Deborah Ritter , Dmitriy Sonkin , Malachi Griffith , Obi Griffith , Dean Pavlick , Jason Saliba , Morteza Seifi , Gordana Raca , Jason Rosenbaum , Somak Roy , Alex Wagner , Shashikant Kulkarni , Marilyn Li , Sharon E. Plon
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For example, Histone H3 SC-VCEP highlighted the need to incorporate classic phenotypes by creating a supporting evidence code (OP5). The CVI requested testing phenotype specificity within OP2, leading to developing recommendations on OP2 extended use. Conversely, if SC-VCEPs specify thresholds or alternative databases for cancer hotspots, these specifications are within the SC-VCEP scope and are not general CVI recommendations or modifications to the Oncogenicity SOP.</div><div>Additional work includes CVI developing guidance for using in-silico predictors (OP1). We are investigating two commonly used predictors - REVEL and FATHMM - that operate by distinct random forest ensemble prediction algorithms and the Hidden Markov model, respectively. On a small variant set from the Oncogenicity SOP manuscript, manually curated 'true' oncogenic GOF and LOF variants displayed modest but significant differences in REVEL scores and larger differences in FATHMM, with potential discriminatory applications. We will report on scaling this comparison as well as general-use considerations. In addition, we share updates and seek community feedback on incorporating detailed functional data (OS2) in the Oncogenicity SOP as well as considering structured text for the curation of resistance variants.</div></div>","PeriodicalId":49225,"journal":{"name":"Cancer Genetics","volume":"286 ","pages":"Page S22"},"PeriodicalIF":1.4000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"68. 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On a small variant set from the Oncogenicity SOP manuscript, manually curated 'true' oncogenic GOF and LOF variants displayed modest but significant differences in REVEL scores and larger differences in FATHMM, with potential discriminatory applications. We will report on scaling this comparison as well as general-use considerations. 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68. ClinGen Cancer Variant Interpretation (CVI): Updates and recommendations on the ClinGen/CGC/VICC Oncogenicity SOP
The Clinical Genome Resource (ClinGen) Somatic Cancer Variant Interpretation Committee (CVI) provides oversight and recommendations in the expert panel process for ClinGen Somatic Cancer Variant Curation Expert Panels (SC-VCEPs). SC-VCEP use of the Oncogenicity SOP (PMID: 35101336) provides critical clarity where modifications (SOP changes), recommendations (CVI guidance), or specifications (SC-VCEP gene/cancer-specific use) are needed. We summarize SC-VCEP Oncogenicity SOP use informing guideline development. For example, Histone H3 SC-VCEP highlighted the need to incorporate classic phenotypes by creating a supporting evidence code (OP5). The CVI requested testing phenotype specificity within OP2, leading to developing recommendations on OP2 extended use. Conversely, if SC-VCEPs specify thresholds or alternative databases for cancer hotspots, these specifications are within the SC-VCEP scope and are not general CVI recommendations or modifications to the Oncogenicity SOP.
Additional work includes CVI developing guidance for using in-silico predictors (OP1). We are investigating two commonly used predictors - REVEL and FATHMM - that operate by distinct random forest ensemble prediction algorithms and the Hidden Markov model, respectively. On a small variant set from the Oncogenicity SOP manuscript, manually curated 'true' oncogenic GOF and LOF variants displayed modest but significant differences in REVEL scores and larger differences in FATHMM, with potential discriminatory applications. We will report on scaling this comparison as well as general-use considerations. In addition, we share updates and seek community feedback on incorporating detailed functional data (OS2) in the Oncogenicity SOP as well as considering structured text for the curation of resistance variants.
期刊介绍:
The aim of Cancer Genetics is to publish high quality scientific papers on the cellular, genetic and molecular aspects of cancer, including cancer predisposition and clinical diagnostic applications. Specific areas of interest include descriptions of new chromosomal, molecular or epigenetic alterations in benign and malignant diseases; novel laboratory approaches for identification and characterization of chromosomal rearrangements or genomic alterations in cancer cells; correlation of genetic changes with pathology and clinical presentation; and the molecular genetics of cancer predisposition. To reach a basic science and clinical multidisciplinary audience, we welcome original full-length articles, reviews, meeting summaries, brief reports, and letters to the editor.