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A gene expression-based study on immune cell subtypes and glioma prognosis

OBJECT: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumour...

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Autores principales: Zhong, Qiu-Yue, Fan, Er-Xi, Feng, Guang-Yong, Chen, Qi-Ying, Gou, Xiao-Xia, Yue, Guo-Jun, Zhang, Gui-hai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858694/
https://www.ncbi.nlm.nih.gov/pubmed/31729963
http://dx.doi.org/10.1186/s12885-019-6324-7
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author Zhong, Qiu-Yue
Fan, Er-Xi
Feng, Guang-Yong
Chen, Qi-Ying
Gou, Xiao-Xia
Yue, Guo-Jun
Zhang, Gui-hai
author_facet Zhong, Qiu-Yue
Fan, Er-Xi
Feng, Guang-Yong
Chen, Qi-Ying
Gou, Xiao-Xia
Yue, Guo-Jun
Zhang, Gui-hai
author_sort Zhong, Qiu-Yue
collection PubMed
description OBJECT: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma. METHODS: We extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample. RESULTS: In total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8(+) T cells, T follicular helper cells, gamma delta T cells and M0 macrophages were negatively related to prognosis in the patients with glioma. Specifically, the proportions of several immune cells were significantly related to patient age and sex. Furthermore, the level of M0 macrophages was significant in regard to interactions with other immune cells, including monocytes and gamma delta T cells, in glioma tissues through sample data analysis. CONCLUSION: We performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma.
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spelling pubmed-68586942019-11-29 A gene expression-based study on immune cell subtypes and glioma prognosis Zhong, Qiu-Yue Fan, Er-Xi Feng, Guang-Yong Chen, Qi-Ying Gou, Xiao-Xia Yue, Guo-Jun Zhang, Gui-hai BMC Cancer Database OBJECT: Glioma is a common malignant tumours in the central nervous system (CNS), that exhibits high morbidity, a low cure rate, and a high recurrence rate. Currently, immune cells are increasingly known to play roles in the suppression of tumourigenesis, progression and tumour growth in many tumours. Therefore, given this increasing evidence, we explored the levels of some immune cell genes for predicting the prognosis of patients with glioma. METHODS: We extracted glioma data from The Cancer Genome Atlas (TCGA). Using the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm, the relative proportions of 22 types of infiltrating immune cells were determined. In addition, the relationships between the scales of some immune cells and sex/age were also calculated by a series of analyses. A P-value was derived for the deconvolution of each sample, providing credibility for the data analysis (P < 0.05). All analyses were conducted using R version 3.5.2. Five-year overall survival (OS) also showed the effectiveness and prognostic value of each proportion of immune cells in glioma; a bar plot, correlation-based heatmap (corheatmap), and heatmap were used to represent the proportions of immune cells in each glioma sample. RESULTS: In total, 703 transcriptomes from a clinical dataset of glioma patients were drawn from the TCGA database. The relative proportions of 22 types of infiltrating immune cells are presented in a bar plot and heatmap. In addition, we identified the levels of immune cells related to prognosis in patients with glioma. Activated dendritic cells (DCs), eosinophils, activated mast cells, monocytes and activated natural killer (NK) cells were positively related to prognosis in the patients with glioma; however, resting NK cells, CD8(+) T cells, T follicular helper cells, gamma delta T cells and M0 macrophages were negatively related to prognosis in the patients with glioma. Specifically, the proportions of several immune cells were significantly related to patient age and sex. Furthermore, the level of M0 macrophages was significant in regard to interactions with other immune cells, including monocytes and gamma delta T cells, in glioma tissues through sample data analysis. CONCLUSION: We performed a novel gene expression-based study of the levels of immune cell subtypes and prognosis in glioma, which has potential clinical prognostic value for patients with glioma. BioMed Central 2019-11-15 /pmc/articles/PMC6858694/ /pubmed/31729963 http://dx.doi.org/10.1186/s12885-019-6324-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Database
Zhong, Qiu-Yue
Fan, Er-Xi
Feng, Guang-Yong
Chen, Qi-Ying
Gou, Xiao-Xia
Yue, Guo-Jun
Zhang, Gui-hai
A gene expression-based study on immune cell subtypes and glioma prognosis
title A gene expression-based study on immune cell subtypes and glioma prognosis
title_full A gene expression-based study on immune cell subtypes and glioma prognosis
title_fullStr A gene expression-based study on immune cell subtypes and glioma prognosis
title_full_unstemmed A gene expression-based study on immune cell subtypes and glioma prognosis
title_short A gene expression-based study on immune cell subtypes and glioma prognosis
title_sort gene expression-based study on immune cell subtypes and glioma prognosis
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858694/
https://www.ncbi.nlm.nih.gov/pubmed/31729963
http://dx.doi.org/10.1186/s12885-019-6324-7
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