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Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing

BACKGROUND: Tumor mutational burden (TMB) is emerging as a promising biomarker in immune checkpoint inhibitor (ICI) therapy. Despite whole-exome sequencing (WES) being the gold standard for quantifying TMB, TMB is determined by selected targeted panels in most cases, and WES-derived TMB data are lac...

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Autores principales: Zhou, Chuang, Chen, Song, Xu, Fei, Wei, Jinwang, Zhou, Xiaoyu, Wu, Zhiqiang, Zhao, Longshuan, Liu, Jun, Guo, Wenbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506705/
https://www.ncbi.nlm.nih.gov/pubmed/34733989
http://dx.doi.org/10.21037/atm-21-4227
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author Zhou, Chuang
Chen, Song
Xu, Fei
Wei, Jinwang
Zhou, Xiaoyu
Wu, Zhiqiang
Zhao, Longshuan
Liu, Jun
Guo, Wenbo
author_facet Zhou, Chuang
Chen, Song
Xu, Fei
Wei, Jinwang
Zhou, Xiaoyu
Wu, Zhiqiang
Zhao, Longshuan
Liu, Jun
Guo, Wenbo
author_sort Zhou, Chuang
collection PubMed
description BACKGROUND: Tumor mutational burden (TMB) is emerging as a promising biomarker in immune checkpoint inhibitor (ICI) therapy. Despite whole-exome sequencing (WES) being the gold standard for quantifying TMB, TMB is determined by selected targeted panels in most cases, and WES-derived TMB data are lacking due to the greater cost and complexity. Determining TMB thresholds is another issue that needs attention. METHODS: A total of 309 patients who had received ICI therapy, representing five cancers (listed in “Results”), were recruited. Among them, 269 patients were evaluable for survival analysis. Tumor and matched blood samples from the patients were analyzed using WES and somatic mutations were determined. TMB is defined as the total number of somatic nonsynonymous mutations in the tumor exome in our study. The patients were divided into different TMB subgroups according to a common fixed number (10 mutations/Mb) or the top tertile within each tumor type. RESULTS: The distribution of WES-derived median TMBs was highly variable across different tumor types, ranging from 2.71 (cholangiocarcinoma) to 2.97 (nervous system tumor), 3.69 (gastric cancer), 4.31 (hepatocellular carcinoma), and 4.64 [colorectal cancer (CRC)] mutations/Mb. In CRC, the survival benefit of TMB-high patients was significant using both the top tertile and the 10 mutations/Mb threshold. In hepatocellular carcinoma, the 10 mutations/Mb threshold showed an advantage over the top tertile threshold. Among patients with nervous system tumors, cholangiocarcinoma, and gastric cancer, no obvious survival differences were observed between the TMB-high and TMB-low groups with either TMB stratification approach. CONCLUSIONS: The TMB threshold criterion may vary for different cancers. Our data suggest that TMB is unable to predict ICI benefit across all cancer types in Chinese patients. However, it may be an effective biomarker for predicting the clinical benefit of ICI therapy for patients with CRC.
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spelling pubmed-85067052021-11-02 Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing Zhou, Chuang Chen, Song Xu, Fei Wei, Jinwang Zhou, Xiaoyu Wu, Zhiqiang Zhao, Longshuan Liu, Jun Guo, Wenbo Ann Transl Med Original Article BACKGROUND: Tumor mutational burden (TMB) is emerging as a promising biomarker in immune checkpoint inhibitor (ICI) therapy. Despite whole-exome sequencing (WES) being the gold standard for quantifying TMB, TMB is determined by selected targeted panels in most cases, and WES-derived TMB data are lacking due to the greater cost and complexity. Determining TMB thresholds is another issue that needs attention. METHODS: A total of 309 patients who had received ICI therapy, representing five cancers (listed in “Results”), were recruited. Among them, 269 patients were evaluable for survival analysis. Tumor and matched blood samples from the patients were analyzed using WES and somatic mutations were determined. TMB is defined as the total number of somatic nonsynonymous mutations in the tumor exome in our study. The patients were divided into different TMB subgroups according to a common fixed number (10 mutations/Mb) or the top tertile within each tumor type. RESULTS: The distribution of WES-derived median TMBs was highly variable across different tumor types, ranging from 2.71 (cholangiocarcinoma) to 2.97 (nervous system tumor), 3.69 (gastric cancer), 4.31 (hepatocellular carcinoma), and 4.64 [colorectal cancer (CRC)] mutations/Mb. In CRC, the survival benefit of TMB-high patients was significant using both the top tertile and the 10 mutations/Mb threshold. In hepatocellular carcinoma, the 10 mutations/Mb threshold showed an advantage over the top tertile threshold. Among patients with nervous system tumors, cholangiocarcinoma, and gastric cancer, no obvious survival differences were observed between the TMB-high and TMB-low groups with either TMB stratification approach. CONCLUSIONS: The TMB threshold criterion may vary for different cancers. Our data suggest that TMB is unable to predict ICI benefit across all cancer types in Chinese patients. However, it may be an effective biomarker for predicting the clinical benefit of ICI therapy for patients with CRC. AME Publishing Company 2021-09 /pmc/articles/PMC8506705/ /pubmed/34733989 http://dx.doi.org/10.21037/atm-21-4227 Text en 2021 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zhou, Chuang
Chen, Song
Xu, Fei
Wei, Jinwang
Zhou, Xiaoyu
Wu, Zhiqiang
Zhao, Longshuan
Liu, Jun
Guo, Wenbo
Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title_full Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title_fullStr Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title_full_unstemmed Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title_short Estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
title_sort estimating tumor mutational burden across multiple cancer types using whole-exome sequencing
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506705/
https://www.ncbi.nlm.nih.gov/pubmed/34733989
http://dx.doi.org/10.21037/atm-21-4227
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