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Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment

Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear. Methods: We identified and evaluated immunophenotyping clusters in ccRC...

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Autores principales: Xu, Wenhao, Anwaier, Aihetaimujiang, Ma, Chunguang, Liu, Wangrui, Tian, Xi, Su, Jiaqi, Zhu, Wenkai, Shi, Guohai, Wei, Shiyin, Xu, Hong, Qu, Yuanyuan, Ye, Dingwei, Zhang, Hailiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685518/
https://www.ncbi.nlm.nih.gov/pubmed/34938737
http://dx.doi.org/10.3389/fcell.2021.785410
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author Xu, Wenhao
Anwaier, Aihetaimujiang
Ma, Chunguang
Liu, Wangrui
Tian, Xi
Su, Jiaqi
Zhu, Wenkai
Shi, Guohai
Wei, Shiyin
Xu, Hong
Qu, Yuanyuan
Ye, Dingwei
Zhang, Hailiang
author_facet Xu, Wenhao
Anwaier, Aihetaimujiang
Ma, Chunguang
Liu, Wangrui
Tian, Xi
Su, Jiaqi
Zhu, Wenkai
Shi, Guohai
Wei, Shiyin
Xu, Hong
Qu, Yuanyuan
Ye, Dingwei
Zhang, Hailiang
author_sort Xu, Wenhao
collection PubMed
description Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear. Methods: We identified and evaluated immunophenotyping clusters in ccRCC using machine-learning algorithms. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies were performed and validated. Results: Three immunophenotyping clusters with gradual levels of immune infiltration were identified. The intermediate and high immune infiltration clusters (Clusters B and C) were associated with a worse prognosis for ccRCC patients. Tumors in the immune-hot Clusters B and C showed pro-tumorigenic immune infiltration, and these patients showed significantly worse survival compared with patients in the immune-cold Cluster A in the training and testing cohorts (n = 422). In addition to distinct immune cell infiltrations of immunophenotyping, we detected significant differences in DNA variation among clusters, suggesting a high degree of genetic heterogeneity. Furthermore, expressions of multiple immune checkpoint molecules were significantly increased. Clusters B and C predicted favorable outcomes in 64 ccRCC patients receiving immune checkpoint therapies from the FUSCC cohort. In 360 ccRCC patients from the FUSCC validation cohort, Clusters B and C significantly predicted worse prognosis compared with Cluster A. After immunophenotyping of ccRCC was confirmed, significantly increased tertiary lymphatic structures, aggressive phenotype, elevated glycolysis and PD-L1 expression, higher abundance of CD8(+) T cells, and TCRn cell infiltration were found in the immune-hot Clusters B and C. Conclusion: This study described immunophenotyping clusters that improved the prognostic accuracy of the immune contexture in the ccRCC microenvironment. Our discovery of the novel independent prognostic indicators in ccRCC highlights the relationship between tumor phenotype and immune microenvironment.
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spelling pubmed-86855182021-12-21 Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment Xu, Wenhao Anwaier, Aihetaimujiang Ma, Chunguang Liu, Wangrui Tian, Xi Su, Jiaqi Zhu, Wenkai Shi, Guohai Wei, Shiyin Xu, Hong Qu, Yuanyuan Ye, Dingwei Zhang, Hailiang Front Cell Dev Biol Cell and Developmental Biology Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear. Methods: We identified and evaluated immunophenotyping clusters in ccRCC using machine-learning algorithms. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies were performed and validated. Results: Three immunophenotyping clusters with gradual levels of immune infiltration were identified. The intermediate and high immune infiltration clusters (Clusters B and C) were associated with a worse prognosis for ccRCC patients. Tumors in the immune-hot Clusters B and C showed pro-tumorigenic immune infiltration, and these patients showed significantly worse survival compared with patients in the immune-cold Cluster A in the training and testing cohorts (n = 422). In addition to distinct immune cell infiltrations of immunophenotyping, we detected significant differences in DNA variation among clusters, suggesting a high degree of genetic heterogeneity. Furthermore, expressions of multiple immune checkpoint molecules were significantly increased. Clusters B and C predicted favorable outcomes in 64 ccRCC patients receiving immune checkpoint therapies from the FUSCC cohort. In 360 ccRCC patients from the FUSCC validation cohort, Clusters B and C significantly predicted worse prognosis compared with Cluster A. After immunophenotyping of ccRCC was confirmed, significantly increased tertiary lymphatic structures, aggressive phenotype, elevated glycolysis and PD-L1 expression, higher abundance of CD8(+) T cells, and TCRn cell infiltration were found in the immune-hot Clusters B and C. Conclusion: This study described immunophenotyping clusters that improved the prognostic accuracy of the immune contexture in the ccRCC microenvironment. Our discovery of the novel independent prognostic indicators in ccRCC highlights the relationship between tumor phenotype and immune microenvironment. Frontiers Media S.A. 2021-12-06 /pmc/articles/PMC8685518/ /pubmed/34938737 http://dx.doi.org/10.3389/fcell.2021.785410 Text en Copyright © 2021 Xu, Anwaier, Ma, Liu, Tian, Su, Zhu, Shi, Wei, Xu, Qu, Ye and Zhang. 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 Cell and Developmental Biology
Xu, Wenhao
Anwaier, Aihetaimujiang
Ma, Chunguang
Liu, Wangrui
Tian, Xi
Su, Jiaqi
Zhu, Wenkai
Shi, Guohai
Wei, Shiyin
Xu, Hong
Qu, Yuanyuan
Ye, Dingwei
Zhang, Hailiang
Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title_full Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title_fullStr Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title_full_unstemmed Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title_short Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment
title_sort prognostic immunophenotyping clusters of clear cell renal cell carcinoma defined by the unique tumor immune microenvironment
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685518/
https://www.ncbi.nlm.nih.gov/pubmed/34938737
http://dx.doi.org/10.3389/fcell.2021.785410
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