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Observational Study
. 2021 Jun 8;5(6):395-409.
doi: 10.4049/immunohorizons.2100008.

Aging- and Tumor-Mediated Increase in CD8+CD28- T Cells Might Impose a Strong Barrier to Success of Immunotherapy in Glioblastoma

Wei X Huff  1 , Marpe Bam  2 , Jack M Shireman  2 , Jae Hyun Kwon  1 , Leo Song  1 , Sharlé Newman  1 , Aaron A Cohen-Gadol  1 , Scott Shapiro  1 , Tamara Jones  3 , Kelsey Fulton  3 , Sheng Liu  3 , Hiromi Tanaka  3 , Yunlong Liu  3 , Jun Wan  3 , Mahua Dey  4
Affiliations
Observational Study

Aging- and Tumor-Mediated Increase in CD8+CD28- T Cells Might Impose a Strong Barrier to Success of Immunotherapy in Glioblastoma

Wei X Huff et al. Immunohorizons. .

Abstract

Clinical use of various forms of immunotherapeutic drugs in glioblastoma (GBM), has highlighted severe T cell dysfunction such as exhaustion in GBM patients. However, reversing T cell exhaustion using immune checkpoint inhibitors in GBM clinical trials has not shown significant overall survival benefit. Phenotypically, CD8+ T cells with downregulated CD28 coreceptors, low CD27 expression, increased CD57 expression, and telomere shortening are classified as senescent T cells. These senescent T cells are normally seen as part of aging and also in many forms of solid cancers. Absence of CD28 on T cells leads to several functional irregularities including reduced TCR diversity, incomplete activation of T cells, and defects in Ag-induced proliferation. In the context of GBM, presence and/or function of these CD8+CD28- T cells is unknown. In this clinical correlative study, we investigated the effect of aging as well as tumor microenvironment on CD8+ T cell phenotype as an indicator of its function in GBM patients. We systematically analyzed and describe a large population of CD8+CD28- T cells in both the blood and tumor-infiltrating lymphocytes of GBM patients. We found that phenotypically these CD8+CD28- T cells represent a distinct population compared with exhausted T cells. Comparative transcriptomic and pathway analysis of CD8+CD28- T cell populations in GBM patients revealed that tumor microenvironment might be influencing several immune related pathways and thus further exaggerating the age associated immune dysfunction in this patient population.

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Conflict of interest statement

Conflict of Interest Statement

Authors have declared that no conflict of interest exists.

Figures

Figure 1:
Figure 1:. Increased CD8+CD28− T-cell population in the blood and TME of GBM patients.
A) Schematic of experimental design and data collection/analysis. B) Percentage of CD8+CD28− T-cell population in the PBL of YA (n = 8) and HAMA (n = 5) and matched blood and tumor of GBM patients (n = 26). C) Percentage of single-positive PD-1 and TIM3 and dual-positive expression on CD8+CD28+ and CD8+CD28− T-cells in the PBL and TIL of GBM patients. (n = 5) D) Percentage of CD57 expression on CD8+CD28+ and CD8+CD28− T-cells in PBL and TIL of GBM patients. (n = 11) E) Percentage of CD107a, CCR7, CD45RO, IL4, and IL10 expression of CD8+CD28+ and CD8+CD28− T-cells in TIL of GBM patients. (n = 11) F) Percentage of CD45RA, IFNy, CD107a, TGF-b, CD27, and IL-6 expression of CD8+CD28− T-cells in the PBL of YA (n = 8) and HAMA (n = 5) and matched PBL and TIL of GBM patients (n = 11). G) Percentage of CD27, CD107a, CCR7, CD57, IL-4, IL-6, IL-10, IFNy, and TGF-b expression of CD8+CD28+ T-cells in the blood of YA (n = 8) and HAMA (n = 5) and matched PBL and TIL of GBM patients (n = 11). The percentage of CD8+ T cells represents these cell types from total CD3+ T cells in the PBMCs or TILs. The CD8+ subpopulations represent these cells within the CD8+ T cells. Data are expressed as mean±SD and were analyzed as (B, D, F, G) one-way ANOVA with Tukey’s multiple comparison post-hoc, (C) two-way ANOVA with Tukey’s multiple comparison post-hoc, (E) Two-tailed paired Student T test. * p<0.05, ** p<0.01, *** p<0.0002, **** p<0.0001
Figure 2:
Figure 2:. GBM TME influences infiltrating CD8+ T-cells by regulating pathways related to T-cell metabolism.
A) Heatmap and PCA analysis of RNAseq gene expression of CD8+CD28+ and CD8+CD28− T-cell in the PBL of YA (n = 3) and HAMA (n = 4) and PBL (n = 4) and TIL (n = 3) of GBM patients normalized by Z-score. B-E) Pathway comparison analysis of immune cell and cellular functions between B) healthy patients vs GBM patients, C) GBM blood vs GBM tumor, D) GBM tumor CD8+CD28+ vs CD8+CD28− T-cells and E) HAMA vs YA quantified by q-score and fold enrichment.
Figure 3:
Figure 3:. GBM amplifies systemic cytotoxic T-cell immune dysfunction.
Volcano plot analysis (false discovery rate cut-off of less than 0.01) and pathway comparison analysis of RNAseq in A) CD8+CD28+ T-cell in YA vs HAMA PBL, GBM PBL vs HAMA PBL, and GBM PBL vs TIL, B) CD8+CD28− T-cell in YA vs HAMA PBL, GBM PBL vs HAMA PBL, and GBM PBL vs TIL, and C) withinGBM patients, CD8+CD28+ vs CD8+CD28− T-cells in the PBL and TIL.
Figure 4:
Figure 4:. CD8+ T cell immune dysfunction in GBM is linked to telomere shortening, in addition to effects of aging.
A) Relative telomere length of CD8+CD28+ and CD8+CD28− T-cells in the PBL of YA (n = 3), HAMA (n = 3), GBM (n = 4) and TIL (n = 3) of GBM patients. B, D, E) RNAseq heatmap analysis of gene expression of CD8+CD28+ and CD8+CD28− T-cell in the PBL of YA (n = 3), HAMA (n = 3), GBM (n = 4) and TIL (n = 3) of GBM patients. Functional analysis was performed on differentially expressed genes with false discovery rate cut-off less than 0.01. C) RNAseq gene expression of cell cycle genes in the PBL of YA (n = 3), HAMA (n = 3), GBM (n = 4) and TIL (n = 3) of GBM patients. Comparisons include YA Blood CD28+ vs YA Blood CD28−, GBM Blood CD28+ vs GBM Blood CD28−, HAMA Blood CD28− vs GBM Tumor CD28−, HAMA Blood CD28+ vs HAMA Blood CD28−, GBM Tumor CD28+ vs GBM Tumor CD28−, and HAMA Blood CD28− vs GBM Blood CD28−. Data are expressed as mean±SD and p values were obtained by performing A) Two-tailed paired Student T test and C) two-way ANOVA with Tukey’s multiple comparison post-hoc. * p<0.05, ** p<0.01, *** p<0.0002, **** p<0.0001
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