致癌性变异解释器(OncoVI):致癌性指南的实施,以支持精确肿瘤学中体细胞变异的解释。

IF 3.4 3区 医学 Q1 PATHOLOGY
Maria Giulia Carta, Lars Tögel, Annett Hölsken, Christoph Schubart, Heinrich Sticht, Robert Stöhr, Silvia Spoerl, Norbert Meidenbauer, Arndt Hartmann, Paolo Magni, Florian Haller, Fulvia Ferrazzi
{"title":"致癌性变异解释器(OncoVI):致癌性指南的实施,以支持精确肿瘤学中体细胞变异的解释。","authors":"Maria Giulia Carta, Lars Tögel, Annett Hölsken, Christoph Schubart, Heinrich Sticht, Robert Stöhr, Silvia Spoerl, Norbert Meidenbauer, Arndt Hartmann, Paolo Magni, Florian Haller, Fulvia Ferrazzi","doi":"10.1016/j.jmoldx.2026.03.004","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50128,"journal":{"name":"Journal of Molecular Diagnostics","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Oncogenicity Variant Interpreter: Oncogenicity Guidelines Implementation to Support Somatic Variants Interpretation in Precision Oncology.\",\"authors\":\"Maria Giulia Carta, Lars Tögel, Annett Hölsken, Christoph Schubart, Heinrich Sticht, Robert Stöhr, Silvia Spoerl, Norbert Meidenbauer, Arndt Hartmann, Paolo Magni, Florian Haller, Fulvia Ferrazzi\",\"doi\":\"10.1016/j.jmoldx.2026.03.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":50128,\"journal\":{\"name\":\"Journal of Molecular Diagnostics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2026-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Diagnostics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jmoldx.2026.03.004\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Diagnostics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jmoldx.2026.03.004","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

准确和可重复的体细胞变异解释是癌症患者治疗决策的基础。为了协调和自动化致癌性分类,开发了基于python的开源ClinGen/CGC/VICC致癌性指南的致癌性变异解释器(OncoVI)。对于每个指南标准,文本描述都被解释,并确定了公开可用的资源作为参考。从变异的基因组坐标出发,OncoVI自动进行功能标注,从整合资源中收集相关证据,对各项标准进行评估,并给出最终的致瘤性分类。在指南提供的93种体细胞变异的金标准集上,OncoVI的准确率达到80%,对致癌/可能致癌变异的灵敏度为88%。当应用于先前由分子肿瘤委员会(MTB) Erlangen评估的557名参与者的7,802个变体时,OncoVI与先前MTB对变异对蛋白质功能影响的评估显示出79%的一致性。此外,专家根据致癌性指南对135种MTB变体进行了重新评估,进一步确认了OncoVI实施的有效性和已确定资源的适当性。综上所述,OncoVI为跨机构体细胞变异的统一和可重复的致癌性分类提供了重要支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Oncogenicity Variant Interpreter: Oncogenicity Guidelines Implementation to Support Somatic Variants Interpretation in Precision Oncology.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.10
自引率
2.40%
发文量
143
审稿时长
43 days
期刊介绍: The Journal of Molecular Diagnostics, the official publication of the Association for Molecular Pathology (AMP), co-owned by the American Society for Investigative Pathology (ASIP), seeks to publish high quality original papers on scientific advances in the translation and validation of molecular discoveries in medicine into the clinical diagnostic setting, and the description and application of technological advances in the field of molecular diagnostic medicine. The editors welcome for review articles that contain: novel discoveries or clinicopathologic correlations including studies in oncology, infectious diseases, inherited diseases, predisposition to disease, clinical informatics, or the description of polymorphisms linked to disease states or normal variations; the application of diagnostic methodologies in clinical trials; or the development of new or improved molecular methods which may be applied to diagnosis or monitoring of disease or disease predisposition.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书