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The immune subtypes and landscape of sarcomas

BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suita...

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Autores principales: Weng, Weiwei, Yu, Lin, Li, Zhang, Tan, Cong, Lv, Jiaojie, Lao, I. Weng, Hu, Wenhuo, Deng, Zhenzhong, Liu, Zebing, Wang, Jian, Xu, Midie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508767/
https://www.ncbi.nlm.nih.gov/pubmed/36153483
http://dx.doi.org/10.1186/s12865-022-00522-3
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author Weng, Weiwei
Yu, Lin
Li, Zhang
Tan, Cong
Lv, Jiaojie
Lao, I. Weng
Hu, Wenhuo
Deng, Zhenzhong
Liu, Zebing
Wang, Jian
Xu, Midie
author_facet Weng, Weiwei
Yu, Lin
Li, Zhang
Tan, Cong
Lv, Jiaojie
Lao, I. Weng
Hu, Wenhuo
Deng, Zhenzhong
Liu, Zebing
Wang, Jian
Xu, Midie
author_sort Weng, Weiwei
collection PubMed
description BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. RESULTS: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune “hot” and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune “cold” phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. CONCLUSIONS: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12865-022-00522-3.
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spelling pubmed-95087672022-09-25 The immune subtypes and landscape of sarcomas Weng, Weiwei Yu, Lin Li, Zhang Tan, Cong Lv, Jiaojie Lao, I. Weng Hu, Wenhuo Deng, Zhenzhong Liu, Zebing Wang, Jian Xu, Midie BMC Immunol Research BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. RESULTS: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune “hot” and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune “cold” phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. CONCLUSIONS: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12865-022-00522-3. BioMed Central 2022-09-24 /pmc/articles/PMC9508767/ /pubmed/36153483 http://dx.doi.org/10.1186/s12865-022-00522-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Weng, Weiwei
Yu, Lin
Li, Zhang
Tan, Cong
Lv, Jiaojie
Lao, I. Weng
Hu, Wenhuo
Deng, Zhenzhong
Liu, Zebing
Wang, Jian
Xu, Midie
The immune subtypes and landscape of sarcomas
title The immune subtypes and landscape of sarcomas
title_full The immune subtypes and landscape of sarcomas
title_fullStr The immune subtypes and landscape of sarcomas
title_full_unstemmed The immune subtypes and landscape of sarcomas
title_short The immune subtypes and landscape of sarcomas
title_sort immune subtypes and landscape of sarcomas
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9508767/
https://www.ncbi.nlm.nih.gov/pubmed/36153483
http://dx.doi.org/10.1186/s12865-022-00522-3
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