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Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers
Background: The US Food and Drug Administration (FDA)’s tumor-agnostic approval of pembrolizumab in high tumor mutational burden (TMB-high, i.e., TMB≥10 mut/Mb) cases, based on the data from KEYNOTE-158, has raised considerable concerns among the immuno-oncology community. This study aims to statist...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248461/ https://www.ncbi.nlm.nih.gov/pubmed/37305681 http://dx.doi.org/10.3389/fcell.2023.1209243 |
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author | Mo, Shu-Fen Cai, Zeng-Zhi Kuai, Wen-Hao Li, Xuexin Chen, Yu-Tong |
author_facet | Mo, Shu-Fen Cai, Zeng-Zhi Kuai, Wen-Hao Li, Xuexin Chen, Yu-Tong |
author_sort | Mo, Shu-Fen |
collection | PubMed |
description | Background: The US Food and Drug Administration (FDA)’s tumor-agnostic approval of pembrolizumab in high tumor mutational burden (TMB-high, i.e., TMB≥10 mut/Mb) cases, based on the data from KEYNOTE-158, has raised considerable concerns among the immuno-oncology community. This study aims to statistically infer the optimal universal cutoff in defining TMB-high that is predictive of the efficacy of anti-PD-(L) 1 therapy in advanced solid tumors. Methods: We integrated MSK-IMPACT TMB data from a public cohort and the objective response rate (ORR) for anti-PD-(L) 1 monotherapy across diverse cancer types in published trials. The optimal TMB cutoff was determined by varying the universal cutoff to define TMB-high across cancer types and examining the cancer-level correlation between objective response rate and the proportion of TMB-high cases. The utility of this cutoff in predicting overall survival (OS) benefits from anti-PD-(L) 1 therapy was then evaluated in a validation cohort of advanced cancers with coupled MSK-IMPACT TMB and OS data. In silico analysis of whole-exome sequencing data from The Cancer Genome Atlas was further employed to assess the generalizability of the identified cutoff among panels comprising several hundred genes. Results: The cancer type-level analysis identified 10 mut/Mb as the optimal cutoff for MSK-IMPACT in defining TMB-high, with the corresponding TMB-high (TMB≥10 mut/Mb) percentage strongly correlated with ORR for PD-(L) 1 blockade across cancer types [correlation coefficient, 0.72 (95% CI, 0.45–0.88)]. This cutoff was also the optimum in defining TMB-high (via MSK-IMPACT) when predicting OS benefits from anti-PD-(L) 1 therapy in the validation cohort. In this cohort, TMB≥10 mut/Mb was associated with significantly improved OS (hazard ratio, 0.58 [95% CI, 0.48–0.71]; p < 0.001). Moreover, in silico analyses revealed excellent agreement of TMB≥10 mut/Mb cases between MSK-IMPACT and the FDA-approved panels and between MSK-IMPACT and various randomly sampled panels. Conclusion: Our study demonstrates that 10 mut/Mb is the optimal, universal cutoff for TMB-high that guides the clinical application of anti-PD-(L) 1 therapy for advanced solid tumors. It also provides rigorous evidence beyond KEYNOTE-158 for the utility of TMB≥10 mut/Mb in predicting the efficacy of PD-(L) 1 blockade in broader settings, which could help to mitigate the challenges in embracing the tumor-agnostic approval of pembrolizumab in TMB-high cases. |
format | Online Article Text |
id | pubmed-10248461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102484612023-06-09 Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers Mo, Shu-Fen Cai, Zeng-Zhi Kuai, Wen-Hao Li, Xuexin Chen, Yu-Tong Front Cell Dev Biol Cell and Developmental Biology Background: The US Food and Drug Administration (FDA)’s tumor-agnostic approval of pembrolizumab in high tumor mutational burden (TMB-high, i.e., TMB≥10 mut/Mb) cases, based on the data from KEYNOTE-158, has raised considerable concerns among the immuno-oncology community. This study aims to statistically infer the optimal universal cutoff in defining TMB-high that is predictive of the efficacy of anti-PD-(L) 1 therapy in advanced solid tumors. Methods: We integrated MSK-IMPACT TMB data from a public cohort and the objective response rate (ORR) for anti-PD-(L) 1 monotherapy across diverse cancer types in published trials. The optimal TMB cutoff was determined by varying the universal cutoff to define TMB-high across cancer types and examining the cancer-level correlation between objective response rate and the proportion of TMB-high cases. The utility of this cutoff in predicting overall survival (OS) benefits from anti-PD-(L) 1 therapy was then evaluated in a validation cohort of advanced cancers with coupled MSK-IMPACT TMB and OS data. In silico analysis of whole-exome sequencing data from The Cancer Genome Atlas was further employed to assess the generalizability of the identified cutoff among panels comprising several hundred genes. Results: The cancer type-level analysis identified 10 mut/Mb as the optimal cutoff for MSK-IMPACT in defining TMB-high, with the corresponding TMB-high (TMB≥10 mut/Mb) percentage strongly correlated with ORR for PD-(L) 1 blockade across cancer types [correlation coefficient, 0.72 (95% CI, 0.45–0.88)]. This cutoff was also the optimum in defining TMB-high (via MSK-IMPACT) when predicting OS benefits from anti-PD-(L) 1 therapy in the validation cohort. In this cohort, TMB≥10 mut/Mb was associated with significantly improved OS (hazard ratio, 0.58 [95% CI, 0.48–0.71]; p < 0.001). Moreover, in silico analyses revealed excellent agreement of TMB≥10 mut/Mb cases between MSK-IMPACT and the FDA-approved panels and between MSK-IMPACT and various randomly sampled panels. Conclusion: Our study demonstrates that 10 mut/Mb is the optimal, universal cutoff for TMB-high that guides the clinical application of anti-PD-(L) 1 therapy for advanced solid tumors. It also provides rigorous evidence beyond KEYNOTE-158 for the utility of TMB≥10 mut/Mb in predicting the efficacy of PD-(L) 1 blockade in broader settings, which could help to mitigate the challenges in embracing the tumor-agnostic approval of pembrolizumab in TMB-high cases. Frontiers Media S.A. 2023-05-25 /pmc/articles/PMC10248461/ /pubmed/37305681 http://dx.doi.org/10.3389/fcell.2023.1209243 Text en Copyright © 2023 Mo, Cai, Kuai, Li and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Mo, Shu-Fen Cai, Zeng-Zhi Kuai, Wen-Hao Li, Xuexin Chen, Yu-Tong Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title | Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title_full | Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title_fullStr | Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title_full_unstemmed | Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title_short | Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers |
title_sort | universal cutoff for tumor mutational burden in predicting the efficacy of anti-pd-(l)1 therapy for advanced cancers |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248461/ https://www.ncbi.nlm.nih.gov/pubmed/37305681 http://dx.doi.org/10.3389/fcell.2023.1209243 |
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