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Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma

Alteration in the polybromo‐1 (PBRM1) protein encoding gene PBRM1 is the second most frequent mutation in clear cell renal cell carcinoma (ccRCC). It causes a series of changes in the tumorigenesis, progression, prognosis, and immune response of ccRCC patients. This study explored the PBRM1‐associat...

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Autores principales: Chen, Jiayi, Yao, Chunlin, Qiao, Nan, Ge, Yangyang, Li, Jianhua, Lin, Yun, Yao, Shanglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495284/
https://www.ncbi.nlm.nih.gov/pubmed/34535962
http://dx.doi.org/10.1002/cam4.4115
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author Chen, Jiayi
Yao, Chunlin
Qiao, Nan
Ge, Yangyang
Li, Jianhua
Lin, Yun
Yao, Shanglong
author_facet Chen, Jiayi
Yao, Chunlin
Qiao, Nan
Ge, Yangyang
Li, Jianhua
Lin, Yun
Yao, Shanglong
author_sort Chen, Jiayi
collection PubMed
description Alteration in the polybromo‐1 (PBRM1) protein encoding gene PBRM1 is the second most frequent mutation in clear cell renal cell carcinoma (ccRCC). It causes a series of changes in the tumorigenesis, progression, prognosis, and immune response of ccRCC patients. This study explored the PBRM1‐associated immunological features and identified the immune‐related genes (IRGs) linked to PBRM1 mutation using bioinformatics methods. A total of 37 survival IRGs associated with PBRM1 mutation in ccRCC patients were identified. To further explore the role of these IRGs in ccRCC and their association with immune status, eight IRGs with remarkable potential as individual targets were selected. An immune model that was constructed showed good performance in stratifying patients into different subgroups, showing clinical application potential compared to traditional clinical factors. Patients in the high‐risk group were inclined to have more advanced stage and higher grade tumors with node metastasis, distant metastasis, and poorer prognosis. Furthermore, these patients had high percentages of regulatory T cells, follicular helper T cells, and M0 macrophages and exhibited high expression levels of immune checkpoints proteins, such as CTLA‐4, PD‐1, LAG‐3, TIGIT, and CD47. Finally, a nomogram integrating the model and clinical factors for clinical application showed a more robust predictive performance for prognosis. The prediction model associated with PBRM1 mutation status and immunity can serve as a promising tool to stratify patients depending upon their immune status, thus facilitating immunotherapy in the future.
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spelling pubmed-84952842021-10-08 Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma Chen, Jiayi Yao, Chunlin Qiao, Nan Ge, Yangyang Li, Jianhua Lin, Yun Yao, Shanglong Cancer Med Clinical Cancer Research Alteration in the polybromo‐1 (PBRM1) protein encoding gene PBRM1 is the second most frequent mutation in clear cell renal cell carcinoma (ccRCC). It causes a series of changes in the tumorigenesis, progression, prognosis, and immune response of ccRCC patients. This study explored the PBRM1‐associated immunological features and identified the immune‐related genes (IRGs) linked to PBRM1 mutation using bioinformatics methods. A total of 37 survival IRGs associated with PBRM1 mutation in ccRCC patients were identified. To further explore the role of these IRGs in ccRCC and their association with immune status, eight IRGs with remarkable potential as individual targets were selected. An immune model that was constructed showed good performance in stratifying patients into different subgroups, showing clinical application potential compared to traditional clinical factors. Patients in the high‐risk group were inclined to have more advanced stage and higher grade tumors with node metastasis, distant metastasis, and poorer prognosis. Furthermore, these patients had high percentages of regulatory T cells, follicular helper T cells, and M0 macrophages and exhibited high expression levels of immune checkpoints proteins, such as CTLA‐4, PD‐1, LAG‐3, TIGIT, and CD47. Finally, a nomogram integrating the model and clinical factors for clinical application showed a more robust predictive performance for prognosis. The prediction model associated with PBRM1 mutation status and immunity can serve as a promising tool to stratify patients depending upon their immune status, thus facilitating immunotherapy in the future. John Wiley and Sons Inc. 2021-09-18 /pmc/articles/PMC8495284/ /pubmed/34535962 http://dx.doi.org/10.1002/cam4.4115 Text en © 2021 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Cancer Research
Chen, Jiayi
Yao, Chunlin
Qiao, Nan
Ge, Yangyang
Li, Jianhua
Lin, Yun
Yao, Shanglong
Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title_full Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title_fullStr Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title_full_unstemmed Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title_short Development and validation of a PBRM1‐associated immune prognostic model for clear cell renal cell carcinoma
title_sort development and validation of a pbrm1‐associated immune prognostic model for clear cell renal cell carcinoma
topic Clinical Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495284/
https://www.ncbi.nlm.nih.gov/pubmed/34535962
http://dx.doi.org/10.1002/cam4.4115
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