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A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma
Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and ri...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548643/ https://www.ncbi.nlm.nih.gov/pubmed/34721517 http://dx.doi.org/10.3389/fgene.2021.698284 |
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author | Lin, Tao Cheng, Hao Liu, Da Wen, Lei Kang, Junlin Xu, Longwen Shan, Changguo Chen, Zhijie Li, Hainan Lai, Mingyao Zhou, Zhaoming Hong, Weiping Hu, Qingjun Li, Shaoqun Zhou, Cheng Geng, Jiwu Jin, Xin |
author_facet | Lin, Tao Cheng, Hao Liu, Da Wen, Lei Kang, Junlin Xu, Longwen Shan, Changguo Chen, Zhijie Li, Hainan Lai, Mingyao Zhou, Zhaoming Hong, Weiping Hu, Qingjun Li, Shaoqun Zhou, Cheng Geng, Jiwu Jin, Xin |
author_sort | Lin, Tao |
collection | PubMed |
description | Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses’ survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG. |
format | Online Article Text |
id | pubmed-8548643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85486432021-10-28 A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma Lin, Tao Cheng, Hao Liu, Da Wen, Lei Kang, Junlin Xu, Longwen Shan, Changguo Chen, Zhijie Li, Hainan Lai, Mingyao Zhou, Zhaoming Hong, Weiping Hu, Qingjun Li, Shaoqun Zhou, Cheng Geng, Jiwu Jin, Xin Front Genet Genetics Since autophagy and the immune microenvironment are deeply involved in the tumor development and progression of Lower-grade gliomas (LGG), our study aimed to construct an autophagy-related risk model for prognosis prediction and investigate the relationship between the immune microenvironment and risk signature in LGG. Therefore, we identified six autophagy-related genes (BAG1, PTK6, EEF2, PEA15, ITGA6, and MAP1LC3C) to build in the training cohort (n = 305 patients) and verify the prognostic model in the validation cohort (n = 128) and the whole cohort (n = 433), based on the data from The Cancer Genome Atlas (TCGA). The six-gene risk signature could divide LGG patients into high- and low-risk groups with distinct overall survival in multiple cohorts (all p < 0.001). The prognostic effect was assessed by area under the time-dependent ROC (t-ROC) analysis in the training, validation, and whole cohorts, in which the AUC value at the survival time of 5 years was 0.837, 0.755, and 0.803, respectively. Cox regression analysis demonstrated that the risk model was an independent risk predictor of OS (HR > 1, p < 0.05). A nomogram including the traditional clinical parameters and risk signature was constructed, and t-ROC, C-index, and calibration curves confirmed its robust predictive capacity. KM analysis revealed a significant difference in the subgroup analyses’ survival. Functional enrichment analysis revealed that these autophagy-related signatures were mainly involved in the phagosome and immune-related pathways. Besides, we also found significant differences in immune cell infiltration and immunotherapy targets between risk groups. In conclusion, we built a powerful predictive signature and explored immune components (including immune cells and emerging immunotherapy targets) in LGG. Frontiers Media S.A. 2021-10-13 /pmc/articles/PMC8548643/ /pubmed/34721517 http://dx.doi.org/10.3389/fgene.2021.698284 Text en Copyright © 2021 Lin, Cheng, Liu, Wen, Kang, Xu, Shan, Chen, Li, Lai, Zhou, Hong, Hu, Li, Zhou, Geng and Jin. 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 Lin, Tao Cheng, Hao Liu, Da Wen, Lei Kang, Junlin Xu, Longwen Shan, Changguo Chen, Zhijie Li, Hainan Lai, Mingyao Zhou, Zhaoming Hong, Weiping Hu, Qingjun Li, Shaoqun Zhou, Cheng Geng, Jiwu Jin, Xin A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title | A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title_full | A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title_fullStr | A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title_full_unstemmed | A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title_short | A Novel Six Autophagy-Related Genes Signature Associated With Outcomes and Immune Microenvironment in Lower-Grade Glioma |
title_sort | novel six autophagy-related genes signature associated with outcomes and immune microenvironment in lower-grade glioma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548643/ https://www.ncbi.nlm.nih.gov/pubmed/34721517 http://dx.doi.org/10.3389/fgene.2021.698284 |
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