A Gene Expression-based Study on Immune Cell Subtypes and Glioma Prognosis

Overview

Journal BMC Cancer

Publisher Biomed Central

Specialty Oncology

Date 2019 Nov 16

PMID 31729963

Citations 35

Authors

Qiu-Yue Zhong

Er-Xi Fan

Guang-Yong Feng

Qi-Ying Chen

Xiao-Xia Gou

Guo-Jun Yue

Gui-Hai Zhang

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Identification of m6A methyltransferase-related WTAP and ZC3H13 predicts immune infiltrates in glioblastoma.

Gao L, Gao J, He J, Fan W, Che X, Wang X Sci Rep. 2025; 15(1):4412.

PMID: 39910141 PMC: 11799344. DOI: 10.1038/s41598-025-88671-4.

Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database.

Yuan H, Cheng J, Xia J, Yang Z, Xu L Discov Oncol. 2025; 16(1):35.

PMID: 39800804 PMC: 11725551. DOI: 10.1007/s12672-024-01653-2.

The Expression Profiles and Clinical Significance of Mixed Lineage Kinases in Glioma.

Huang J, Liu Y, Wang G, Chen Y, Shen Y, Zhang J Mediators Inflamm. 2024; 2024:5521016.

PMID: 39610810 PMC: 11604285. DOI: 10.1155/2024/5521016.

Bioinformatics analysis of in glioblastoma multiforme to evaluate immune features and predict prognosis.

Yang T, Li C, Xu D, Quan R, Wang L, Ren Y Transl Cancer Res. 2024; 13(8):4242-4256.

PMID: 39262462 PMC: 11384316. DOI: 10.21037/tcr-23-2000.

The interplay between metal ions and immune cells in glioma: pathways to immune escape.

Li J, Mao Y, Chen S, Ye R, Fei Y, Li Y Discov Oncol. 2024; 15(1):348.

PMID: 39134820 PMC: 11319581. DOI: 10.1007/s12672-024-01229-0.

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