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Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden
BACKGROUND: Pembrolizumab is FDA approved for tumors with tumor mutational burden (TMB) of ≥10 mutations/megabase (mut/Mb). However, the response to immune checkpoint inhibitors (ICI) varies significantly among cancer histologies. We describe the landscape of frameshift mutations (FSs) and evaluated...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432623/ https://www.ncbi.nlm.nih.gov/pubmed/37586768 http://dx.doi.org/10.1136/jitc-2023-007440 |
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author | Florou, Vaia Floudas, Charalampos S Maoz, Asaf Naqash, Abdul Rafeh Norton, Carter Tan, Aik Choon Sokol, Ethan S Frampton, Garrett Soares, Heloisa P Puri, Sonam Swami, Umang Wilky, Breelyn Hosein, Peter Trent, Jonathan Lopes, Gilberto de Lima Park, Wungki Garrido-Laguna, Ignacio |
author_facet | Florou, Vaia Floudas, Charalampos S Maoz, Asaf Naqash, Abdul Rafeh Norton, Carter Tan, Aik Choon Sokol, Ethan S Frampton, Garrett Soares, Heloisa P Puri, Sonam Swami, Umang Wilky, Breelyn Hosein, Peter Trent, Jonathan Lopes, Gilberto de Lima Park, Wungki Garrido-Laguna, Ignacio |
author_sort | Florou, Vaia |
collection | PubMed |
description | BACKGROUND: Pembrolizumab is FDA approved for tumors with tumor mutational burden (TMB) of ≥10 mutations/megabase (mut/Mb). However, the response to immune checkpoint inhibitors (ICI) varies significantly among cancer histologies. We describe the landscape of frameshift mutations (FSs) and evaluated their role as a predictive biomarker to ICI in a clinical cohort of patients. METHODS: Comprehensive genomic profiling was performed on a cohort of solid tumor samples examining at least 324 genes. The clinical cohort included patients with metastatic solid malignancies who received ICI monotherapy and had tumor sequencing. Progression-free survival (PFS), overall survival, and objective response rates (ORR) were compared between the groups. RESULTS: We analyzed 246,252 microsatellite stable (MSS) and 4561 samples with microsatellite instability across solid tumors. Histologies were divided into groups according to TMB and FS. MSS distribution: TMB-L (<10 mut/Mb)/FS-A (absent FS) (N=111,065, 45%), TMB-H (≥10 mut/Mb)/FS-A (N=15,313, 6%), TMB-L/FS-P (present ≥1 FS) (N=98,389, 40%) and TMB-H/FS-P (N=21,485, 9%). FSs were predominantly identified in the p53 pathway. In the clinical cohort, 212 patients were included. Groups: TMB-L/FS-A (N=80, 38%), TMB-H/FS-A (N=36, 17%), TMB-L/FS-P (N=57, 27%), TMB-H/FS-P (N=39, 18%). FSs were associated with a higher ORR to ICI, 23.8% vs 12.8% (p=0.02). TMB-L/FS-P had superior median PFS (5.1 months) vs TMB-L/FS-A (3.6 months, p<0.01). The 12-month PFS probability was 34% for TMB-L/FS-P vs 17.1% for TMB-L/FS-A. CONCLUSIONS: FSs are found in 47% of patients with MSS/TMB-L solid tumors in a pan-cancer cohort. FS may complement TMB in predicting immunotherapy responses, particularly for tumors with low TMB. |
format | Online Article Text |
id | pubmed-10432623 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-104326232023-08-18 Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden Florou, Vaia Floudas, Charalampos S Maoz, Asaf Naqash, Abdul Rafeh Norton, Carter Tan, Aik Choon Sokol, Ethan S Frampton, Garrett Soares, Heloisa P Puri, Sonam Swami, Umang Wilky, Breelyn Hosein, Peter Trent, Jonathan Lopes, Gilberto de Lima Park, Wungki Garrido-Laguna, Ignacio J Immunother Cancer Immunotherapy Biomarkers BACKGROUND: Pembrolizumab is FDA approved for tumors with tumor mutational burden (TMB) of ≥10 mutations/megabase (mut/Mb). However, the response to immune checkpoint inhibitors (ICI) varies significantly among cancer histologies. We describe the landscape of frameshift mutations (FSs) and evaluated their role as a predictive biomarker to ICI in a clinical cohort of patients. METHODS: Comprehensive genomic profiling was performed on a cohort of solid tumor samples examining at least 324 genes. The clinical cohort included patients with metastatic solid malignancies who received ICI monotherapy and had tumor sequencing. Progression-free survival (PFS), overall survival, and objective response rates (ORR) were compared between the groups. RESULTS: We analyzed 246,252 microsatellite stable (MSS) and 4561 samples with microsatellite instability across solid tumors. Histologies were divided into groups according to TMB and FS. MSS distribution: TMB-L (<10 mut/Mb)/FS-A (absent FS) (N=111,065, 45%), TMB-H (≥10 mut/Mb)/FS-A (N=15,313, 6%), TMB-L/FS-P (present ≥1 FS) (N=98,389, 40%) and TMB-H/FS-P (N=21,485, 9%). FSs were predominantly identified in the p53 pathway. In the clinical cohort, 212 patients were included. Groups: TMB-L/FS-A (N=80, 38%), TMB-H/FS-A (N=36, 17%), TMB-L/FS-P (N=57, 27%), TMB-H/FS-P (N=39, 18%). FSs were associated with a higher ORR to ICI, 23.8% vs 12.8% (p=0.02). TMB-L/FS-P had superior median PFS (5.1 months) vs TMB-L/FS-A (3.6 months, p<0.01). The 12-month PFS probability was 34% for TMB-L/FS-P vs 17.1% for TMB-L/FS-A. CONCLUSIONS: FSs are found in 47% of patients with MSS/TMB-L solid tumors in a pan-cancer cohort. FS may complement TMB in predicting immunotherapy responses, particularly for tumors with low TMB. BMJ Publishing Group 2023-08-16 /pmc/articles/PMC10432623/ /pubmed/37586768 http://dx.doi.org/10.1136/jitc-2023-007440 Text en © Author(s) (or their employer(s)) 2023. 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 Florou, Vaia Floudas, Charalampos S Maoz, Asaf Naqash, Abdul Rafeh Norton, Carter Tan, Aik Choon Sokol, Ethan S Frampton, Garrett Soares, Heloisa P Puri, Sonam Swami, Umang Wilky, Breelyn Hosein, Peter Trent, Jonathan Lopes, Gilberto de Lima Park, Wungki Garrido-Laguna, Ignacio Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title | Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title_full | Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title_fullStr | Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title_full_unstemmed | Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title_short | Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
title_sort | real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden |
topic | Immunotherapy Biomarkers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432623/ https://www.ncbi.nlm.nih.gov/pubmed/37586768 http://dx.doi.org/10.1136/jitc-2023-007440 |
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