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TMB in NSCLC: A Broken Dream?

Although immune checkpoint inhibitors have changed the treatment paradigm of a variety of cancers, including non-small-cell lung cancer, not all patients respond to immunotherapy in the same way. Predictive biomarkers for patient selection are thus needed. Tumor mutation burden (TMB), defined as the...

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Detalles Bibliográficos
Autores principales: Bravaccini, Sara, Bronte, Giuseppe, Ulivi, Paola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234326/
https://www.ncbi.nlm.nih.gov/pubmed/34207126
http://dx.doi.org/10.3390/ijms22126536
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author Bravaccini, Sara
Bronte, Giuseppe
Ulivi, Paola
author_facet Bravaccini, Sara
Bronte, Giuseppe
Ulivi, Paola
author_sort Bravaccini, Sara
collection PubMed
description Although immune checkpoint inhibitors have changed the treatment paradigm of a variety of cancers, including non-small-cell lung cancer, not all patients respond to immunotherapy in the same way. Predictive biomarkers for patient selection are thus needed. Tumor mutation burden (TMB), defined as the total number of somatic/acquired mutations per coding area of a tumor genome (Mut/Mb), has emerged as a potential predictive biomarker of response to immune checkpoint inhibitors. We found that the limited use of TMB in clinical practice is due to the difficulty in its detection and compounded by several different biological, methodological and economic issues. The incorporation of both TMB and PD-L1 expression or other biomarkers into multivariable predictive models could result in greater predictive power.
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spelling pubmed-82343262021-06-27 TMB in NSCLC: A Broken Dream? Bravaccini, Sara Bronte, Giuseppe Ulivi, Paola Int J Mol Sci Review Although immune checkpoint inhibitors have changed the treatment paradigm of a variety of cancers, including non-small-cell lung cancer, not all patients respond to immunotherapy in the same way. Predictive biomarkers for patient selection are thus needed. Tumor mutation burden (TMB), defined as the total number of somatic/acquired mutations per coding area of a tumor genome (Mut/Mb), has emerged as a potential predictive biomarker of response to immune checkpoint inhibitors. We found that the limited use of TMB in clinical practice is due to the difficulty in its detection and compounded by several different biological, methodological and economic issues. The incorporation of both TMB and PD-L1 expression or other biomarkers into multivariable predictive models could result in greater predictive power. MDPI 2021-06-18 /pmc/articles/PMC8234326/ /pubmed/34207126 http://dx.doi.org/10.3390/ijms22126536 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Bravaccini, Sara
Bronte, Giuseppe
Ulivi, Paola
TMB in NSCLC: A Broken Dream?
title TMB in NSCLC: A Broken Dream?
title_full TMB in NSCLC: A Broken Dream?
title_fullStr TMB in NSCLC: A Broken Dream?
title_full_unstemmed TMB in NSCLC: A Broken Dream?
title_short TMB in NSCLC: A Broken Dream?
title_sort tmb in nsclc: a broken dream?
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234326/
https://www.ncbi.nlm.nih.gov/pubmed/34207126
http://dx.doi.org/10.3390/ijms22126536
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