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Bamba-Funck J, Fabre EE, Kambouchner M, Schischmanoff O. Performance Characteristics of Oncomine Focus Assay for Theranostic Analysis of Solid Tumors, A (21-Months) Real-Life Study. Diagnostics (Basel) 2023; 13:diagnostics13050937. [PMID: 36900081 PMCID: PMC10001101 DOI: 10.3390/diagnostics13050937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 03/06/2023] Open
Abstract
Next generation sequencing analysis is crucial for therapeutic decision in various solid tumor contexts. The sequencing method must remain accurate and robust throughout the instrument lifespan allowing the biological validation of patients' results. This study aims to evaluate the long-term sequencing performances of the Oncomine Focus assay kit allowing theranostic DNA and RNA variants detection on the Ion S5XL instrument. We evaluated the sequencing performances of 73 consecutive chips over a 21-month period and detailed the sequencing data obtained from both quality controls and clinical samples. The metrics describing sequencing quality remained stable throughout the study. We showed that an average of 11 × 106 (±0.3 × 106) reads were obtained using a 520 chip leading to an average of 6.0 × 105 (±2.6 × 105) mapped reads per sample. Of 400 consecutive samples, 95.8 ± 16% of amplicons reached the depth threshold of 500X. Slight modifications of the bioinformatics workflow improved DNA analytical sensitivity and allowed the systematic detection of expected SNV, indel, CNV, and RNA alterations in quality controls samples. The low inter-run variability of DNA and RNA-even at low variant allelic fraction, amplification factor, or reads counts-indicated that our method was adapted to clinical practice. The analysis of 429 clinical DNA samples indicated that the modified bioinformatics workflow allowed detection of 353 DNA variants and 88 gene amplifications. RNA analysis of 55 clinical samples revealed 7 alterations. This is the first study showing the long-term robustness of the Oncomine Focus assay in clinical routine practice.
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Affiliation(s)
- Jessica Bamba-Funck
- Laboratory of Biochemistry, Hôpital Avicenne, Hôpitaux Universitaires Paris-Seine-Saint-Denis, Assistance Publique—Hôpitaux de Paris, F-93000 Bobigny, France
- Laboratory for Vascular Translational Science, LVTS, UMR INSERM 1148, UFR SMBH, Université Sorbonne Paris Nord, F-93000 Bobigny, France
- Correspondence: (J.B.-F.); (O.S.); Tel.: +33-1-4895-7827 (O.S.)
| | - Emmanuelle E. Fabre
- Laboratory of Biochemistry, Hôpital Avicenne, Hôpitaux Universitaires Paris-Seine-Saint-Denis, Assistance Publique—Hôpitaux de Paris, F-93000 Bobigny, France
- Signaling, Microenvironment and B Cell Malignancies, SIMEL, UMR INSERM U978, UFR SMBH, Université Sorbonne Paris Nord, 8, F-93000 Bobigny, France
| | - Marianne Kambouchner
- Department of Pathology, Hôpital Avicenne, Hôpitaux Universitaires Paris-Seine-Saint-Denis, Assistance Publique—Hôpitaux de Paris, F-93000 Bobigny, France
| | - Olivier Schischmanoff
- Laboratory of Biochemistry, Hôpital Avicenne, Hôpitaux Universitaires Paris-Seine-Saint-Denis, Assistance Publique—Hôpitaux de Paris, F-93000 Bobigny, France
- Signaling, Microenvironment and B Cell Malignancies, SIMEL, UMR INSERM U978, UFR SMBH, Université Sorbonne Paris Nord, 8, F-93000 Bobigny, France
- Correspondence: (J.B.-F.); (O.S.); Tel.: +33-1-4895-7827 (O.S.)
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Li MM, Cottrell CE, Pullambhatla M, Roy S, Temple-Smolkin RL, Turner SA, Wang K, Zhou Y, Vnencak-Jones CL. Assessments of Somatic Variant Classification Using the Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists Guidelines: A Report from the Association for Molecular Pathology. J Mol Diagn 2023; 25:69-86. [PMID: 36503149 DOI: 10.1016/j.jmoldx.2022.11.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 11/09/2022] [Accepted: 11/18/2022] [Indexed: 12/13/2022] Open
Abstract
To assess the clinical implementation of the 2017 Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists, identify content that may result in classification inconsistencies, and evaluate implementation barriers, an Association for Molecular Pathology Working Group conducted variant interpretation challenges and a guideline implementation survey. A total of 134 participants participated in the variant interpretation challenges, consisting of 11 variants in four cancer cases. Results demonstrate 86% (range, 54% to 94%) of the respondents correctly classified clinically significant variants, variants of uncertain significance, and benign/likely benign variants; however, only 59% (range, 39% to 84%) of responses agreed with the working group's consensus intended responses regarding both tiers and categories of clinical significance. In the implementation survey, 71% (157/220) of respondents have implemented the 2017 guidelines for variant classification and reporting either with or without modifications. Collectively, this study demonstrates that, although they may not yet be optimized, the 2017 guideline recommendations are being adopted for standardized somatic variant classification. The working group identified significant areas for future guideline improvement, including the need for a more granular and comprehensive classification system and education resources to meet the growing needs of both laboratory professionals and medical oncologists.
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Affiliation(s)
- Marilyn M Li
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
| | - Catherine E Cottrell
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio; Department of Pathology, The Ohio State University College of Medicine, Columbus, Ohio
| | | | - Somak Roy
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | | | - Scott A Turner
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Virginia Commonwealth University, Richmond, Virginia
| | - Kai Wang
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania; Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Yunyun Zhou
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Cindy L Vnencak-Jones
- The Variant Interpretation Testing Across Laboratories (VITAL) Somatic Working Group of the Clinical Practice Committee, Association for Molecular Pathology, Rockville, Maryland; Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
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An Independent Assessment of a Commercial Clinical Interpretation Software Indicates That Software Can Mitigate Variation in Human Assessment. JOURNAL OF MOLECULAR PATHOLOGY 2022. [DOI: 10.3390/jmp3030012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Comprehensive next-generation sequencing (NGS) panels for cancer diagnostics create a bottleneck for interpretation. QIAGEN Clinical Insights Interpret One (QCI) is a clinical decision support software that supports molecular pathologists in the classification of oncology-related variants. This study compares variant assessments by QCI to assessments utilizing current laboratory methods. Eight laboratories were recruited by the external quality assessment organization GenQA. The laboratories submitted VCFs from sequencing studies performed on both hematological disorders and solid tumors for analysis by QCI and an independent laboratory. Results were compared and conflicts were resolved using a panel of experts. In total, 14/149 variants (9%) reported as Tier 1 or Tier 2 by either QCI or the submitting laboratory were found to be discordant after expert panel review. In contrast, 41/149 variants (28%) reflected discrepancy among human reviewers. The expert panel was unable to reach resolution on eight variants. QCI demonstrates high concordance in the classification of actionable mutations with independent laboratory methods and expert assessment. The rate of disagreement among laboratories and the expert panel was greater than the disagreement between QCI and expert assessment. Disagreement among experts highlights the subjectivity of classifying variants. The study demonstrates that QCI interpretation supports streamlining and standardization of NGS variant interpretation.
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From Information Overload to Actionable Insights: Digital Solutions for Interpreting Cancer Variants from Genomic Testing. JOURNAL OF MOLECULAR PATHOLOGY 2021. [DOI: 10.3390/jmp2040027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Given the increase in genomic testing in routine clinical use, there is a growing need for digital technology solutions to assist pathologists, oncologists, and researchers in translating variant calls into actionable knowledge to personalize patient management plans. In this article, we discuss the challenges facing molecular geneticists and medical oncologists in working with test results from next-generation sequencing for somatic oncology, and propose key considerations for implementing a decision support software to aid the interpretation of clinically important variants. In addition, we review results from an example decision support software, NAVIFY Mutation Profiler. NAVIFY Mutation Profiler is a cloud-based software that provides curation, annotation, interpretation, and reporting of somatic variants identified by next-generation sequencing. The software reports a tiered classification based on consensus recommendations from AMP, ASCO, CAP, and ACMG. Studies with NAVIFY Mutation Profiler demonstrated that the software provided timely updates and accurate curation, as well as interpretation of variant combinations, demonstrating that decision support tools can help advance implementation of precision oncology.
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Giles HH, Hegde MR, Lyon E, Stanley CM, Kerr ID, Garlapow ME, Eggington JM. The Science and Art of Clinical Genetic Variant Classification and Its Impact on Test Accuracy. Annu Rev Genomics Hum Genet 2021; 22:285-307. [PMID: 33900788 DOI: 10.1146/annurev-genom-121620-082709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Clinical genetic variant classification science is a growing subspecialty of clinical genetics and genomics. The field's continued improvement is essential for the success of precision medicine in both germline (hereditary) and somatic (oncology) contexts. This review focuses on variant classification for DNA next-generation sequencing tests. We first summarize current limitations in variant discovery and definition, and then describe the current five- and four-tier classification systems outlined in dominant standards and guideline publications for germline and somatic tests, respectively. We then discuss measures of variant classification discordance and the field's bias for positive results, as well as considerations for panel size and population screening in the context of estimates of positive predictive value thatincorporate estimated variant classification imperfections. Finally, we share opinions on the current state of variant classification from some of the authors of the most widely used standards and guideline publications and from other domain experts.
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Affiliation(s)
- Hunter H Giles
- Center for Genomic Interpretation, Sandy, Utah 84092, USA; , ,
| | - Madhuri R Hegde
- PerkinElmer Genomics, Waltham, Massachusetts 02450, USA; .,Department of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Elaine Lyon
- HudsonAlpha Clinical Services Lab, Huntsville, Alabama 35806, USA;
| | - Christine M Stanley
- C2i Genomics, Cambridge, Massachusetts 02139, USA.,Variantyx, Framingham, Massachusetts 01701, USA;
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Yaung SJ, Krishna S, Xi L, Ju C, Palma JF, Schmid M. Assessment of a Highly Curated Somatic Oncology Database to Aid in the Interpretation of Clinically Important Variants in Next-Generation Sequencing Results. J Mol Diagn 2020; 22:1356-1366. [PMID: 32961319 DOI: 10.1016/j.jmoldx.2020.08.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 08/02/2020] [Accepted: 08/17/2020] [Indexed: 12/29/2022] Open
Abstract
This study evaluated the accuracy of NAVIFY Mutation Profiler, a cloud-based CE-IVD software that aids in interpreting clinically relevant variants detected in somatic oncology next-generation sequencing tests. This tool reports tiered classifications based on different levels of clinical evidence from a highly curated, regularly updated database derived from medical guidelines, drug approvals, and peer-reviewed literature. A retrospective analysis was performed on next-generation sequencing results from 37 lung cancer cases treated with chemotherapy (n = 10), EGFR tyrosine kinase inhibitor (TKI) (n = 5), or ALK TKI (n = 22). Several aspects were assessed, including accuracy of interpretation compared with manual curation, validity of curation content updates over time, and agreement with public databases. For chemotherapy cases with no targetable biomarkers, NAVIFY Mutation Profiler did not identify any targeted therapies. In EGFR and ALK TKI cases, the software associated appropriate targeted therapies and accurately interpreted variant combinations containing drug-resistance variants. Of the nine unique ALK mutations conferring resistance to crizotinib, NAVIFY Mutation Profiler provided correct annotation for nine of nine mutations, whereas OncoKB and Catalogue of Somatic Mutations in Cancer indicated crizotinib resistance for eight of nine mutations. Of all 145 variants analyzed, there was substantial agreement (Cohen κ = 0.62) between NAVIFY Mutation Profiler and OncoKB for classifying actionable mutations. Furthermore, NAVIFY Mutation Profiler presented accurate targeted therapies across different regions (eg, European Union versus Canada) and remained up-to-date with evolving regional approvals and medical guidelines.
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Affiliation(s)
- Stephanie J Yaung
- Medical and Scientific Affairs, Roche Sequencing Solutions, Inc., Pleasanton, California.
| | - Shuba Krishna
- Bioinformatics Research and Early Development, Roche Sequencing Solutions, Inc., Belmont, California
| | - Liu Xi
- Bioinformatics Development, Roche Sequencing Solutions, Inc., Pleasanton, California
| | - Christine Ju
- Clinical Operations and Biometrics, Roche Sequencing Solutions, Inc., Pleasanton, California
| | - John F Palma
- Medical and Scientific Affairs, Roche Sequencing Solutions, Inc., Pleasanton, California
| | - Maximilian Schmid
- Medical and Scientific Affairs, Roche Sequencing Solutions, Inc., Pleasanton, California
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Rao S, Pitel B, Wagner AH, Boca SM, McCoy M, King I, Gupta S, Park BH, Warner JL, Chen J, Rogan PK, Chakravarty D, Griffith M, Griffith OL, Madhavan S. Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices. JCO Clin Cancer Inform 2020; 4:602-613. [PMID: 32644817 PMCID: PMC7397775 DOI: 10.1200/cci.19.00169] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2020] [Indexed: 12/17/2022] Open
Abstract
PURPOSE The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade. Many informatics efforts focused on genomic interpretation resources for neoplasms are underway to support data collection, deposition, curation, harmonization, integration, and analytics to support case review and treatment planning. METHODS In this review, we evaluate and summarize the landscape of available tools, resources, and evidence used in the evaluation of somatic and germline tumor variants within the context of molecular tumor boards. RESULTS Molecular tumor boards (MTBs) are collaborative efforts of multidisciplinary cancer experts equipped with genomic interpretation resources to aid in the delivery of accurate and timely clinical interpretations of complex genomic results for each patient, within an institution or hospital network. Virtual MTBs (VMTBs) provide an online forum for collaborative governance, provenance, and information sharing between experts outside a given hospital network with the potential to enhance MTB discussions. Knowledge sharing in VMTBs and communication with guideline-developing organizations can lead to progress evidenced by data harmonization across resources, crowd-sourced and expert-curated genomic assertions, and a more informed and explainable usage of artificial intelligence. CONCLUSION Advances in cancer genomics interpretation aid in better patient and disease classification, more streamlined identification of relevant literature, and a more thorough review of available treatments and predicted patient outcomes.
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Affiliation(s)
- Shruti Rao
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC
| | - Beth Pitel
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Alex H. Wagner
- McDonnell Genome Institute and Department of Medicine, Washington University School of Medicine, St Louis, MO
| | - Simina M. Boca
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC
| | - Matthew McCoy
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC
| | - Ian King
- Laboratory Medicine Program, University Health Network and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Samir Gupta
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC
| | - Ben Ho Park
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Jeremy L. Warner
- Departments of Medicine and Biomedical Informatics, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - James Chen
- Division of Medical Oncology, Department of Biomedical Informatics, The Ohio State University, Columbus, OH
| | - Peter K. Rogan
- Departments of Biochemistry and Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Debyani Chakravarty
- Kravis Center of Molecular Oncology, Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Malachi Griffith
- McDonnell Genome Institute and Department of Medicine, Washington University School of Medicine, St Louis, MO
| | - Obi L. Griffith
- McDonnell Genome Institute and Department of Medicine, Washington University School of Medicine, St Louis, MO
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC
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Assessment of significant procedures in multigene molecular detection for breast cancer in clinical laboratories: from variant detection to targeted therapy. Breast Cancer 2019; 27:111-121. [PMID: 31388961 DOI: 10.1007/s12282-019-01000-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 08/01/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND In recent years, numerous novel targeted drugs against breast cancer have been developed because of the rapid progress in multigene molecular testing based on next-generation sequencing (NGS). However, it is a great challenge for clinicians to update the drug information timely, therefore necessitating that clinical laboratories provide adequate and comprehensive targeted drugs information to clinicians as a reference. The premise of providing this information is the accuracy of variant detection. Our study aimed to assess the entire process of variant detection, interpretation, and targeted therapy. METHODS Laboratories were instructed to use routine methods for variant detection. The results were evaluated based on a predefined score system, and differences in variant interpretation were analyzed. Targeted drug information provided by laboratories was also summarized, and its accuracy and sufficiency were assessed. RESULTS Overall, 90.1% (82/91) of the laboratories produced accurate results. 78.9% (15/19) of the errors were false positives or false negatives. Incorrect and insufficient drug information was mainly provided due to failure in timely database updating, inconsistencies with the detected mutations or given clinical information, and negligence during phase I clinical trials. To prioritize providing targeted drug information, laboratories collected data were based on different factors, including variant clinical significance, allele frequency, and variant positions in the signal pathway. CONCLUSION The variant detection capability was satisfactory, but the ability to provide accuracy and comprehensive targeted drug information should be urgently improved. Our study summarized a completed NGS-based multigene molecular detection pipeline, aiming to better inform precision treatment for breast cancer patients.
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