Evidence map›Paper›PMID 41339070›Full record

ArticleJournal of medical genetics2026

Association for Clinical Genomic Science (ACGS) guidelines for the classification of oncogenicity of somatic variants in cancer: recommendations by the UK somatic variant interpretation group (SVIG-UK).

George J Burghel, Joanne Mason, Kevin Baker, Kate Moloney, Claire Holt McKeeve, Ashley Cartwright, Ana M Brás-Goldberg, Debbie Travis, Siân Lewis, Jennifer A Fairley and 4 more

Abstract read
In one paragraph

Article in Journal of medical genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Guideline
  2. Article
  3. Article
  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

14 authors.

George J Burghel *North West Genomic Laboratory Hub, Manchester University NHS Foundation Trust, Manchester, UK George.Burghel@mft.nhs.uk.ORCID http://orcid.org/0000-0001-9360-8194
Joanne Mason *West Midlands Genomics Laboratory, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
Kevin Baker *Wessex Genomics Laboratory Service (Salisbury), University Hospital Southampton NHS Foundation Trust, Southampton, UK.
Kate Moloney *Wessex Genomics Laboratory Service (Salisbury), University Hospital Southampton NHS Foundation Trust, Southampton, UK.
Claire Holt McKeeveWest of Scotland Centre for Genomic Medicine, NHS Greater Glasgow and Clyde, Glasgow, UK.
Ashley CartwrightUK NEQAS for Leucocyte Immunophenotyping, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Ana M Brás-GoldbergWest Midlands Genomics Laboratory, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
Debbie TravisUK NEQAS for Leucocyte Immunophenotyping, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
Siân LewisAll Wales Medical Genetics Service, Cardiff, UK.
Jennifer A FairleyGenQA, Edinburgh, UK.
Jonathan WilliamsOxford Medical Genetics Laboratories, Oxford, UK.
Kirsty RussellGenomics England Limited, London, UK.
Suzanne MacMahonCentre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK.
Christopher Wragg *Bristol Genetics Laboratory, North Bristol NHS Trust South West Genomic Laboratory Hub, Bristol, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comprehensive genomic testing in routine cancer care pathways has created the need to interpret the consequences of somatic (acquired) genomic variants beyond the currently well-characterised driver variants in cancer gene hotspots. While several guidelines have been published to determine the oncogenicity of somatic cancer gene variants, they lack a comprehensive and flexible approach that encompasses all available lines of evidence. Individual UK laboratories have developed local approaches to standardise somatic variant interpretation, often based on different sets of published guidelines, but a comprehensive national standardised framework is lacking. The absence of standardisation in approaches to somatic variant interpretation highlights a significant gap in the field of genomic medicine within the UK healthcare system. Key stakeholders from across the UK cancer genomics diagnostic community formed the UK Somatic Variant Interpretation Group (SVIG-UK) in September 2018 to develop a consensus approach for interpretation of somatic variants identified through genomic testing in patients with solid tumours and haematological malignancies. SVIG-UK scientists conducted a review of existing somatic variant interpretation classification systems and although they mostly agreed on evidence sources for variant interpretation, differences were identified in how the evidence should be used, weighted and combined. The SVIG-UK team subsequently developed a single, standardised UK-wide approach to somatic variant interpretation which encompassed both solid tumour and haematological cancer genomic testing. This framework was shared with stakeholders across the UK alongside variants for preliminary testing. Outcomes were then reviewed and following engagement sessions across the community, the variant interpretation recommendations were updated and ratified by the UK Association of Clinical Genomics Sciences. We present herein the SVIG-UK framework and recommendations, which provide a standardised, comprehensive and flexible approach for classifying the oncogenicity of somatic variants in cancer genes.

Indexed as

CarcinogenesisGenetic VariationGenomicsNeoplasmsGenetic TestingHumansMutationPractice Guidelines as TopicUnited KingdomGeneticsGenomics

Identifiers

PMID41339070
PMCPMC13018753

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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.