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Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better

BACKGROUND: Recently, the US Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) for treating cancer patients with tumor mutation burden (TMB) >10 mutations/megabase (mut/Mb). However, high TMB (TMB-H) defined by >10 mut/Mb fails to predict ICB response across diff...

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Autor principal: Zheng, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804687/
https://www.ncbi.nlm.nih.gov/pubmed/35101940
http://dx.doi.org/10.1136/jitc-2021-003087
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author Zheng, Ming
author_facet Zheng, Ming
author_sort Zheng, Ming
collection PubMed
description BACKGROUND: Recently, the US Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) for treating cancer patients with tumor mutation burden (TMB) >10 mutations/megabase (mut/Mb). However, high TMB (TMB-H) defined by >10 mut/Mb fails to predict ICB response across different cancer types, which has raised serious concerns on the current FDA approval. Thus, to better implement TMB as a robust biomarker of ICB response, an optimal and generalizable TMB cut-off within and across cancer types must be addressed as soon as possible. METHODS: Using Morris’s and Kurzrock’s cohorts (n=1662 and 102), we exhaustively tested all possible TMB cut-offs for predicting ICB treatment outcomes in 10 cancer types. The bootstrap method was applied to generate 10,000 randomly resampled cohorts using original cohorts to measure the reproducibility of TMB cut-off. ICB treatment outcomes were analyzed by overall survival, progression-free survival and objective response rate. RESULTS: No universally valid TMB cut-off was available for all cancer types. Only in cancer types with higher TMB (category I), such as melanoma, colorectal cancer, bladder cancer, and non-small cell lung cancer, the associations between TMB-H and ICB treatment outcomes were less affected by TMB cut-off selection. Moreover, high TMB (category I) cancer types shared a wide range of TMB cut-offs and a universally optimal TMB cut-off of 13 mut/Mb for predicting favorable ICB outcomes. In contrast, low TMB (category II) cancer types, for which the prognostic associations were sensitive to TMB cut-off selection, showed markedly limited and distinct ranges of significantly favorable TMB cut-offs. Equivalent results were obtained in the analyses of pooled tumors. CONCLUSIONS: Our finding—the correlation that TMB-H is more robustly associated with favorable ICB treatment outcomes in cancer types with higher TMBs—can be used to predict whether TMB could be a robust predictive biomarker in cancer types for which TMB data are available, but ICB treatment has not been investigated. This theory was tested in cancer of unknown primary successfully. Additionally, the universal TMB cut-off of 13 mut/Mb might reveal a general requirement to trigger the sequential cascade from somatic mutations to an effective antitumor immunity.
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spelling pubmed-88046872022-02-07 Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better Zheng, Ming J Immunother Cancer Immunotherapy Biomarkers BACKGROUND: Recently, the US Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) for treating cancer patients with tumor mutation burden (TMB) >10 mutations/megabase (mut/Mb). However, high TMB (TMB-H) defined by >10 mut/Mb fails to predict ICB response across different cancer types, which has raised serious concerns on the current FDA approval. Thus, to better implement TMB as a robust biomarker of ICB response, an optimal and generalizable TMB cut-off within and across cancer types must be addressed as soon as possible. METHODS: Using Morris’s and Kurzrock’s cohorts (n=1662 and 102), we exhaustively tested all possible TMB cut-offs for predicting ICB treatment outcomes in 10 cancer types. The bootstrap method was applied to generate 10,000 randomly resampled cohorts using original cohorts to measure the reproducibility of TMB cut-off. ICB treatment outcomes were analyzed by overall survival, progression-free survival and objective response rate. RESULTS: No universally valid TMB cut-off was available for all cancer types. Only in cancer types with higher TMB (category I), such as melanoma, colorectal cancer, bladder cancer, and non-small cell lung cancer, the associations between TMB-H and ICB treatment outcomes were less affected by TMB cut-off selection. Moreover, high TMB (category I) cancer types shared a wide range of TMB cut-offs and a universally optimal TMB cut-off of 13 mut/Mb for predicting favorable ICB outcomes. In contrast, low TMB (category II) cancer types, for which the prognostic associations were sensitive to TMB cut-off selection, showed markedly limited and distinct ranges of significantly favorable TMB cut-offs. Equivalent results were obtained in the analyses of pooled tumors. CONCLUSIONS: Our finding—the correlation that TMB-H is more robustly associated with favorable ICB treatment outcomes in cancer types with higher TMBs—can be used to predict whether TMB could be a robust predictive biomarker in cancer types for which TMB data are available, but ICB treatment has not been investigated. This theory was tested in cancer of unknown primary successfully. Additionally, the universal TMB cut-off of 13 mut/Mb might reveal a general requirement to trigger the sequential cascade from somatic mutations to an effective antitumor immunity. BMJ Publishing Group 2022-01-31 /pmc/articles/PMC8804687/ /pubmed/35101940 http://dx.doi.org/10.1136/jitc-2021-003087 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Immunotherapy Biomarkers
Zheng, Ming
Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title_full Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title_fullStr Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title_full_unstemmed Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title_short Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
title_sort tumor mutation burden for predicting immune checkpoint blockade response: the more, the better
topic Immunotherapy Biomarkers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8804687/
https://www.ncbi.nlm.nih.gov/pubmed/35101940
http://dx.doi.org/10.1136/jitc-2021-003087
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