Literature DB >> 23810758

Comparison of clinical targeted next-generation sequence data from formalin-fixed and fresh-frozen tissue specimens.

David H Spencer1, Jennifer K Sehn, Haley J Abel, Mark A Watson, John D Pfeifer, Eric J Duncavage.   

Abstract

Next-generation sequencing (NGS) has emerged as a powerful technique for the detection of genetic variants in the clinical laboratory. NGS can be performed using DNA from FFPE tissue, but it is unknown whether such specimens are truly equivalent to unfixed tissue for NGS applications. To address this question, we performed hybridization-capture enrichment and multiplexed Illumina NGS for 27 cancer-related genes using DNA from 16 paired fresh-frozen and routine FFPE lung adenocarcinoma specimens and conducted extensive comparisons between the sequence data from each sample type. This analysis revealed small but detectable differences between FFPE and frozen samples. Compared with frozen samples, NGS data from FFPE samples had smaller library insert sizes, greater coverage variability, and an increase in C to T transitions that was most pronounced at CpG dinucleotides, suggesting interplay between DNA methylation and formalin-induced changes; however, the error rate, library complexity, enrichment performance, and coverage statistics were not significantly different. Comparison of base calls between paired samples demonstrated concordances of >99.99%, with 96.8% agreement in the single-nucleotide variants detected and >98% accuracy of NGS data when compared with genotypes from an orthogonal single-nucleotide polymorphism array platform. This study demonstrates that routine processing of FFPE samples has a detectable but negligible effect on NGS data and that these samples can be a reliable substrate for clinical NGS testing.
Copyright © 2013 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23810758      PMCID: PMC4912568          DOI: 10.1016/j.jmoldx.2013.05.004

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  34 in total

1.  Selection of higher molecular weight genomic DNA for molecular diagnosis from formalin-fixed material.

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Journal:  Diagn Mol Pathol       Date:  2003-12

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Journal:  Am J Pathol       Date:  1996-11       Impact factor: 4.307

3.  Accurate and exact CNV identification from targeted high-throughput sequence data.

Authors:  Alex S Nord; Ming Lee; Mary-Claire King; Tom Walsh
Journal:  BMC Genomics       Date:  2011-04-12       Impact factor: 3.969

Review 4.  Reactions of nucleic acids and nucleoproteins with formaldehyde.

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5.  Global mutational profiling of formalin-fixed human colon cancers from a pathology archive.

Authors:  Mark D Adams; Martina L Veigl; Zhenghe Wang; Neil Molyneux; Shuying Sun; Kishore Guda; Xiaoqing Yu; Sanford D Markowitz; Joseph Willis
Journal:  Mod Pathol       Date:  2012-08-10       Impact factor: 7.842

6.  DNMT3A mutations in acute myeloid leukemia.

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Journal:  N Engl J Med       Date:  2010-11-10       Impact factor: 91.245

7.  Modifications of human and viral deoxyribonucleic acid by formaldehyde fixation.

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Journal:  Lab Invest       Date:  1994-10       Impact factor: 5.662

Review 8.  RNA expression analysis from formalin fixed paraffin embedded tissues.

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Journal:  Histochem Cell Biol       Date:  2008-08-05       Impact factor: 4.304

Review 9.  Effects of fixative and fixation time on the extraction and polymerase chain reaction amplification of RNA from paraffin-embedded tissue. Comparison of two housekeeping gene mRNA controls.

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Journal:  Diagn Mol Pathol       Date:  1994-09

10.  Targeted high throughput sequencing in clinical cancer settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity.

Authors:  Martin Kerick; Melanie Isau; Bernd Timmermann; Holger Sültmann; Ralf Herwig; Sylvia Krobitsch; Georg Schaefer; Irmgard Verdorfer; Georg Bartsch; Helmut Klocker; Hans Lehrach; Michal R Schweiger
Journal:  BMC Med Genomics       Date:  2011-09-29       Impact factor: 3.063

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  78 in total

1.  Validation of a next-generation sequencing assay for clinical molecular oncology.

Authors:  Catherine E Cottrell; Hussam Al-Kateb; Andrew J Bredemeyer; Eric J Duncavage; David H Spencer; Haley J Abel; Christina M Lockwood; Ian S Hagemann; Stephanie M O'Guin; Lauren C Burcea; Christopher S Sawyer; Dayna M Oschwald; Jennifer L Stratman; Dorie A Sher; Mark R Johnson; Justin T Brown; Paul F Cliften; Bijoy George; Leslie D McIntosh; Savita Shrivastava; Tudung T Nguyen; Jacqueline E Payton; Mark A Watson; Seth D Crosby; Richard D Head; Robi D Mitra; Rakesh Nagarajan; Shashikant Kulkarni; Karen Seibert; Herbert W Virgin; Jeffrey Milbrandt; John D Pfeifer
Journal:  J Mol Diagn       Date:  2013-11-06       Impact factor: 5.568

2.  Formalin-fixed paraffin-embedded sample conditions for deep next generation sequencing.

Authors:  Masayuki Nagahashi; Yoshifumi Shimada; Hiroshi Ichikawa; Satoru Nakagawa; Nobuaki Sato; Koji Kaneko; Keiichi Homma; Takashi Kawasaki; Keisuke Kodama; Stephen Lyle; Kazuaki Takabe; Toshifumi Wakai
Journal:  J Surg Res       Date:  2017-07-27       Impact factor: 2.192

3.  Somatic genetic aberrations in benign breast disease and the risk of subsequent breast cancer.

Authors:  Zexian Zeng; Andy Vo; Xiaoyu Li; Ali Shidfar; Paulette Saldana; Luis Blanco; Xiaoling Xuei; Yuan Luo; Seema A Khan; Susan E Clare
Journal:  NPJ Breast Cancer       Date:  2020-06-12

4.  Non-reproducible sequence artifacts in FFPE tissue: an experience report.

Authors:  Richard Ofner; Cathrin Ritter; Selma Ugurel; Lorenzo Cerroni; Mathias Stiller; Thomas Bogenrieder; Flavio Solca; David Schrama; Jürgen C Becker
Journal:  J Cancer Res Clin Oncol       Date:  2017-03-17       Impact factor: 4.553

5.  Next-Generation Sequencing of Retinoblastoma Identifies Pathogenic Alterations beyond RB1 Inactivation That Correlate with Aggressive Histopathologic Features.

Authors:  Armin R Afshar; Melike Pekmezci; Michele M Bloomer; Nicola J Cadenas; Meredith Stevers; Anuradha Banerjee; Ritu Roy; Adam B Olshen; Jessica Van Ziffle; Courtney Onodera; W Patrick Devine; James P Grenert; Boris C Bastian; David A Solomon; Bertil E Damato
Journal:  Ophthalmology       Date:  2019-12-12       Impact factor: 12.079

6.  Targeted next-generation sequencing for molecular diagnosis of endometriosis-associated ovarian cancer.

Authors:  Tze-Kiong Er; Yu-Fa Su; Chun-Chieh Wu; Chih-Chieh Chen; Jing Wang; Tsung-Hua Hsieh; Marta Herreros-Villanueva; Wan-Tzu Chen; Yi-Ting Chen; Ta-Chih Liu; Hung-Sheng Chen; Eing-Mei Tsai
Journal:  J Mol Med (Berl)       Date:  2016-02-27       Impact factor: 4.599

Review 7.  Next-Generation Sequencing to Guide Clinical Trials.

Authors:  Lillian L Siu; Barbara A Conley; Scott Boerner; Patricia M LoRusso
Journal:  Clin Cancer Res       Date:  2015-10-15       Impact factor: 12.531

8.  Detection of gene rearrangements in targeted clinical next-generation sequencing.

Authors:  Haley J Abel; Hussam Al-Kateb; Catherine E Cottrell; Andrew J Bredemeyer; Colin C Pritchard; Allie H Grossmann; Michelle L Wallander; John D Pfeifer; Christina M Lockwood; Eric J Duncavage
Journal:  J Mol Diagn       Date:  2014-05-09       Impact factor: 5.568

Review 9.  Guidelines for Validation of Next-Generation Sequencing-Based Oncology Panels: A Joint Consensus Recommendation of the Association for Molecular Pathology and College of American Pathologists.

Authors:  Lawrence J Jennings; Maria E Arcila; Christopher Corless; Suzanne Kamel-Reid; Ira M Lubin; John Pfeifer; Robyn L Temple-Smolkin; Karl V Voelkerding; Marina N Nikiforova
Journal:  J Mol Diagn       Date:  2017-03-21       Impact factor: 5.568

10.  Performance of common analysis methods for detecting low-frequency single nucleotide variants in targeted next-generation sequence data.

Authors:  David H Spencer; Manoj Tyagi; Francesco Vallania; Andrew J Bredemeyer; John D Pfeifer; Rob D Mitra; Eric J Duncavage
Journal:  J Mol Diagn       Date:  2013-11-05       Impact factor: 5.568

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