Evidence map›Paper›PMID 41936821›Full record

ArticleThe Journal of molecular diagnostics : JMD2026

Oncogenicity Variant Interpreter (OncoVI) Supports Harmonized Somatic Variant Interpretation in Precision Oncology.

Maria Giulia Carta, Lars Tögel, Annett Hölsken, Christoph Schubart, Heinrich Sticht, Robert Stöhr, Silvia Spoerl, Norbert Meidenbauer, Arndt Hartmann, Paolo Magni and 2 more

Abstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

12 authors.

Maria Giulia CartaInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany; Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Lars TögelInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany.
Annett HölskenInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany.
Christoph SchubartInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany.
Heinrich StichtInstitute of Biochemistry, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Robert StöhrInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany.
Silvia SpoerlComprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany; Department of Internal Medicine 5, Hematology and Oncology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Norbert MeidenbauerComprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany; Department of Internal Medicine 5, Hematology and Oncology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Arndt HartmannInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany.
Paolo MagniDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Florian HallerInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany.
Fulvia FerrazziInstitute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany; Bavarian Cancer Research Centre, Erlangen, Germany; Center for Personalized Medicine, Erlangen, Germany; Department of Nephropathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. Electronic address: fulvia.ferrazzi@uk-erlangen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and reproducible interpretation of somatic variants is fundamental for therapy decision-making in patients with cancer. To harmonize and automate oncogenicity classification, Oncogenicity Variant Interpreter (OncoVI), an open-source, Python-based implementation of the Clinical Genome Resource/Cancer Genomics Consortium/Variant Interpretation for Cancer Consortium oncogenicity guidelines, was developed. For each of the guideline criteria, the textual descriptions were interpreted, and publicly available resources were identified to be used as reference. Starting from the genomic coordinates of a variant, OncoVI automatically performs functional annotation, collects relevant evidence from the integrated resources, evaluates each criterion, and provides a final oncogenicity classification. OncoVI achieved an accuracy of 80% on a gold standard set of 93 somatic variants provided by the guidelines, with a sensitivity of 88% for oncogenic/likely oncogenic variants. When applied to a real-world set of 7802 variants from 557 participants previously evaluated by the Molecular Tumor Board (MTB) Erlangen, OncoVI showed 79% concordance with the prior MTB assessment of variant impact on protein function. In addition, expert reassessment of 135 MTB variants, conducted in accordance with the oncogenicity guidelines, further confirmed both the validity of OncoVI implementation and the appropriateness of the identified resources. Taken together, OncoVI provides significant support for the harmonized and reproducible oncogenicity classification of somatic variants across institutions.

Indexed as

Genetic VariationMedical OncologyNeoplasmsOncogenesPrecision MedicineSoftwareComputational BiologyGenomicsHumansMutation

Identifiers

PMID41936821
PMCPMC13269341

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.