Hans-Peter Adams , Matthew C. Hiemenz , Kay Hertel , Frederike Fuhlbrück , Mara Thomas , James Oughton , Helle Sorensen , Ulrich Schlecht , Justin M. Allen , Martina Cantone , Sophie Osswald , David Gonzalez , Eli Pikarsky , Muriel De Vos , Ed Schuuring , Thomas Wieland
{"title":"两种市售内部组织综合基因组图谱分析解决方案的结果比较:仅供研究使用的 AVENIO 肿瘤组织综合基因组图谱分析试剂盒和 TruSight Oncology 500 分析法","authors":"Hans-Peter Adams , Matthew C. Hiemenz , Kay Hertel , Frederike Fuhlbrück , Mara Thomas , James Oughton , Helle Sorensen , Ulrich Schlecht , Justin M. Allen , Martina Cantone , Sophie Osswald , David Gonzalez , Eli Pikarsky , Muriel De Vos , Ed Schuuring , Thomas Wieland","doi":"10.1016/j.jmoldx.2024.08.001","DOIUrl":null,"url":null,"abstract":"<div><div>Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants, copy number alterations, rearrangements, tumor mutational burden, and microsatellite instability, including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for short variant, known gene fusion, and microsatellite instability detection. Important differences were obtained in tumor mutational burden scoring, copy number alteration detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results.</div></div>","PeriodicalId":50128,"journal":{"name":"Journal of Molecular Diagnostics","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Results from Two Commercially Available In-House Tissue-Based Comprehensive Genomic Profiling Solutions\",\"authors\":\"Hans-Peter Adams , Matthew C. Hiemenz , Kay Hertel , Frederike Fuhlbrück , Mara Thomas , James Oughton , Helle Sorensen , Ulrich Schlecht , Justin M. Allen , Martina Cantone , Sophie Osswald , David Gonzalez , Eli Pikarsky , Muriel De Vos , Ed Schuuring , Thomas Wieland\",\"doi\":\"10.1016/j.jmoldx.2024.08.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants, copy number alterations, rearrangements, tumor mutational burden, and microsatellite instability, including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for short variant, known gene fusion, and microsatellite instability detection. Important differences were obtained in tumor mutational burden scoring, copy number alteration detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results.</div></div>\",\"PeriodicalId\":50128,\"journal\":{\"name\":\"Journal of Molecular Diagnostics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-09-11\",\"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://www.sciencedirect.com/science/article/pii/S1525157824001946\",\"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://www.sciencedirect.com/science/article/pii/S1525157824001946","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
Comparison of Results from Two Commercially Available In-House Tissue-Based Comprehensive Genomic Profiling Solutions
Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants, copy number alterations, rearrangements, tumor mutational burden, and microsatellite instability, including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for short variant, known gene fusion, and microsatellite instability detection. Important differences were obtained in tumor mutational burden scoring, copy number alteration detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results.
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.