The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and trea...

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Autores principales: Golkaram, Mahdi, Zhao, Chen, Kruglyak, Kristina, Zhang, Shile, Bilke, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676656/
https://www.ncbi.nlm.nih.gov/pubmed/33166276
http://dx.doi.org/10.1371/journal.pcbi.1008332
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author Golkaram, Mahdi
Zhao, Chen
Kruglyak, Kristina
Zhang, Shile
Bilke, Sven
author_facet Golkaram, Mahdi
Zhao, Chen
Kruglyak, Kristina
Zhang, Shile
Bilke, Sven
author_sort Golkaram, Mahdi
collection PubMed
description The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.
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spelling pubmed-76766562020-12-02 The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy Golkaram, Mahdi Zhao, Chen Kruglyak, Kristina Zhang, Shile Bilke, Sven PLoS Comput Biol Research Article The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms. Public Library of Science 2020-11-09 /pmc/articles/PMC7676656/ /pubmed/33166276 http://dx.doi.org/10.1371/journal.pcbi.1008332 Text en © 2020 Golkaram et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Golkaram, Mahdi
Zhao, Chen
Kruglyak, Kristina
Zhang, Shile
Bilke, Sven
The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title_full The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title_fullStr The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title_full_unstemmed The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title_short The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
title_sort interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7676656/
https://www.ncbi.nlm.nih.gov/pubmed/33166276
http://dx.doi.org/10.1371/journal.pcbi.1008332
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