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TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types
Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. W...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004558/ https://www.ncbi.nlm.nih.gov/pubmed/35344507 http://dx.doi.org/10.18632/aging.203980 |
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author | Cao, Jia-Zheng Yao, Gao-Sheng Liu, Fei Tang, Yi-Ming Li, Peng-Ju Feng, Zi-Hao Luo, Jun-Hang Wei, Jin-Huan |
author_facet | Cao, Jia-Zheng Yao, Gao-Sheng Liu, Fei Tang, Yi-Ming Li, Peng-Ju Feng, Zi-Hao Luo, Jun-Hang Wei, Jin-Huan |
author_sort | Cao, Jia-Zheng |
collection | PubMed |
description | Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. We downloaded somatic mutation data for 46,697 patients and tumor-infiltrating immune cells levels data for 11070 patients, then combined TP53 and BRAF mutation status into a biomarker model and found that the predict ability of TP53/BRAF mutation model is more powerful than some past models. Commonly, patients with high-TMB status have better response to ICI therapy than patients with low-TMB status. However, the genotype of TP53(MUT)BRAF(WT) in high-TMB status cohort have poorer response to ICI therapy than the genotype of BRAF(MUT)TP53(WT) in low-TMB status (Median, 18 months vs 47 month). Thus, TP53/BRAF mutation model can add predictive value to TMB in identifying patients who benefited from ICI treatment, which can enable more informed treatment decisions. |
format | Online Article Text |
id | pubmed-9004558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-90045582022-04-13 TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types Cao, Jia-Zheng Yao, Gao-Sheng Liu, Fei Tang, Yi-Ming Li, Peng-Ju Feng, Zi-Hao Luo, Jun-Hang Wei, Jin-Huan Aging (Albany NY) Research Paper Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. We downloaded somatic mutation data for 46,697 patients and tumor-infiltrating immune cells levels data for 11070 patients, then combined TP53 and BRAF mutation status into a biomarker model and found that the predict ability of TP53/BRAF mutation model is more powerful than some past models. Commonly, patients with high-TMB status have better response to ICI therapy than patients with low-TMB status. However, the genotype of TP53(MUT)BRAF(WT) in high-TMB status cohort have poorer response to ICI therapy than the genotype of BRAF(MUT)TP53(WT) in low-TMB status (Median, 18 months vs 47 month). Thus, TP53/BRAF mutation model can add predictive value to TMB in identifying patients who benefited from ICI treatment, which can enable more informed treatment decisions. Impact Journals 2022-03-27 /pmc/articles/PMC9004558/ /pubmed/35344507 http://dx.doi.org/10.18632/aging.203980 Text en Copyright: © 2022 Cao et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Cao, Jia-Zheng Yao, Gao-Sheng Liu, Fei Tang, Yi-Ming Li, Peng-Ju Feng, Zi-Hao Luo, Jun-Hang Wei, Jin-Huan TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title | TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title_full | TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title_fullStr | TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title_full_unstemmed | TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title_short | TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
title_sort | tp53/braf mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9004558/ https://www.ncbi.nlm.nih.gov/pubmed/35344507 http://dx.doi.org/10.18632/aging.203980 |
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