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Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories

Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. Several independent studies suggest that higher non-synonymous mutational burden assessed by whole exome sequencing (WES) in tumors is associated with improved objective response...

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Detalles Bibliográficos
Autores principales: Qiu, Ping, Pang, Ling, Arreaza, Gladys, Maguire, Maureen, Chang, Ken C. N., Marton, Matthew J., Levitan, Diane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881477/
https://www.ncbi.nlm.nih.gov/pubmed/27136543
http://dx.doi.org/10.3390/ijms17050651
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author Qiu, Ping
Pang, Ling
Arreaza, Gladys
Maguire, Maureen
Chang, Ken C. N.
Marton, Matthew J.
Levitan, Diane
author_facet Qiu, Ping
Pang, Ling
Arreaza, Gladys
Maguire, Maureen
Chang, Ken C. N.
Marton, Matthew J.
Levitan, Diane
author_sort Qiu, Ping
collection PubMed
description Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. Several independent studies suggest that higher non-synonymous mutational burden assessed by whole exome sequencing (WES) in tumors is associated with improved objective response, durable clinical benefit, and progression-free survival in immune checkpoint inhibitors treatment. Next-generation sequencing (NGS) is a promising technology being used in the clinic to direct patient treatment. Cancer genome WES poses a unique challenge due to tumor heterogeneity and sequencing artifacts introduced by formalin-fixed, paraffin-embedded (FFPE) tissue. In order to evaluate the data interoperability of WES data from different sources to survey tumor mutational landscape, we compared WES data of several tumor/normal matched samples from five commercial vendors. A large data discrepancy was observed from vendors’ self-reported data. Independent data analysis from vendors’ raw NGS data shows that whole exome sequencing data from qualified vendors can be combined and analyzed uniformly to derive comparable quantitative estimates of tumor mutational burden.
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spelling pubmed-48814772016-05-27 Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories Qiu, Ping Pang, Ling Arreaza, Gladys Maguire, Maureen Chang, Ken C. N. Marton, Matthew J. Levitan, Diane Int J Mol Sci Communication Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. Several independent studies suggest that higher non-synonymous mutational burden assessed by whole exome sequencing (WES) in tumors is associated with improved objective response, durable clinical benefit, and progression-free survival in immune checkpoint inhibitors treatment. Next-generation sequencing (NGS) is a promising technology being used in the clinic to direct patient treatment. Cancer genome WES poses a unique challenge due to tumor heterogeneity and sequencing artifacts introduced by formalin-fixed, paraffin-embedded (FFPE) tissue. In order to evaluate the data interoperability of WES data from different sources to survey tumor mutational landscape, we compared WES data of several tumor/normal matched samples from five commercial vendors. A large data discrepancy was observed from vendors’ self-reported data. Independent data analysis from vendors’ raw NGS data shows that whole exome sequencing data from qualified vendors can be combined and analyzed uniformly to derive comparable quantitative estimates of tumor mutational burden. MDPI 2016-04-29 /pmc/articles/PMC4881477/ /pubmed/27136543 http://dx.doi.org/10.3390/ijms17050651 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Qiu, Ping
Pang, Ling
Arreaza, Gladys
Maguire, Maureen
Chang, Ken C. N.
Marton, Matthew J.
Levitan, Diane
Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title_full Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title_fullStr Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title_full_unstemmed Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title_short Data Interoperability of Whole Exome Sequencing (WES) Based Mutational Burden Estimates from Different Laboratories
title_sort data interoperability of whole exome sequencing (wes) based mutational burden estimates from different laboratories
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881477/
https://www.ncbi.nlm.nih.gov/pubmed/27136543
http://dx.doi.org/10.3390/ijms17050651
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