Evidence map›Paper›PMID 33410475›Full record

ArticleHuman molecular genetics2021

Germline variants are associated with increased primary melanoma tumor thickness at diagnosis.

Ernest Mangantig, Stuart MacGregor, Mark M Iles, Richard A Scolyer, Anne E Cust, Nicholas K Hayward, Grant W Montgomery, David L Duffy, John F Thompson, Anjali Henders and 10 more

Open access · bronzeAbstract read
In one paragraph

Article in Human molecular genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. GermlineBiomolecules · 2025
    Article
  2. Article
  3. Review
  4. Article
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

20 authors at 7 institutions in 3 countries.

Ernest MangantigRegenerative Medicine Cluster, Advanced Medical and Dental Institute, Universiti Sains Malaysia, 13200, Pulau Pinang, Malaysia.
Stuart MacGregorStatistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
Mark M IlesLeeds Institute for Data Analytics, University of Leeds, Leeds LS2 9JT, UK.
Richard A ScolyerMelanoma Institute Australia, The University of Sydney, Sydney, New South Wales, 2065, Australia.
Anne E CustMelanoma Institute Australia, The University of Sydney, Sydney, New South Wales, 2065, Australia.
Nicholas K HaywardOncogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
Grant W MontgomeryMolecular Biology, The University of Queensland, Brisbane, Queensland, 4102, Australia.
David L DuffyGenetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
John F ThompsonMelanoma Institute Australia, The University of Sydney, Sydney, New South Wales, 2065, Australia.
Anjali HendersMolecular Biology, The University of Queensland, Brisbane, Queensland, 4102, Australia.
Lisa BowdlerGenetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
Casey RoweExperimental Dermatology Group, Diamantina Institute, The University of Queensland, Brisbane, Queensland, 4102, Australia.
Gemma CadbySchool of Population and Global Health, The University of Western Australia, Perth, Western Australia, 6009, Australia.
Graham J MannMelanoma Institute Australia, The University of Sydney, Sydney, New South Wales, 2065, Australia.
David C WhitemanCancer Control, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
Georgina V LongMelanoma Institute Australia, The University of Sydney, Sydney, New South Wales, 2065, Australia.
Sarah V WardSchool of Population and Global Health, The University of Western Australia, Perth, Western Australia, 6009, Australia.
Kiarash KhosrotehraniExperimental Dermatology Group, Diamantina Institute, The University of Queensland, Brisbane, Queensland, 4102, Australia.
Jennifer H BarrettLeeds Institute for Data Analytics, University of Leeds, Leeds LS2 9JT, UK.
Matthew H LawStatistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.
QIMR Berghofer Medical Research Institute · AUThe University of Queensland · AUThe University of Sydney · AUThe University of Western Australia · AUUniversity of Leeds · GBAustralian National University · AUUniversiti Sains Malaysia · MY

Funding

Cancer Research UK C588/A19167
6 · The paper itself

Abstract

Germline genetic variants have been identified, which predispose individuals and families to develop melanoma. Tumor thickness is the strongest predictor of outcome for clinically localized primary melanoma patients. We sought to determine whether there is a heritable genetic contribution to variation in tumor thickness. If confirmed, this will justify the search for specific genetic variants influencing tumor thickness. To address this, we estimated the proportion of variation in tumor thickness attributable to genome-wide genetic variation (variant-based heritability) using unrelated patients with measured primary cutaneous melanoma thickness. As a secondary analysis, we conducted a genome-wide association study (GWAS) of tumor thickness. The analyses utilized 10 604 individuals with primary cutaneous melanoma drawn from nine GWAS datasets from eight cohorts recruited from the general population, primary care and melanoma treatment centers. Following quality control and filtering to unrelated individuals with study phenotypes, 8125 patients were used in the primary analysis to test whether tumor thickness is heritable. An expanded set of 8505 individuals (47.6% female) were analyzed for the secondary GWAS meta-analysis. Analyses were adjusted for participant age, sex, cohort and ancestry. We found that 26.6% (SE 11.9%, P = 0.0128) of variation in tumor thickness is attributable to genome-wide genetic variation. While requiring replication, a chromosome 11 locus was associated (P < 5 × 10-8) with tumor thickness. Our work indicates that sufficiently large datasets will enable the discovery of genetic variants associated with greater tumor thickness, and this will lead to the identification of host biological processes influencing melanoma growth and invasion.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyGerm-Line MutationBiomarkers, TumorHumansMelanomaPhenotypePrognosisSkin NeoplasmsSurvival RateBiomarkers, Tumor

Identifiers

PMID33410475
PMCPMC7788289
OpenAlexW3119646896

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.