Literature DB >> 29807778

Multi-laboratory proficiency testing of clinical cancer genomic profiling by next-generation sequencing.

Qing Zhong1, Ulrich Wagner2, Henriette Kurt3, Francesca Molinari4, Gieri Cathomas5, Paul Komminoth6, Jasmin Barman-Aksözen7, Xiaoye Schneider-Yin7, Jean-Philippe Rey8, Erik Vassella9, Uwe Rogel10, Joachim Diebold11, Thomas McKee12, Wolfram Jochum13, Karl Kashofer14, Paul Hofman15, Melanie Zischka16, Holger Moch2, Markus Rechsteiner17, Peter J Wild18.   

Abstract

Next-generation sequencing (NGS) enables parallel analysis of multiple genomic targets. The increasing demand for NGS-based multiplexed molecular diagnostics requires standardized protocols and recommendations to ensure reproducibility and accuracy of test results for routine clinical decision making. However, the lack of clinical NGS data from multi-laboratory tests and the absence of inter-laboratory comparisons have hampered the establishment of instructive clinical NGS standards. To fill the gap, we set up Proficiency Testing (PT) for inter-laboratory comparison, in which formalin-fixed paraffin-embedded specimens from eight lung and eight colon cancers were analyzed by 15 European molecular diagnostic laboratories on three different platforms using multiple target enrichment systems. We first performed platform, test, and informatics pipeline validation and conducted sensitivity and specificity analysis by random in silico down-sampling. We then implemented a multi-level filtering strategy based on performance tests of base substitution, replicate runs, and Sanger sequencing verified variants. We finally applied the filter criteria to the NGS data from the respective PT participants and obtained high inter-laboratory agreement. We demonstrated accuracy, scalability, and robustness of NGS by means of PT, serving as a benchmark for detecting clinically actionable molecular alterations in research and diagnostic laboratories. In conclusion, this study strongly highlights the importance of establishing standards for NGS-based testing, particularly when the test results impact on clinical decisions, and systematically provides data sets from multiple different labs to infer such standards.
Copyright © 2018 Elsevier GmbH. All rights reserved.

Entities:  

Keywords:  Colon Cancer; Lung Cancer; Molecular Pathology; Multi-Laboratory Test; Next Generation Sequencing; Proficiency Testing

Mesh:

Substances:

Year:  2018        PMID: 29807778     DOI: 10.1016/j.prp.2018.05.020

Source DB:  PubMed          Journal:  Pathol Res Pract        ISSN: 0344-0338            Impact factor:   3.250


  6 in total

1.  Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study.

Authors:  Jonathan Foox; Scott W Tighe; Charles M Nicolet; Justin M Zook; Marta Byrska-Bishop; Wayne E Clarke; Michael M Khayat; Medhat Mahmoud; Phoebe K Laaguiby; Zachary T Herbert; Derek Warner; George S Grills; Jin Jen; Shawn Levy; Jenny Xiang; Alicia Alonso; Xia Zhao; Wenwei Zhang; Fei Teng; Yonggang Zhao; Haorong Lu; Gary P Schroth; Giuseppe Narzisi; William Farmerie; Fritz J Sedlazeck; Don A Baldwin; Christopher E Mason
Journal:  Nat Biotechnol       Date:  2021-09-09       Impact factor: 54.908

Review 2.  Genetic Markers in Lung Cancer Diagnosis: A Review.

Authors:  Katarzyna Wadowska; Iwona Bil-Lula; Łukasz Trembecki; Mariola Śliwińska-Mossoń
Journal:  Int J Mol Sci       Date:  2020-06-27       Impact factor: 5.923

Review 3.  Machine learning for multi-omics data integration in cancer.

Authors:  Zhaoxiang Cai; Rebecca C Poulos; Jia Liu; Qing Zhong
Journal:  iScience       Date:  2022-01-22

Review 4.  Expert opinion on NSCLC small specimen biomarker testing - Part 1: Tissue collection and management.

Authors:  Frédérique Penault-Llorca; Keith M Kerr; Pilar Garrido; Erik Thunnissen; Elisabeth Dequeker; Nicola Normanno; Simon J Patton; Jenni Fairley; Joshua Kapp; Daniëlle de Ridder; Aleš Ryška; Holger Moch
Journal:  Virchows Arch       Date:  2022-07-20       Impact factor: 4.535

5.  Sequencing of animal viruses: quality data assurance for NGS bioinformatics.

Authors:  Gianpiero Zamperin; Pierrick Lucas; Irene Cano; David Ryder; Miriam Abbadi; David Stone; Argelia Cuenca; Estelle Vigouroux; Yannick Blanchard; Valentina Panzarin
Journal:  Virol J       Date:  2019-11-21       Impact factor: 4.099

6.  Gen-FS coordinated proficiency test data for genomic foodborne pathogen surveillance, 2017 and 2018 exercises.

Authors:  Ruth E Timme; Patricia C Lafon; Maria Balkey; Jennifer K Adams; Darlene Wagner; Heather Carleton; Errol Strain; Maria Hoffmann; Ashley Sabol; Hugh Rand; Rebecca Lindsey; Deborah Sheehan; Joseph D Baugher; Eija Trees
Journal:  Sci Data       Date:  2020-11-19       Impact factor: 6.444

  6 in total

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