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PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers
Background: There has been evidence that Polybromo-1 (PBRM1) mutation was closely associated with immunotherapy response in clear cell renal cell carcinoma (ccRCC). However, it remains incompletely unclear whether PBRM1 mutations correlate with ICI response in pan-cancer. Methods: The clinical data...
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/PMC9868445/ https://www.ncbi.nlm.nih.gov/pubmed/36699446 http://dx.doi.org/10.3389/fgene.2022.1066347 |
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author | Dai, Jiali Cui, Yanan Liang, Xiao Xu, Jiali Li, Jun Chen, Yu Zhang, Erbao Guo, Renhua |
author_facet | Dai, Jiali Cui, Yanan Liang, Xiao Xu, Jiali Li, Jun Chen, Yu Zhang, Erbao Guo, Renhua |
author_sort | Dai, Jiali |
collection | PubMed |
description | Background: There has been evidence that Polybromo-1 (PBRM1) mutation was closely associated with immunotherapy response in clear cell renal cell carcinoma (ccRCC). However, it remains incompletely unclear whether PBRM1 mutations correlate with ICI response in pan-cancer. Methods: The clinical data and whole exome sequencing (WES) data were collected from seven published immunotherapy studies to evaluate the association between PBRM1 mutation and ICIs efficacy in the discovery cohort. In order to provide further insight into the relationship between PBRM1 and immunity, we analyzed a relatively large sample as a validation cohort. Moreover, we also collected the clinical data and mutation information of 134 non-small cell lung cancer (NSCLC) patients from the First Affiliated Hospital of Nanjing Medical University to verify the findings. Gene set enrichment analysis (GSEA) was used to evaluate the relationship between PBRM1 and immune-related pathway. Results: Our results found that PBRM1 mutation were associated with immune response in the discovery cohort (Progression free survival [PFS]: hazard ratio (HR) = .51, 95% CI: .28–.95, p = .030; objective response rate [ORR]: 47.92% vs. 28.21%, p = .0044; disease control rate [DCR]: 72.92% vs. 47.53%, p = .0008). In the validation cohort, the patients with PBRM1 mutation had a longer overall survival (OS) (hazard ratio = .69, 95% CI: .53–.91, p = .006). In our non-small cell lung cancer cohort, PFS, objective response rate and disease control rate had obvious superiority in the patients with PBRM1 mutation than those without PBRM1 mutation (PFS: HR = .268, 95% CI: 084–.854, p = .04, ORR: 55.56% vs. 20.00%, p = .027, DCR: 100% vs. 75.20%). Using the Gene set enrichment analysis (GSEA) in TCGA cohorts, PBRM1 mutation was closely related to immune efficacy and immune microenvironment, including killer cell mediated immunity regulation, cell cytokine production, CD8(+) T-cell activation and MHC protein binding process. Conclusion: There is a strong correlation between PBRM1 mutation and prognosis and immune response. Based on the findings, PBRM1 mutation may be a promising immunotherapeutic signature that could guide clinical management and personalized immunotherapy. |
format | Online Article Text |
id | pubmed-9868445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98684452023-01-24 PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers Dai, Jiali Cui, Yanan Liang, Xiao Xu, Jiali Li, Jun Chen, Yu Zhang, Erbao Guo, Renhua Front Genet Genetics Background: There has been evidence that Polybromo-1 (PBRM1) mutation was closely associated with immunotherapy response in clear cell renal cell carcinoma (ccRCC). However, it remains incompletely unclear whether PBRM1 mutations correlate with ICI response in pan-cancer. Methods: The clinical data and whole exome sequencing (WES) data were collected from seven published immunotherapy studies to evaluate the association between PBRM1 mutation and ICIs efficacy in the discovery cohort. In order to provide further insight into the relationship between PBRM1 and immunity, we analyzed a relatively large sample as a validation cohort. Moreover, we also collected the clinical data and mutation information of 134 non-small cell lung cancer (NSCLC) patients from the First Affiliated Hospital of Nanjing Medical University to verify the findings. Gene set enrichment analysis (GSEA) was used to evaluate the relationship between PBRM1 and immune-related pathway. Results: Our results found that PBRM1 mutation were associated with immune response in the discovery cohort (Progression free survival [PFS]: hazard ratio (HR) = .51, 95% CI: .28–.95, p = .030; objective response rate [ORR]: 47.92% vs. 28.21%, p = .0044; disease control rate [DCR]: 72.92% vs. 47.53%, p = .0008). In the validation cohort, the patients with PBRM1 mutation had a longer overall survival (OS) (hazard ratio = .69, 95% CI: .53–.91, p = .006). In our non-small cell lung cancer cohort, PFS, objective response rate and disease control rate had obvious superiority in the patients with PBRM1 mutation than those without PBRM1 mutation (PFS: HR = .268, 95% CI: 084–.854, p = .04, ORR: 55.56% vs. 20.00%, p = .027, DCR: 100% vs. 75.20%). Using the Gene set enrichment analysis (GSEA) in TCGA cohorts, PBRM1 mutation was closely related to immune efficacy and immune microenvironment, including killer cell mediated immunity regulation, cell cytokine production, CD8(+) T-cell activation and MHC protein binding process. Conclusion: There is a strong correlation between PBRM1 mutation and prognosis and immune response. Based on the findings, PBRM1 mutation may be a promising immunotherapeutic signature that could guide clinical management and personalized immunotherapy. Frontiers Media S.A. 2023-01-09 /pmc/articles/PMC9868445/ /pubmed/36699446 http://dx.doi.org/10.3389/fgene.2022.1066347 Text en Copyright © 2023 Dai, Cui, Liang, Xu, Li, Chen, Zhang and Guo. 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 | Genetics Dai, Jiali Cui, Yanan Liang, Xiao Xu, Jiali Li, Jun Chen, Yu Zhang, Erbao Guo, Renhua PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title | PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title_full | PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title_fullStr | PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title_full_unstemmed | PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title_short | PBRM1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
title_sort | pbrm1 mutation as a predictive biomarker for immunotherapy in multiple cancers |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868445/ https://www.ncbi.nlm.nih.gov/pubmed/36699446 http://dx.doi.org/10.3389/fgene.2022.1066347 |
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