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Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden

BACKGROUND: High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC...

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Autores principales: Chalmers, Zachary R., Connelly, Caitlin F., Fabrizio, David, Gay, Laurie, Ali, Siraj M., Ennis, Riley, Schrock, Alexa, Campbell, Brittany, Shlien, Adam, Chmielecki, Juliann, Huang, Franklin, He, Yuting, Sun, James, Tabori, Uri, Kennedy, Mark, Lieber, Daniel S., Roels, Steven, White, Jared, Otto, Geoffrey A., Ross, Jeffrey S., Garraway, Levi, Miller, Vincent A., Stephens, Phillip J., Frampton, Garrett M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395719/
https://www.ncbi.nlm.nih.gov/pubmed/28420421
http://dx.doi.org/10.1186/s13073-017-0424-2
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author Chalmers, Zachary R.
Connelly, Caitlin F.
Fabrizio, David
Gay, Laurie
Ali, Siraj M.
Ennis, Riley
Schrock, Alexa
Campbell, Brittany
Shlien, Adam
Chmielecki, Juliann
Huang, Franklin
He, Yuting
Sun, James
Tabori, Uri
Kennedy, Mark
Lieber, Daniel S.
Roels, Steven
White, Jared
Otto, Geoffrey A.
Ross, Jeffrey S.
Garraway, Levi
Miller, Vincent A.
Stephens, Phillip J.
Frampton, Garrett M.
author_facet Chalmers, Zachary R.
Connelly, Caitlin F.
Fabrizio, David
Gay, Laurie
Ali, Siraj M.
Ennis, Riley
Schrock, Alexa
Campbell, Brittany
Shlien, Adam
Chmielecki, Juliann
Huang, Franklin
He, Yuting
Sun, James
Tabori, Uri
Kennedy, Mark
Lieber, Daniel S.
Roels, Steven
White, Jared
Otto, Geoffrey A.
Ross, Jeffrey S.
Garraway, Levi
Miller, Vincent A.
Stephens, Phillip J.
Frampton, Garrett M.
author_sort Chalmers, Zachary R.
collection PubMed
description BACKGROUND: High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. METHODS: In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. RESULTS: We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. CONCLUSIONS: These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-017-0424-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-53957192017-04-20 Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden Chalmers, Zachary R. Connelly, Caitlin F. Fabrizio, David Gay, Laurie Ali, Siraj M. Ennis, Riley Schrock, Alexa Campbell, Brittany Shlien, Adam Chmielecki, Juliann Huang, Franklin He, Yuting Sun, James Tabori, Uri Kennedy, Mark Lieber, Daniel S. Roels, Steven White, Jared Otto, Geoffrey A. Ross, Jeffrey S. Garraway, Levi Miller, Vincent A. Stephens, Phillip J. Frampton, Garrett M. Genome Med Research BACKGROUND: High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. METHODS: In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. RESULTS: We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. CONCLUSIONS: These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-017-0424-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-04-19 /pmc/articles/PMC5395719/ /pubmed/28420421 http://dx.doi.org/10.1186/s13073-017-0424-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Chalmers, Zachary R.
Connelly, Caitlin F.
Fabrizio, David
Gay, Laurie
Ali, Siraj M.
Ennis, Riley
Schrock, Alexa
Campbell, Brittany
Shlien, Adam
Chmielecki, Juliann
Huang, Franklin
He, Yuting
Sun, James
Tabori, Uri
Kennedy, Mark
Lieber, Daniel S.
Roels, Steven
White, Jared
Otto, Geoffrey A.
Ross, Jeffrey S.
Garraway, Levi
Miller, Vincent A.
Stephens, Phillip J.
Frampton, Garrett M.
Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title_full Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title_fullStr Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title_full_unstemmed Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title_short Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
title_sort analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395719/
https://www.ncbi.nlm.nih.gov/pubmed/28420421
http://dx.doi.org/10.1186/s13073-017-0424-2
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