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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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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. |
format | Online Article Text |
id | pubmed-4881477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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