Literature DB >> 31186376

Association Between Preanalytical Factors and Tumor Mutational Burden Estimated by Next-Generation Sequencing-Based Multiplex Gene Panel Assay.

Pham Nguyen Quy1, Masashi Kanai2, Keita Fukuyama3, Tadayuki Kou1, Tomohiro Kondo1, Yoshihiro Yamamoto1, Junichi Matsubara1, Akinori Hiroshima4, Hiroaki Mochizuki4, Tomohiro Sakuma4, Mayumi Kamada5, Masahiko Nakatsui5, Yuji Eso6, Hiroshi Seno6, Toshihiko Masui3, Kyoichi Takaori3, Sachiko Minamiguchi7, Shigemi Matsumoto1, Manabu Muto1.   

Abstract

BACKGROUND: Tumor mutational burden (TMB) measured via next-generation sequencing (NGS)-based gene panel is a promising biomarker for response to immune checkpoint inhibitors (ICIs) in solid tumors. However, little is known about the preanalytical factors that can affect the TMB score.
MATERIALS AND METHODS: Data of 199 patients with solid tumors who underwent multiplex NGS gene panel (OncoPrime), which was commercially provided by a Clinical Laboratory Improvement Amendments-licensed laboratory and covered 0.78 megabase (Mb) of capture size relevant to the TMB calculation, were reviewed. Associations between the TMB score and preanalytical factors, including sample DNA quality, sample type, sampling site, and storage period, were analyzed. Clinical outcomes of patients with a high TMB score (≥10 mutations per megabase) who received anti-programmed cell death protein 1 antibodies (n = 22) were also analyzed.
RESULTS: Low DNA library concentration (<5 nM), formalin-fixed paraffin-embedded tissue (FFPE), and the prolonged sample storage period (range, 0.9-58.1 months) correlated with a higher TMB score. After excluding low DNA library samples from the analysis, FFPE samples, but not the sample storage period, exhibited a marked correlation with a high TMB score. Of 22 patients with a high TMB score, we observed the partial response in 2 patients (9.1%).
CONCLUSION: Our results indicate that the TMB score estimated via NGS-based gene panel could be affected by the DNA library concentration and sample type. These factors could potentially increase the false-positive and/or artifactual variant calls. As each gene panel has its own pipeline for variant calling, it is unknown whether these factors have a significant effect in other platforms. IMPLICATIONS FOR PRACTICE: A high tumor mutational burden score, as estimated via next-generation sequencing-based gene panel testing, should be carefully interpreted as it could be affected by the DNA library concentration and sample type. © AlphaMed Press 2019.

Entities:  

Keywords:  DNA quality; Immune checkpoint inhibitors; Mutational burden; Next‐generation sequencing

Mesh:

Substances:

Year:  2019        PMID: 31186376      PMCID: PMC6975932          DOI: 10.1634/theoncologist.2018-0587

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  39 in total

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Authors:  Xin Ye; Zhong-Zheng Zhu; Lei Zhong; Yachao Lu; Yun Sun; Xiaolu Yin; Zhenfan Yang; Guanshan Zhu; Qunsheng Ji
Journal:  J Thorac Oncol       Date:  2013-09       Impact factor: 15.609

2.  Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden.

Authors:  Matthew D Hellmann; Tudor-Eliade Ciuleanu; Adam Pluzanski; Jong Seok Lee; Gregory A Otterson; Clarisse Audigier-Valette; Elisa Minenza; Helena Linardou; Sjaak Burgers; Pamela Salman; Hossein Borghaei; Suresh S Ramalingam; Julie Brahmer; Martin Reck; Kenneth J O'Byrne; William J Geese; George Green; Han Chang; Joseph Szustakowski; Prabhu Bhagavatheeswaran; Diane Healey; Yali Fu; Faith Nathan; Luis Paz-Ares
Journal:  N Engl J Med       Date:  2018-04-16       Impact factor: 91.245

Review 3.  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

4.  DNA degrades during storage in formalin-fixed and paraffin-embedded tissue blocks.

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5.  Targeted Next Generation Sequencing Identifies Markers of Response to PD-1 Blockade.

Authors:  Douglas B Johnson; Garrett M Frampton; Matthew J Rioth; Erik Yusko; Yaomin Xu; Xingyi Guo; Riley C Ennis; David Fabrizio; Zachary R Chalmers; Joel Greenbowe; Siraj M Ali; Sohail Balasubramanian; James X Sun; Yuting He; Dennie T Frederick; Igor Puzanov; Justin M Balko; Justin M Cates; Jeffrey S Ross; Catherine Sanders; Harlan Robins; Yu Shyr; Vincent A Miller; Philip J Stephens; Ryan J Sullivan; Jeffrey A Sosman; Christine M Lovly
Journal:  Cancer Immunol Res       Date:  2016-09-26       Impact factor: 11.151

6.  Genomic Features of Response to Combination Immunotherapy in Lung Cancer.

Authors:  Martin Früh; Solange Peters
Journal:  Cancer Cell       Date:  2018-05-14       Impact factor: 31.743

7.  Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial.

Authors:  Arjun V Balar; Matthew D Galsky; Jonathan E Rosenberg; Thomas Powles; Daniel P Petrylak; Joaquim Bellmunt; Yohann Loriot; Andrea Necchi; Jean Hoffman-Censits; Jose Luis Perez-Gracia; Nancy A Dawson; Michiel S van der Heijden; Robert Dreicer; Sandy Srinivas; Margitta M Retz; Richard W Joseph; Alexandra Drakaki; Ulka N Vaishampayan; Srikala S Sridhar; David I Quinn; Ignacio Durán; David R Shaffer; Bernhard J Eigl; Petros D Grivas; Evan Y Yu; Shi Li; Edward E Kadel; Zachary Boyd; Richard Bourgon; Priti S Hegde; Sanjeev Mariathasan; AnnChristine Thåström; Oyewale O Abidoye; Gregg D Fine; Dean F Bajorin
Journal:  Lancet       Date:  2016-12-08       Impact factor: 79.321

8.  Molecular Determinants of Response to Anti-Programmed Cell Death (PD)-1 and Anti-Programmed Death-Ligand 1 (PD-L1) Blockade in Patients With Non-Small-Cell Lung Cancer Profiled With Targeted Next-Generation Sequencing.

Authors:  Hira Rizvi; Francisco Sanchez-Vega; Konnor La; Walid Chatila; Philip Jonsson; Darragh Halpenny; Andrew Plodkowski; Niamh Long; Jennifer L Sauter; Natasha Rekhtman; Travis Hollmann; Kurt A Schalper; Justin F Gainor; Ronglai Shen; Ai Ni; Kathryn C Arbour; Taha Merghoub; Jedd Wolchok; Alexandra Snyder; Jamie E Chaft; Mark G Kris; Charles M Rudin; Nicholas D Socci; Michael F Berger; Barry S Taylor; Ahmet Zehir; David B Solit; Maria E Arcila; Marc Ladanyi; Gregory J Riely; Nikolaus Schultz; Matthew D Hellmann
Journal:  J Clin Oncol       Date:  2018-01-16       Impact factor: 44.544

9.  Exomics and immunogenics: Bridging mutational load and immune checkpoints efficacy.

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Journal:  Oncoimmunology       Date:  2014-01-16       Impact factor: 8.110

10.  Mutational heterogeneity in cancer and the search for new cancer-associated genes.

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Journal:  Nature       Date:  2013-06-16       Impact factor: 49.962

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  3 in total

Review 1.  Open the Technical Black Box of Tumor Mutational Burden (TMB): Factors Affecting Harmonization and Standardization of Panel-Based TMB.

Authors:  Meng-Ta Sung; Yeh-Han Wang; Chien-Feng Li
Journal:  Int J Mol Sci       Date:  2022-05-03       Impact factor: 6.208

2.  [Research Progress on Heterogeneity of Tumor Mutation Burden in Patients with 
Non-small Cell Lung Cancer].

Authors:  Abdurazik Mihray; Peng Chen
Journal:  Zhongguo Fei Ai Za Zhi       Date:  2021-04-20

3.  Inter-assay variability of next-generation sequencing-based gene panels.

Authors:  Pham Nguyen Quy; Keita Fukuyama; Masashi Kanai; Tadayuki Kou; Tomohiro Kondo; Masahiro Yoshioka; Junichi Matsubara; Tomohiro Sakuma; Sachiko Minamiguchi; Shigemi Matsumoto; Manabu Muto
Journal:  BMC Med Genomics       Date:  2022-04-15       Impact factor: 3.622

  3 in total

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