Clinical characterization and immunosuppressive regulation of CD161 (KLRB1) in glioma through 916 samples

Abstract

Background: Glioblastoma is a paradigm of cancer-associated immunosuppression, limiting the effects of immunotherapeutic strategies. Thus, identifying the molecular mechanisms underlying immune surveillance evasion is critical. Recently, the preferential expression of inhibitory natural killer (NK) cell receptor CD161 on glioma-infiltrating cytotoxic T cells was identified. Focusing on the molecularly annotated, large-scale clinical samples from different ethnic origins, the data presented here provide evidence of this immune modulator's essential roles in brain tumor biology.

Methods: Retrospective RNA-seq data analysis was conducted in a cohort of 313 patients with glioma in the Chinese Glioma Genome Atlas (CGGA) database and 603 patients in The Cancer Genome Atlas (TCGA) database. In addition, single-cell sequencing data from seven surgical specimens of glioblastoma patients and a model in which patient-derived glioma stem cells were cocultured with peripheral lymphocytes, were used to analyze the molecular evolution process during gliomagenesis.

Results: CD161 was enriched in high-grade gliomas and isocitrate dehydrogenase (IDH)-wildtype glioma. CD161 acted as a potential biomarker for the mesenchymal subtype of glioma and an independent prognostic factor for the overall survival (OS) of patients with glioma. In addition, CD161 played an essential role in inhibiting the cytotoxicity of T cells in glioma patients. During the process of gliomagenesis, the expression of CD161 on different lymphocytes dynamically evolved.

Conclusion: The expression of CD161 was closely related to the pathology and molecular pathology of glioma. Meanwhile, CD161 promoted the progression and evolution of gliomas through its unique effect on T cell dysfunction. Thus, CD161 is a promising novel target for immunotherapeutic strategies in glioma treatment.

Keywords: CD161; T cell evolution; glioma; immunotherapy; neuro-immunity; prognosis.

FIGURE 1

Association between CD161 and clinicopathological characteristics of gliomas. A, The landscape of CD161‐related clinicopathological features of gliomas in the Chinese Glioma Genome Atlas (CGGA) database. B, The landscape of CD161‐related clinicopathological features of gliomas in the The Cancer Genome Atlas (TCGA) database. C and G, CD161 was significantly increased in higher‐grade gliomas in the CGGA and TCGA databases. The significance of the difference was tested by one‐way ANOVA. D and H, CD161 was significantly increased in gliomas without isocitrate dehydrogenase (IDH) mutation in the CGGA and TCGA databases. The significance of the difference was tested with an unpaired t test. E and I, CD161 was significantly increased in gliomas without 1p/19q codeletion in the CGGA and TCGA databases. The significance of the difference was tested with an unpaired t test. F and J, CD161 was increased in the O⁶‐methylguanine‐DNA methyltransferase (MGMT) promoter–unmethylated gliomas. This difference was statistically significant in the TCGA database, not in the CGGA database. The significance of the difference was tested using an unpaired t test

FIGURE 2

CD161 is specifically enriched in the mesenchymal subtype of gliomas. A and C, CD161 was enriched in the mesenchymal subtype of gliomas in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The significance of the difference was tested by one‐way ANOVA. B and D, The receiver‐operating characteristic (ROC) curve showed the high‐expression specificity of CD161 in the mesenchymal subtype of gliomas in the CGGA and TCGA databases. AUC, area under the curve

FIGURE 3

CD161 is closely associated with immune process regulation in gliomas. A‐C, Biological processes (BP), cellular components (CC), and molecular functions are mostly related to CD161 in the Chinese Glioma Genome Atlas (CGGA) database. D, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of CD161 in the CGGA database. E‐G, Biological processes (BP), cellular components (CC), and molecular functions are mostly related to CD161 in the CGGA database. H, KEGG pathway analysis of CD161 in the CGGA database

FIGURE 4

Correlation analysis between CD161 expression and immune function enrichment scores. A and B, The heatmap showed the expression of CD161 and the enrichment scores of immune functions of each patient in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The samples were arranged in ascending order of the expression of CD161. The column graph and line graph on the right showed the R‐value and P‐value of the correlation analysis

FIGURE 5

The correlation between CD161 expression and T cell immunity and inflammatory activities in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. A, Pearson correlation between CD161 and inhibitory immune checkpoints. The width of the band represented the R‐value. The color of the band represented the P‐value. The correlation was tested by Pearson correlation analysis. B and C, Correlation matrix of CD161 and inflammatory‐related metagenes. The bottom left showed the correlation coefficient. The correlation coefficients were demonstrated as the proportion of the pie charts. The red parts represented a positive correlation, while the green parts represented a negative correlation. The correlation was tested by Pearson correlation analysis

FIGURE 6

The expression pattern of CD161 in lymphocytes. A, Subtypes of lymphocytes from the coculture model. B, The expression of CD161 and other T cell markers in different subtypes of lymphocytes from the coculture model. C, Subtypes of lymphocytes from the surgical samples of glioblastoma patients. D, The expression of CD161 and other T cell markers in different subtypes of lymphocytes from the surgical specimens of glioblastoma multiforme (GBM) patients. E, Subtypes of cells from isocitrate dehydrogenase (IDH)‐wildtype glioblastomas in a public database (GSE131928). F, The expression of CD161 in different cells from IDH‐wildtype glioblastomas in a public database (GSE131928)

FIGURE 7

Similarity analysis of T cell subgroups between the coculture model and GBM surgical samples. The width of the band represented the counts of genes simultaneously expressed in different subtypes of lymphocytes

FIGURE 8

Biological processes and pathway activation of lymphocyte subtypes from the coculture model and glioblastoma multiforme (GBM) surgical samples. A and B, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of CD4+ lymphocyte subtypes with high or low expression of CD161 from the coculture model. C and D, GO and KEGG analysis of CD8+ lymphocyte subtypes with high or low expression of CD161 from the coculture model. E and F, GO and KEGG analysis of CD4+ and CD8+ lymphocyte subtypes from the GBM surgical specimens

FIGURE 9

Kaplan‐Meier analysis of CD161 expression in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. A and B, The cutoff of the group is the median expression of CD161. The significance of the prognostic value was tested by a log‐rank test

FIGURE 10

Negative correlation between CD161 expression level and cytotoxicity of T cells. A, qPCR analysis of KLRB1 (CD161) expression in T cells after transfecting siRNA and plasmid. B, SDS‐PAGE analysis of KLRB1(CD161) expression in T cells after transfecting siRNA and plasmid. C and D, Lactate dehydrogenase (LDH) assay in U87 and LN229 cell lines cocultured with transfected T cells. E:T, effective cells to tumor cells ratio. E and F, Tumor necrosis factor α (TNF‐α) and interferon γ (IFN‐γ) in the supernatant of the coculture model were detected with ELISA. G and H, Apoptosis analysis using Annexin V/PI. Q4: viable cells (Annexin V–/PI–), Q3: early apoptosis (Annexin V+/PI–), Q2: late apoptosis (Annexin V+/PI+), and Q1: necrosis (Annexin V–/PI+). Data given as means ± standard deviations (SDs) (*means under t test, P < .05, **means under t test, P < .01, ***means under t test, P < .001)