HHLA2 is a novel prognostic predictor and potential therapeutic target in malignant glioma
Corrigendum in: /10.3892/or.2022.8473
- Authors:
- Published online on: October 1, 2019 https://doi.org/10.3892/or.2019.7343
- Pages: 2309-2322
-
Copyright: © Qi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Glioma is the most common malignant tumor type of the central nervous system and the 5-year overall survival (OS) is <10%. According to the biological behavior and malignancy of the tumor, glioma may be divided into four grades from World Health Organization (WHO) grade I to IV. Low-grade glioma (LGG) includes WHO grade-I and -II tumors, while the other two grades III and IV are classified as high-grade glioma (HGG). Of note, glioblastoma multiforme (GBM), the most malignant glioma type with WHO grade IV, accounts for ~50% of glioma cases, and has a median survival time of 14.2 months and a 5-year survival rate of <5% (1). In the past decades, despite improvements in surgical, radio- and chemotherapies, the treatment of glioma has remained a tremendous challenge (2,3). However, with the development of novel emerging immunotherapies, which aim to reinvigorate antitumor immune responses, outcomes have been significantly improved in a variety of advanced hematologic and solid malignancies (4–8). This points out a new direction in terms of treatment strategies for glioma. Thus, novel therapeutic approaches targeting the interaction between the tumor microenvironment and immune response are urgently required in this field.
Various preclinical studies have demonstrated the success of immunotherapy-based approaches in animal models and numerous phase I and II clinical trials suggested immunotherapy to be safe and, in certain cases, improve progression-free survival (PFS) and OS (9–13). Preclinical studies using murine models with orthotopic-transplanted gliomas have provided a marked benefit of checkpoint inhibitors used individually or in combination with other immunotherapeutic strategies (42). Numerous glioma-associated antigens, including interleukin (IL)-13 receptor subunit α2, human epidermal growth factor receptor 2, EPH receptor A2, gp100 and AIM-2 are being targeted in glioma (14–16). In addition, tumor-specific neoantigens, including epidermal growth factor receptor variant III, are being used to target tumor cells (16,17). The successful preclinical studies have prompted a number of clinical studies using dendritic cell vaccines (11). Furthermore, considerable progress has been achieved in immunotherapy with antibodies, adoptive T-cell transfer and chimeric antigen receptor T cells in their respective fields (18–20). Among the aforementioned therapeutic strategies, immune checkpoint blockade appears to be an exciting avenue that warrants further development based on the preclinical studies.
Immune checkpoint proteins are surface molecules on certain immune cell populations that activate or inhibit immune function when engaged to their ligands. Numerous studies have indicated an interaction between the expression of the co-inhibitory protein and tumor immune escape (21). Therefore, immunotherapy based on blocking the interaction between an immune checkpoint protein and its ligands has the potential to restore functional immune cells and inhibit tumor progression.
The B7 family, an important class of the immune checkpoint superfamily, has exhibited great potential for regulating T-cell function and participating in the immune response. The growing B7 family is now comprised of 10 members, including CD80 (B7-1), CD86 (B7-2), programmed cell death 1 ligand 1 (PD-L1 or B7-H1), PD-L2 (B7-DC), inducible T cell co-stimulator ligand (B7-H2), CD276 (B7-H3), B7-H4, V-set immunoregulatory receptor (B7-H5), B7-H6 and human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2 or B7-H7) (22). Among these ligands, PD-L1 and PD-L2 represent two ligands for the PD-1 receptor. Recent studies have indicated that upregulation of PD-1 and PD-L1 in tumor tissue was associated with poor prognosis in certain cancer types, demonstrating that PD-1 and PD-L1 may inhibit the function of T-cells and promote the immune escape of tumor cells (23–25). The clinical application of a specific antibody which inhibits the PD-1/PD-L1 pathway has achieved satisfactory curative effects (26,27). A recent study reported that upregulation of PD-1 in glioma predicted a poor prognosis (28), indicating the potential value of this immune checkpoint protein as a therapeutic target in glioma.
HHLA2 is the most recently discovered member of the B7 family. Transmembrane and immunoglobulin domain-containing 2 (TMIGD2, also known as IGPR-1 or CD28H) is the only known receptor identified for HHLA2 (29). While its exact function remains elusive, it has been reported to have co-stimulatory as well as co-inhibitory properties (30,31). Zhu et al (31) indicated that the interaction between CD28H and B7-H7 on antigen-presenting cells (APCs) co-stimulated human T-cell proliferation and cytokine production via a pathway involving AKT phosphorylation. By contrast, Zhao et al (30) proposed the opposite function for B7H7: In the presence of the T-cell antigen receptor (TCR) signaling pathway, B7-H7 inhibits the proliferation of CD4+ and CD8+ T cells. In addition, B7-H7 significantly reduces cytokine production by T cells, including interferon-γ, tumor necrosis factor-α, IL-5, IL-10, IL-13, IL-17α and IL-22. Thus, the ligation of B7-H7 to T cells suppresses T-cell responses. As with B7-H3, a T-cell co-inhibitory role and a co-stimulatory role have been reported for this ligand (22). One explanation is that HHLA2 has two ligands with opposite functions-TMIGD has a co-stimulatory role, while the other remains elusive. HHLA2 on APCs or tumor cells may interact with unknown ligands and exert a co-inhibitory function in the microenvironment of certain cancers. Furthermore, it may promote angiogenesis within the tumor microenvironment via its interaction with TMIGD2 expressed in the endothelium.
The expression of HHLA2 has been reported in a large proportion of tumor specimens, including breast, lung, thyroid, melanoma, pancreas, ovary, liver, bladder, colon, prostate, kidney and esophageal, but not in endometrial, gallbladder, laryngeal, stomach and uterine cancer or in lymphoma (29). To date, no systematic study on the expression status and biological function of HHLA2 in patients with glioma has been performed, to the best of our knowledge. The present study aimed to examine the expression of HHLA2 in normal brain specimens and tumor specimens obtained from patients with glioma. Furthermore, the potential mechanistic role of HHLA2 in glioma and the association between HHLA2 expression and tumor behavior were investigated, and its clinical utility as a prognostic predictor was assessed.
Materials and methods
Sample and data collection
RNA sequencing data from human glioma samples were obtained from The Cancer Genome Atlas (TCGA) database (http://www.tcga.org/) and downloaded from the GlioVis database (http://gliovis.bioinfo.cnio.es/). The dataset contained 515 LGG samples, 152 GBM samples and 2 undefined samples (Table I). The characteristics of the patients are listed in Table I. Furthermore, data regarding IDH mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) mutation for the TCGA cohort were obtained by whole-exon sequencing or pyrosequencing.
Immunohistochemistry (IHC)
The IHC labelling images of normal brain tissue and tumor tissue were obtained from The Human Protein Atlas (http://www.proteinatlas.org/). The Human Protein Atlas used anti-HHLA2 (cat. no. HPA055478; Sigma-Aldrich; Merck KGaA) as a primary antibody and the tumor tissues were obtained from TCGA database.
Model of tumor-infiltrating immune cells (TIICs)
xCell (http://xcell.ucsf.edu/) was used to obtain the expression level of 64 types of immune cells in the tumor microenvironment of patients with glioma. Then 20 types of immune cells with significant difference in infiltration ratio were screened out using the R package limma (http://bioconductor.riken.jp/packages/3.0/bioc/html/limma.html).
Functional enrichment analysis
Gene ontology (GO) and pathway enrichment analysis [Kyoto Encyclopedia of Genes and Genomes (KEGG)] were performed to analyze the genes associated with HHLA2 by using Metascape (http://metascape.org). Enriched ontological terms and pathways with P<0.05 were selected and presented in a heatmap using the R package ‘ComplexHeatmap’ (http://www.bioconductor.org/packages/stats/bioc/ComplexHeatmap/).
Cox proportional hazards regression model
The prognostic value of each factor was first assessed by univariate Cox proportional hazards regression. Subsequently, statistically significant genes were used to construct the multivariate Cox regression model. Glioma samples were divided into high-expression and low-expression groups based on the median level of HHLA2 expression. Kaplan-Meier survival curves were generated to assess the prognostic value of the model using the R package survival (https://CRAN.R-project.org/package=survival). A receiver operating characteristic (ROC) curve was generated to assess the accuracy of the model with the R package ‘survivalROC’ (https://CRAN.R-project.org/package=survivalROC).
Statistical analysis
Statistical analysis was mainly performed with R (https://www.r-project.org/) with several publicly available packages. P<0.05 was considered to indicate statistical significance. (*P<0.05, **P<0.01, ***P<0.001 and ****P<0.0001, respectively, as indicated in the figures and legends).
Results
HHLA2 expression is absent in GBM
To evaluate the expression level of HHLA2 in glioma, the IHC staining data of glioma and normal brain tissue were obtained from the Human Protein Atlas dataset and analyzed individually. Overall, positive staining for HHLA2 was observed in endothelial cells and neuropils of normal brain tissue (Fig. 1A and B), while staining was negative in glial cells and neurons. Furthermore, no tumoral HHLA2 expression was detected in HGG (Fig. 1C and D). Of note, only a small percentage of LGG samples were positive for HHLA2 and IHC labeling was observed in tumor cell nuclei rather than endothelial cells, while other samples with LGG were negative for HHLA2 (Fig. 1E and F). This result indicated that with the increasing degree of tumor malignancy, HHLA2 expression in glioma was gradually reduced until it was absent.
Downregulated HHLA2 predicts poor prognosis in glioma
To explore the prognostic role of HHLA2 in glioma, the association between HHLA2 and several prognostic factors was analyzed. The results indicated that the mRNA expression levels of HHLA2 were significantly decreased with the increase in the grade of glioma and that the expression level was lowest in GBM (P<0.0001; Fig. 2A), indicating a strong correlation between HHLA2 expression and malignancy of glioma. IDH-mutant and 1p/19q co-deletion types were associated with a better outcome in glioma. When taking into account the IDH mutation status, it was indicated that HHLA2 expression was significantly higher in the IDH mutant group than in the IDH wild-type group (P<0.0001; Fig. 2B). Furthermore, compared with the 1p/19q no-deletion group, the 1p/19q co-deletion group had a higher expression of HHLA2 (P<0.05; Fig. 2C). TERT promoter mutations are usually considered to be associated with poor outcome (32), and the present results revealed that in the TERT wild-type group, the expression of HHLA2 was significantly increased (P<0.05; Fig. 2D). These results indicated HHLA2 expression was more prevalent in glioma with lower malignancy.
To further elucidate the association between HHLA2 expression and molecular subtypes, patients were divided into four groups according to subtypes defined by TCGA. Upregulated HHLA2 expression was observed in the neural (NE) subtype rather than in proneural (PN), classical (CL), and mesenchymal (ME) subtypes (P<0.0001; Fig. 3A). In addition, ROC curves were used to evaluate the specificity and sensitivity of our previous findings, indicating that the expression status of HHLA2 may serve as a good predictor for the neural subtype of gliomas [area under curve (AUC)=0.707; Fig. 3B].
Model of tumor-infiltrating immune cells (TIICs) and tumor-associated macrophages (TAMs) in glioma
To date, tumor immunotherapy has yielded significantly improved outcomes in a variety of advanced hematologic and solid malignancies, including glioma. Hence, to further understand the function of immune cells in the tumor microenvironment, the expression model of TIICs in patients with glioma was explored using xCell (http://xcell.ucsf.edu/) and several immune cells with significant difference in infiltration ratio were screened out (Table II). It was revealed that macrophages were markedly increased in GBM (Fig. 4A). TAMs, developed from monocytes, have been confirmed to be the most important type of immune cell in the stroma of tumors, accounting for 50% of the total number of immune cells, and to have an important role in neoplasia, metastasis, immune escape and tumor angiogenesis (33,34). Previous studies have also indicated that HHLA2 is constitutively expressed on human monocytes and takes part in angiogenesis (21). In the present study, it was observed that TAMs were significantly higher in the HHLA2 low-expression group (Fig. 4B) and predicted a worse prognosis (Fig. 4C). The aforementioned results indicated that HHLA2 may have an important role in the tumor immune microenvironment, tumor angiogenesis and the process of monocytes developing into TAMs. Thus, the association between HHLA2 and TAMs may provide a novel therapeutic method.
Correlation of HHLA2 and associated immune molecules
To further explore the function of HHLA2 in the immune microenvironment, the correlation between HHLA2 and several immune-associated molecules was analyzed at the mRNA level. Pearson correlation analysis indicated that HHLA2 was revealed to be negatively correlated with co-inhibitory immune checkpoint molecules, including programmed cell death 1 (PD-1; r=−0.172), lymphocyte activating 3 (LAG3; r=−0.171), cytotoxic T-lymphocyte associated protein 4 (CTLA4; r=−0.045) and CD276 (r=−0.434; Fig. 5A). However, HHLA2 was positively correlated with CD160 (r=0.261), which is commonly known as a stimulatory molecule (21,29,30). In addition, common immune inhibitors, including IL-10 and transforming growth factor (TGF)-β, were significantly higher in the HHLA2 low-expression group (Fig. 5C and D). These results indicated that HHLA2 may co-stimulate the immune response and have a positive role in tumor immune microenvironment.
Mechanism of HHLA2 acting on TAMs
It has been reported that cytokines, including vascular endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF), have important roles in the formation of TAMs and tumor angiogenesis (33,34). To further assess the mechanisms by which HHLA2 acts on TAMs in malignant glioma, five common molecules associated with angiogenesis were selected and analyzed individually (35,36). In the TCGA dataset, it was observed that HHLA2 was significantly negatively correlated with molecules including VEGF (r=−0.400), δ-like canonical Notch ligand 4 (DDL4; r=−0.358), PDGFA (r=−0.228), fibroblast growth factor receptor 1 (FGFR1; r=−0.164) and hepatocyte growth factor (HGF; r=−0.137; Fig. 5B). These results demonstrated that overexpression of HHLA2 may have a potential application in anti-tumor angiogenesis treatment and inhibiting the formation of TAMs by decreasing VEGF and PDGF.
Enrichment analysis of HHLA2-associated genes
To further explore the biological function of HHLA2 in glioma, an enrichment analysis with Metascape (http://metascape.org) was also performed. Genes significantly associated with HHLA2 expression were screened out by Pearson correlation analysis (Pearson |R|>0.4, P<0.05). Sequentially, 234 positively correlated genes and 211 negatively correlated genes were analyzed individually. It was revealed that positively correlated genes were involved in membrane trafficking, the glutamate receptor signaling pathway, regulation of neuronal death, response to toxic substances, regulation of protein ubiquitination and negative regulation of protein modification process (Fig. 6A), while negatively correlated genes were involved in processes that promote abnormal proliferation, including cell division, DNA replication, DNA repair, activation of E2F transcription factor 1 (E2F1) target genes at the G1/S checkpoint, the FOXM1 pathway and the ATR pathway (Fig. 6B). These results indicated that HHLA2 may have an important role in preventing normal neurons from damage, promoting the immune response and inhibiting neoplastic cell proliferation.
Patients with increased HHLA2 have a favorable survival prognosis
As HHLA2 expression was correlated with favorable prognostic factors, the prognostic value of HHLA2 expression in glioma as well as in GBM was then explored. Patients were divided into a high-expression group and a low-expression group based on the median HHLA2 level. Kaplan-Meier analysis demonstrated that higher HHLA2 expression was associated with a better outcome in patients with glioma of all grades (P<0.0001) as well as in GBM patients (P=0.021; Fig. 7A and B).
To further comprehend this model, a survival analysis was performed in four different subtypes of glioma defined by TCGA (Fig. 8A-D). The results demonstrated that no statistical significance was detected in the CL, NE and PN subtypes (Fig. 8A, C and D). However, higher HHLA2 expression was significantly associated with a better prognosis in the ME subtype (P=0.013; Fig. 8B). In addition, compared with the CL and ME subtypes, patients with the NE and PN subtypes had a significantly better outcome (P<0.0001; Fig. 8E).
In order to take into account key clinical and molecular factors, the Cox proportional hazards model was further applied. Univariate analysis indicated that age, IDH status, grade and HHLA2 expression were significantly associated with OS (P<0.0001; Table III). Furthermore, multivariate analysis indicated that age, IDH status and grade were independent prognostic factors (P<0.0001; Table III). However, HHLA2 expression was not an independent prognostic factor according to the multivariate analysis (P=0.257).
Discussion
The present study first focused on detecting the expression level of HHLA2 in normal brain tissue and tumor tissue obtained from patients with glioma by IHC labeling in the Human Protein Atlas dataset. By individually analyzing the normal brain tissue and tumor tissue, it was revealed that HHLA2 was absent in normal brain cells, including glial cells and neurons, but abundant in endothelial cells. Furthermore, it was observed that tumoral HHLA2 expression was absent in HGG, particularly in GBM. Of note, in contrast to the aforementioned, weak expression of HHLA2 in the nuclei of tumor cells was observed in part of the patients with LGG. This result suggested a downward trend in HHLA2 expression with the increase in the degree of malignancy of the tumor, which is opposite to previous results according to which HHLA2 expression was not detected in most organs, but was widely expressed in human cancers of the breast, lung, thyroid, skin, pancreas, ovary, liver, bladder, colon, prostate, kidney and esophagus (29). However, Yan et al (37) also reported that HHLA2 was widely overexpressed in early pancreatic precancerous lesions compared with pancreatic cancer, although it was not expressed in normal acinar, islet and ductal cells. Furthermore, overexpression of HHLA2 was indicated to be significantly associated with a better outcome. In addition, Zhu et al (31) indicated that HHLA2 engaged with CD28H to co-stimulate human T-cell proliferation and cytokine production via a pathway involving AKT phosphorylation. Based on the aforementioned results, it is reasonable to assume that higher HHLA2 expression in the early stage of glioma co-stimulated the immune response, while the expression decreased with the increasing malignancy of the tumor. It may be speculated that the expression model of HHLA2 in glioma is similar to that in the pancreas. However, most patients with glioma only present at the hospital after evident clinical symptoms have occurred. On this account, it is difficult to obtain tumor tissue in the early stage of glioma for IHC labeling and detection of HHLA2 expression. Furthermore, the present cancer model was validated in the TCGA dataset at the mRNA level at the same time.
Through analysis of TCGA, the largest cancer dataset, HHLA2 expression in malignant glioma was assessed at the transcriptional level. It was revealed that HHLA2 expression in GBM was significantly lower than that in glioma of other grades. According to a study by Eckel-Passow et al (32), a single TERT mutation predicted poor prognosis in glioma, while IDH mutation and 1p/19q co-deletion predicted a favorable outcome. In the present study, tumors with IDH mutation, 1p/19q co-deletion and wild-type TERT expressed higher levels of HHLA2, which was in line with our previous assumption. Furthermore, the expression levels of HHLA2 were detected in four different molecular subtypes of glioma defined by TCGA: PN, NE, CL and ME (38,39). Studies have indicated that PN and NE subtypes mostly occurred among LGG and were associated with a favorable prognosis, while the CL and ME subtypes were associated with a worse outcome (38,40). Of note, in the NE subtype, a significantly higher expression of HHLA2 compared with that in the other subtypes was observed, and the HHLA2 expression status was a good predictor for NE-subtype glioma. These results were in line with a previous study and indicated that higher expression of HHLA2 may predict a favorable outcome (37).
The present study further explored the expression model of TIICs in glioma, and it was indicated that macrophages were markedly increased in GBM vs. LGG. TAMs, developed from monocytes, have been confirmed to be the most important type of immune cell in the stroma of tumors, accounting for 50% of all immune cells, and to have an important role in neoplasia, metastasis, immune escape and tumoral angiogenesis (33,34). Immature monocytes migrate to tumor tissues and develop into TAMs through several cytokines, including VEGF, PDGF, colony-stimulating factor-1 (CSF-1) and C-C motif chemokine ligand 2. Notably, a previous study confirmed that HHLA2 was constitutively expressed on human monocytes (22). Thus, the association between TAMs and the expression levels of HHLA2 was explored in the present study. Lower TAMs were observed in the HHLA2 high-expression group and predicted a better outcome. To further explore the mechanism of HHLA2 acting on TAMs, several cytokines linked to angiogenesis and processes that develop monocytes into TAMs were selected for assessment, revealing that HHLA2 was negatively correlated with VEGF and PDGF. These results demonstrated that HHLA2 may inhibit TAM development and tumor angiogenesis via anti-VEGF and anti-PDGF processes. Kumar et al (41) reported that anti-CSF1 receptor, specifically targeting TAMs, plus anti-PD1 treatment significantly improved therapies, compared with anti-PD1 treatment alone. HHLA2, which may not only inhibit TAM development but also co-stimulate immune function, has promising potential in immune therapy for patients with glioma.
The function of HHLA2 in the immune microenvironment of glioma was then assessed. Taking its role as an immune stimulator into account, its correlation with several common immune inhibitors was explored. According to Kamran et al (42), TGF-β and IL-10 are central to maintaining the immunosuppressive microenvironment of glioma. Thus, TGF-β and IL-10 were selected as representative immune inhibitors and included in the analysis. It was observed that IL-10 was significantly increased in the low HHLA2 expression group, which was also the case for TGF-β. The function of HHLA2 was then explored in-depth via GO and KEGG enrichment analysis. The results demonstrated that HHLA2 was positively associated with response to toxic substances, regulation of neuronal death, the glutamate receptor signaling pathway and regulation of protein processes. This indicated that HHLA2 is able to prevent normal neurons from damage by negatively regulating the glutamate receptor signaling pathway. Furthermore, genes which were negatively correlated with HHLA2 were enriched in cell cycle, DNA replication, DNA repair, activation of E2F1 target genes at G1/S, the FOXM1 pathway and the ATR pathway. Activation of E2F1 target genes at G1/S, the FOXM1 pathway and the ATR pathway have been previously confirmed to promote neoplastic proliferation and tumor progression (43–45). These results indicated that HHLA2 inhibits tumor progression in the early stage of glioma by participating in early immune response and inhibiting neoplastic proliferation and angiogenesis. Hence, exploring the mechanism of HHLA2 acting on tumor cells may facilitate the discovery of a cure for this disease.
Notably, the present study was the first to report on the prognostic significance of HHLA2 in glioma. Kaplan-Meier survival analysis revealed that higher HHLA2 expression was consistently and significantly associated with better survival in glioma and GBM. Furthermore, a subsequent Kaplan-Meier survival curve analysis for each subtype yielded a similar result for the MΕ subtype of glioma. Lin et al (40) reported that the CL subtype had the worst outcome and accounted for a large part of GBM, while the NE and PN subtypes had a high proportion of LGG with a better outcome. These results may explain for the absence of a significant correlation between higher HHLA2 expression and better prognosis in the CL, NE and PN subtypes of glioma. Furthermore, the univariate analysis indicated that HHLA2 expression was a significant prognostic factor, while multivariate analysis demonstrated that the expression of HHLA2 was not an independent prognostic factor. Regarding the limitations of the present study, part of the patients included were lost to follow-up. Thus, the potential of HHLA2 to be an independent prognostic predictor for glioma should be further investigated in a larger and more comprehensive dataset.
However, in other types of human cancer, HHLA2 expression is not always a favourable predictor for patient survival. The prognostic significance of HHLA2 expression in osteosarcoma and colorectal carcinoma was identified to be correlated with metastasis and poor survival (46,47). Similarly, in triple-negative breast cancer, overexpression of HHLA2 was associated with lymph node positivity and advanced stage of the disease at the time of diagnosis, and also with an increased risk of recurrence (29). HHLA2 has also been reported to predict a favorable outcome in pancreatic ductal adenocarcinoma and gastric cancer (37,48). One explanation is that HHLA2 has two opposite ligands (22), including TMIGD that has a co-stimulatory role, while the other ligand remains elusive. TMIGD was indicated to be the major receptor in certain cancer types due to the tumoral immune microenvironment. It is not uncommon for members of the B7 family to have a dual function depending on the immune environment, tumor microenvironment or interaction with different receptors (22). HHLA2 belongs to group III of the B7 family, which also includes B7-H3 (also known as CD276) and B7×. As with HHLA2, the prognostic significance of B7-H3 and B7× also remains to be further delineated (49,50). Wang et al (51) reported that B7-H3 was positively associated with the Toll-like receptor signaling pathway and predicted poor survival for glioma patients. Zhou et al (52) also identified that overexpression of B7-H3 was associated with the malignancy grade of brainstem gliomas. However, results demonstrating B7-H3 as a co-stimulatory molecule associated with prolonged survival in pancreatic cancer (53) and gastric cancer (54) have also been reported. Therefore, the association between HHLA2 and other immune checkpoint molecules was then analyzed, revealing a negative correlation with checkpoint inhibitors, including PD-1, LAG3 and B7-H3. These results indicated that anti-PD-1 plus anti-B7-H3 treatment may be a strategy for glioma treatment, as it may lead to upregulation of HHLA2. Notably, the present study was the first to indicate that HHLA2 may act as a co-stimulatory molecule in glioma, in contrast to other B7 family members, which are commonly characterized as immune checkpoint inhibitors.
To date, observable progress has been made in the area of immunotherapy. However, blocking the PD-1/PD-L1 pathway was only effective in a small number of cases and most patients with glioma still suffered from disease. Thus, novel therapeutic strategies targeting other immune checkpoint molecules are in urgent demand. HHLA2, acting as an immune stimulator and inhibiting the formation of TAMs, may be a potential therapeutic target.
To the best of our knowledge, the present study was the first to explore the biological function and clinical roles of HHLA2 in glioma. The results indicated that HHLA2 acts as an immune stimulator and inhibits the formation of TAMs. Furthermore, HHLA2 expression was significantly correlated with a favorable outcome. The present study indicated its potential as a prognostic predictor and novel therapeutic target.
Acknowledgements
We gratefully acknowledge the TCGA project organizers as well as all study participants for making data and results available. In addition, we would like to thank GlioVis database.
Funding
The present study was supported by the National Natural Science Foundation of China (nos. 81372683 and 81572489) (to QC), and (no. 81502175) (to BL).
Availability of data and materials
The datasets used during the present study are available from the corresponding author upon reasonable request.
Authors contributions
YQ, GD and QC designed this study. YQ, GD, PX, HZ, FY, RG, HJ and BL performed the data collection and collation. All the authors were involved in the analysis and interpretation of data. YQ wrote the paper, with the help of the co-authors. GD, BL and QC reviewed and revised the manuscript. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
All authors declare that they have no competing interests.
References
|
Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, et al: Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med. 352:987–996. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Jiang T, Mao Y, Ma W, Mao Q, You Y, Yang X, Jiang C, Kang C, Li X, Chen L, et al: CGCG clinical practice guidelines for the management of adult diffuse gliomas. Cancer Lett. 375:263–273. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Yang P, Wang Y, Peng X, You G, Zhang W, Yan W, Bao Z, Wang Y, Qiu X and Jiang T: Management and survival rates in patients with glioma in China (2004–2010): A retrospective study from a singleinstitution. J Neurooncol. 113:259–266. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Robert C, Long GV, Brady B, Dutriaux C, Maio M, Mortier L, Hassel JC, Rutkowski P, McNeil C, Kalinka-Warzocha E, et al: Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med. 372:320–330. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Robert C, Schachter J, Long GV, Arance A, Grob JJ, Mortier L, Daud A, Carlino MS, McNeil C, Lotem M, et al: Pembrolizumab versus ipilimumab in advanced melanoma. N Engl J Med. 372:2521–2532. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Brahmer J, Reckamp KL, Baas P, Crinò L, Eberhardt WEE, Poddubskaya E, Antonia S, Pluzanski A, Vokes EE, Holgado E, et al: Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med. 373:123–135. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, Tykodi SS, Sosman JA, Procopio G, Plimack ER, et al: Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med. 373:1803–1813. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL, Lao CD, Schadendorf D, Dummer R, Smylie M, Rutkowski P, et al: Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med. 373:23–34. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Bloch O, Crane CA, Fuks Y, Kaur R, Aghi MK, Berger MS, Butowski NA, Chang SM, Clarke JL, McDermott MW, et al: Heat-shock protein peptide complex-96 vaccination for recurrent glioblastoma: A phase II, single-arm trial. Neuro Oncol. 16:274–279. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Mitchell DA, Batich KA, Gunn MD, Huang MN, Sanchez-Perez L, Nair SK, Congdon KL, Reap EA, Archer GE, Desjardins A, et al: Tetanus toxoid and CCL3 improve dendritic cell vaccines in mice and glioblastoma patients. Nature. 519:366–369. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Phuphanich S, Wheeler CJ, Rudnick JD, Mazer M, Wang H, Nuño MA, Richardson JE, Fan X, Ji J, Chu RM, et al: Phase I trial of a multi-epitope-pulsed dendritic cell vaccine for patients with newly diagnosed glioblastoma. Cancer Immunol Immunother. 62:125–135. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Schuster J, Lai RK, Recht LD, Reardon DA, Paleologos NA, Groves MD, Mrugala MM, Jensen R, Baehring JM, Sloan A, et al: A phase II, multicenter trial of rindopepimut (CDX-110) in newly diagnosed glioblastoma: the ACT III study. Neuro Oncol. 17:854–861. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Vik-Mo EO, Nyakas M, Mikkelsen BV, Moe MC, Due-Tønnesen P, Suso EM, Sæbøe-Larssen S, Sandberg C, Brinchmann JE, Helseth E, et al: Therapeutic vaccination against autologous cancer stem cells with mRNA-transfected dendritic cells in patients with glioblastoma. Cancer Immunol Immunother. 62:1499–1509. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Reardon DA, Wucherpfennig KW, Freeman G, Wu CJ, Chiocca EA, Wen PY, Curry WT Jr, Mitchell DA, Fecci PE, Sampson JH and Dranoff G: An update on vaccine therapy and other immunotherapeutic approaches for glioblastoma. Expert Rev Vaccines. 12:597–615. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Weller M, Roth P, Preusser M, Wick W, Reardon DA, Platten M and Sampson JH: Vaccine-based immunotherapeutic approaches to gliomas and beyond. Nat Rev Neurol. 13:363–374. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Srinivasan VM, Ferguson SD, Lee S, Weathers SP, Kerrigan BCP and Heimberger AB: Tumor vaccines for malignant gliomas. Neurotherapeutics. 14:345–357. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Heimberger AB, Suki D, Yang D, Shi W and Aldape K: The natural history of EGFR and EGFRvIII in glioblastoma patients. J Transl Med. 3:382005. View Article : Google Scholar : PubMed/NCBI | |
|
Chandramohan V, Mitchell DA, Johnson LA, Sampson JH and Bigner DD: Antibody, T-cell and dendritic cell immunotherapy for malignant brain tumors. Future Oncol. 9:977–990. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Schuessler A, Smith C, Beagley L, Boyle GM, Rehan S, Matthews K, Jones L, Crough T, Dasari V, Klein K, et al: Autologous T-cell therapy for cytomegalovirus as a consolidative treatment for recurrent glioblastoma. Cancer Res. 74:3466–3476. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Bonifant CL, Jackson HJ, Brentjens RJ and Curran KJ: Toxicity and management in CAR T-cell therapy. Mol Ther Oncolytics. 3:160112016. View Article : Google Scholar : PubMed/NCBI | |
|
Janakiram M, Chinai JM, Zhao A, Sparano JA and Zang X: HHLA2 and TMIGD2: New immunotherapeutic targets of the B7 and CD28 families. Oncoimmunology. 4:e10265342015. View Article : Google Scholar : PubMed/NCBI | |
|
Ni L and Dong C: New B7 family checkpoint in human cancers. Mol Cancer Ther. 16:1203–1211. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Zou W, Wolchok JD and Chen L: PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Sci Transl Med. 8:328rv42016. View Article : Google Scholar : PubMed/NCBI | |
|
Ohaegbulam KC, Assal A, Lazar-Molnar E, Yao Y and Zang X: Human cancer immunotherapy with antibodies to the PD-1 and PD-L1 pathway. Trends Mol Med. 21:24–33. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Alsaab HO, Sau S, Alzhrani R, Tatiparti K, Bhise K, Kashaw SK and Iyer AK: PD-1 and PD-L1 checkpoint signaling inhibition for cancer immunotherapy: Mechanism, combinations, and clinical outcome. Front Pharmacol. 8:5612017. View Article : Google Scholar : PubMed/NCBI | |
|
Sharma P and Allison JP: The future of immune checkpoint therapy. Science. 348:56–61. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Brahmer JR, Tykodi SS, Chow LQ, Hwu WJ, Topalian SL, Hwu P, Drake CG, Camacho LH, Kauh J, Odunsi K, et al: Safety and activity of antiPD-L1 antibody in patients with advanced cancer. N Engl J Med. 366:2455–2465. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Liu S, Wang Z, Wang Y1 Fan X, Zhang C, Ma W, Qiu X and Jiang T: PD-1 related transcriptome profile and clinical outcome in diffuse gliomas. Oncoimmunology. 7:e13827922017. View Article : Google Scholar : PubMed/NCBI | |
|
Janakiram M, Chinai JM, Fineberg S, Fiser A, Montagna C, Medavarapu R, Castano E, Jeon H, Ohaegbulam KC, Zhao R, et al: Expression, clinical significance, and receptor identification of the newest B7 family member HHLA2 protein. Clin Cancer Res. 21:2359–2366. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Zhao R, Chinai JM, Buhl S, Scandiuzzi L, Ray A, Jeon H, Ohaegbulam KC, Ghosh K, Zhao A, Scharff MD and Zang X: HHLA2 is a member of the B7 family and inhibits human CD4 and CD8 T-cell function. Proc Natl Acad Sci USA. 110:9879–9884. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Zhu Y, Yao S, Iliopoulou BP, Han X, Augustine MM, Xu H, Phennicie RT, Flies SJ, Broadwater M, Ruff W, et al: Chen. B7-H5 costimulates human T cells via CD28H. Nat Commun. 4:20432013. View Article : Google Scholar : PubMed/NCBI | |
|
Eckel-Passow JE, Lachance DH, Molinaro AM, Walsh KM, Decker PA, Sicotte H, Pekmezci M, Rice T, Kosel ML, Smirnov IV, et al: Glioma groups based on 1p/19q, IDH, and TERT promoter mutations in tumors. N Engl J Med. 372:2499–2508. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Liu Y and Cao X: The origin and function of tumor-associated macrophages. Cell Mol Immunol. 12:1–4. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
de Groot AE and Pienta KJ: Epigenetic control of macrophage polarization: Implications for targeting tumor-associated macrophages. Oncotarget. 9:20908–20927. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Arokiaraj MC: A novel targeted angiogenesis technique using VEGF conjugated magnetic nanoparticles and in-vitro endothelial barrier crossing. BMC Cardiovasc Disord. 17:2092017. View Article : Google Scholar : PubMed/NCBI | |
|
Pitulescu ME, Schmidt I, Giaimo BD, Antoine T, Berkenfeld F, Ferrante F, Park H, Ehling M, Biljes D, Rocha SF, et al: Dll4 and Notch signalling couples sprouting angiogenesis and artery formation. Nat Cell Biol. 19:915–927. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Yan H, Qiu W, Koehne de Gonzalez AK, Wei JS, Tu M, Xi CH, Yang YR, Peng YP, Tsai WY, Remotti HE, et al: HHLA2 is a novel immune checkpoint protein in pancreatic ductal adenocarcinoma and predicts post-surgical survival. Cancer Lett. 442:333–340. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Bhat KPL, Balasubramaniyan V, Vaillant B, Ezhilarasan R, Hummelink K, Hollingsworth F, Wani K, Heathcock L, James JD, Goodman LD, et al: Mesenchymal differentiation mediated by NF-κB promotes radiation resistance in glioblastoma. Cancer Cell. 24:331–346. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Verhaak RG, Hoadley KA, Purdom E, Wang V, Qi Y, Wilkerson MD, Miller CR, Ding L, Golub T, Mesirov JP, et al: Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell. 17:98–110. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Lin N, Yan W, Gao K, Wang Y, Zhang J and You Y: Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: A multi-institutional analysis of 941 cases. PLoS One. 9:e948712014. View Article : Google Scholar : PubMed/NCBI | |
|
Kumar V, Donthireddy L, Marvel D, Condamine T, Wang F, Lavilla-Alonso S, Hashimoto A, Vonteddu P, Behera R, Goins MA, et al: Cancer-associated fibroblasts neutralize the anti-tumor effect of CSF1 receptor blockade by inducing PMN-MDSC infiltration of tumors. Cancer Cell. 32:654–668.e5. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Kamran N, Alghamri MS, Nunez FJ, Shah D, Asad AS, Candolfi M, Altshuler D, Lowenstein PR and Castro MG: Current state and future prospects of immunotherapy for glioma. Immunotherapy. 10:317–339. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Liang YX, Lu JM, Mo RJ, He HC, Xie J, Jiang FN, Lin ZY, Chen YR, Wu YD, Luo HW, et al: E2F1 promotes tumor cell invasion and migration through regulating CD147 in prostate cancer. Int J Oncol. 48:1650–1658. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Gartel AL: FOXM1 in cancer: Interactions and vulnerabilities. Cancer Res. 77:3135–3139. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Rundle S, Bradbury A, Drew Y and Curtin NJ: Targeting the ATR-CHK1 axis in cancer therapy. Cancers (Basel). 9(pii): E412017. View Article : Google Scholar : PubMed/NCBI | |
|
Koirala P, Roth ME, Gill J, Chinai JM, Ewart MR, Piperdi S, Geller DS, Hoang BH, Fatakhova YV, Ghorpade M, et al: HHLA2, a member of the B7 family, is expressed in human osteosarcoma and is associated with metastases and worse survival. Sci Rep. 6:311542016. View Article : Google Scholar : PubMed/NCBI | |
|
Zhu Z and Dong W: Overexpression of HHLA2, a member of the B7 family, is associated with worse survival in human colorectal carcinoma. Onco Targets Ther. 11:1563–1570. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Shimonosono M, Arigami T, Yanagita S, Matsushita D, Uchikado Y, Kijima Y, Kurahara H, Kita Y, Mori S, Sasaki K, et al: The association of human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2) expression with gastric cancer prognosis. Oncotarget. 9:22069–22078. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Janakiram M, Shah UA, Liu W, Zhao A, Schoenberg MP and Zang X: The third group of the B7-CD28 immune checkpoint family: HHLA2, TMIGD2, B7×, and B7-H3. Immunol Rev. 276:26–39. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Xiao Y and Freeman GJ: A New B7:CD28 family checkpoint target for cancer immunotherapy: HHLA2. Clin Cancer Res. 21:2201–2203. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Wang Z, Wang Z, Zhang C, Liu X, Li G, Liu S, Sun L, Liang J, Hu H, Liu Y, et al: Genetic and clinical characterization of B7-H3 (CD276) expression and epigenetic regulation in diffuse brain glioma. Cancer Sci. 109:2697–2705. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Zhou Z, Luther N, Ibrahim GM, Hawkins C, Vibhakar R, Handler MH and Souweidane MM: B7-H3, a potential therapeutic target, is expressed in diffuse intrinsic pontine glioma. J Neurooncol. 111:257–264. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Loos M, Hedderich DM, Ottenhausen M, Giese NA, Laschinger M, Esposito I, Kleeff J and Friess H: Expression of the costimulatory molecule B7-H3 is associated with prolonged survival in human pancreatic cancer. BMC Cancer. 9:4632009. View Article : Google Scholar : PubMed/NCBI | |
|
Wu CP, Jiang JT, Tan M, Zhu YB, Ji M, Xu KF, Zhao JM, Zhang GB and Zhang XG: Relationship between co-stimulatory molecule B7-H3 expression and gastric carcinoma histology and prognosis. World J Gastroenterol. 12:457–459. 2006. View Article : Google Scholar : PubMed/NCBI |
