Gliomas, the most common primary neoplasms in the brain, are notorious for their ability to evade the immune response. Despite microglial infiltration in gliomas, expression of MHC class II molecules in those microglia is compromised. Here, we report that Toll-like receptor 2 (TLR2) activation downregulated expression of MHC class II molecules in microglia in an orthotopic murine glioma model. TLR2-induced microglial impairment hindered the proliferation and activation of CD4+ T cells, which facilitated glioma immune evasion. TLR2-induced downregulation of MHC class II molecules was caused by suppression of the master regulator of MHC class II molecule transcription, Ciita. TLR2 activation triggered downstream MAPK/ERK1/2 signaling and loss of histone H3 acetylation at Ciita promoters, which in turn inhibited Ciita expression. In glioblastoma tissues, various endogenous TLR2 ligands, including the heat shock proteins that are endogenous TLR2 ligands, were upregulated, a response that correlated with CIITA inhibition. Thus, TLR2 promotes glioma immune-system evasion. These results advance our understanding of microglia as antigen-presenting cells in the context of glioma. In the glioma tumor microenvironment, TLR2 activation of microglia induces downregulation of microglial MHC class II expression. Impaired MHC class II expression limits T-cell–dependent antitumor immunity. Cancer Immunol Res; 6(10); 1220–33. ©2018 AACR.

Gliomas are the most common primary intracranial malignancy in humans, and despite clinical intervention, the prognosis for patients with glioma remains dismal (1). Median overall survival of the patients with IDH1/2 wild-type (WT) glioblastoma multiforme (GBM) is shorter than 15 months (2). Fortunately, immunotherapies are being investigated for gliomas, including peptide or dendritic cell–based vaccines, chimeric T-cell receptors, and checkpoint inhibitors (3). Many of these strategies are dependent on the T-cell–mediated immune response, which needs local antigen-presenting cells (APCs) for initiation and sustenance (4). Microglia, the major APC subset within the central nervous system (CNS; refs. 5, 6), infiltrate gliomas (7). However, microglia are functionally compromised in the glioma microenvironment, thus limiting the effectiveness of T-cell–dependent tumor eradication.

Normally, microglia scan the environment to detect pathogens and other disturbances (8). Resting microglia express low amounts of the accessory molecules needed for antigen presentation (8). Under pathologic conditions like multiple sclerosis and infections, microglia move toward lesions, transform to amoeboid-like phagocytic cells, and upregulate expression of MHC class II molecules (MHC class II; refs. 6, 9), suggesting their participation in antigen presentation. Glioma-associated microglia (GAM), which show compromised ability to upregulate MHC class II expression in a murine model (10), are likely less effective than they could be at activating T helper cells. In humans, expression of MHC class II by microglia is reduced in high-grade gliomas (11). Expression of costimulatory molecules CD80 and CD86 in glioma-infiltrating microglia (10, 12) is also reduced. Expression of MHC class II, CD80, and CD86 increased after microglia were isolated from intracranial tumors and cultured ex vivo (13). These studies indicate that the tumor microenvironment renders GAM incompetent to induce T-cell activation and antiglioma immunity. The mechanism by which molecules related to antigen-presenting in GAM are downregulated has not been identified.

Toll-like receptors (TLR) are necessary for microglia to initiate the innate and adaptive immune responses in the CNS (14). TLRs are activated not only by pathogen-associated molecular patterns but also by danger-associated molecular patterns, such as heat shock proteins (HSP) and extracellular matrix (ECM) components (15). Activation of TLR signaling pathways leads to the induction of several genes that function in host defense, including those encoding inflammatory cytokines and chemokines (16). In certain types of innate immune cells, such as macrophage and dendritic cells, activation of TLR signaling is associated with the expression of costimulatory molecules and MHC molecules (17, 18). Whether TLR signaling regulates the antigen-presentation function of GAM remains unknown.

In the present study, we found that TLR2 expression was upregulated in GAM. Glioma-derived factors impaired MHC class II expression of microglia in a TLR2-dependent manner, which dampened the activation and proliferation of CD4+ T cells. According to The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas database, several kinds of endogenous TLR2 ligands are upregulated in human glioblastoma tissues. Among these ligands, we identified HSPs as inducers of TLR2 activation in correlation with the MHC class II inhibition in human GBM samples. Our results clarified the mechanisms behind glioma-induced impairment of APCs and revealed the function of TLR in tumor immune evasion.

Mice

C57BL/6 mice (6–8 weeks) were purchased from Shanghai Slac Laboratory Animal Co., Ltd. TLR2-deficient C57BL/6 mice were purchased from the Model Animal Research Center, Nanjing University (Nanjing, China). OT II transgenic mice were kindly provided by Dr. Rui He (Fudan University, Shanghai, China). All mice were housed under the pathogen-free condition in the Animal Facility of Fudan University (Shanghai, China). All animal experiments adhered to the Guidelines for the Care and Use of Laboratory Animals (No. 55 issued by Ministry of Health, the People's Republic of China on January 25, 1998) and were approved by the Institutional Animal Care and Use Committee of Fudan University.

Cell lines

The murine glioma cell line, GL261, was kindly provided by Dr. Liangfu Zhou (Huashan Hospital, Shanghai, China) in 2012. The murine microglial cell line, BV2, was obtained from the Shanghai Cell Bank of the Chinese Academy of Science (Shanghai, China) in 2014. After obtaining the cell lines, cells were expanded to passage 5 and stored in aliquots in liquid nitrogen. All cell lines were grown in DMEM/F12 (Thermo Fisher) supplemented with 10% heat-inactivated FBS (Thermo Fisher), 2 mmol/L glutamine (Thermo Fisher), 100 U/mL penicillin (Thermo Fisher), and 100 μg/mL streptomycin (Thermo Fisher). Cell cultures were maintained in the incubator at 37°C in a humidified atmosphere of 5% CO2/95% with routine checks for mycoplasma contamination every 3 months. All cells were used in experiments before they reach passage 15. All cell lines were authenticated using short tandem repeat profiling in 2015. Glioma-derived conditioned medium (GCM) was collected after 24 hours from 80% confluent GL261 cultures, filtered through 0.2 μm filter, and applied to microglia cultures.

Primary adult microglia culture, cell stimulation, and T-cell coculture assay

Microglia were prepared from 6- to 8-week-old mice: the cerebrum was dissected and transferred to cold PBS. The tissue was triturated mechanically and collected in a 50-mL Falcon tube and washed with PBS by centrifuging for 7 minutes at 500 × g at 4°C. The supernatant was discarded, and pellets were resuspended and adjusted to 37% Percoll. Percoll gradients (70%/37%/30%/0%) were set up and centrifuged for 5 minutes at 500 × g at 18°C with low acceleration with the brake off. Mononuclear cells were collected at the 70%/37% interface and washed with PBS. Microglia were enriched by adhesion to CD11b microbeads (BD Bioscience) and harvested for purity check and further tests. For cultivation, microglia were plated onto 24-well plates at a density of 1 × 105 cells per well with DMEM/F12 supplemented with 10% heat-inactivated FBS, 2 mmol/L glutamine, 100 U/mL penicillin, 100 μg/mL streptomycin, 5 ng/mL recombination TGFβ1 (Miltenyi), and 10 ng/mL Recombinant Mouse M-CSF Protein (R&D). Half of the medium was changed every 3 days, for a total of 10 to 14 days.

In most cases of the study, for microglial TLR2 activation, primary microglia or BV2 cells were treated with 100 ng/mL Pam3CSK4 (Invivogen) or GCM (20%, vol/vol) for 24 hours. For MHC class II induction, primary microglia or BV2 cells were treated with 20 ng/mL IFNγ (PeproTech) for another 24 hours. Other TLR agonists (Invivogen) used in the study include Poly(I:C) (10 μg/mL), LPS (100 ng/mL), Pam2CSK4 (100 ng/mL), and CpG (2.5 μmol/L). The inhibitors in specific experiments were used by pretreatment of cell cultures for 30 minutes. The working concentrations of inhibitors are listed as follows: PI3K inhibitor (CST), Ly294002 (10 μmol/L); ERK1/2 inhibitor (Selleck), U0126 (10 μmol/L); p38 inhibitor (Selleck), SB203580 (10 μmol/L); JNK inhibitor (Selleck), SP600125 (10 μmol/L); DNMT inhibitor (Sigma-Aldrich), 5-aza-2′-deoxycytidine (5-AZA, 1 μmol/L); histone deacetylase (HDAC) inhibitor (MCE), Trichostatin A (TSA, 0.1 μmol/L); HDAC inhibitor (Selleck), Nicotinamide (Nico, 10 μmol/L).

For T-cell coculture assays, freshly isolated adult microglia were plated onto 96-well plates at a density of 1 × 105 cells per well. Half of the medium was changed every 3 days, for a total of 7 days. On day 8, microglia were treated with 100 ng/mL Pam3CSK4 or 20% GCM for 24 hours. Then, microglia were washed with PBS after stimulation. The CD4+ T Cell Isolation Kit (Miltenyi) was used for purification of CD4+ T cells from the spleen of OT II mice. CD4+ T cells were stained with carboxyfluorescein succinimidyl ester (CFSE) dye (Invitrogen) following the manufacturer's instructions. The microglia were washed with PBS for 3 times, and then cocultured with CD4+ T cells (4 × 105 cells per well) for 4 days supplied with 0.1 μmol/L OVA323-339 peptides (Sigma-Aldrich). After coculture, both microglia and T cells were determined by flow cytometric analysis.

Stereotactic intracranial tumor inoculation and cannula implantation

GL261 glioma cells were harvested and diluted to a concentration of 2 × 107 cells/mL. Anesthetized mice were immobilized and mounted onto a stereotactic head holder in the flat-skull position. The skin of the skull was dissected in the midline by a scalpel. The skull was carefully drilled with a 20-gauge needle tip (ML: +2.0 RC: +1.0 DV: 3.0 mm). Then a microliter Hamilton syringe was inserted to a depth of 3 mm and retracted to a depth of 2.5 mm from the dural surface. Note that 5 μL (2 × 104 cells/μL) cell suspension or PBS was slowly injected over 2 minutes. The needle was then slowly taken out from the injection canal, and the skin was sutured. For cannula implantation, a hole was drilled for insertion of the cannula (ML: +1.0 RC: –0.4 DV: 2.0 mm), which was used for intracerebroventricular (ICV) injection. In the study, Pam3CSK4 (5 μg) were delivered to the lateral ventricle via cannula on days 6, 12, and 18 after tumor inoculation, and mice were sacrificed on day 20 for further analysis.

RNA isolation, reverse transcription, and quantitative RT-PCR

RNA was isolated with RNAiso (Takara) following the manufacturer's protocol. RNA samples were reversely transcribed using the PrimeScriptTM RT reagent Kit with gDNA Eraser (Perfect Real Time; Takara), and gene expression was detected using the SYBR Premix Ex TaqTM II (Tli RNaseH Plus) Kit (Takara). All real-time PCR amplifications were performed in triplicates in a 20 μL reaction volume with the indicated primer pairs (Supplementary Table S1). RT-PCRs were performed using 7500 Fast Real-Time PCR System (Applied Biosystems). The amount of target mRNA was normalized to the expression level of β-actin generated from the same sample and subsequently to controls. Relative expression was calculated as 2−ΔCt. Fold induction was calculated as 2−ΔΔCt.

Chromatin immunoprecipitation

Primary microglia (contain 5.0 × 105–1.0 × 106 cells per sample) were used for following chromatin immunoprecipitation (ChIP), performed using the SimpleChIP Enzymatic Chromatin IP Kit (Cell Signaling Technology) according to the manufacturer's protocol. DNA was eluted and purified, followed by qPCR analysis using primers specific for Ciita promoter (Supplementary Table S1). All antibodies used for these experiments were listed in Supplementary Table S1, and normal rabbit IgG (Cell Signaling Technology) was used as the isotype control. The fold enrichment method was used for data normalization.

RNA-seq

Total RNA was extracted using TRIZOL Reagent (Thermo Fisher) following the manufacturer's protocol. Paired-end libraries were synthesized by using the TruSeq RNA Sample Preparation Kit (Illumina) following TruSeq RNA Sample Preparation Guide. The cluster was generated by cBot with the library diluted to 10 pmol/L and then was sequenced on the Illumina HiSeq X Ten (Illumina). The P value significance threshold in multiple tests was set by the FDR. The fold changes were also estimated according to the fragments per kilobaseof exon per million fragments mapped (FPKM) in each sample. The differentially expressed genes were selected using the following filter criteria: FDR ≤ 0.05 and fold change ≥ 2. R language was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology analysis. The Gene Expression Omnibus (GEO) accession number for the RNA-seq data is GSE109297.

Immunofluorescence

For frozen sections, mice were fully anesthetized, transcardially perfused with 20 mL of PBS, and followed by 20 mL of paraformaldehyde (PFA; 4% in PBS). Tissues were incubated in PFA overnight at 4°C, then transferred to sucrose (20%) for 1 day at 4°C, and finally transferred to sucrose (30%) for another day at 4°C. All tissues were embedded and frozen in Optimal Cutting Temperature compound, and the brains were mounted on a freezing microtome (Leica). Sections (20 μm thick) were obtained and stored at –80°C for all subsequent staining and analysis.

For immunofluorescence, sections were thawed and dried at room temperature and rinsed in PBS. For cell culture, cells were washed with PBS and followed by 4% PFA cell fixation (5 minutes at room temperature). Samples were permeabilized with 0.25% Triton-X 100 for 15 minutes at room temperature and blocked in blocking buffer containing 10% donkey serum for 2 hours at room temperature or overnight at 4°C. Then, samples were incubated with indicated primary antibodies (Supplementary Table S2) overnight at 4°C. Samples were then washed with PBS and incubated with the appropriate fluorophore-conjugated secondary antibodies: Alexa Flour-488, 594 (Thermo Fisher), and Cy3 (Jackson ImmunoResearch Laboratory) at a dilution of 1:500 in 1% BSA for 1 hour at room temperature, and 4′, 6-diamidino-2-phenylindole (DAPI) were used as a counterstain. Images were acquired by a fluorescence microscope Olympus IX73 (Olympus) or a spectral confocal microscope (TCS SP5, TCS SP8; Leica). Appropriate gain and black level settings were determined by control tissues stained with secondary antibodies alone. Analyses of images were performed using ImageJ software (U.S. National Institutes of Health).

Fluorescence-activated cell sorting analyses

For fluorescence-activated cell sorting (FACS) analysis of brain tumor–infiltrated immune cells, mice were euthanized at the defined endpoint or when symptomatic (poor grooming, lethargy, weight loss, or seizures). Brains were harvested with olfactory bulbs and cerebella removed, dissociated mechanically with Dounce homogenizers to make homogenates, and then forced through a filter for single-cell suspension and washed with PBS. Cell pallets were resuspended in 37% Percoll. Percoll gradients (70%/37%/30%/0%) were set up and centrifuged for 40 minutes at 200 × g at 18°C with low acceleration with the brake off. Mononuclear cells were collected at 70%/37% interface and washed with PBS. Mononuclear cells were stained afterward with the respective antibodies for FACS analysis.

For flow cytometry, cells were counted and incubated with Fc block (eBioscience) for 30 minutes, followed by another 30-minute incubation with conjugated antibodies for extracellular markers. For intracellular cytokine detection, cells were stimulated in vitro with Cell Stimulation Cocktail (eBioscience) for 5 hours at 37°C before FACS analysis. After stimulation, the cells were stained for surface markers and cytokines with Intracellular Fixation and Permeabilization Buffer Set (eBioscience). All antibodies used for these experiments were listed in Supplementary Table S2. Proper isotype controls and compensation controls were performed in parallel. A BD Biosciences Canto II was used for flow cytometry, and a Beckman Coulter MoFlo XDP was used for cell sorting. FlowJo software (Tree Star) was used for FACS data analysis.

Immunoblotting analysis

The procedure was performed as described previously. Briefly, proteins were extracted using radio-immunoprecipitation assay (RIPA) buffer (Cell Signaling Technology) according to the manufacturer's protocol. Equal amounts of protein were resolved by SDS/PAGE (Beyotime) and then transferred to polyvinylidene difluoride membranes (Merck Millipore). Membranes were probed with the primary Abs after blocking with 5% nonfat milk. All antibodies used for these experiments were listed in Supplementary Table S2. After that, membranes were washed and incubated with horseradish peroxidase–conjugated secondary Abs. Specific proteins were detected by enhanced chemiluminescence (Thermo Fisher).

Data presentation and statistical analysis

GraphPad Prism 6.0 (GraphPad Software Inc.) was used for all data analysis. Parametric data are presented as mean ± SEM. Differences between two groups were analyzed using the Student unpaired t test. ANOVA was used to investigate more than two groups, and the Pearson correlation coefficient was used to analyze the correlation among the levels of genes. For survival curves, the cumulative survival time was calculated using the Kaplan–Meier method and analyzed using the log-rank test. P < 0.05 was considered statistically significant.

Microglia accumulate at the tumor site and upregulate TLR2 expression

To investigate the mechanism underlying the downregulation of molecules related to antigen-presenting in GAM, we used the GL261 murine glioma model due to its immunogenic features and predictable tumor progression (19). The GL261 tumor-bearing WT C57BL/6 mice died around 4 weeks after GL261 inoculation. The histologic hematoxylin and eosin (H&E) staining showed that tumor size expanded 20 days after of inoculation (Supplementary Fig. S1A), with significant loss of body weight (Supplementary Fig. S1B). Weight of spleens of tumor-bearing mice significantly increased between day 10 and day 20 (Supplementary Fig. S1C), concomitant with increased numbers of tumor-infiltrating peripheral immune cells (CD45hi cells; Supplementary Fig. S1D and S1E). These results indicate that immune microenvironment is established along with glioma progression. Around day 20, the balance tilts in favor of the tumor, resulting in rapid deterioration of the mouse.

We found that expression of microglial protumor genes, including Il6, Il10, Tgfb2, Mmp14 (encoding MT-MMP1), Cd274 (encoding PDL1), and Ccl2 (7), was elevated in the tumor-bearing brain; expression of some of these genes peaked on day 20 (Supplementary Fig. S1F). Next, we investigated the microglial infiltration pattern on day 20 after GL261 inoculation. Immunofluorescence staining showed that Iba1+ microglia accumulated along the tumor perimeter, where they change morphology from ramified, characteristic of normal tissue, to the amoeboid form characteristic of tumor invasion. Within the tumor, microglia appear as rod-like shapes (Fig. 1A). Based on the Iba1+ cell counts and Iba1-labeled area, microglial density increased successively from normal tissue, tumor rim, invasive margin, to intratumoral region (Fig. 1B).

Figure 1.

Microglia accumulate at tumor sites and upregulate TLR2 expression. A, Representative staining for Iba1 (green) and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation. Right plots, different regions of the tumor-bearing brain. N, normal tissue; TR, tumor rim; IM, invasive margin; IT, intratumoral region. B, Iba1+ cell counts per field and percentage of Iba1 labeled area were calculated. Data were collected from 20 random fields for each region per mouse, n = 3. C, TLR expression in different cell subsets of the normal brain according to GEO dataset (GSE52564). D, qPCR analysis of TLRs’ expression pattern in FACS-sorted CD45loCD11b+ microglia isolated from glioma model (day 20) and normal brain, each sample represents 5 mice brains pooled, and expression was normalized to β-actin (n = 3). E, mRNA expression of TLR2 in human glioma samples, data from TCGA LGG/GBM datasets. N, normal tissue, n = 4; OD, oligodendroglioma, n = 191; OA, oligoastrocytoma, n = 130; AST, astrocytoma, n = 194; GBM, n = 152. F and G, Flow cytometry analysis of CD45loCD11b+ microglia for TLRs’ expression pattern, n = 5. Unpaired Student t test was performed in D and G. One-way ANOVA was performed in E. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Figure 1.

Microglia accumulate at tumor sites and upregulate TLR2 expression. A, Representative staining for Iba1 (green) and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation. Right plots, different regions of the tumor-bearing brain. N, normal tissue; TR, tumor rim; IM, invasive margin; IT, intratumoral region. B, Iba1+ cell counts per field and percentage of Iba1 labeled area were calculated. Data were collected from 20 random fields for each region per mouse, n = 3. C, TLR expression in different cell subsets of the normal brain according to GEO dataset (GSE52564). D, qPCR analysis of TLRs’ expression pattern in FACS-sorted CD45loCD11b+ microglia isolated from glioma model (day 20) and normal brain, each sample represents 5 mice brains pooled, and expression was normalized to β-actin (n = 3). E, mRNA expression of TLR2 in human glioma samples, data from TCGA LGG/GBM datasets. N, normal tissue, n = 4; OD, oligodendroglioma, n = 191; OA, oligoastrocytoma, n = 130; AST, astrocytoma, n = 194; GBM, n = 152. F and G, Flow cytometry analysis of CD45loCD11b+ microglia for TLRs’ expression pattern, n = 5. Unpaired Student t test was performed in D and G. One-way ANOVA was performed in E. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Close modal

We then focused on expression of TLRs in GAM. In the normal brain, according to an RNA-sequencing database of the cerebral cortex (20), most TLRs are expressed by microglia. Certain TLRs, namely TLR2, TLR7, and TLR9, are predominantly expressed in microglia (Fig. 1C). We compared the TLR expression pattern between microglia isolated from the normal and tumor-bearing brain by qPCR analysis. The results revealed that Tlr2 and Tlr8 mRNA levels were upregulated in the GAM (Fig. 1D), which is consistent with the previous study of the GL261 model (21). In a genetically engineered mouse model of glioma, TLR2 is also the predominant TLR expressed by GAM (22). Expression of TLR2 in human glioma samples was higher than that in normal tissues and was associated with higher-grade malignancy (Fig. 1E). The amount of TLR2 protein in GAM was consistent with the amount of mRNA (Fig. 1F and G). TLR2 is mainly expressed in microglia and peripheral macrophages in the tumor-bearing brain (Supplementary Fig. S2A–S2C). These findings indicate that TLR2 is upregulated in GAM and may modulate GAM function.

TLR2 activation downregulates MHC class II in microglia

To investigate the role of TLR2 in the modification of antigen-presenting function of GAM, we established the GL261 model in Tlr2−/ and WT mice. The analysis of cumulative survival revealed that Tlr2−/− mice survived longer than WT mice (Fig. 2A) with less tumor burden on day 20 according to the histologic H&E staining (Fig. 2B). We evaluated the expression of molecules related to antigen-presenting in GAM by flow cytometry (Supplementary Fig. S3). The brain-resident microglia were gated as CD45loCD11b+CD49d−/lo cells according to the previous report (22). Molecules related to antigen-presenting function on Tlr2−/− and WT-derived microglia were measured. Results showed no difference in the expression of costimulatory molecules (CD80 and CD86) or the coinhibitory molecule (PD-L1) between Tlr2−/− and WT mice, whereas expression of MHC class II was upregulated in microglia from Tlr2−/− mice (Fig. 2C). Histology indicated the MHC class II+ microglia were mainly in the tumor invasive margin, and that microglia in Tlr2−/− mice expressed more MHC class II than WT mice (Fig. 2D).

Figure 2.

TLR2 activation downregulates MHC class II in microglia. A, The Kaplan–Meier survival curves represent the cumulative survival of WT and TLR2−/− mice after GL261 inoculation, n = 8. B, H&E staining for sections of tumor-bearing WT and TLR2−/− mice (day 20). Scale bar, 500 μm. Right plot, tumor area was calculated, n = 5–15. C, Flow cytometry analysis of the glioma model (day 20) derived CD45loCD11b+ microglia for antigen-presenting function-related markers. Right plot, summary of the data, n = 8–10. Data are representative of three independent experiments. D, Representative staining for Iba1 (green), MHC class II (red), and DAPI (blue) in tumor-bearing brains on day 20 after GL261 inoculation. Dashed line, tumor boundary; IM, invasive margin; T, tumor; N, normal tissue. Bottom plots, higher magnification of the regions indicated in the dashed boxes. E, Representative staining for Iba1 (green), MHC class II (red), and DAPI (blue) in primary microglia. Control, microglia treated with IFNγ. GCM, microglia treated with GCM and followed with IFNγ. F, Flow cytometry analysis of primary microglia for MHC class II expression. Right plot, summary of the data, n = 3. G, Flow cytometry analysis of primary microglia (treated with the indicated dose of Pam3CSK4 and followed with IFNγ) for MHC class II expression. Right plot, the summary of the data: mean fluorescence intensity (MFI) values were normalized against respective control groups, n = 3. Data are representative of three independent experiments. H, Schematic figure of the Pam3CSK4 administration experiments in vivo. I, Flow cytometry analysis of CD45loCD11b+ microglia that isolated from mice described in H; the MFI values of MHC class II were normalized against corresponding normal brain samples (N), pooled data from two separate experiments. Ctr, mice treated with PBS; 1st, 2nd, and 3rd, mice treated with Pam3CSK4 (5 μg) for 1, 2, and 3 times at indicated time points. The log-rank (Mantel–Cox) test was performed in A. One-way ANOVA was performed in G and I. Two-way ANOVA was performed in F. Unpaired Student t test was performed in C. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Figure 2.

TLR2 activation downregulates MHC class II in microglia. A, The Kaplan–Meier survival curves represent the cumulative survival of WT and TLR2−/− mice after GL261 inoculation, n = 8. B, H&E staining for sections of tumor-bearing WT and TLR2−/− mice (day 20). Scale bar, 500 μm. Right plot, tumor area was calculated, n = 5–15. C, Flow cytometry analysis of the glioma model (day 20) derived CD45loCD11b+ microglia for antigen-presenting function-related markers. Right plot, summary of the data, n = 8–10. Data are representative of three independent experiments. D, Representative staining for Iba1 (green), MHC class II (red), and DAPI (blue) in tumor-bearing brains on day 20 after GL261 inoculation. Dashed line, tumor boundary; IM, invasive margin; T, tumor; N, normal tissue. Bottom plots, higher magnification of the regions indicated in the dashed boxes. E, Representative staining for Iba1 (green), MHC class II (red), and DAPI (blue) in primary microglia. Control, microglia treated with IFNγ. GCM, microglia treated with GCM and followed with IFNγ. F, Flow cytometry analysis of primary microglia for MHC class II expression. Right plot, summary of the data, n = 3. G, Flow cytometry analysis of primary microglia (treated with the indicated dose of Pam3CSK4 and followed with IFNγ) for MHC class II expression. Right plot, the summary of the data: mean fluorescence intensity (MFI) values were normalized against respective control groups, n = 3. Data are representative of three independent experiments. H, Schematic figure of the Pam3CSK4 administration experiments in vivo. I, Flow cytometry analysis of CD45loCD11b+ microglia that isolated from mice described in H; the MFI values of MHC class II were normalized against corresponding normal brain samples (N), pooled data from two separate experiments. Ctr, mice treated with PBS; 1st, 2nd, and 3rd, mice treated with Pam3CSK4 (5 μg) for 1, 2, and 3 times at indicated time points. The log-rank (Mantel–Cox) test was performed in A. One-way ANOVA was performed in G and I. Two-way ANOVA was performed in F. Unpaired Student t test was performed in C. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Close modal

To clarify that MHC class II downregulation was caused by activation of TLR2 on microglia rather than on other cells, we set up a primary adult microglia culture system. Murine adult microglia were isolated with the purity checked by flow cytometry (Supplementary Fig. S4A) and cultured in the presence of M-CSF and TGFβ1. TGFβ1 is essential for maintenance and survival of microglia (23). The reactivity of the primary microglia was tested (Supplementary Fig. S4B). The expression of microglia-specific genes (23) was higher in adult microglia cultured with TGFβ1 (Supplementary Fig. S4C). GCM was used to stimulate the primary cultured microglia. MHC class II expression could be induced in normal microglia by IFNγ, but less so in GCM-treated microglia (Fig. 2E). Primary microglia appeared more amoeboid in shape, consistent with the previous observation in tumor sites. These results indicate that tumor-derived factors could impair microglial MHC class II expression.

When WT and Tlr2−/− microglia were treated with GCM, and we observed no morphologic change in Tlr2−/− microglia, we evaluated the MHC class II expression of GCM-treated Tlr2−/− microglia by flow cytometry and found that the MHC class II level remained unchanged (Fig. 2F), indicating that tumor-derived endogenous TLR2 ligands triggered microglial MHC class II downregulation. We then applied TLR2 agonist Pam3CSK4 to mimic the GCM-induced effect. The MHC class II level of Pam3CSK4-treated cells showed a dose-dependent decrease compared with control cells (Fig. 2G). We confirmed that TLR2-mediated downregulation of MHC class II also occurs in bone marrow–derived macrophage (BMDM) (Supplementary Fig. S5A and S5B) and CD45+CD11b+ peripheral myeloid cells (Supplementary Fig. S5C). We tested the TLR2-induced effect in vivo by ICV injection of Pam3CSK4 in the glioma model. We buried the cannula in the lateral ventricle ipsilateral to the tumor inoculation site. Pam3CSK4 or PBS was given via cannula on day 6 after tumor inoculation and given every 6 days for a total of 3 times. All animals were sacrificed on day 20 for further analysis (Fig. 2H). We found that MHC class II expression in microglia was lower in the Pam3CSK4-treated group in a time-dependent manner (Fig. 2I). These data suggest that TLR2 induced downregulation of MHC class II in microglia.

Downregulation of MHC class II in microglia impedes their antigen-presenting function

To elucidate whether the TLR2-induced downregulation of MHC class II affected the antigen-presenting function of microglia, we assayed OT-II T-cell proliferation (Fig. 3A). After coculture, microglia in both the Pam3CSK4- and GCM-treated groups showed impaired MHC class II expression (Fig. 3B). T-cell proliferation was evaluated by the percentage of divided cells. T cells in both Pam3CSK4- and GCM-treated groups showed less proliferation than the OVA group (Fig. 3C). When TLR2−/− microglia were tested, T cells in the GCM-treated group showed consistent proliferation as in the OVA group (Supplementary Fig. S6A). With CD69 and PD-1 as T-cell activation markers, T cells in both Pam3CSK4- and GCM-treated groups showed diminished activation (Fig. 3C). These results demonstrate that TLR2-induced microglial MHC class II downregulation could diminish the antigen-presenting function of microglia.

Figure 3.

TLR2-induced downregulation of MHC class II suppresses the antigen-presenting function of microglia. A, Timescales of the microglia-induced OT II CD4+ T-cell proliferation assay. B, Flow cytometry analysis of the cocultured microglia for MHC class II level. Histogram numbers indicated the mean fluorescence intensity (MFI) values of MHC class II for each group, representative data of two experiments. C, Flow cytometry analysis of cocultured OT II CD4+ T cells for proliferation, CD69, and PD-1 expression. Right plots, the summary of the data, n = 3, representative data of three independent experiments. D, Representative staining for CD4 (green) and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation; right panel, CD4+ cell counts per field were calculated. Data were collected from 16 to 20 random fields per mouse, n = 3. Scale bar, 50 μm. E, Representative staining for CD4 (green), Iba1 (red), MHC class II (white), and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation. Scale bar, 100 μm. F, Flow cytometry analysis of tumor-infiltrated CD4+ T cells for IFNγ, TNFα, Foxp3, and PD-1. Right plots, the summary of the data, n = 4–5, representative data of two independent experiments. One-way ANOVA was performed in C. Unpaired Student t test was performed in D and F. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Figure 3.

TLR2-induced downregulation of MHC class II suppresses the antigen-presenting function of microglia. A, Timescales of the microglia-induced OT II CD4+ T-cell proliferation assay. B, Flow cytometry analysis of the cocultured microglia for MHC class II level. Histogram numbers indicated the mean fluorescence intensity (MFI) values of MHC class II for each group, representative data of two experiments. C, Flow cytometry analysis of cocultured OT II CD4+ T cells for proliferation, CD69, and PD-1 expression. Right plots, the summary of the data, n = 3, representative data of three independent experiments. D, Representative staining for CD4 (green) and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation; right panel, CD4+ cell counts per field were calculated. Data were collected from 16 to 20 random fields per mouse, n = 3. Scale bar, 50 μm. E, Representative staining for CD4 (green), Iba1 (red), MHC class II (white), and DAPI (blue) in the tumor-bearing brain on day 20 after GL261 inoculation. Scale bar, 100 μm. F, Flow cytometry analysis of tumor-infiltrated CD4+ T cells for IFNγ, TNFα, Foxp3, and PD-1. Right plots, the summary of the data, n = 4–5, representative data of two independent experiments. One-way ANOVA was performed in C. Unpaired Student t test was performed in D and F. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

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We then analyzed the condition of CD4+ T cells in vivo. CD4+ T-cell density in the tumor tissue of Tlr2−/− mice was higher than in the tumor tissue of WT mice (Fig. 3D). The MHC class II+ microglia accumulated at the invasive margin and colocalized with CD4+ T cells. CD4+ T cells appeared morphologically activated in Tlr2−/− tumor brain (Fig. 3E). We analyzed the phenotype of CD4+ T cells isolated from tumor-bearing brain. Based on expression capacity of IFNγ, the function of CD4+ T cells was more Th1-biased in Tlr2−/− mice than in WT mice. However, TNFα expression and Foxp3+ regulatory T-cell numbers were comparable between WT and Tlr2−/− mice (Fig. 3F). We found more PD-1, an activated T-cell marker, in Tlr2−/− mice (Fig. 3F). We found that expression of T-cell activation markers CD25 and CD69 was higher in the CD4+ T cells from TLR2−/− mice, although exhaustion marker Lag-3 was higher as well (Supplementary Fig. S6B). All these results suggest that the CD4+ T cells have a relatively better response in the tumor site in Tlr2−/− mice compared with WT mice.

MHC class II transactivator, Ciita, is inhibited in TLR2-activated microglia

To figure out the mechanisms of the TLR2-induced downregulation of MHC class II in microglia, we conducted RNA-seq analysis to generate the transcriptomic profile of TLR2-activated microglia. The microglia were treated with or without Pam3CSK4 for 24 hours, followed by stimulation with IFNγ for 24 hours for MHC class II induction. As expected, several inflammatory cytokines and chemokines, including Ccl3, Ccl5, and Il1b, were upregulated in Pam3CSK4-treated microglia, so was Nos2. P2ry12, the signature gene of microglia, was downregulated in the Pam3CSK4-treated group (Fig. 4A). P2ry12 expression is robust in the “resting” status but dropped after microglial activation (24). Some MHC class II–related genes were downregulated in Pam3CSK4-treated microglia, including genes encoding mouse MHC class II molecules (H2-A and H2-E), invariant chain (Ii), and nonclassical MHC class II molecules (H2-M; Fig. 4A). Expression of Ciita was decreased in the Pam3CSK4-treated microglia (Fig. 4A and B). CIITA is the master coactivator for regulation of MHC class II transcription (25). Inhibition of Ciita in TLR2-activated microglia shuts down these MHC class II–related genes. Pathway analysis indicated that the TLR, TNF, and NF-κB signaling pathways were activated (Fig. 4C), as expected (16). Inhibition of antigen processing– and presentation–related pathways was also evident (Fig. 4C). We applied Gene Ontology analysis for all categories of genes that differed in expression between the two groups and listed top related pathways in Fig. 4D. The most enriched pathways were related to antigen presentation. Most of the genes in these pathways were downregulated. Other enriched pathways were related to inflammation, cytokines, and immune cell chemotaxis. These results indicate that TLR2 activation leads to Ciita shutdown and inhibition of MHC class II–related genes.

Figure 4.

RNA-seq analysis reveals the inhibition of MHC class II–related genes in TLR2-activated microglia. Primary microglia treated with or without Pam3CSK4 and followed with IFNγ. Pam3, microglia with Pam3CSK4 treatment; Control, microglia without Pam3CSK4 treatment. A, Scatterplot of FPKM values for all genes in both groups. The differentially expressed genes were selected using the following filter criteria: FDR ≤ 0.05 and fold change ≥ 2. B, Heat map of the most upregulated and downregulated genes (based on P value) in Pam3 group compared with Control group. Genes in red, MHC class II–related genes. C and D, KEGG pathway (C) and Gene Ontology enrichment analysis (D) were performed using the differentially expressed genes. The details of the enriched Gene Ontology terms were listed in Supplementary Table S3.

Figure 4.

RNA-seq analysis reveals the inhibition of MHC class II–related genes in TLR2-activated microglia. Primary microglia treated with or without Pam3CSK4 and followed with IFNγ. Pam3, microglia with Pam3CSK4 treatment; Control, microglia without Pam3CSK4 treatment. A, Scatterplot of FPKM values for all genes in both groups. The differentially expressed genes were selected using the following filter criteria: FDR ≤ 0.05 and fold change ≥ 2. B, Heat map of the most upregulated and downregulated genes (based on P value) in Pam3 group compared with Control group. Genes in red, MHC class II–related genes. C and D, KEGG pathway (C) and Gene Ontology enrichment analysis (D) were performed using the differentially expressed genes. The details of the enriched Gene Ontology terms were listed in Supplementary Table S3.

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TLR2-induced activation of ERK1/2 signaling pathway inhibits Ciita in microglia

To clarify the pathway that mediates TLR2-induced downregulation of MHC class II in microglia, we confirmed that Pam3CSK4-induced downregulation of MHC class II was associated with the decrease in MHC class II mRNA (Fig. 5A). Ciita mRNA expression decreased in the Pam3CSK4-treated group (Fig. 5B), suggesting that failure of the transcription factor Ciita causes downregulation of MHC class II, consistent with data from RNA-seq analysis. Then, we analyzed the effects of TLRs’ agonists in the BV2 microglia cell line. Most TLRs’ agonists caused reduced Ciita expression in microglia, although TLR3 ligands Poly (I: C) did not, suggesting that the effect is controlled via the Myd88-dependent pathway, not the TRIF-dependent pathway (Fig. 5C). Next, we stimulated microglia with IFNγ for 24 hours and then added Pam3CSK4 at time points from 30 minutes to 24 hours. Ciita mRNA began to decrease 2 hours after Pam3CSK4 stimulation and continued decreasing over 24 hours (Fig. 5D). These results indicate that the effect is related to signaling early in the process. We thus focused on the PI3K and MAPK signaling pathways. We used inhibitors to block individual signaling pathways (Fig. 5E and F). In the Erk1/2 inhibitor–treated group, Erk1/2 phosphorylation was decreased, and expression of Ciita was restored. We verified this mechanism in primary microglia by flow cytometric analysis. Results showed that Erk1/2 inhibitor U0126 restored microglial MHC class II amounts in Pam3CSK4-treated microglia (Fig. 5G and H). These data suggest that TLR2-induced downregulation of MHC class II relates to the Erk1/2 signaling pathway.

Figure 5.

TLR2-induced MAPK Erk1/2 signaling pathway inhibits Ciita expression, leading to the downregulation of MHC class II in microglia. qPCR analysis of primary microglia for MHC class II (H2-Ab1) mRNA (A) and Ciita mRNA (B), n = 3. The data presented represent one of three individual experiments. C, BV2 microglia were treated with GCM or different TLRs’ ligands and IFNγ. Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. D, BV2 microglia were treated with IFNγ and followed with Pam3CSK4 for indicated time points, Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. E and F, BV2 microglia were pretreated with the PI3K (E) or MAPK (F) inhibitors and treated with Pam3CSK4,for 2 hours followed with IFNγ for 18 hours. Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. Bottom plot in E, phosphorylated Akt of the corresponding samples was analyzed by Western blotting. Bottom plot in F, phosphorylated p65, phosphorylated ERK1/2, phosphorylated p38, and phosphorylated JNK of the corresponding samples were analyzed by Western blotting. G and H, Primary microglia were pretreated with U0126 and treated with Pam3CSK4 for 2 hours, followed by IFNγ for 18 hours, and MHC class II was quantified by flow cytometry (G). Summary of the MHC class II quantification (H), n = 3. Bottom plot, phosphorylated ERK1/2, total ERK1/2, phosphorylated p65, and phosphorylated Akt of the corresponding samples were analyzed by Western blotting. β-Actin was used as an internal control. All experiments were repeated 3 times. One-way ANOVA was performed in C, D, E, F, and H. Unpaired Student t test was performed in A and B. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Figure 5.

TLR2-induced MAPK Erk1/2 signaling pathway inhibits Ciita expression, leading to the downregulation of MHC class II in microglia. qPCR analysis of primary microglia for MHC class II (H2-Ab1) mRNA (A) and Ciita mRNA (B), n = 3. The data presented represent one of three individual experiments. C, BV2 microglia were treated with GCM or different TLRs’ ligands and IFNγ. Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. D, BV2 microglia were treated with IFNγ and followed with Pam3CSK4 for indicated time points, Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. E and F, BV2 microglia were pretreated with the PI3K (E) or MAPK (F) inhibitors and treated with Pam3CSK4,for 2 hours followed with IFNγ for 18 hours. Ciita mRNA was measured by qPCR, and expression was normalized to β-actin and subsequently to control group, n = 3. Bottom plot in E, phosphorylated Akt of the corresponding samples was analyzed by Western blotting. Bottom plot in F, phosphorylated p65, phosphorylated ERK1/2, phosphorylated p38, and phosphorylated JNK of the corresponding samples were analyzed by Western blotting. G and H, Primary microglia were pretreated with U0126 and treated with Pam3CSK4 for 2 hours, followed by IFNγ for 18 hours, and MHC class II was quantified by flow cytometry (G). Summary of the MHC class II quantification (H), n = 3. Bottom plot, phosphorylated ERK1/2, total ERK1/2, phosphorylated p65, and phosphorylated Akt of the corresponding samples were analyzed by Western blotting. β-Actin was used as an internal control. All experiments were repeated 3 times. One-way ANOVA was performed in C, D, E, F, and H. Unpaired Student t test was performed in A and B. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

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H3K9ac deacetylation contributes to the TLR2-induced Ciita inhibition

The Ciita gene is transcriptionally regulated by three distinct promoters, each transcribing a different first exon (ref. 26; Fig. 6A). Transcription of Ciita from promoter I (pI) is restricted to cells of the myeloid lineage including conventional dendritic cells and macrophages (27), whereas promoter III (pIII) is active primarily in cells of lymphoid lineage, including B and T cells (28, 29), and promoter IV (pIV) is responsive to IFN in nonhematopoietic cells (30). However, it remains unclear which promoter is used in adult microglia. To address this issue, we analyzed amounts of Ciita mRNA isoforms derived from different promoters (Fig. 6A). We found that adult microglia use both pI and pIV for Ciita transcription, and Pam3CSK4 stimulation could impair Ciita mRNA expression derived from both promoters (Fig. 6B).

Figure 6.

Histone acetylation at Ciita promoters was reduced in TLR2-activated microglia. A, The modular structure of the regulatory region of Ciita. Ciita isoforms 1, 2, and 3 are shown as typical mRNA isoforms that derive from promoter pI, pIII, and pIV, respectively. For gene structure visualization, SnapGene software was used. B, TLR2 activation impairs the expression of Ciita mRNA derived from promoters pI and pIV. Primary microglia treated with or without Pam3CSK4 and followed by IFNγ, qPCR analysis of the microglia for the isoforms of Ciita mRNA. Expression was normalized to β-actin, n = 3. C, Primary microglia were pretreated with epigenetic inhibitors, and then treated with or without Pam3CSK, followed with IFNγ. qPCR analysis of the microglia for MHC class II (H2-Ab1), Total Ciita, pI Ciita, and pIV Ciita mRNA. Expression was normalized to β-actin, n = 3. D, ChIP qPCR was applied to quantify H3K9ac and H3K4me2 in the promoter region of Ciita. The fold enrichment method was used for data normalization. Shown is one of two individual experiments. One-way ANOVA was performed in C. Unpaired Student t test was performed in B and D. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

Figure 6.

Histone acetylation at Ciita promoters was reduced in TLR2-activated microglia. A, The modular structure of the regulatory region of Ciita. Ciita isoforms 1, 2, and 3 are shown as typical mRNA isoforms that derive from promoter pI, pIII, and pIV, respectively. For gene structure visualization, SnapGene software was used. B, TLR2 activation impairs the expression of Ciita mRNA derived from promoters pI and pIV. Primary microglia treated with or without Pam3CSK4 and followed by IFNγ, qPCR analysis of the microglia for the isoforms of Ciita mRNA. Expression was normalized to β-actin, n = 3. C, Primary microglia were pretreated with epigenetic inhibitors, and then treated with or without Pam3CSK, followed with IFNγ. qPCR analysis of the microglia for MHC class II (H2-Ab1), Total Ciita, pI Ciita, and pIV Ciita mRNA. Expression was normalized to β-actin, n = 3. D, ChIP qPCR was applied to quantify H3K9ac and H3K4me2 in the promoter region of Ciita. The fold enrichment method was used for data normalization. Shown is one of two individual experiments. One-way ANOVA was performed in C. Unpaired Student t test was performed in B and D. *, P < 0.05 and **, P < 0.01. All values are shown as mean ± SEM.

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To understand if there was an epigenetic modulation controlling such Ciita inhibition, a DNMT inhibitor, 5-AZA, and two HDAC inhibitors, TSA and Nico, were applied. TSA selectively inhibits class I and II HDACs (31), whereas Nico inhibits class III HDACs (32). The results indicated that TSA could reverse the Pam3CSK4-induced Ciita inhibition in both promoters (Fig. 6C), indicating that class I or II HDACs participate in Pam3CSK4-induced histone deacetylation of CIITA promoters. Next, to assess H3 acetylation at promoters, ChIP qPCR was performed. We found that H3K9ac at both pI and pIV promoters was decreased after Pam3CSK4 stimulation, but H3K4me2 remained unchanged (Fig. 6D). These data indicate that TLR2 activation in microglia could lead to the H3 deacetylation of the Ciita promoters, inhibiting Ciita expression.

Increase of endogenous HSPs is correlated with Ciita inhibition in patients with glioma

Several endogenous TLR ligands have been reported, such as HSPs and ECM components (33). According to proteomics data (34), glioma cell line GL261 secretes several TLR2 ligands, including HSPA4, HSPA5, HSPA9, HSPA13, HSPD1, and VCAN. We searched for TLR2 ligands in the TCGA database that were secreted by GL261. We used the GlioVis data portal to export the data describing gene expression from the TCGA GBM datasets (35). We found that many of these ligands were upregulated in GBM samples, including HSPA5, HSPD1, BGN, VCAN, and HMGB1 (Fig. 7A). According to the Human Protein Atlas database (36), TLR2 ligands are upregulated in human GBM samples compared with normal tissue (Fig. 7B), and some TLR2 ligands with unchanged mRNA expression, such as HSPA1A and HSPA9, are also overexpressed as proteins in GBM samples compared with normal tissues.

Figure 7.

HSPs are enriched in GBM samples and correlate with CIITA inhibition. A, Expression of endogenous TLR2 ligand mRNAs in human GBM samples, data from TCGA database. Normal, n = 4; GBM, n = 156. Underlined ligands are detectable in GL261 glioma supernatants. Unpaired Student t test was performed. **, P < 0.01. Values are shown as mean ± SEM. B, Immunohistochemistry staining for TLR2 ligands in human GBM samples; image credit, Human Protein Atlas. Scale bar, 200 μm. The information details (including URL links) of the GBM samples were listed in Supplementary Table S4. C, The RNA-seq profiles of laser-microdissected structures of GBM samples. Expression from genes encoding TLR2 ligands and MHC class II–related molecules is indicated as heat maps. The data were derived from the Ivy Glioblastoma Atlas Project; image credit, Allen Institute. D, Correlation analysis between CIITA and genes encoding endogenous TLR2 ligands was based on the pool of samples from immune cells’ infiltrated PCAN and MvP regions. The data were derived from the Ivy Glioblastoma Atlas Project. Pearson correlation coefficient was calculated to analyze the correlation between gene expression levels.

Figure 7.

HSPs are enriched in GBM samples and correlate with CIITA inhibition. A, Expression of endogenous TLR2 ligand mRNAs in human GBM samples, data from TCGA database. Normal, n = 4; GBM, n = 156. Underlined ligands are detectable in GL261 glioma supernatants. Unpaired Student t test was performed. **, P < 0.01. Values are shown as mean ± SEM. B, Immunohistochemistry staining for TLR2 ligands in human GBM samples; image credit, Human Protein Atlas. Scale bar, 200 μm. The information details (including URL links) of the GBM samples were listed in Supplementary Table S4. C, The RNA-seq profiles of laser-microdissected structures of GBM samples. Expression from genes encoding TLR2 ligands and MHC class II–related molecules is indicated as heat maps. The data were derived from the Ivy Glioblastoma Atlas Project; image credit, Allen Institute. D, Correlation analysis between CIITA and genes encoding endogenous TLR2 ligands was based on the pool of samples from immune cells’ infiltrated PCAN and MvP regions. The data were derived from the Ivy Glioblastoma Atlas Project. Pearson correlation coefficient was calculated to analyze the correlation between gene expression levels.

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We further analyzed expression of genes encoding TLR2 ligands and MHC class II–related molecules in the RNA-seq database of the Ivy Glioblastoma Atlas Project (Fig. 7C). The RNA-seq profiles contain GBM samples from different laser-microdissected structures, including leading edge, infiltrating tumor, cellular tumor, pseudopalisading cells around necrosis (PCAN), and microvascular proliferation (MvP), thus facilitating our research for gene expression patterns at a fine scale. Based on PTPRC (which encodes CD45) and CD4, the peripheral infiltrating CD4+ T cells accumulated mainly at the PCAN and MvP regions, indicating that these regions are where T cells recognize antigens. We checked for MHC class II–related genes, including genes encoding three human MHC class II (HLA-DP, HLA-DQ, and HLA-DR) and nonclassical MHC class II (HLA-DM and HLA-DO). These genes were barely expressed in PCAN region, indicating that the APC in this region had impaired MHC class II expression, which is similar to the phenomenon in the murine glioma model. The CD4 expression pattern was identical to that of the MHC class II–related genes, consistent with the colocalization of MHC class II+ microglia and CD4+ T cells in the murine glioma model.

Intracellular chaperone HSPs signal CNS injury by activating microglia through TLR- and MyD88-dependent pathways. HSPs are released from CNS cells undergoing necrotic or apoptotic cell death and bind to microglia (37). According to the Ivy GAP database, genes encoding HSPs are more highly expressed at the necrotic PCAN region than in the MvP region, which is better oxygenated and has fewer necrotic cells. We conducted a series of correlation analyses between CIITA and genes encoding endogenous TLR2 ligands based on the pool of samples from CD4+ T cells that infiltrated PCAN and MvP regions (Fig. 7D). We found that several kinds of HSPs were negatively correlated with CIITA expression. Meanwhile, no significant correlation was found between CIITA and ECM components (BGN and VCAN). The HLA-DPA1 and CD4 levels were positively correlated with CIITA expression as expected. These data suggest that the presence of HSPs correlates with CIITA inhibition in patients with GBM.

Although microglia infiltrate gliomas, their expression of MHC class II is compromised. In the current study, we showed that TLR2 suppresses GAM function. TLR2 is upregulated in GAM, and several kinds of endogenous TLR2 ligands are enriched in the glioma microenvironment. TLR2 activation triggers its downstream MAPK Erk1/2 signaling pathway and subsequently inhibits CIITA expression by epigenetic modulation, ultimately causing the downregulation of MHC class II in GAM. Furthermore, impaired MHC class II expression limits the activation and maintenance of CD4+ T cells at tumor sites, jeopardizing T-cell–dependent antitumor immunity.

In the brain parenchyma, only microglia express the immunoproteasome, a multicatalytic protease complex involved in the generation of antigenic peptides presented on MHC (38). Microglia are the predominant APC subset in the GL261 glioma model, whereas macrophages only contribute to the tumor mass at the late stage of growth and constitute merely 25% of the myeloid cells (39). GAM upregulate MHC class II expression somewhat compared with resting microglia, but this upregulation of MHC class II is impaired. MHC class II induction after injection of IFNγ is muted in tumor microglia (10). The upregulation of MHC class II by local APC facilitates tumor eradication by T cells during the early stages of tumor growth. We have found that the reduced amounts of microglial MHC class II could lessen the activation and proliferation of antigen-specific CD4+ T cells in vitro. IFNγ+CD4+ T cells could induce tumor eradication in GL261 murine glioma model (40). The TLR2-induced downregulation of MHC class II may reflect negative feedback regulation, which would prevent excessive T-cell–mediated immunity. With TLR2 ligands, the tumor cells have subverted this otherwise protective mechanism to ensure their own survival.

Various TLR2 ligands, including HSPs and ECM components, are enriched in human glioma tissues. It remains unclear whether a specific TLR2 ligand downregulates MHC class II in microglia and whether nonprotein TLR2 ligands, such as hyaluronic acid fragments and pyrroles (41, 42), can also downregulate MHC class II. The RNA-seq profiles of laser-microdissected structures revealed that necrotic cells might be a source of TLR2 ligands in gliomas. Necrotic cells induce expression of genes involved in inflammatory and tissue-repair responses in macrophages via TLR2 (43). In gliomas, such TLR2-induced tissue-repair responses may promote tumor angiogenesis and tumor growth. TLR2 is also associated with the invasive growth pattern of glioma and protumor phenotype reprogramming of DCs (44, 45). In the experimental autoimmune encephalomyelitis (EAE) model and in multiple sclerosis patients, TLR2 agonists function as inhibitors of neuroinflammation, and TLR tolerance induces the immune regulatory response to create an immunosuppressive microenvironment (46, 47). Our study uncovered the role of TLR2 and its endogenous ligands in downregulating microglial MHC class II expression and elucidated the mechanisms that underlie glioma escape from the attack of infiltrated immune cells.

Activation of TLRs’ signaling initiates the immune response and leads to the increase of MHC class II expression in myeloid cells like DCs (16). NF-κB activation induced by TLR signaling leads to assembly of the transcription complex regulating CIITA expression in DCs (48). However, during DC maturation, TLR signaling inhibits de novo biosynthesis of MHC class II by reduction of CIITA mRNA expression (49, 50). TLR signaling–induced CIITA shutdown limits the presentation of antigens associated with the maturation stimulus and prohibits the presentation of antigens experienced by the APCs (49). The mechanisms drive immune regulation as well as functional accuracy and efficiency. In gliomas, microglia transiently upregulate MHC class II in the early stage of tumor growth. However, long-term exposure to TLR2 ligands results in the shutdown of Ciita expression and downregulation of MHC class II in microglia. We believe that the CIITA shutdown by TLR2 ligands is a protective mechanism by which microglia shield brain tissue from the attack of immune system and initiate tissue-repairing process. Unfortunately, such mechanisms allow the glioma to escape the immune system.

In conclusion, our findings highlight the role of TLR2 in GAM. TLR2 ligands in the tumor microenvironment could facilitate tumor immune evasion. Similar mechanisms may also occur in macrophages or dendritic cells in various solid tumors. Because MHC class II are downregulated in GAM, antagonists for TLR2 or downstream signaling might modify the function of tumor-infiltrated APCs and improve antiglioma immunity. Our results might inform the development of more efficient immunotherapies for the treatment of glioma.

No potential conflicts of interest were disclosed.

Conception and design: J. Qian, Y. Chu

Development of methodology: J. Qian, F. Luo, J. Yang, J. Liu, Z. Lu, Y. Chu

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): J. Qian, F. Luo, J. Yang, R. Liu

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J. Qian

Writing, review, and/or revision of the manuscript: J. Qian, J. Liu, R. Liu, C. Wang, Y. Chu

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): F. Luo, J. Yang, R. Liu, Y. Deng, Y. Wang, Y. Chu

Study supervision: J.-Y. Wang, Y. Chu

Other (provided advice): J. Liu, L. Wang, Y. Deng, Z. Lu, Y. Wang, M. Lu

This work was supported by the National Science Foundation of China (31570892, 31770992, 81730045, and 91527305) and the Science and Technology Commission of Shanghai Municipality (15JC1401200).

We thank Dr. Rui He for providing the OT-II transgenic mice, Dr. Liangfu Zhou for providing GL261 murine glioma cell line, and Dr. Dapeng Yan for the helpful support and discussions. We thank Dr. Xiaoming Liu and Enyu Huang for critiquing the article.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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