom; Department of Pharmacology and Molecular Sciences and Department of Medicine, Johns Hopkins University School of Medicine, Baltimore MD 21205, USA. Electronic address: a.dinkovakostova@dundee.ac.uk.
University of Dundee · GBGhent University · BEJohns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCutaneous squamous cell carcinomas (cSCC) are among the most common and highly mutated human malignancies. Understanding the impact of DNA methylation in cSCC may provide avenues for new therapeutic strategies.

methodsWe used reduced-representation bisulfite sequencing for DNA methylation analysis of murine cSCC. Differential methylation was assessed at the CpG level using limma. Next, we compared with human cSCC Infinium HumanMethylation BeadArray data. Genes were considered to be of major relevance when they featured at least one significantly differentially methylated CpGs (RRBS) / probes (Infinium) with at least a 30% difference between tumour vs. control in both a murine gene and its human orthologue. The human EPIC Infinium data were used to distinguish two cSCC subtypes, stem-cell-like and keratinocyte-like tumours.

findingsWe found increased average methylation in mouse cSCC (by 12.8%, p = 0.0011) as well as in stem-cell like (by 3.1%, p=0.002), but not keratinocyte-like (0.2%, p = 0.98), human cSCC. Comparison of differentially methylated genes revealed striking similarities between human and mouse cSCC. Locus specific methylation changes in mouse cSCC often occurred in regions of potential regulatory function, including enhancers and promoters. A key differentially methylated region was located in a potential enhancer of the tumour suppressor gene Filip1l and its expression was reduced in mouse tumours. Moreover, the FILIP1L locus showed hypermethylation in human cSCC and lower expression in human cSCC cell lines.

interpretationDeregulation of DNA methylation is an important feature of murine and human cSCC that likely contributes to silencing of tumour suppressor genes, as shown for Filip1l.

fundingBritish Skin Foundation, Cancer Research UK.

Indexed as

DNA MethylationAnimalsCarcinoma, Squamous CellCarrier ProteinsCell Line, TumorCytoskeletal ProteinsDown-RegulationGene Expression Regulation, NeoplasticHumansMiceSkin NeoplasmsCarrier ProteinsCytoskeletal ProteinsFILIP1 protein, humancSCCDNA methylationFILIP1LRRBS

Identifiers

PMID34000624
PMCPMC8138604
OpenAlexW3162674083

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.