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Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma
BACKGROUND: Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403952/ https://www.ncbi.nlm.nih.gov/pubmed/37543576 http://dx.doi.org/10.1186/s12885-023-11222-5 |
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author | Li, Jinna Guo, Qing Xing, Rui |
author_facet | Li, Jinna Guo, Qing Xing, Rui |
author_sort | Li, Jinna |
collection | PubMed |
description | BACKGROUND: Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored. METHODS: Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model. RESULTS: Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy. CONCLUSION: Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11222-5. |
format | Online Article Text |
id | pubmed-10403952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104039522023-08-06 Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma Li, Jinna Guo, Qing Xing, Rui BMC Cancer Research BACKGROUND: Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored. METHODS: Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model. RESULTS: Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy. CONCLUSION: Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11222-5. BioMed Central 2023-08-05 /pmc/articles/PMC10403952/ /pubmed/37543576 http://dx.doi.org/10.1186/s12885-023-11222-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Li, Jinna Guo, Qing Xing, Rui Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title | Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title_full | Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title_fullStr | Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title_full_unstemmed | Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title_short | Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
title_sort | construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10403952/ https://www.ncbi.nlm.nih.gov/pubmed/37543576 http://dx.doi.org/10.1186/s12885-023-11222-5 |
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