Volume 145, Issue 11 pp. 2996-3010
Cancer Genetics and Epigenetics

Variant classification in precision oncology

Jonas Leichsenring

Jonas Leichsenring

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

J.L. and P.H. shared first authorshipSearch for more papers by this author
Peter Horak

Peter Horak

National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany

German Cancer Consortium (DKTK), Heidelberg, Germany

J.L. and P.H. shared first authorshipSearch for more papers by this author
Simon Kreutzfeldt

Simon Kreutzfeldt

National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany

German Cancer Consortium (DKTK), Heidelberg, Germany

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Christoph Heining

Christoph Heining

National Center for Tumor Diseases (NCT), Dresden, Germany

University Hospital Carl Gustav Carus, Dresden, Germany

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Petros Christopoulos

Petros Christopoulos

Thoraxklinik, Heidelberg, Germany

Translational Lung Cancer Research Heidelberg (TLCR-H), German Center for Lung Research (DZL), Giessen, Germany

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Anna-Lena Volckmar

Anna-Lena Volckmar

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Olaf Neumann

Olaf Neumann

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Martina Kirchner

Martina Kirchner

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Carolin Ploeger

Carolin Ploeger

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Jan Budczies

Jan Budczies

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Christoph E. Heilig

Christoph E. Heilig

National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany

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Barbara Hutter

Barbara Hutter

German Cancer Research Center (DKFZ), Heidelberg, Germany

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Martina Fröhlich

Martina Fröhlich

German Cancer Research Center (DKFZ), Heidelberg, Germany

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Sebastian Uhrig

Sebastian Uhrig

German Cancer Research Center (DKFZ), Heidelberg, Germany

Faculty of Biosciences, Heidelberg University, Heidelberg, Germany

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Daniel Kazdal

Daniel Kazdal

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Michael Allgäuer

Michael Allgäuer

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Alexander Harms

Alexander Harms

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Eugen Rempel

Eugen Rempel

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Ulrich Lehmann

Ulrich Lehmann

Institute of Pathology, Hannover Medical School, Hanover, Germany

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Michael Thomas

Michael Thomas

Thoraxklinik, Heidelberg, Germany

Translational Lung Cancer Research Heidelberg (TLCR-H), German Center for Lung Research (DZL), Giessen, Germany

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Nicole Pfarr

Nicole Pfarr

Institute of Pathology, Technische Universität München, Munich, Germany

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Ninel Azoitei

Ninel Azoitei

Clinic of Internal Medicine I, University Hospital Ulm, Ulm, Germany

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Irina Bonzheim

Irina Bonzheim

Institute of Pathology, University Hospital Tübingen, Tübingen, Germany

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Ralf Marienfeld

Ralf Marienfeld

Institute of Pathology, University Hospital Ulm, Ulm, Germany

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Peter Möller

Peter Möller

Institute of Pathology, University Hospital Ulm, Ulm, Germany

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Martin Werner

Martin Werner

Institute of Pathology, Medical Center, University of Freiburg, Breisgau, Germany

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Falko Fend

Falko Fend

Institute of Pathology, University Hospital Tübingen, Tübingen, Germany

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Melanie Boerries

Melanie Boerries

German Cancer Consortium (DKTK), Heidelberg, Germany

German Cancer Research Center (DKFZ), Heidelberg, Germany

Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany

MIRACUM Consortium of the Medical Informatics Initiative, Freiburg, Germany

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Nikolas von Bubnoff

Nikolas von Bubnoff

German Cancer Consortium (DKTK), Heidelberg, Germany

German Cancer Research Center (DKFZ), Heidelberg, Germany

Department of Hematology, Oncology and Stem Cell Transplantation, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany

Department of Hematology and Oncology, Medical Center, University of Schleswig-Holstein, Lübeck, Germany

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Silke Lassmann

Silke Lassmann

Institute of Pathology, Medical Center, University of Freiburg, Breisgau, Germany

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Thomas Longerich

Thomas Longerich

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

Heidelberg-Göttingen-Hannover Medizininformatik (HiGHmed) Konsortium, Heidelberg, Germany

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Michael Bitzer

Michael Bitzer

Department of Internal Medicine I, University Hospital Tübingen, Tübingen, Germany

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Thomas Seufferlein

Thomas Seufferlein

Clinic of Internal Medicine I, University Hospital Ulm, Ulm, Germany

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Nisar Malek

Nisar Malek

Department of Internal Medicine I, University Hospital Tübingen, Tübingen, Germany

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Wilko Weichert

Wilko Weichert

Institute of Pathology, Technische Universität München, Munich, Germany

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Peter Schirmacher

Peter Schirmacher

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

German Cancer Consortium (DKTK), Heidelberg, Germany

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Roland Penzel

Roland Penzel

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Volker Endris

Volker Endris

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

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Benedikt Brors

Benedikt Brors

National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany

German Cancer Consortium (DKTK), Heidelberg, Germany

German Cancer Research Center (DKFZ), Heidelberg, Germany

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Frederick Klauschen

Frederick Klauschen

Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany

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Hanno Glimm

Hanno Glimm

National Center for Tumor Diseases (NCT), Dresden, Germany

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Stefan Fröhling

Stefan Fröhling

National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany

German Cancer Consortium (DKTK), Heidelberg, Germany

DKFZ-Heidelberg Center for Personalized Oncology (HIPO), Heidelberg, Germany

S.F. and A.S. shared last authorshipSearch for more papers by this author
Albrecht Stenzinger

Corresponding Author

Albrecht Stenzinger

Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany

DKFZ-Heidelberg Center for Personalized Oncology (HIPO), Heidelberg, Germany

S.F. and A.S. shared last authorshipCorrespondence to: Stefan Fröhling, National Center for Tumor Diseases (NCT) Heidelberg, Im Neuenheimer Feld 460, 69120 Germany, Tel.: +49-6221-566990, Fax: +49-6221-566967, E-mail: [email protected]; or Albrecht Stenzinger, Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 224, 69120 Heidelberg, Germany, Tel.: +49-6221-5634380, Fax: +49-6221-565251, E-mail: [email protected]Search for more papers by this author
First published: 22 April 2019
Citations: 93
Conflict of interests: AS: advisory board honoraria from Bayer, Novartis, BMS, AstraZeneca, ThermoFisher, Illumina; speaker's honoraria from Takeda, Roche, BMS, Illumina, AstraZeneca, Novartis, ThermoFisher, Bayer, MSD and research funding from Chugai and BMS. VE: advisory board honoraria from Thermo Fischer. Speaker's honoraria from AstraZeneca. ALV: speaker's honoraria from AstraZeneca. PS: advisory board honoraria, research funding and speaker's honoraria from Novartis and AstraZeneca. WW: Advisory board and speaker's bureau from Roche, MSD, BMS, AstraZeneca, Pfizer, Merck, Lilly, Boehringer, Novartis, Takeda. Research funding from Roche, MSD, BMS, Bruker. PC: Speakers honoraria from Roche, Novartis, Chugai. NP: Speaker's honoraria and travel costs from Novartis, Roche, BMS. SL: Research funding from Agilent, Illumina, Qiagen, BMS. Advisory boards: AstraZeneca, Novartis, Roche. Travel grants from Illumina, Agilent. MW: Advisory boards: Roche, Novartis. Research funding from Agilent, Novartis, Roche. Honoraria and travel grants from Diakovere. MT: advisory board honoraria from Novartis, Lilly, BMS, MSD, Roche, Celgene, Takeda, AbbVie, Boehringer, speaker's honoraria from Lilly, MSD, Takeda, research funding from AstraZeneca, BMS, Celgene, Roche, and travel grants from BMS, MSD, Novartis, Boehringer. NvB: Honoraria from AstraZeneca, Amgen, Novartis, BMS. Research funding from Novartis. All other authors declared no conflicts of interest.
[Correction added on September 21, 2019 after first online publication: affiliation updated.]

Abstract

Next-generation sequencing has become a cornerstone of therapy guidance in cancer precision medicine and an indispensable research tool in translational oncology. Its rapidly increasing use during the last decade has expanded the options for targeted tumor therapies, and molecular tumor boards have grown accordingly. However, with increasing detection of genetic alterations, their interpretation has become more complex and error-prone, potentially introducing biases and reducing benefits in clinical practice. To facilitate interdisciplinary discussions of genetic alterations for treatment stratification between pathologists, oncologists, bioinformaticians, genetic counselors and medical scientists in specialized molecular tumor boards, several systems for the classification of variants detected by large-scale sequencing have been proposed. We review three recent and commonly applied classifications and discuss their individual strengths and weaknesses. Comparison of the classifications underlines the need for a clinically useful and universally applicable variant reporting system, which will be instrumental for efficient decision making based on sequencing analysis in oncology. Integrating these data, we propose a generalizable classification concept featuring a conservative and a more progressive scheme, which can be readily applied in a clinical setting.

Abstract

What's new?

With increasingly comprehensive molecular profiling of cancers, the clinical interpretation of genetic alterations is becoming more and more challenging. Here the authors review several classifications for gene variant interpretation that were recently introduced to guide clinical management. They highlight shared features and differences and point out major influencing factors and unresolved issues that still need to be addressed. Based on this analysis, they propose a unified classification concept that may become broadly implemented when remaining issues are solved.

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