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Tumor mutational burden quantification from targeted gene panels: major advancements and challenges
Tumor mutational burden (TMB), the total number of somatic coding mutations in a tumor, is emerging as a promising biomarker for immunotherapy response in cancer patients. TMB can be quantitated by a number of NGS-based sequencing technologies. Whole Exome Sequencing (WES) allows comprehensive measu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631597/ https://www.ncbi.nlm.nih.gov/pubmed/31307554 http://dx.doi.org/10.1186/s40425-019-0647-4 |
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author | Fancello, Laura Gandini, Sara Pelicci, Pier Giuseppe Mazzarella, Luca |
author_facet | Fancello, Laura Gandini, Sara Pelicci, Pier Giuseppe Mazzarella, Luca |
author_sort | Fancello, Laura |
collection | PubMed |
description | Tumor mutational burden (TMB), the total number of somatic coding mutations in a tumor, is emerging as a promising biomarker for immunotherapy response in cancer patients. TMB can be quantitated by a number of NGS-based sequencing technologies. Whole Exome Sequencing (WES) allows comprehensive measurement of TMB and is considered the gold standard. However, to date WES remains confined to research settings, due to high cost of the large genomic space sequenced. In the clinical setting, instead, targeted enrichment panels (gene panels) of various genomic sizes are emerging as the routine technology for TMB assessment. This stimulated the development of various methods for panel-based TMB quantification, and prompted the multiplication of studies assessing whether TMB can be confidently estimated from the smaller genomic space sampled by gene panels. In this review, we inventory the collection of available gene panels tested for this purpose, illustrating their technical specifications and describing their accuracy and clinical value in TMB assessment. Moreover, we highlight how various experimental, platform-related or methodological variables, as well as bioinformatic pipelines, influence panel-based TMB quantification. The lack of harmonization in panel-based TMB quantification, of adequate methods to convert TMB estimates across different panels and of robust predictive cutoffs, currently represents one of the main limitations to adopt TMB as a biomarker in clinical practice. This overview on the heterogeneous landscape of panel-based TMB quantification aims at providing a context to discuss common standards and illustrates the strong need of further validation and consolidation studies for the clinical interpretation of panel-based TMB values. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40425-019-0647-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6631597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66315972019-07-24 Tumor mutational burden quantification from targeted gene panels: major advancements and challenges Fancello, Laura Gandini, Sara Pelicci, Pier Giuseppe Mazzarella, Luca J Immunother Cancer Review Tumor mutational burden (TMB), the total number of somatic coding mutations in a tumor, is emerging as a promising biomarker for immunotherapy response in cancer patients. TMB can be quantitated by a number of NGS-based sequencing technologies. Whole Exome Sequencing (WES) allows comprehensive measurement of TMB and is considered the gold standard. However, to date WES remains confined to research settings, due to high cost of the large genomic space sequenced. In the clinical setting, instead, targeted enrichment panels (gene panels) of various genomic sizes are emerging as the routine technology for TMB assessment. This stimulated the development of various methods for panel-based TMB quantification, and prompted the multiplication of studies assessing whether TMB can be confidently estimated from the smaller genomic space sampled by gene panels. In this review, we inventory the collection of available gene panels tested for this purpose, illustrating their technical specifications and describing their accuracy and clinical value in TMB assessment. Moreover, we highlight how various experimental, platform-related or methodological variables, as well as bioinformatic pipelines, influence panel-based TMB quantification. The lack of harmonization in panel-based TMB quantification, of adequate methods to convert TMB estimates across different panels and of robust predictive cutoffs, currently represents one of the main limitations to adopt TMB as a biomarker in clinical practice. This overview on the heterogeneous landscape of panel-based TMB quantification aims at providing a context to discuss common standards and illustrates the strong need of further validation and consolidation studies for the clinical interpretation of panel-based TMB values. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40425-019-0647-4) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-15 /pmc/articles/PMC6631597/ /pubmed/31307554 http://dx.doi.org/10.1186/s40425-019-0647-4 Text en © The Author(s). 2019 Open Access This 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 | Review Fancello, Laura Gandini, Sara Pelicci, Pier Giuseppe Mazzarella, Luca Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title | Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title_full | Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title_fullStr | Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title_full_unstemmed | Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title_short | Tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
title_sort | tumor mutational burden quantification from targeted gene panels: major advancements and challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6631597/ https://www.ncbi.nlm.nih.gov/pubmed/31307554 http://dx.doi.org/10.1186/s40425-019-0647-4 |
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