Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer
Objective Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance...
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doaj-98ddadfdad874cbf99c15c5ec5afd03d2021-04-02T16:07:49ZengElsevierESMO Open2059-70292020-10-015510.1136/esmoopen-2020-000872Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancerHarry J M Groen0Qing Zhou1Ellen Heitzer2Michael R Speicher3Ed Schuuring4Samantha O Perakis5Sabrina Weber6Ricarda Graf7Sabine Hojas8Jakob M Riedl9Armin Gerger10Nadia Dandachi11Marija Balic12Gerald Hoefler13Jochen B Geigl14Department of Pulmonary Diseases, University of Groningen, University Medical Centre Groningen, Groningen, NetherlandsInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaDepartment of Pathology, University of Groningen, University Medical Centre Groningen, Groningen, NetherlandsInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaDepartment of Internal Medicine, LKH Fuerstenfeld, Fuerstenfeld, AustriaDepartment of Internal Medicine, Division of Oncology, Medical University of Graz, Graz, AustriaDepartment of Internal Medicine, Division of Oncology, Medical University of Graz, Graz, AustriaDepartment of Internal Medicine, Division of Oncology, Medical University of Graz, Graz, AustriaDepartment of Internal Medicine, Division of Oncology, Medical University of Graz, Graz, AustriaInstitute of Pathology, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaInstitute of Human Genetics, Diagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, AustriaObjective Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).Methods In order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.Results Each platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.Conclusions Treatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.https://esmoopen.bmj.com/content/5/5/e000872.full |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Harry J M Groen Qing Zhou Ellen Heitzer Michael R Speicher Ed Schuuring Samantha O Perakis Sabrina Weber Ricarda Graf Sabine Hojas Jakob M Riedl Armin Gerger Nadia Dandachi Marija Balic Gerald Hoefler Jochen B Geigl |
spellingShingle |
Harry J M Groen Qing Zhou Ellen Heitzer Michael R Speicher Ed Schuuring Samantha O Perakis Sabrina Weber Ricarda Graf Sabine Hojas Jakob M Riedl Armin Gerger Nadia Dandachi Marija Balic Gerald Hoefler Jochen B Geigl Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer ESMO Open |
author_facet |
Harry J M Groen Qing Zhou Ellen Heitzer Michael R Speicher Ed Schuuring Samantha O Perakis Sabrina Weber Ricarda Graf Sabine Hojas Jakob M Riedl Armin Gerger Nadia Dandachi Marija Balic Gerald Hoefler Jochen B Geigl |
author_sort |
Harry J M Groen |
title |
Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
title_short |
Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
title_full |
Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
title_fullStr |
Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
title_full_unstemmed |
Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
title_sort |
comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer |
publisher |
Elsevier |
series |
ESMO Open |
issn |
2059-7029 |
publishDate |
2020-10-01 |
description |
Objective Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).Methods In order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.Results Each platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.Conclusions Treatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine. |
url |
https://esmoopen.bmj.com/content/5/5/e000872.full |
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