ORIGINAL RESEARCH article

Front. Immunol., 30 November 2020

Sec. Cancer Immunity and Immunotherapy

Volume 11 - 2020 | https://doi.org/10.3389/fimmu.2020.580934

Redox Regulator GLRX Is Associated With Tumor Immunity in Glioma

  • 1. Department of Molecular Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China

  • 2. Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

  • 3. China National Clinical Research Center for Neurological Diseases, Beijing, China

  • 4. Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA), Beijing, China

Abstract

Glutaredoxin is central to cellular redox chemistry and regulates redox homeostasis and malignant progression of many cancers. In glioma, the role of its coding gene (GLRX) remains unclear. We aimed to elucidate the role of glutaredoxin at the transcriptome level and its clinical prognostic value in glioma. In total, we evaluated 1,717 glioma samples with transcriptome data and corresponding clinical data as well as single-cell sequencing data from 6 glioma patients from publicly available databases. Gene set variation analysis and gene ontology analysis were performed to reveal the biological function of GLRX. The immune cell enrichment score was calculated by GSVA analysis. Single-cell sequencing data was visualized by t-distributed stochastic neighbor embedding analysis. The prognostic value of GLRX in glioma was verified by the Kaplan-Meier curve and multivariate COX analysis. GLRX was found to be highly enriched in gliomas of higher grades with wild-type IDH, without 1p/19q co-deletion, and with a methylated MGMT promoter. Moreover, GLRX could be a potential marker for the mesenchymal molecular subtype of gliomas. The expression of GLRX was closely related to the tumor immune process, immune checkpoints, and inflammatory factors with GLRX being specifically expressed in M0 macrophages. GLRX is also shown to be an independent prognostic factor in glioma. Altogether, our study outcomes show that GLRX is highly enriched in malignant gliomas and is closely related to the tumor immune microenvironment. Therefore, GLRX-targeted cell redox regulatory therapy may enhance the efficacy of glioma immunotherapy.

Introduction

Glioma is the most common malignant tumor affecting the central nervous system, and it is mainly characterized by a high recurrence rate and short survival time (1). To date, the most effective treatment for glioma is surgical resection to maximum safety extent (2), which can be followed by additional individualized treatments such as radiotherapy and chemotherapy. Even with aggressive treatment, the prognosis for glioma patients remains very poor. Therefore, finding novel therapeutic targets and molecular targeted drugs may pave the way for an improved prognosis for these patients.

Glutaredoxin (Grx), also known as thiol transferase, is ubiquitously expressed in bacteria, viruses, and mammals. It has a relative molecular weight of approximately 12 kDa and comprises 106–107 amino acids (3). Grx is an important component of the thiol-disulfide bond oxidoreductase family and catalyzes the redox reaction between glutathione (GSH) and protein disulfide bonds that are necessary for optimal protein activity (4). Several studies have reported that Grx performs a variety of biological functions in cancer related to relieving oxidative stress, transcription regulation, and control of DNA synthesis by modulating the activity of ribonucleotide reductase (3, 5, 6). However, there are few reports on the role of Grx in glioma.

The GSH system is an essential regulator of redox balance in the brain (7), and Grx acts as a central “antioxidant” in neurons to protect them from oxidative stress injury. Previous studies have reported that Grx is also involved in glioma and metastasis development as well as in drug resistance (6, 8). Therefore, understanding the role of Grx in the context of glioma is pivotal for the development of novel therapeutic approaches targeting malignant gliomas.

We investigated the expression and function of the Grx coding gene (GLRX) at the transcriptome level using publicly available data sets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), which included RNA sequencing (RNA-seq) data and corresponding clinical details about the cancer patients. We found that GLRX is associated with high tumor grade and malignant phenotypes. Moreover, gene ontology analysis and gene set variation analysis revealed, for the first time, that GLRX can function as a mediator of the immune response. Further CIBERSORT analysis revealed that a higher expression level of GLRX is correlated with enrichment of macrophages in glioma tissue. Single-cell analysis, immunohistochemical (IHC) staining, and immunofluorescent staining (IF) validated that GLRX may be specifically expressed in M0 macrophages. Last, we found that GLRX is an independent prognostic factor in glioma. Altogether, these findings suggest that GLRX is highly enriched in malignant gliomas and is closely related to the tumor immune microenvironment. Therefore, GLRX-targeted cell redox regulatory therapy may enhance response to immunotherapy in patients with glioma.

Materials and Methods

Data Collection

This study was approved by the Capital Medical University Institutional Review Board. We collected transcriptome sequencing data generated by the Illumina HiSeq platform that was publicly available from the CGGA and CGGA (2019) databases (https://www.cgga.org.cn) for 325 and 693 samples, respectively. We evaluated the status of isocitrate dehydrogenase (IDH) mutation, 1p/19q, and MGMT promoter methylation as described in previous studies (911). Overall patient survival was estimated from the date of diagnosis to the reported date of death or last follow-up. RNA-seq data were obtained from TCGA (https://tcgadata.nci.nih.gov), and single-cell sequencing data were retrieved from the GSE89567 data set of the Gene Expression Omnibus database. All clinical and molecular information on the samples evaluated in the present study is presented in Table 1. We used the online software GEPIA (http://gepia.cancer-pku.cn) (12) to evaluate expression differences between glioblastoma multiform (GBM) and normal brain tissues.

Table 1

Characteristics (CGGA)No. of Patients (n=325)
Age
<45191
≥45134
Gender
Male203
Female122
WHO Grade
Grade II103
Grade III79
Grade IV139
NA4
TCGA Subtypes
Proneural102
Neural81
Classical74
Mesenchymal68
Radiotherapy+TMZ Chemotherapy
Yes154
No24
Radiotherapy
Yes258
No51
NA16
TMZ Chemotherapy
Yes178
No124
NA23
IDH1/2 mutation
Mutation175
Wild type149
NA1
1p/19q codeletion
Co-deletion67
Non-co-deletion250
NA8
MGMT methylation
Methylation130
Unmethylation112
NA64
Characteristics [CGGA(2019)]No. of Patients (n=693)
Age
<45382
≥45310
NA1
Gender
Male398
Female295
WHO Grade
Grade II188
Grade III255
Grade IV249
NA1
TCGA Subtypes
Proneural296
Neural167
Classical83
Mesenchymal147
Radiotherapy+TMZ Chemotherapy
Yes413
No67
Radiotherapy
Yes509
No113
NA71
TMZ Chemotherapy
Yes457
No151
NA85
IDH1/2 mutation
Mutation356
Wild type286
NA51
1p/19q co-deletion
Co-deletion145
Non-co-deletion478
NA70
MGMT methylation
Methylation127
Unmethylation73
NA492
Characteristics (TCGA)No. of Patients (n=699)
Age
<45296
≥45340
NA63
Gender
Male368
Female268
NA63
WHO Grade
Grade II223
Grade III245
Grade IV168
NA63
TCGA Subtypes
Proneural250
Neural115
Classical92
Mesenchymal105
NA137
IDH1/2 mutation
Mutation443
Wild type246
NA10
1p/19q co-deletion
Co-deletion172
Non-co-deletion520
NA7
MGMT methylation
Methylation492
Unmethylation168
NA39

Sample information.

The number of glioma patients engaged in our study is listed. All patients were stratified with age, clinicopathological characteristics, and treatment options, respectively.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Analyses

The biological functions and signaling pathways related to GLRX were explored by GO and KEGG analyses using the DAVID bioinformatics resource (version 6.7) (13). After Spearman correlation analysis, GO results on the most correlated genes were visualized by heat map.

Gene Set Variation Analysis (GSVA)

GSVA was performed with the GSVA package (from R Project 3.5.1) of R software with default parameters. The list of GO terms was obtained from the Gene Set Enrichment Analysis database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Relationships between genes and biological functions were determined using Pearson correlation analysis.

Immune Function Analysis

The relationship between GLRX expression and immune function was evaluated by Pearson correlation analysis. Immune function scores (14) were calculated by GSVA analysis, and the immune function gene set was downloaded from AmiGO 2 (http://amigo.geneontology.org/amigo/landing). The classification of immune functions was done according to the guidelines of AmiGO 2.

CIBERSORT

RNA-seq data were evaluated using the CIBERSORT software (https://cibersort.stanford.edu). The signature gene profile of 22 immune cell types was used in CIBERSORT to estimate the proportion of tumor-infiltrating immune cell types (15).

T-Distributed Stochastic Neighbor Embedding (T-SNE) Analysis

T-SNE analysis was performed with the Rtsne package from R Project (version 3.5.1); perplexity was set to 20. Identification of cell types was based on the specific cell markers obtained from the CellMarker database (http://biocc.hrbmu.edu.cn/CellMarker/).

Prognostic Analysis

Patient survival distribution and significance was evaluated by Kaplan-Meier survival curve and log-rank test. Kaplan-Meier analysis was performed using R software (version 3.5.1, http://www.r-project.org). The prognostic value of GLRX was estimated by univariate and multivariate Cox proportional hazard model analysis using SPSS statistical software (version 25.0; IBM, Armonk, NY, USA). Patients with missing information were excluded from the analysis.

IHC Staining

Paraffin-embedded samples were obtained from the CGGA sample bank. First, 5-µm sections were cut for IHC staining. Samples were deparaffinized in an oven at 65°C for 1 h. Then the samples were rehydrated in decreasing concentrations of alcohol. IHC analysis with GLRX1 (Abcam, ab45953,1:1000) and CD11b antibodies (Proteintech, 66519-1-lg, 1:1000) was conducted according to standard procedures. Photos were taken with an optical microscope.

Cell Culture and Reagents

THP-1 cells (purchased from National Infrastructure of Cell Line Resource, http://www.cellresource.cn/) were maintained in RPMI1640 media supplemented with L-glutamine, 1% penicillin and streptomycin, β-mercaptoethanol (Gibco, 2169148, 0.055 mM) and 10% fetal bovine serum (FBS, Gibco) at 37°C under a humidified, 5% CO2 atmosphere (16). THP-1 cells were differentiated to M0 macrophages by treatment with 25 nM phorbol 12-myristate 13-acetate (MCE, HY-18739) for 48 h, washed and incubated with normal RPMI1640 media for 24 h, and then incubated with recombinant human GM-CSF (50 ng/ml, Peprotech, 300-03) for 96 h. For M2 polarization, 50% of complete RPMI1640 medium was added, and it was incubated for 48 h. Then the M2 macrophage was obtained by removing the culture medium and culturing cells for an additional 48 h in M2 medium with recombinant human M-CSF (100 ng/ml, Peprotech, 300-25) (17).

IF Staining

Macrophages were washed with PBS three times. Four percent fixative solution (Solarbio, P1110) was added to the Petri dish for 10 min. Then, the solution was removed and cells washed three times. Next, 0.5% Triton X-100 (Solarbio, T8200) was added to the dish for 10 min. The solution was removed and cells washed three times. Five percent BSA (Solarbio, A8010) was added to the dish, and it was incubated for 1 h at room temperature. Then, primary antibodies were added to the M0 (GLRX1: 1:500, Abcam, ab45953; CD11b: 1:100, Proteintech, 66519-1-lg) and M2 macrophages (GLRX1: 1:500, Abcam, ab45953; CD163: 1:100, Abcam, ab156769) (18), respectively, and they were incubated overnight at 4°C. The solution was removed and cells washed three times. Secondary antibodies (DyLight 488 goat antirabbit polyclonal antibody, Abcam, ab96899, 1:200; DyLight 594 goat antimouse polyclonal antibody, Abcam, ab96881, 1:200) were used for 1 h at room temperature. The solution was removed and cells washed three times. Prolong™ Diamond Antifade Mountant with DAPI (Invitrogen, P36962) was added to the dish, and photos were taken with confocal microscopy.

Other Immune Biological Analysis

Pearson’s correlation analysis was used to evaluate the relationship between GLRX and immune checkpoints. Inflammation-related metagenes were described as before (19).

Statistical Analysis

A multiple group comparison was performed using Tukey’s test. Other statistical computations and figure drawing were performed with several R packages, including ggplot2, pheatmap, pROC, and corrgram. All statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant in all analyses.

Results

Association of GLRX Expression With Clinical and Molecular Pathological Characteristics in Glioma

To investigate the role of GLRX in gliomas, we compared the expression levels of GLRX between normal brain tissue and GBM (grade IV, according to the World Health Organization [WHO]). The analysis revealed that GLRX expression was significantly enriched in GBM samples (p < 0.05, Figure 1A). Due to the histopathological heterogeneity of gliomas, RNA-seq data of glioma samples from three independent databases were analyzed according to WHO guidelines, and the analysis included IDH mutation status, 1p/19q co-deletion status, and MGMT promoter status. Among samples from the CGGA database, GLRX expression was higher in GBM (grade IV) compared with glioma (grades II and III) (Figure 1B). This result was further validated in the RNA-seq data from TCGA and CGGA (2019) databases (Figure 1F and Supplementary Figure S1A). In addition, IHC staining was conducted to explore the expression of GLRX in glioma tissues. Consistent with the RNA-seq data, we found that GLRX was enriched in GBM tissues (Figures 1J, K). The IDH mutation status, 1p/19q co-deletion status, and MGMT promoter status play important roles in the prognosis and chemotherapy outcomes of glioma patients and vary significantly among glioma patients (20). Therefore, we explored the correlation between GLRX expression and these three molecular pathologic statuses. We found that GLRX expression was highly enriched in IDH wild-type glioma patients compared with those harboring IDH mutations (Figures 1C, G and Supplementary Figure S1B). Moreover, patients with 1p/19q non-co-deletion had a higher expression of GLRX in all three databases (Figures 1D, H and Supplementary Figure S1C). Regarding the MGMT promoter status in the CGGA database, we found that gliomas with a methylated MGMT promoter had lower GLRX expression compared to those in the unmethylated group (Figure 1E). A similar trend was observed in the two other databases (Figure 1I and Supplementary Figure S1D). These findings indicate that GLRX expression is enriched in GBM and is tightly correlated with the malignant phenotype of glioma.

Figure 1

GLRX Is a Potential Marker for Mesenchymal Molecular Subtype Glioma

Next, we investigated the molecular expression pattern of GLRX in different molecular subtypes defined by TCGA network (21). GLRX was significantly upregulated in the mesenchymal subtype of glioma compared with the other three subtypes in the CGGA (Figure 2A), TCGA (Figure 2C), and CGGA (2019) databases (Supplementary Figure S2A). The IHC staining of GLRX in GBM tissues also verified this finding (Figures 3E–G). To further validate this finding, we evaluated the receiver operating characteristic (ROC) curve for GLRX expression and mesenchymal subtype for gliomas of all grades. Surprisingly, the area under the curve (AUC) of GLRX expression was up to 90.9%, 90.2%, and 78.0% for the CGGA, TCGA, and CGGA (2019) data sets, respectively (Figures 2B, D and Supplementary Figure S2B). These results suggest that GLRX is highly expressed in mesenchymal subtype glioma and may play an oncogenic role in glioma progression. BMI1 and CD44 were reported to differentiate the mesenchymal molecular subtype from other gliomas (22, 23). Thus, we took these two well-studied biomarker genes as positive controls to performed ROC curve analysis (Supplementary Figure S2C–H). Through comparing the AUC of these three genes, we inferred that GLRX may serve as a biomarker for mesenchymal subtype gliomas.

Figure 2

Figure 3

GLRX Is Strongly Associated With Immune Functions in Glioma

We performed GO analysis to identify the GLRX-related biological functions in gliomas. At first, we screened genes that were strongly correlated with GLRX (Pearson R > 0.55 and p < 0.0001) in all three databases. The analysis revealed a total of 479 genes in CGGA, 877 genes in TCGA, and 537 genes in CGGA (2019) that were significantly correlated with GLRX expression. The genes positively correlated with GLRX expression were mostly involved in immune response, defense response, and inflammatory response in all databases (Figures 3A, C and Supplementary Figure S3A). Additionally, we performed KEGG pathway analysis to further explore the signaling pathways associated with the abovementioned genes. As expected, the KEGG analysis identified these genes to be associated with immune response pathways, including FcγR-mediated phagocytosis, the toll-like receptor signaling pathway, and complementary and coagulation cascades in the three databases (Figures 3B, D and Supplementary Figure S3B). The heat map representation of the genes (shown in Table 2) within each biological process exhibits a clear positive correlation with GLRX expression and the landscape of corresponding clinical patient features (Figures 3E, F and Supplementary Figure S3C). These findings suggest that GLRX takes part in the immune response process and may be a marker for predicting immune-related biological processes in gliomas.

Table 2

GeneGO_Terms
NFKB2immune response
B2Mimmune response
IL4Rimmune response
LILRA6immune response
FCGR3Aimmune response
LAIR1immune response
DBNLimmune response
NCF4immune response
STXBP2immune response
TNFRSF14immune response
CTSSimmune response
PDCD1LG2immune response
BCAP31immune response
LILRB1immune response
LAT2immune response
CTSCimmune response
GBP2immune response
GALNT2immune response
SBNO2immune response
IFITM3immune response
GPSM3immune response
GPR65immune response
FCGRTimmune response
FTH1immune response
SQSTM1immune response
FCER1Gimmune response
MR1immune response
ARHGDIBimmune response
PSMB8immune response
TNFSF8immune response
PSMB9immune response
IKBKEimmune response
FCGR2Bimmune response
CD300Aimmune response
CD274immune response
RNF19Bimmune response
TNIP1defense response
C5AR1defense response
CLIC1defense response
SP140defense response
MNDAdefense response
CLEC5Adefense response
TYROBPdefense response
TCIRG1defense response
HCKdefense response
MAP2K3defense response
CD300Cdefense response
APOL2defense response
CYBBdefense response
STAB1defense response
ALOX5defense response
CD14defense response
CCL2inflammatory response
NMIinflammatory response
ADORA3inflammatory response
S100A8inflammatory response
AIF1inflammatory response
CCR1inflammatory response
S100A9inflammatory response
ITGB2inflammatory response
TNFRSF1Binflammatory response
IL10RBinflammatory response
HMOX1inflammatory response
TICAM2inflammatory response
SERPINA3inflammatory response
C2inflammatory response
SPP1inflammatory response
B4GALT1inflammatory response
NFKBIZinflammatory response
CEBPBinflammatory response
LY96inflammatory response
PDPNinflammatory response
LYZinflammatory response
NFAM1inflammatory response
IL6Rinflammatory response
CD40inflammatory response
CD163inflammatory response
CCR5inflammatory response
KYNUinnate immune response
IL1R1innate immune response
TLR1innate immune response
NCF1Cinnate immune response
TLR2innate immune response
C1Rinnate immune response
APOBEC3Ginnate immune response
C1Sinnate immune response
C1QCinnate immune response
GCH1innate immune response
SP100innate immune response
NCF2innate immune response
NCF1innate immune response
SERPING1innate immune response
C1QAinnate immune response
CYBAinnate immune response
C1QBinnate immune response
CORO1Ainnate immune response
C1RLinnate immune response
VSIG4innate immune response
PTPRCT cell activation
STAT5AT cell activation
RELBT cell activation
PTPN22T cell activation
VAV1T cell activation
ITGAMT cell activation
DOCK2T cell activation
CD86T cell activation
IRF1T cell activation
CLEC7AT cell activation
FAST cell activation
LCP1T cell activation
RAB27AT cell activation
SYKT cell activation
SLC11A1cytokine production
NLRC4cytokine production
MYD88cytokine production
LYNcytokine production
CD4cytokine production
CD226cytokine production
PRKCDcytokine production
PTAFRcytokine production
LCP2cytokine production

Representative genes of each biological function.

The representative genes of each biological function are which obtained from GO analysis in heat map are listed.

Special Immune Function of GLRX

Tumor-infiltrated immune cells, including T cells, NK cells, macrophages, and other cells, mount the immune response to kill or induce apoptosis of cancer cells (24). To further clarify the role of GLRX in the immune response in gliomas, we first assessed the correlation between GLRX and GO terms downloaded from the AmiGO2 web portal (http://amigo.geneontology.org/). We found 84.69%, 78.90%, and 87.07% biofunction of the immune system to be positively correlated with GLRX in the CGGA, TCGA, and CGGA (2019) data sets, respectively (Figures 4A, B and Supplementary Figure S4A). Overall, more immune-related GO terms were positively correlated with GLRX than any other kind of GO term. This further illustrates that GLRX has a strong correlation with the immune system. Last, to understand the role of GLRX in the immune system, we performed a correlation coefficient analysis on data from the three databases (Figure 4C and Supplementary Figure S4B). We observed that the majority of immune functions showed positive correlation with GLRX; only the term “T cell-mediated immune response to tumor cell (T cell response)” was found to be negatively correlated with GLRX.

Figure 4

GLRX Is Associated With Inhibitory Immune Checkpoints and Inflammatory Responses

As mentioned above, most immune functions had positive correlation with GLRX with the exception of T cell responses. In a previous study, we reported that glioma patients with a stronger immune response had a much poorer prognosis (25). This abnormal phenomenon suggests that depletion of immune components in gliomas triggered by immune checkpoints could contribute to a malignant tumor phenotype. To validate this hypothesis, we investigated the relationship between GLRX and known immune checkpoint genes, including PD-1, TIM-3, PD-L1, and PD-L2, in the CGGA, TCGA, and CGGA (2019) databases (Figures 5A–H and Supplementary Figure S5A-D). The results indicated that GLRX had a strong positive correlation with these inhibitory immune checkpoint molecules and that GLRX may influence their expression to support glioma cells escaping immunological surveillance. Additionally, we also analyzed the role of GLRX in the glioma inflammatory response in these databases as described previously (19) (Figures 5I, J and Supplementary Figure S5E). We found that GLRX was positively associated with HCK, interferons, LCK, MHC-I, MHC-II, STAT1, and STAT2 expression, and it was negatively associated with IgG expression. These results suggest that upregulation of GLRX is involved in the activation of signal transduction in T cells, macrophages, and antigen-presenting cells, but it is negatively associated with B lymphocytes related metagenes. All these findings collectively confirm that GLRX plays an important role in immune response in gliomas.

Figure 5

GLRX Is Associated With M0 Macrophages

An activated immune response may promote the infiltration of immune cells into the tumor microenvironment and change its dynamics. To investigate whether GLRX was associated with infiltrated immune cells, we used CIBERSORT software to analyze the CGGA, TCGA, and CGGA (2019) databases (Figure 6A and Supplementary Figure S6). The analysis revealed that higher GLRX expression was positively correlated with enrichment of macrophages in glioma tissue. Moreover, single-cell sequencing data (Figures 6B–G) demonstrated that GLRX may be specifically expressed in M0 macrophages compared to other types of macrophages. To verify this finding, IHC co-localization staining was performed to explore the expression of GLRX in macrophages in tumor specimens. A previous study reported that CD11b was a biomarker of M0 macrophages (17). The results showed that GLRX was expressed in most M0 macrophages (Figures 7A, B). Furthermore, GM-CSF and PMA were used to induce THP-1 cells to differentiate toward M0 macrophages in vitro. Under this circumstance, M-CSF was added to medium to induce M0 macrophages to polarize to M2 macrophages (16, 17). IF staining results showed that GLRX was highly expressed by M0 macrophages compared to M2 macrophages (Figures 7C, D). These findings suggest that the effect of GLRX on the immune system is mediated by M0 macrophages, further validating that GLRX plays a pivotal role in the immune response.

Figure 6

Figure 7

GLRX Predicts Survival Outcome in Gliomas

Because GLRX showed a robust negative correlation with the T cell response, we further investigated the prognostic value of GLRX by Kaplan-Meier and Cox proportional hazard model analyses. We found that patients with a higher expression of GLRX had a significantly shorter overall survival compared with those with lower GLRX expression (Figures 8A, B and Supplementary Figure S7A). Moreover, GLRX expression, WHO grade, age at diagnosis, IDH status, 1p/19q status, and MGMT promoter status were significantly associated with overall patient survival in all the three data sets that were evaluated. Multivariate analysis further confirmed GLRX as a significant predictor after adjusting for the clinical factors mentioned above (Figures 8C, D and Supplementary Figure S7B). These findings reveal that GLRX may serve as an indicator for the poor prognosis in gliomas due to its suppressive effects on the T cell immune response against tumor cells.

Figure 8

Discussion

Glioma is one of the most fatal malignancies to afflict human health (1). Although temozolomide was approved for the treatment of gliomas by the U.S. Food and Drug Administration in 2005, researchers have continued to search for novel chemotherapeutic drugs with improved efficacy to treat gliomas (26). Nevertheless, no significant results have been achieved so far. Therefore, novel therapeutic approaches against gliomas remain an urgent requirement. In recent years, targeted drugs and immunotherapeutic approaches have exhibited extraordinary prospects (27, 28). Based on high-throughput sequencing, our team built the CGGA database and screened the PTPRZ1-MET fusion gene, which is expressed almost exclusively in secondary glioblastomas. The targeted drug PLB-1001 showed a good response rate in phase 2 clinical trials (29). Moreover, immune checkpoint blockade therapy also achieved success in treating gliomas. Cloughesy et al. reported that neoadjuvant anti-PD-1 immunotherapy, which enhances T cell–mediated antitumor immunity, could significantly extend overall survival of patients with recurrent glioblastomas (30). Despite the promising clinical results, these therapeutic approaches can benefit just a fraction of patients with gliomas. Therefore, exploring therapeutic approaches or a multifunctional small molecule that could benefit most glioma patients is of great interest.

The thioredoxin and glutathione systems are the key cellular redox systems involved in gliomas (8, 31, 32). Glioma proliferation is associated with parenchymal alterations and oxidative stress that further leads to the impairment of brain homeostasis (4). Tumor cellular respiration produces hyperoxides, such as H2O2, and reactive oxygen species (ROS), which, when present at high levels, damage the DNA. This process is considered to be a pernicious factor in malignant glioma development (33). Hence, functional antioxidant systems that can scavenge these hyperoxides hold promise to keep the cell cycle of glioma cells under control. Simultaneously, a better understanding of the antioxidant system can pave the way for finding new therapeutic approaches to fight gliomas. Because glioma cells are more susceptible to oxidative stress induced by hyperoxides, inhibition of antioxidant systems or their components can prevent them from performing oxidative scavenging, thereby exposing the glioma cells to intense oxidative stress and blocking their proliferation, leading to their death. The endogenous antioxidative molecule Grx plays an important role in the glutathione system (7, 34). Grx expression is associated with tumor proliferation and therapy resistance in several cancers. Previous studies report that Grx is overexpressed in pancreatic ductal carcinoma compared to normal pancreatic tissue and that Grx overexpression increases MCF-7 adenocarcinoma cell resistance to doxorubicin (35, 36). However, little is known about the role of Grx in gliomas. Therefore, as a potential therapeutic target, it is imperative to explore the unique role of Grx and how it works in gliomas.

We started by checking the expression of GLRX in glioblastoma tissue compared with normal brain tissue. Our results showed that, similar to other tumor types, glioblastoma samples exhibited higher expression of GLRX. Next, we analyzed RNA-seq data of 1,717 glioma patients compiled from the CGGA, CGGA (2019), and TCGA databases. As expected, GLRX expression was significantly upregulated in higher malignant pathological grades of gliomas. Moreover, we also found that GLRX expression was significantly higher in glioma patients with malignant molecular phenotypes, including those harboring the IDH wild-type state, 1p/19q non-codeletion state, and MGMT unmethylated promoters. Furthermore, GLRX was highly enriched in mesenchymal subtype gliomas. The mesenchymal subtype is characterized by stronger immunosuppression, and aggressive phenotype, and malignant proliferation due to the mesenchymal differentiation triggered by NF1 mutations (21). A previous study has reported enhanced expression of immune checkpoints in mesenchymal subtype cancers compared with the other three transcriptional characteristic subtypes (37). Therefore, GLRX may be upregulated and involved in the immunosuppressive microenvironment of gliomas via modulation of the cellular component of the immune system. These findings suggest that GLRX expression is associated with the malignant behavior of gliomas. Thus, unraveling the mechanism of GLRX in gliomas may pave the way for the development of novel therapeutic approaches to fight this deadly malignancy.

To gain an in-depth understanding of the biological functions of GLRX, a series of analyses were performed. GO analysis revealed that GLRX plays a crucial role in immune and inflammatory responses in gliomas. Consistent with these results, KEGG and GSVA analyses also show that GLRX and related genes are involved in several immune response pathways, and GLRX is positively correlated with most immune functions with the exception of T cell response. Furthermore, GLRX was found to be significantly enriched in the mesenchymal glioma subtype with GLRX negatively mediating the T cell response and playing a suppressive role in the antitumor immune response. Taken together, these results suggest that GLRX may upregulate the expression of immune checkpoints to perform these functions. Upon analysis of the relationship between GLRX and known immune checkpoint genes, we confirm that GLRX is positively correlated with most inhibitory immune checkpoints, including PD-1, TIM-3, PD-L1, and PD-L2, which are involved in the regulation of the PD-1/PD-L1 pathway. These immune checkpoints are major negative immune regulators and are involved in regulating T cell activation, tolerance, and exhaustion (19). Our findings demonstrate that GLRX may exert antiglioma immune roles by affecting the expression of these inhibitory immune checkpoints. Additionally, GLRX is involved in inflammatory activities known to promote glioma progression via activation of tumor-associated macrophages (14, 38). To further validate the role of GLRX in the immune response, we used CIBERSORT software to calculate the percentage of each type of infiltrated immune cell. Our results show that GLRX is positively correlated with macrophages but negatively correlated with different subgroups of T cells. This further confirms the conclusions of our study. Last, single-cell sequencing analysis and IHC co-localization staining were performed to identify the exact components of the immune system that express GLRX. RNA-seq data and cellular molecular biomarkers reveal that GLRX is enriched in immune cells, particularly in M0 macrophages. M0 macrophages are a subgroup of resting immune cells that can undergo a directional polarization (17) to classically activated M1 macrophages and alternatively activated M2 macrophages. Macrophages in glioma tissue are prone to M2-like phenotypes, which are considered to be tumor-supporting macrophages (39). A previous study also reported that patients with higher expression of M0 macrophages had a poorer prognosis (17). Thus, we suspected that GLRX may play a role in M0 polarization and have an immuno-suppressive function. Based on the results of our present study, we hypothesize that GLRX is a potential target for redox and immunotherapy of gliomas.

Importantly, high levels of GLRX were associated with poor patient prognosis. Univariate and multivariate analyses indicated that high expression of GLRX predicted significantly lower survival. As a result, GLRX may serve as a potential prognostic predictor for glioma patients.

Redox therapy is being increasingly explored in tumor therapy (40, 41). Studies on breast, liver, pancreatic, and non-small cell lung cancers report that blocking the glutathione system could prevent tumor cell proliferation in vitro and in vivo (33, 35, 36, 42). As gliomas have access to abundant oxygen as well as to cellular respiration products, glioma cells become more dependent on the antioxidant system to survive and proliferate. Even a slight reduction in antioxidant levels could lead to glioma cell death (43). Meanwhile, cancer immunotherapy has also shown potential benefits for glioma patients. CAR-T, anti-PD-1, and anti-PD-L1 immunotherapies have shown higher immune response rates and longer survival in patients with brain metastases (2, 24, 27, 30). Our study suggests that GLRX is a key regulator of immune checkpoints and the immune response. Therefore, as a co-regulator of both redox and immune systems, inhibiting Grx could not only kill glioma cells through directly enhancing oxidative stress, but also downregulate the expression of inhibitory immune checkpoints and enhance the immune response. Thus, our study establishes GLRX as a novel potential target to enhance the efficacy of anticancer therapies, thereby paving the way for novel therapeutic approaches for treating gliomas.

Funding

This work was supported by grants from the National Natural Science Foundation of China (No. 81972816, 81672479).

Statements

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.cgga.org.cn, CGGA.

Ethics statement

The studies involving human participants were reviewed and approved by Capital Medical University Institutional Review Board (IRB). The patients/participants provided their written informed consent to participate in this study.

Author contributions

YC, GL: data analysis and editing the manuscript. YZ, LH: data collection and organization of CGGA database. YF, DW: data collection and organization of TCGA database. WZ, HH: conception, supervision, and design of the manuscript. All authors contributed to the article and approved the submitted version.

Acknowledgments

We thank Ms. Shuqing Sun and Hua Huang for tissue sample collection and clinical data retrieval.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.580934/full#supplementary-material

Supplementary Figure 1

GLRX is correlated with the relative malignant molecular pathological characteristics of glioma. (A) GLRX was significantly increased in GBM (WHO grade IV) in the CGGA (2019) database. (B) GLRX was significantly increased in IDH wild-type gliomas in the CGGA (2019) database (Mut: IDH mutation; WT: IDH wild type). (C) GLRX was significantly increased in 1p/19q non-co-deletion gliomas in the CGGA (2019) database (Codel: 1p/19q co-deletion; Non-codel: 1p/19q non-co-deletion). (D) GLRX was significantly increased in the MGMT unmethylated group in the CGGA (2019) database. ns and **** indicate no statistical difference and p < 0.0001, respectively.

Supplementary Figure 2

GLRX is a potential marker for malignant subtypes of gliomas. (A) GLRX was highly expressed in the mesenchymal subtype in the CGGA (2019) database. (B) ROC curve analysis showed that GLRX was highly sensitive and specific to predict the mesenchymal subtype in the CGGA (2019) database. (C–E) ROC curve analysis showed that BMI1 was less sensitive and specific to predict the mesenchymal subtype in the CGGA, TCGA, and CGGA (2019) databases, respectively. (F–H) ROC curve analysis showed that CD44 was highly sensitive and specific to predict the mesenchymal subtype in the CGGA, TCGA, and CGGA (2019) databases, respectively. Differences between groups were tested by Tukey’s multiple comparisons test. *** and **** indicate p < 0.001 and p < 0.0001, respectively.

Supplementary Figure 3

GLRX is strongly associated with immune processes in gliomas. (A) GO analysis showed that GLRX was mostly associated with immune, defense, and inflammatory responses in the CGGA (2019) database. (B) KEGG pathway analysis showed that GLRX was mostly involved in the immune response–related pathway in the CGGA (2019) database. (C) Most immune process–related genes were significantly positively correlated with GLRX expression in the CGGA (2019) database.

Supplementary Figure 4

GLRX is closely related to the state of tumor immune functions. (A, B) GLRX had positive correlation with 87.07% of the biological functions of the immune system process in the CGGA (2019) database. The scale values in the graph represent the proportions of significantly correlated biological functions in each biological function classification. (B) The correlation coefficient between GLRX and the immune function scores in the CGGA (2019) database. The red words represent a positive correlation. The green words represent a negative correlation.

Supplementary Figure 5

GLRX is associated with immune checkpoints and inflammatory activities. (A–D) GLRX was synergistic with inhibitory immune checkpoints in tumor-induced immune responses. A strong correlation between GLRX and inhibitory immune checkpoint expression was found in the CGGA (2019) database. (E) The correlation coefficient between GLRX and inflammatory activity function scores in the CGGA (2019) database. The red circle represents a positive correlation. The blue circle represents a negative correlation. The grey “×” represents no significant correlation.

Supplementary Figure 6

The relationship between GLRX and infiltrated immune cells in the CGGA (2019) database. ns, *, **, ***, and **** indicate no statistical difference, p < 0.05, p < 0.01, p < 0.001, and p<0.0001, respectively.

Supplementary Figure 7

GLRX is a prognostic factor in glioma patients. (A) Clinical outcomes of patients with gliomas of low or high expression of GLRX. Kaplan-Meier survival analysis was performed in the CGGA database. (B) Univariate and multivariate analyses of clinical prognostic parameters in CGGA database.

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Summary

Keywords

glioma, GLRX, macrophage, prognosis, tumor immunity

Citation

Chang Y, Li G, Zhai Y, Huang L, Feng Y, Wang D, Zhang W and Hu H (2020) Redox Regulator GLRX Is Associated With Tumor Immunity in Glioma. Front. Immunol. 11:580934. doi: 10.3389/fimmu.2020.580934

Received

07 July 2020

Accepted

26 October 2020

Published

30 November 2020

Volume

11 - 2020

Edited by

Chunsheng Kang, Tianjin Medical University General Hospital, China

Reviewed by

Jun Wei, University of Texas MD Anderson Cancer Center, United States; Xian Zeng, Fudan University, China

Updates

Copyright

*Correspondence: Wei Zhang, ; Huimin Hu,

†These authors have contributed equally to this work

This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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