Evidence map›Paper›PMID 33549134›Full record

ArticleGenome medicine2021

Genetic and functional interaction network analysis reveals global enrichment of regulatory T cell genes influencing basal cell carcinoma susceptibility.

Christelle Adolphe, Angli Xue, Atefeh Taherian Fard, Laura A Genovesi, Jian Yang, Brandon J Wainwright

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 4% 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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  14. Skin Development and Disease: A Molecular Perspective.Current issues in molecular biology · 2024
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  19. Genetic causal relationship between gut microbiota and basal cell carcinoma: A two-sample mendelian randomization study.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
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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 2 institutions in 2 countries.

Christelle Adolphe *Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Angli Xue *Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Atefeh Taherian FardAustralian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, 4072, Australia.
Laura A GenovesiInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Jian YangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@westlake.edu.cn.
Brandon J WainwrightInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. b.wainwright@imb.uq.edu.au.ORCID 0000-0003-0406-2092
The University of Queensland · AUTranslational Research Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBasal cell carcinoma (BCC) of the skin is the most common form of human cancer, with more than 90% of tumours presenting with clear genetic activation of the Hedgehog pathway. However, polygenic risk factors affecting mechanisms such as DNA repair and cell cycle checkpoints or which modulate the tumour microenvironment or host immune system play significant roles in determining whether genetic mutations culminate in BCC development. We set out to define background genetic factors that play a role in influencing BCC susceptibility via promoting or suppressing the effects of oncogenic drivers of BCC.

methodsWe performed genome-wide association studies (GWAS) on 17,416 cases and 375,455 controls. We subsequently performed statistical analysis by integrating data from population-based genetic studies of multi-omics data, including blood- and skin-specific expression quantitative trait loci and methylation quantitative trait loci, thereby defining a list of functionally relevant candidate BCC susceptibility genes from our GWAS loci. We also constructed a local GWAS functional interaction network (consisting of GWAS nearest genes) and another functional interaction network, consisting specifically of candidate BCC susceptibility genes.

resultsA total of 71 GWAS loci and 46 functional candidate BCC susceptibility genes were identified. Increased risk of BCC was associated with the decreased expression of 26 susceptibility genes and increased expression of 20 susceptibility genes. Pathway analysis of the functional candidate gene regulatory network revealed strong enrichment for cell cycle, cell death, and immune regulation processes, with a global enrichment of genes and proteins linked to T

conclusionsOur genome-wide association analyses and functional interaction network analysis reveal an enrichment of risk variants that function in an immunosuppressive regulatory network, likely hindering cancer immune surveillance and effective antitumour immunity.

Indexed as

Gene Regulatory NetworksGenetic Predisposition to DiseaseBasal Cell CarcinomaBiological Specimen BanksDNA MethylationGene Expression Regulation, NeoplasticGenome-Wide Association StudyHumansMendelian Randomization AnalysisOrgan SpecificityProtein Interaction MapsQuantitative Trait LociSkin NeoplasmsT-Lymphocytes, RegulatoryBCCCancer susceptibilityGWASImmune surveillanceProtein interaction networks

Identifiers

PMID33549134
PMCPMC7866769
OpenAlexW3129019355

What OpenQuestion holds

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LicenceCC BY
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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.