The prognostic significance of PD-L1 expression in patients with glioblastoma: A meta-analysis

RIP2/NF-κB/PD-L1 signaling pathway is involved in temozolomide resistance by inducing autophagy in glioblastoma cells

Autophagy is an important factor in temozolomide (TMZ) resistance in glioblastoma (GBM). Receptor-interacting protein 2 (RIP2) is associated with autophagy, but its role and mechanism in regulating autophagy in GBM cells remain unclear. To analyze RIP2 expression in GBM in The Cancer Genome Atlas (TCGA) dataset. GBM cells were stimulated using recombinant human RIP2 protein (rRIP2) or RIP2 plasmid. Cell proliferation and apoptosis were assessed using CCK-8 assay and flow cytometry. Western blotting and immunofluorescence (IF) assays were performed to detect protein expression in cells and tumor tissues. Moreover, the relationship between RIP2-induced autophagy and TMZ resistance was verified in a GBM xenograft model. We determined that RIP2 expression was upregulated in GBM. rRIP2 and RIP2 overexpression induced TMZ resistance in the GBM cell lines. RIP2 overexpressing xenograft tumors have reduced sensitivity to TMZ. In addition, we showed that PD-L1 protein expression was upregulated in GBM tissues with RIP2 overexpression. rRIP2 and RIP2 overexpression induced autophagy in GBM cells through AMPK. Notably, RIP2 upregulated PD-L1 expression through the NF-κB signaling pathway, which induced autophagy and TMZ resistance in GBM cells. Moreover, NF-κB or autophagy inhibition reversed TMZ resistance in RIP2 overexpressing GBM cells in a xenograft model. In conclusion, RIP2 induces TMZ resistance in GBM cells by promoting autophagy through the NF-κB/PD-L1 signaling pathway, indicating that the RIP2/NF-κB/PD-L1 pathway may be therapeutic target for TMZ resistance.

Predicting Treatment Outcomes in Glioblastoma: A Risk Score Model for TMZ Resistance and Immune Checkpoint Inhibition

Glioblastoma (GBM) presents significant therapeutic challenges due to its invasive nature and resistance to standard chemotherapy, i.e., temozolomide (TMZ). This study aimed to identify gene signatures that predict poor TMZ response and high PD-L1/PD-1 tumor expression, and explore potential sensitivity to alternative drugs. We analyzed The Cancer Genome Atlas (TCGA) biopsy data to identify differentially expressed genes (DEGs) linked to these characteristics. Among 33 upregulated DEGs, 5 were significantly correlated with overall survival. A risk score model was built using these 5 DEGs, classifying patients into low-, medium-, and high-risk groups. We assessed immune cell infiltration, immunosuppressive mediators, and epithelial-mesenchymal transition (EMT) markers in each group using correlation analysis, Gene Set Enrichment Analysis (GSEA), and machine learning. The model demonstrated strong predictive power, with high-risk patients exhibiting poorer survival and increased immune infiltration. GSEA revealed upregulation of immune and EMT-related pathways in high-risk patients. Our analyses suggest that high-risk patients may exhibit limited response to PD-1 inhibitors, but could show sensitivity to etoposide and paclitaxel. This risk score model provides a valuable tool for guiding therapeutic decisions and identifying alternative chemotherapy options to enable the development of personalized and cost-effective treatments for GBM patients.

PD-L1 importance in malignancies comprehensive insights into the role of PD-L1 in malignancies: from molecular mechanisms to therapeutic opportunities

The phenomenon of upregulated programmed death-ligand 1 (PD-L1) expression is common in numerous human malignancies. The overexpression of PD-L1 significantly contributes to immune evasion because its interaction with the PD-1 receptor on activated T lymphocytes impairs anti-tumour immunity by neutralizing T cell stimulatory signals. Furthermore, beyond its immunological interface, PD-L1 possesses intrinsic capabilities that directly modulate oncogenic processes, fostering cancer cell proliferation and survival. This dual function of PD-L1 challenges the efficacy of immune checkpoint inhibitors and highlights its possible application as a direct target for therapy. Recent discoveries concerning the cancer cell-intrinsic signalling pathways of PD-L1 have significantly enhanced our understanding of the pathological implications linked to its tumour-specific expression. These entail the orchestration of tumour proliferation and viability, maintenance of cancer stem cell-like phenotypes, modulation of immune responses, as well as impacts on DNA repair mechanisms and transcriptional regulation. This review aims to deliver an exhaustive synthesis of PD-L1's molecular underpinnings alongside its clinical implications in a spectrum of cancers, spanning both solid neoplasms and haematological disorders. It underscores the necessity for an integrated understanding of PD-L1 in further refining therapeutic strategies and improving patient outcomes.

Current progress of anti‑PD‑1/PDL1 immunotherapy for glioblastoma (Review)

Glioblastoma (GBM) is the most common central nervous system malignancy in adults. GBM may be classified as grade IV diffuse astrocytoma according to the 2021 World Health Organization revised classification of central nervous system tumors, which means it is the most aggressive, invasive, undifferentiated type of tumor. Immune checkpoint blockade (ICB), particularly anti‑programmed cell death protein‑1 (PD‑1)/PD‑1 ligand‑1 immunotherapy, has been confirmed to be successful across several tumor types. However, in GBM, this treatment is still uncommon and the efficacy is unpredictable, and <10% of patients show long‑term responses. Recently, numerous studies have been conducted to explore what factors may indicate or affect the ICB response rate in GBM, including molecular alterations, immune expression signatures and immune infiltration. The present review aimed to summarize the current progress to improve the understanding of immunotherapy for GBM.

Immune checkpoint pathways in glioblastoma: a diverse and evolving landscape

Immune checkpoint (IC) inhibition in glioblastoma (GBM) has not shown promising results in the last decade compared to other solid tumors. Several factors contributing to the lack of immunotherapy response include the profound immunosuppressive nature of GBM, highly redundant signaling pathways underlying immune checkpoints, and the negative immunogenic impact of current standard of care on the tumor microenvironment. In this review, we will discuss various ICs in the context of GBM, their interplay with the tumor immune microenvironment, relevant pre-clinical and clinical studies, and the impact of current treatment modalities on GBM IC blockade therapy. Understanding the molecular mechanisms that drive ICs, and how they contribute to an immunosuppressive tumor microenvironment is critical in advancing IC inhibition therapy in GBM. Furthermore, revisiting current treatment modalities and their impact on the immune landscape is instrumental in designing future combinatorial therapies that may overcome treatment resistance.

PD-1/PD-L1 axis is involved in the interaction between microglial polarization and glioma

The tumor microenvironment plays a vital role in glioblastoma growth and invasion. PD-1 and PD-L1 modulate the immunity in the brain tumor microenvironment. However, the underlying mechanisms remain unclear. In the present study, in vivo and in vitro experiments were conducted to reveal the effects of PD-1/PD-L1 on the crosstalk between microglia and glioma. Results showed that glioma cells secreted PD-L1 to the peritumoral areas, particularly microglia containing highly expressed PD-1. In the early stages of glioma, microglia mainly polarized into the pro-inflammatory subtype (M1). Subsequently, the secreted PD-L1 accumulated and bound to PD-1 on microglia, facilitating their polarization toward the microglial anti-inflammatory (M2) subtype primarily via the STAT3 signaling pathway. The role of PD-1/PD-L1 in M2 polarization of microglia was partially due to PD-1/PD-L1 depletion or application of BMS-1166, a novel inhibitor of PD-1/PD-L1. Consistently, co-culturing with microglia promoted glioma cell growth and invasion, and blocking PD-1/PD-L1 significantly suppressed these processes. Our findings reveal that the PD-1/PD-L1 axis engages in the microglial M2 polarization in the glioma microenvironment and promotes tumor growth and invasion.

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

The first half of 2022 saw the publication of several major research advances in image-based models and artificial intelligence applications to optimize treatment strategies for high-grade gliomas, the deadliest brain tumors. We review them and discuss the barriers that delay their entry into clinical practice; particularly, the small sample size and the heterogeneity of the study designs and methodologies used. We will also write about the poor and late palliation that patients suffering from high-grade glioma can count on at the end of life, as well as the current legislative instruments, with particular reference to Italy. We suggest measures to accelerate the gradual progress in image-based models and end of life care for patients with high-grade glioma.

Tumor-associated microenvironment, PD-L1 expression and their relationship with immunotherapy in glioblastoma, IDH-wild type: A comprehensive review with emphasis on the implications for neuropathologists

Although novel knowledge has been acquired on the molecular landscape of glioblastoma (GBM), a relatively few steps forward have been made regarding its therapy. With the increasing use of novel immunotherapeutic drugs capable of stimulating the antitumor inflammatory response, in the last decades numerous studies aimed to characterize the tumor-associated microenvironment (TME) and its relationship with the immunogenicity of GBM. In this regard, although the tumor-associated microglia and macrophages (TAMs) and PD-L1/PD-1 axis have been emerged as one of the most relevant components of the GBM TME and one of the potential molecular pathways targetable with immunotherapy, respectively. It has been supposed that TAMs may acquire different phenotypes, switching from M1 to M2 phenotypes, with tumor-suppressive and tumor-stimulating role depending on the different surrounding conditions. PD-L1 is a type 1 transmembrane protein ligand expressed by T-cells, B-cells and antigen-presenting cells, with a main inhibitory checkpoint role on tumor immune regulation. While PD-L1 immunohistochemical expression has been extensively investigated in many cancers, its usefulness in the evaluation of GBM response rates to immunotherapy and its standardized evaluation by immunohistochemistry are still debated. The present review paper focuses on the current "state of the art" about the relationship between TME, PD-L1/PD-1 pathway and immunotherapy in GBM, also providing neuropathologists with an updated guide about the clinical trials conducted with PD-L1 and PD-1 inhibitors.

Systematic integration of m6A regulators and autophagy-related genes in combination with long non-coding RNAs predicts survival in glioblastoma multiforme

Glioblastoma multiforme (GBM) is probably the only tumor in which a unique epigenetic alteration, namely methylation of the MGMT gene, possesses direct clinical relevance. Now with the emergence of aberrant N6 methyladenosine (m6A) modifications (the most common epigenetic modification of mRNA, closely linked to the autophagy process) in cancer, the epi-transcriptomic landscape of GBM pathobiology has been expanded. Considering this, herein, we systematically analyzed m6A regulators, assessed their correlation with autophagy-related genes (ATG), and established a long non-coding RNAs (lncRNA)-dependent prognostic signature (m6A-autophagy-lncRNAs) for GBM. Our analysis identified a novel signature of five long non-coding RNAs (lncRNAs: ITGA6-AS1, AC124248.1, NFYC-AS1, AC025171.1, and AC005229.3) associated with survival of GBM patients, and four among them clearly showed cancer-associated potential. We further validated and confirmed the altered expression of two lncRNAs (AC124248.1, AC005229.3) in GBM associated clinical samples using RT-PCR. Concerning the prognostic ability, the obtained signature determined high-/low-risk groups in GBM patients and showed sensitivity to anticancer drugs. Collectively, the m6A-autophagy-lncRNAs signature presented in the study is clinically relevant and is the first attempt to systematically predict the potential interaction between the three key determinants (m6A, autophagy, lncRNA) in cancer, particularly in GBM.

Histone acetylation gene-based biomarkers as novel markers of the immune microenvironment in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a primary malignant tumour with high intracranial morbidity, high malignancy and poor prognosis. Abnormal changes in histone acetylation are closely related to the occurrence and development of cancer. However, there is still a lack of systematic research on histone acetylation in GBM.

METHODS

Whole-transcriptome sequencing data and clinical data of GBM patients were obtained through the TCGA database. Single-cell RNA-sequencing (scRNA-seq) data from GBM patients were obtained from GSE146711 in the Gene Expression Omnibus database. Cell descending fractionation was first performed for scRNA-seq on GBM. The CellChat and PROGENy scores explore the impact of the histone acetylation pathway in GBM on intercellular chat and tumour pathways. The AddModuleScore function evaluates the enrichment score of histone acetylation in cells and divides them into high-histone acetylation and low-histone acetylation groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on the differential genes between different histone acetylation states, and the biological processes and pathways that may be affected by histone acetylation were evaluated. Based on this, a prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) analysis, and survival analysis was performed to evaluate its prognostic performance. Finally, we also analysed the main effects of the constructed histone acetylation-related model on GBM immune infiltration by multiple methods, and analysed the main mutation data of its different subgroups.

RESULTS

GBM samples mainly include seven large cell populations: oligodendrocyte precursor cells (OPCs), myeloid, neoplastic, oligodendrocytes, astrocytes, vascular and neurons. Cellchat and ProgenY scores revealed that in GBM tumours, histone acetylation interacts closely with multiple immune cells and tumour pathways. GO and KEGG analyses revealed the main impact proteins and pathway correlates of histone acetylation. Five histone acetylation genes were screened using LASSO analysis and a prognostic model was constructed. The results revealed that prognostic models were significant in the prognostic stratification of patients in both the training and validation groups of GBM patients. Immune infiltration analysis revealed that the mechanism of histone acetylation in GBM may be related to the immune infiltration of multiple effector immune cells.

CONCLUSIONS

Our histone acetylation-based biomarkers are closely associated with immune microenvironmental infiltration and functional mutations in multiple tumour pathways in GBM. This suggests that histone acetylation may reveal microscopic alterations in the tumour microenvironment, and may provide potential evidence and a research basis for the development of novel therapeutic targets for GBM. On this basis, a novel perspective on the spatial biology and immunological understanding of GBM is provided.

Recruitment of myeloid‑derived suppressor cells and regulatory T‑cells is associated with the occurrence of acute myocardial infarction

The roles of myeloid-derived suppressor cells (MDSCs) and regulatory T-cells (Tregs) in acute myocardial infarction (AMI) remain elusive. The present study aimed to analyze the proportions of the granulocytic and monocytic populations of MDSCs (G-MDSCs and M-MDSCs, respectively), and Tregs in the peripheral blood mononuclear cells (PBMCs) of patients with AMI. The present study recruited 34 patients with AMI and 37 healthy controls without clinical signs of myocardial ischemia. PBMCs were isolated from the peripheral blood samples of patients with AMI within 24 h following admission to the hospital and from those of the healthy controls during a physical examination. Two subsets of MDSCs, G-MDSCs (CD15+CD33+CD11b+CD14-HLA-DRlow) and M-MDSCs (CD14+CD15-CD11b+HLA-DRlow), and Tregs (CD3+CD4+CD25highCD127low T-cells) in the PBMCs derived from the patients with AMI and healthy controls were analyzed using flow cytometry. The effects of MDSCs derived from patients with AMI on naïve CD4+ T-cells were examined in the co-culture system. The results revealed that the proportions of G-MDSCs and M-MDSCs were higher in the peripheral blood of patients with AMI than in that of the healthy controls. The patients with AMI had significantly higher numbers of programmed death-ligand (PD-L)1- and PD-L2-positive G-MDSCs and M-MDSCs compared with the healthy controls (P<0.05). The MDSCs could acquire a granulocytic phenotype following AMI, and the G-MDSCs and M-MDSCs would be more likely to express PD-L2 and PD-L1, respectively. The ratios of Tregs to CD4+ T-cells and PD-1+ Tregs in the peripheral blood of patients with AMI were significantly higher than those in the healthy controls (P<0.05). The results of flow cytometry demonstrated an increase in the numbers of inducible Tregs in the co-culture system with the G-MDSCs derived from patients with AMI compared with the G-MDSCs derived from the healthy controls (P<0.01). On the whole, the findings presented herein demonstrate the accumulation of MDSCs, and the upregulation of PD-L1 and PD-L2 expression on the surface of MDSCs in patients with AMI. MDSCs can induce the expansion of Tregs by binding PD-1 on the surface of Tregs, thus playing a crucial role in AMI.

Genomic analysis of immunogenic cell death-related subtypes for predicting prognosis and immunotherapy outcomes in glioblastoma multiforme

Immunogenic cell death (ICD), a unique form of cancer cell death, has therapeutic potential in anti-tumour immunotherapy. The aim of this study is to explore the predictive potential of ICD in the prognosis and immunotherapy outcomes of glioblastoma multiforme (GBM). RNA sequencing data and clinical information were downloaded from three databases. Unsupervised consistency clustering analysis was used to identify ICD-related clusters and gene clusters. Additionally, the ICD scores were determined using principal component analysis and the Boruta algorithm via dimensionality reduction techniques. Subsequently, three ICD-related clusters and three gene clusters with different prognoses were identified, with differences in specific tumour immune infiltration-related lymphocytes in these clusters. Moreover, the ICD score was well differentiated among patients with GBM, and the ICD score was considered an independent prognostic factor for patients with GBM. Furthermore, two datasets were used for the external validation of ICD scores as predictors of prognosis and immunotherapy outcomes. The validation analysis suggested that patients with high ICD scores had a worse prognosis. Additionally, a higher proportion of patients with high ICD scores were non-responsive to immunotherapy. Thus, the ICD score has the potential as a biomarker to predict the prognosis and immunotherapy outcomes of patients with GBM.