Without restricting to any languages or time, the Web of Science, Scopus, PubMed, and Embase databases were systematically searched to obtain the peer-reviewed records published before 1 January 2021. For this purpose, all fields of records were systematically searched with the following keywords: (“glioma” OR “glioblastoma multiforme” OR “glioblastoma” OR “astrocytoma” OR “ependymoma” OR “subependymoma” OR “oligodendroglioma” OR “oligoastrocytoma” OR “sub-ependymoma” OR “sub ependymoma”) and (“programmed death-ligand 1” OR “PD-L1” OR “PD L1” OR “PDL1” OR “B7-H1” OR “B7 H1” OR “B7H1” OR “CD274” OR “cluster of differentiation 274” OR “CD 274” OR “cluster of differentiation274” OR “B7 homolog 1” OR “PDCD1 Ligand 1” OR “PDCD1LG1” OR “PDCD1L1” OR “HPD-L1”) and (“CD8” OR “CD 8” OR “Cluster of differentiation 8” OR “Cluster of differentiation-8” OR “Cluster of differentiation8” OR “CD8A” OR “T-lymphocyte differentiation antigen T8/Leu-2” OR “CD8 antigen” OR “CD 8 antigen” OR “Leu2 T-Lymphocyte antigen” OR “CD8a molecule” OR “T-cell antigen Leu2” OR “cytotoxic T cell” OR “cytotoxic T lymphocyte” OR “CTL” OR “T-killer cell” OR “cytolytic T cell” OR “CD8+ T-cell” OR “killer T cell”).

Following the systematic search, the obtained records were reviewed in two phases. In phase I, two authors (NH and ZA) independently screened the relevant papers based on their titles and abstracts. In phase II, the same authors independently reviewed the full text of the remaining papers, along with their supplementary data. Any disagreements were resolved via consulting with B.B and consensus.

Records with the following eligibility criteria were included in this study : (1) clinical studies, (2) investigations with the objective of assessing the tumor-infiltrating CD8⁺ T-cells and the protein expression of PD-L1 in patients with high-grade glial tumors, (3) studies, which investigated and published the quantified relationship between PD-L1 and tumor-infiltrating CD8⁺ T-cells or the clinicopathological significance of PD-L1 and tumor-infiltrating CD8⁺ T-cells or the prognostic values of PD-L1 and tumor-infiltrating CD8⁺ T-cells in patients with high-grade glial tumors, and (4) studies, which were published in English.

Based on the following criteria, records were excluded from this study: (1) studies that investigated the tumor-infiltrating CD8⁺ T-cells and the protein expression of PD-L1 in patients with low-grade glial tumors, (2) studies that investigated the tumor-infiltrating CD8⁺ T-cells and the expression of tumoral PD-L1 in glial tumors without considering tumor grades, (3) studies that investigated the cross-talk between PD-L1 and circulating CD8⁺ T-cells in the blood of the affected patients, (4) studies that investigated the CD8⁺ T-cells and PD-L1 in a co-culture system, and (5) studies that were based on the data from databases, like The Cancer Genome Atlas (TCGA).

The following data were extracted from the included studies: (1) the first author, (2) publication year, (3) the used antibody, (4) the endpoint, (5) the country, (6) the type of high-grade glial tumor, (7) the sample size, (8) the treatment of affected patients, (9) the prognostic values of protein expression of PD-L1/tumor-infiltrating CD8⁺ T-cells, (10) the association between protein expression of PD-L1/tumor-infiltrating CD8⁺ T-cells, (11) the clinicopathological significance of protein expression of PD-L1/tumor-infiltrating CD8⁺ T-cells, and (12) and the cut-off for PD-L1 and tumor-infiltrating CD8⁺ T-cells.

We applied the criteria of Hayden et al. statements for assessing the quality of the prognostic studies (18). We also utilized the Joanna Briggs Institute (JBI) checklist for assessing the studies that investigated the relationship between PD-L1 and tumor-infiltrating CD8⁺ T-cells in patients with high-grade glial tumors (19).

Our systematic search on PubMed, Scopus, Embase, and Web of Science retrieved 7468 records. After removing duplication records, 7142 records remained. Based on the independent review of two authors in phase I, 5983 studies were excluded. In phase II, two authors independently reviewed the full text of 1159 studies, along with their supplementary data. Finally, based on the full-text assessment of studies, seven papers were included in the qualitative synthesis. Figure 1 demonstrates the flowchart of literature identification, inclusion, and exclusion.

The included studies were published between 2015 to 2020. Six out of seven studies have investigated high-grade glioma patients (15, 16, 20–23), and one study has investigated high-grade ependymoma patients (24). Table 1 . demonstrates the general characteristics of the included studies.

We have found a significant increase in the level of tumor-infiltrating CD8⁺ T-cells in the second surgery of glioblastoma patients treated with surgery/fractionated radiotherapy/temozolomide compared to the first resected tumor (P-value=0.009) ( Table 2 ). Besides, membranous PD-L1 expression has been more pronounced in the newly diagnosed glioblastoma tissues compared to recurrent glioblastoma tissues (P-value=0.034) ( Table 2 ).

The increased level of tumor-infiltrating CD8⁺ T-cells has been associated with improved overall survival (OS) in high-grade glioma patients who have not been exposed to anti-cancer therapies (P-value<0.05) ( Table 3 ). However, increased level of tumor-infiltrating CD8⁺ T-cells has been associated with worse OS from the second surgery glioblastoma patients who have been exposed to anti-cancer therapies (P-value=0.017) ( Table 3 ). Besides, the increased level of tumor-infiltrating CD8⁺ T-cells has been associated with inferior survival from the second surgery in glioblastoma patients who have been exposed to anti-cancer therapies (P-value=0.005) ( Table 3 ). We have observed that PD-L1 overexpression is associated with inferior OS in glioblastoma patients who have not been exposed to anti-cancer therapies (P-value=0.0119) ( Table 3 ).

We have found that PD-L1 expression is inversely correlated with tumor-infiltrating CD8⁺ T-cells in glioblastoma patients who have not been exposed to anti-cancer therapies (r = -0.5064, and P-value= 0.0003) ( Table 4 ). Also, we have observed that there is a remarkable relationship between the tumor-infiltrating CD8⁺ PD-1⁺ T-cells with tumor-infiltrating PD-1⁺ lymphocytes in glioblastoma patients (P<0.001) ( Table 4 ). Besides, increased PD-1⁺/tumor-infiltrating CD8⁺ T-cell ratio is associated with worse OS and progression-free survival (PFS) in glioblastoma patients (P-value<0.001, and P-value=0.01, respectively) ( Table 4 ). The survival of patients with low PD‐L1 expression and low CD8⁺ infiltration is similar to those with high PD‐L1 expression and low CD8⁺ infiltration in glioblastoma patients who have not been exposed to anti-cancer therapies (P-value<0.05) ( Table 4 ). Moreover, the low expression of PD-L1 and high level of tumor-infiltrating CD8⁺ T-cells are associated with improved OS in glioblastoma patients who have not been exposed to anti-cancer therapies (P-value<0.05) ( Table 4 ). Furthermore, a high PD-1⁺/tumor-infiltrating CD8⁺ T-cells ratio is negatively associated with improved PFS and OS of glioblastoma patients (r =-0.444, P-value<0.02, and r=-0.655, P-value<0.001, respectively) ( Table 4 ). We have observed a strong positive association between PD-L1 expression and tumor-infiltrating CD8⁺ T-cell in patients with high-grade ependymomas (P-value=0.03) ( Table 3S ).

We assessed the included studies concerned with the prognostic values of the PD-L1/tumor-infiltrating CD8⁺ T-cells axis based on the Hayden et al. statement (18). The main risk areas were confounding measurement and outcome measurement ( Table 1S ). Furthermore, we evaluated the remaining studies based on the JBI checklists (19). The main risk areas were addressing potential cofounders ( Table 2S ).

We have found a significant increase in the level of tumor-infiltrating CD8⁺ T-cells in the second resected glioblastoma tumors treated with anti-cancer therapies (paired data). However, there has been no statistically significant change in the level of tumor-infiltrating CD8⁺ T-cells in recurrent glioblastoma patients and newly diagnosed glioblastoma patients treated with chemotherapy/investigational agents (unpaired data) ( Table 2 ). Consistent with our results, Yue et al. have reported a strong positive association between increased CD8⁺ T-cells infiltration and positive O⁶-methylguanine DNA methyltransferase (MGMT) expression in glioblastoma patients (28). Indeed, positive MGMT has been associated with chemoresistant tumors in glioblastoma patients (29). These findings are consistent with our observed results regarding the increased infiltration of CD8⁺ T-cells in recurrent glioblastomas. In line with these, preclinical studies have also indicated that anti-cancer therapy of glioma can pave the way for T-cells infiltration. Weichselbaum et al. have shown that radiotherapy can facilitate T-cell infiltration via the release of tumor antigens and danger-associated molecular patterns. Indeed, radiotherapy can up-regulate the expression of C-X-C motif ligand 9 (CXCL9) and C-X-C motif ligand 10 (CXCL10), leading to the recruitment of immune cells (30). Moreover, recent findings indicate that radiation can induce major histocompatibility complex (MHC)-I expression, associated with the infiltration of CD8⁺ T-cells into the microenvironment (31).

We have found a remarkable upregulation in PD-L1 in the newly diagnosed glioblastomas compared to the recurrent glioblastomas treated with chemotherapy/investigational agents ( Table 2 ). Consistent with this, Heynckes et al. have indicated that temozolomide can inhibit PD-L1 expression in recurrent glioblastoma (32). Besides, it has been reported that PD-L1 expression in recurrent glioblastoma is substantially downregulated following treatment with temozolomide in affected patients (33). Therefore, the insignificant result of the study by Miyazaki et al. might be stemmed from their low sample size. Collectively, based on the current evidence, the level of tumor-infiltrating CD8⁺ T-cells and the expression level of PD-L1 are substantially increased and decreased in the recurrent glioblastomas compared to newly diagnosed glioblastomas.

We have found that PD-L1 overexpression can be associated with inferior OS in glioblastoma patients who have not been exposed to anti-cancer therapies ( Table 3 ). Consistent with our detected results, Xue et al. have pooled the data from the patients who underwent chemo/radiotherapy after resection with patients treated with other therapeutic modalities and have indicated that PD-L1 can be associated with worse OS in patients with gliomas (34). Nduom et al. have shown that PD-L1 overexpression can be associated with shorter survival in glioblastoma patients (35). Han et al. have indicated that the overexpression of PD-L1 in resected glioblastoma tissues is remarkably associated with the inferior survival of affected patients (36). Besides, Lee et al. have indicated that PD-L1 expression in resected unexposed glioblastoma tissues is associated with worse OS in glioblastoma patients (37).

Regarding the prognostic value of tumor-infiltrating CD8⁺ T-cells, the level of tumor-infiltrating CD8⁺ T-cells might be associated with improved OS in glioblastoma patients who have not been exposed to anti-cancer therapies before. However, tumor-infiltrating CD8⁺ T-cells might be associated with inferior OS and worse survival from the second surgery in glioblastoma patients who were previously exposed to anti-cancer therapies ( Table 3 ). Consistent with our detected results, Madkouri et al. have indicated increased infiltration of CD8⁺ T-cells is associated with improved OS of glioblastoma patients who have not been exposed to anti-cancer therapies before (13). Moreover, Kim et al. have demonstrated that increased infiltration of CD8⁺ T-cells in the resected glioblastoma tissues, which have not been exposed to anti-cancer therapies before, can improve the survival of glioblastoma patients (14). In other words, these results have indicated that anti-cancer therapies can continuously lead to the exhaustion of tumor infiltrated CD8⁺ T-cells and pave the way for the transformation of the pro-inflammatory tumor microenvironment into the immunosuppressive one.

Our observed results are also consistent with the preclinical findings. Dai et al. have shown that the combination of anti-PD-1 and temozolomide can substantially decrease tumor size and increase the survival of mice bearing gliomas (10). In mice models of glioblastoma, anti-PD-1 has also remarkably increased the anti-tumoral proprieties of temozolomide via down-regulating the expression of lymphocyte-activation gene 3 (LAG-3) and PD-1 (11). Grapin et al. have indicated that radiotherapy can lead to the TIGIT upregulation in the tumor-infiltrating CD8⁺ T-cells (38). In line with this, the combination of fractionated radiotherapy and the administration of immune checkpoint inhibitors can lead to the abscopal effect, resulting in tumor rejection (31). Besides, it has been reported that anti-PD-1 with localized radiation can substantially increase the survival of mice bearing gliomas compared to monotherapy with radiation (39). Consistent with these, Li et al. have highlighted a remarkable PD-1 upregulation in CD8⁺ T-cells following radiation therapy (40). Besides, Dovedi et al. have shown that fractionated radiotherapy can up-regulate PD-1 expression in CD8⁺ T-cells, and the administration of immune checkpoint inhibitors can considerably increase the survival of affected mice (41). Moreover, accumulating evidence indicates that radiation can facilitate the recruitment of regulatory T-cells (Tregs) into the tumor microenvironment. Tregs can up-regulate the expression of interleukin (IL)-10 and transforming growth factor-beta (TGF-β) in the tumor microenvironment. Sharabi et al. have shown that the anti-PD-1 or Treg depletion can substantially increase radiation efficacy in eliminating tumoral cells (42). Besides, Tregs can up-regulate cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) expression and further attenuate the anti-tumoral immune responses. Indeed, CTLA-4 upregulation might be one of the reasons for developing resistance in immune-radiotherapy (43). Besides the beneficial effect of immune checkpoint inhibition on the response rate of glioma radiotherapy, radiotherapy can also increase the permeability of the blood-brain barrier for immune checkpoint inhibitors (44, 45). Therefore, the administration of immune checkpoint inhibitors can increase radiotherapy efficacy and vice versa (41, 42). Collectively, the current evidence indicates that exposure to anti-cancer therapies, e.g., chemo-radiotherapy, can up-regulate inhibitory immune checkpoint molecules in tumor-infiltrating CD8⁺ T-cells, and unlike unexposed patients, increased tumor-infiltrating CD8⁺ T-cells in anti-cancer therapy-exposed tumoral tissues can be associated with the inferior prognosis of affected patients.

We have observed a significant association between tumor-infiltrating PD-1⁺ lymphocytes with tumor-infiltrating CD8⁺ PD-1⁺ T-cells in glioblastoma patients treated with chemotherapy/investigational agents. Su et al. have shown a significant inverse relationship between PD-L1 expression and the intensity of tumor-infiltrating CD8⁺ T-cells in glioblastoma patients who have not been exposed to anti-cancer therapies ( Table 4 ). Nambirajan et al. have reported a strong positive association between PD-L1 expression and the level of tumor-infiltrating CD8⁺ T-cells in patients with high-grade ependymoma ( Table 3S ).

We have found that the combination of low PD-L1 expression and high infiltration of CD8⁺ T-cells is associated with improved OS in glioblastoma patients who have not been exposed to anti-cancer therapies. Also, the survival rate of glioblastoma patients with low PD-L1 expression and low level of tumor-infiltrating CD8⁺ T-cells has been similar to the survival rate of glioblastoma patients with high PD-L1 expression and low level of tumor-infiltrating CD8⁺ T-cells, indicating the critical prognostic value of CD8⁺ T-cells and its phenotype in determining the survival of glioblastoma patients who have not been exposed to anti-cancer therapies. Besides, a high PD-1⁺/tumor-infiltrating CD8⁺ T-cell ratio has been associated with substantially inferior PFS and OS in glioblastoma patients ( Table 4 ). Collectively, the presence phenotype of tumor-infiltrating CD8⁺ T-cells has an essential role in determining the survival of glioblastoma patients.

Although PD-1 expression in the tumor-infiltrating CD8⁺ T-cells can substantially attenuate anti-tumoral effects of cancer therapies, the tumor microenvironment of glioblastoma is more complicated than its direction can be determined by the expression level of a single inhibitory immune checkpoint molecule. Indeed, various axes, which the PD-L1/PD-1 axis is one of them, determine the fate of anti-tumoral immune responses. Besides the remarkable association between CTLA-4 and PD-1, recent findings have indicated remarkable associations between other inhibitory immune checkpoints, e.g., TIGIT, in gliomas (46). Thus, immunotherapies for glioblastoma patients should be focused on disrupting these inhibitory checkpoints to restore anti-tumoral immune responses.

Furthermore, the low response rate of glioblastoma patients to immune-checkpoint inhibitors compared to melanoma patients also indicates that the glioblastoma tumor microenvironment might not be regulated by a single inhibitory molecule rather a network of the inhibitory immune checkpoints. Nayak et al. have reported that the objective response rate of glioblastoma patients to monotherapy with pembrolizumab is 0% (47). Reardon et al. have shown that the objective response rate of glioblastoma patients to monotherapy with nivolumab is approximately 7.8% (12). Blumenthal et al. have found that monotherapy with pembrolizumab does not bring clinical benefits for patients with brain tumors (48). In contrast to these dismal results, a meta-analysis by Li et al. has shown that PD-1 inhibitors can remarkably improve the OS of melanoma patients (49).

Moreover, the current method of immune checkpoint inhibitors administration can increase the risk of immune-related adverse events development. Administrating immune checkpoint inhibitors without considering the expression patterns of immune checkpoint molecules in the tumor microenvironment cannot effectively stimulate anti-tumoral immune responses in the tumor microenvironment rather can increase the risk of autoimmunity development in healthy tissues (50, 51). Simonelli et al. have reported a glioblastoma patient that nivolumab administration led to severe liver damage (52). Comito et al. have reported a glioblastoma patient that developed aplastic anemia following treatment with nivolumab (53). Therefore, immune checkpoint inhibitors should be administrated according to the immune checkpoints expression patterns in the cells residing in the tumor microenvironment to minimize the risk of immune-related adverse events development (6–8).

Single-cell sequencing technology has allowed us to study the cells at the single-cell level. The single-cell sequencing of immune cells, e.g., tumor-infiltrating CD8⁺ T-cells, enables us to demonstrate the expression patterns of various inhibitory immune checkpoint molecules (54). Indeed, the expression profile of the cells in the tumor microenvironment can allow us to design a precise regimen for each patient to increase the response rate of immune checkpoint inhibitors and decrease the risk of immune-related adverse events development following the administration of immune checkpoint inhibitors (54, 55) ( Figure 2 ).

Besides, single-cell sequencing can provide valuable insights for predicting the response rate of affected patients to immune checkpoint inhibitors. Although there are established biomarkers for predicting the response rate of patients with solid cancers to immune checkpoint inhibitors, e.g., BRCA1/2 alteration and mismatch-repair status, the data from single-cell sequencing can study the cells and their origins at the single-cell level and provide with more valuable prognostic biomarkers (56, 57). In this regard, it has been identified that the expression of TCF7 in CD8⁺ T-cells can be a prognostic factor for predicting the response rate of melanoma patients to anti-PD-1 therapy (58).

Zhai et al. have applied single-cell sequencing techniques to investigate the expression of immune checkpoints in resected high-grade glioma. They have found that the expression of the inhibitory immune checkpoints and their pertained ligands in tumoral cells is substantially increased during tumorigenesis (59). Huang et al. have used bioinformatic single-cell sequencing data of immune cells and have demonstrated that CTLA-4 is remarkably up-regulated in natural killer cells (60). Besides the potentiality of this technology in profiling the expression of known inhibitory immune checkpoint molecules and their expression intensities, this technology can also provide new insights about novel inhibitory immune checkpoints in high-grade glial tumors. Li et al. have reported that the sialic acid-binding Ig-like lectin family is a novel inhibitory immune checkpoint in glioma. They have shown that sialic acid-binding Ig-like lectin-16 is functionally similar to PD-L1 and sialic acid-binding Ig-like lectin-5/-7/-9 are functionally similar to immunoglobulin mucin-3 (TIM-3). Besides, their expression levels have been associated with advanced tumor grades in patients with glioma (61). Tan et al. have used bioinformatic single-cell sequencing data of immune cells and have indicated that the expression of sialic acid-binding Ig like lectin 1 is positively correlated with PD-1 and CTLA-4 in glioma (62). A recent clinical trial has used cytometry by time-of-flight technique to identify the reason for the low response rate of glioblastoma patients to pembrolizumab. They have found that the overexpression of CD68 in the tumor microenvironment can be the culprit for the low response rate of glioblastoma patients to pembrolizumab (63). Indeed, the application of single-cell sequencing can provide ample opportunities to investigate the factors that are implicated in immune resistance. Besides, radio/chemotherapy can augment the inhibitory immune checkpoint axes in glioblastoma patients; thus, integrating the results of single-cell sequencing to proscribe immune checkpoint inhibitors can also effectively and precisely improve the response rates of glioblastoma patients.

Despite the promising future of this approach for patients with high-grade glial tumors, this approach has some limitations. The most noticeable limitation of this approach is its complex nature that requires the implantation of high technologies. Its second limitation might be stemmed from the fact that the expression level obtained from sequencing RNAs does not always correlate with their protein expressions because the post-transcriptional modifications can substantially alter the protein expressions. Nevertheless, the recent advances in antibody sequencing and RNA expression and protein sequencing (REAP-seq) technologies can overcome this issue and provide a better insight into the phenotype of cells (55). Its third limitation is that the tumor-microenvironment is highly dynamic, and serial sequencing might be required for optimal results. Thus, follow-up sequencing might be needed. Nevertheless, the promising preclinical results and the recent advances in deep learning might justify its translation and open a new era in the neuro-oncology field (64).

Collectively, PD-L1 overexpression can be associated with the poor prognosis of glioblastoma patients who have not been exposed to anti-cancer therapies. Since anti-cancer therapies, like chemo-radiotherapy, can increase the expression of inhibitory immune checkpoint molecules in tumor-infiltrating CD8⁺ T-cells, exposed glioblastoma tissues to anti-cancer therapies can exhaust tumor-infiltrating CD8⁺ T-cells and these exhausted tumor-infiltrating CD8⁺ T-cells are associated with the inferior prognosis of glioblastoma patients. Nevertheless, the increased infiltration of tumor-infiltrating CD8⁺ T-cells is associated with the improved prognosis of glioblastoma patients who have not been exposed to anti-cancer therapies. Therefore, profiling the expression pattern of inhibitory immune checkpoints in the tumor microenvironment via single-cell sequencing technologies and administrating related immune checkpoint inhibitors based on these data can pave the way to increase the response rate of anti-cancer therapies, enhance the efficacy of immune checkpoint inhibitors, decrease the risk of tumor recurrence, improve the immune-resistance state, and reduce the risk of autoimmunity development in the affected patients.

The current systematic review has some strengths: First, all fields of the major electronic databases, i.e., Web of Science, Scopus, PubMed, and Embase, have been searched to minimize the risk of not including eligible studies. Second, the current systematic review has shed light on the controversial results accumulating during the past decade and, via a systematic and unbiased approach, have elucidated the significance of the tumor-infiltrating CD8⁺ T-cells/PD-L1 axis in the affected patients. Third, the current systemic review has sorted out the inconsistencies between preclinical and clinical studies and presented novel insights into the tumor microenvironment. Fourth, along with the recent phase II “window-of-opportunity” clinical trial, we have highlighted the potential role of single-cell sequencing in increasing the response rates of anti-cancer therapies, decreasing the risk of immune-related adverse events development, preventing the immune-resistance development, and reducing the risk of tumor recurrence in affected patients. Nevertheless, the current systematic review has some limitations as well. First, the number of included studies has been low because high-grade glial tumors are not as prevalent as other cancers, like breast and lung cancers. Second, our included studies have been limited to the investigations that have been published in English. Third, ideally, studies would apply novel single-cell sequencing-based approaches, e.g., mass cytometry, to study the expression profile of well-established inhibitory immune checkpoints on immune cells; however, so far, the main detection method has been immunohistochemistry (IHC). Therefore, more investigations on the promising potentiality of single-cell sequencing on the profiling of inhibitory immune checkpoints expression are recommended to ameliorate affected patients’ prognosis.