Immunotherapy in Glioblastoma: A Clinical Perspective

Development of a prognostic model for glioblastoma multiforme based on the expression levels of efferocytosis-related genes

Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. The microenvironment of GBM is characterized by its highly immunosuppressive nature with infiltration of immunosuppressive cells and the expression levels of cytokines. Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. Efferocytosis plays a noticeable function in the formation of immunosuppressive environment. This study aimed to develop an efferocytosis-related prognostic model for GBM. The bioinformatic methods were utilized to analyze the transcriptomic data of GBM and normal samples. Clinical and RNA-seq data were sourced from TCGA database comprising 167 tumor samples and 5 normal samples, and 167 tumor samples for which survival information was available. Transcriptomic data of 1034 normal samples were collected from the Genotype-Tissue Expression (GTEx) database as a control sample supplement to the TCGA database. In the end, 167 tumor samples and 1039 normal samples were obtained for transcriptome analysis. Efferocytosis-related differentially expressed genes (ERDEGs) were obtained by intersecting 7487 differentially expressed genes (DEGs) between GBM and normal samples along with 1189 hub genes. Functional enrichment analyses revealed that ERDEGs were mainly involved in cytokine-mediated immune responses. Moreover, 9 prognosis-related genes (PRGs) were identified by the least absolute shrinkage and selection operator (LASSO) regression analysis, and a prognostic model was therefore developed. The nomogram combining age and risk score could effectively predict GBM patients' prognosis. GBM patients in the high-risk group had higher immune infiltration, invasion, epithelial-mesenchymal transition, angiogenesis scores and poorer tumor purity. In addition, the high-risk group exhibited higher half maximal inhibitory concentration (IC50) values for temozolomide, carmustine, and vincristine. Expression analysis indicated that PRGs were overexpressed in GBM cells. PDIA4 knockdown reduced efferocytosis in vitro. In summary, the proposed prognostic model for GBM based on efferocytosis-related genes exhibited a robust performance.

Recent advances in drug delivery systems for targeting brain tumors

Brain tumor accounts for about 1.6% of incidence and 2.5% of mortality of all tumors, and the median survival for brain tumor patients is only about 20 months. The treatment for brain tumor still faces many challenges, such as the blood-brain barrier (BBB), blood-brain tumor barrier (BBTB), the overexpressed efflux pumps, the infiltration, invasion, high heterogeneity of tumor cells, drug resistance and immune escape caused by tumor microenvironment (TME) and cancer stem cells (CSC). This review attempts to clarify the challenges for multi-functional nano drug delivery systems (NDDS) to cross the BBB and target the cancer cells or organelles, and also provides a brief description of the different types of targeted multi-functional NDDS that have shown potential for success in delivering drugs to the brain. Further, this review also summarizes the research progress of multi-functional NDDS in the combination therapy of brain tumors from the following sections, the combination of chemotherapy drugs, chemotherapy-chemodynamic combination therapy, chemotherapy-immunization combination therapy, and chemotherapy-gene combination therapy. We also provide an insight into the recent advances in designing multi-functional NDDS for combination therapy.

Biology-aware mutation-based deep learning for outcome prediction of cancer immunotherapy with immune checkpoint inhibitors

The response rate of cancer immune checkpoint inhibitors (ICI) varies among patients, making it challenging to pre-determine whether a particular patient will respond to immunotherapy. While gene mutation is critical to the treatment outcome, a framework capable of explicitly incorporating biology knowledge has yet to be established. Here we aim to propose and validate a mutation-based deep learning model for survival analysis on 1571 patients treated with ICI. Our model achieves an average concordance index of 0.59 ± 0.13 across nine types of cancer, compared to the gold standard Cox-PH model (0.52 ± 0.10). The "black box" nature of deep learning is a major concern in healthcare field. This model's interpretability, which results from incorporating the gene pathways and protein interaction (i.e., biology-aware) rather than relying on a 'black box' approach, helps patient stratification and provides insight into novel gene biomarkers, advancing our understanding of ICI treatment.

The local microenvironment drives activation of neutrophils in human brain tumors

Neutrophils are abundant immune cells in the circulation and frequently infiltrate tumors in substantial numbers. However, their precise functions in different cancer types remain incompletely understood, including in the brain microenvironment. We therefore investigated neutrophils in tumor tissue of glioma and brain metastasis patients, with matched peripheral blood, and herein describe the first in-depth analysis of neutrophil phenotypes and functions in these tissues. Orthogonal profiling strategies in humans and mice revealed that brain tumor-associated neutrophils (TANs) differ significantly from blood neutrophils and have a prolonged lifespan and immune-suppressive and pro-angiogenic capacity. TANs exhibit a distinct inflammatory signature, driven by a combination of soluble inflammatory mediators including tumor necrosis factor alpha (TNF-ɑ) and Ceruloplasmin, which is more pronounced in TANs from brain metastasis versus glioma. Myeloid cells, including tumor-associated macrophages, emerge at the core of this network of pro-inflammatory mediators, supporting the concept of a critical myeloid niche regulating overall immune suppression in human brain tumors.

NR2F6, a new immune checkpoint that acts as a potential biomarker of immunosuppression and contributes to poor clinical outcome in human glioma

Intoroduction

Nuclear receptor subfamily 2 group F member 6 (NR2F6) is a promising checkpoint target for cancer immunotherapy. However, there has been no investigation of NR2F6 in glioma. Our study systematically explored the clinical characteristics and biological functions of NR2F6 in gliomas.

Methods

We extracted RNA sequencing (RNA-seq) data of 663 glioma samples from The Cancer Genome Atlas (TCGA) as the training cohort and 325 samples from the Chinese Glioma Genome Atlas (CGGA) as the validation cohort. We also confirmed the NR2F6 gene expression feature in our own cohort of 60 glioma patients. R language and GraphPad Prism softwares were mainly used for statistical analysis and graphical work.

Results

We found that NR2F6 was significantly related to high tumor aggressiveness and poor outcomes for glioma patients. Functional enrichment analysis demonstrated that NR2F6 was associated with many biological processes that are related to glioma progression, such as angiogenesis, and with multiple immune-related functions. Moreover, NR2F6 was found to be significantly correlated with stromal and immune infiltration in gliomas. Subsequent analysis based on Gliomas single-cell sequencing datasets showed that NR2F6 was expressed in immune cells, tumor cells, and stromal cells. Mechanistically, results suggested that NR2F6 might act as a potential immunosuppression-mediated molecule in the glioma microenvironment through multiple ways, such as the recruitment of immunosuppressive cells, secretion of immunosuppressive cytokines, M2 polarization of macrophages, in addition to combining with other immune checkpoint inhibitors.

Conclusion

Our findings indicated that intracellular targeting of NR2F6 in both immune cells and tumor cells, as well as stromal cells, may represent a promising immunotherapeutic strategy for glioma. Stromal cells, may represent a promising immunotherapeutic strategy for glioma.

Dendritic cell vaccines improve the glioma microenvironment: Influence, challenges, and future directions

INTRODUCTION

Gliomas, especially the glioblastomas, are one of the most aggressive intracranial tumors with poor prognosis. This might be explained by the heterogeneity of tumor cells and the inhibitory immunological microenvironment. Dendritic cells (DCs), as the most potent in vivo functional antigen-presenting cells, link innate immunity with adaptive immunity. However, their function is suppressed in gliomas. Therefore, overcoming the dysfunction of DCs in the TME might be critical to treat gliomas.

METHOD

In this paper we proposed the specificity of the glioma microenvironment, analyzed the pathways leading to the dysfunction of DCs in tumor microenvironment of patients with glioma, summarized influence of DC-based immunotherapy on the tumor microenvironment and proposed new development directions and possible challenges of DC vaccines.

RESULT

DC vaccines can improve the immunosuppressive microenvironment of glioma patients. It will bring good treatment prospects to patients. We also proposed new development directions and possible challenges of DC vaccines, thus providing an integrated understanding of efficacy on DC vaccines for glioma treatment.

Identification and validation of an anoikis-associated gene signature to predict clinical character, stemness, IDH mutation, and immune filtration in glioblastoma

Background

Glioblastoma (GBM) is the most prominent and aggressive primary brain tumor in adults. Anoikis is a specific form of programmed cell death that plays a key role in tumor invasion and metastasis. The presence of anti-anoikis factors is associated with tumor aggressiveness and drug resistance.

Methods

The non-negative matrix factorization algorithm was used for effective dimension reduction for integrated datasets. Differences in the tumor microenvironment (TME), stemness indices, and clinical characteristics between the two clusters were analyzed. Difference analysis, weighted gene coexpression network analysis (WGCNA), univariate Cox regression, and least absolute shrinkage and selection operator regression were leveraged to screen prognosis-related genes and construct a risk score model. Immunohistochemistry was performed to evaluate the expression of representative genes in clinical specimens. The relationship between the risk score and the TME, stemness, clinical traits, and immunotherapy response was assessed in GBM and pancancer.

Results

Two definite clusters were identified on the basis of anoikis-related gene expression. Patients with GBM assigned to C1 were characterized by shortened overall survival, higher suppressive immune infiltration levels, and lower stemness indices. We further constructed a risk scoring model to quantify the regulatory patterns of anoikis-related genes. The higher risk score group was characterized by a poor prognosis, the infiltration of suppressive immune cells and a differentiated phenotype, whereas the lower risk score group exhibited the opposite effects. In addition, patients in the lower risk score group exhibited a higher frequency of isocitrate dehydrogenase (IDH) mutations and a more sensitive response to immunotherapy. Drug sensitivity analysis was performed, revealing that the higher risk group may benefit more from drugs targeting the PI3K/mTOR signaling pathway.

Conclusion

We revealed potential relationships between anoikis-related genes and clinical features, TME, stemness, IDH mutation, and immunotherapy and elucidated their therapeutic value.

Combinatorial approaches to effective therapy in glioblastoma (GBM): Current status and what the future holds

The aggressive and recurrent nature of glioblastoma is multifactorial and has been attributed to its biological heterogeneity, dysfunctional metabolic signaling pathways, rigid blood-brain barrier, inherent resistance to standard therapy due to the stemness property of the gliomas cells, immunosuppressive tumor microenvironment, hypoxia and neoangiogenesis which are very well orchestrated and create the tumor's own highly pro-tumorigenic milieu. Once the relay of events starts amongst these components, eventually it becomes difficult to control the cascade using only the balanced contemporary care of treatment consisting of maximal resection, radiotherapy and chemotherapy with temozolamide. Over the past few decades, implementation of contemporary treatment modalities has shown benefit to some extent, but no significant overall survival benefit is achieved. Therefore, there is an unmet need for advanced multifaceted combinatorial strategies. Recent advances in molecular biology, development of innovative therapeutics and novel delivery platforms over the years has resulted in a paradigm shift in gliomas therapeutics. Decades of research has led to emergence of several treatment molecules, including immunotherapies such as immune checkpoint blockade, oncolytic virotherapy, adoptive cell therapy, nanoparticles, CED and BNCT, each with the unique proficiency to overcome the mentioned challenges, present research. Recent years are seeing innovative combinatorial strategies to overcome the multifactorial resistance put forth by the GBM cell and its TME. This review discusses the contemporary and the investigational combinatorial strategies being employed to treat GBM and summarizes the evidence accumulated till date.

Expression and Prognostic Role of Glia Maturation Factor-γ in Gliomas

Background

Glia maturation factor-γ (GMFG) regulates actin cytoskeletal organization and promotes the invasion of cancer cells. However, its expression pattern and molecular function in gliomas have not been clearly defined.

Methods

In this study, public datasets comprising 2,518 gliomas samples were used to explore GMFG expression and its correlation with malignancy in gliomas. Immunohistochemistry (IHC) staining was performed to determine the expression of GMFG in gliomas using an in-house cohort that contained 120 gliomas samples. Gene ontology enrichment analysis was conducted using the DAVID tool. The correlation between GMFG expression and immune cell infiltration was evaluated using TIMER, Tumor Immune Single-Cell Hub (TISCH) database, and IHC staining assays. The Kaplan–Meier analysis was performed to determine the prognostic role of GMFG and its association with temozolomide (TMZ) response in gliomas.

Results

The GMFG expression was higher in gliomas compared with non-tumor brain tissues both in public datasets and in-house cohort. High expression of GMFG was significantly associated with WHO grade IV, IDH 1/2 wild-type, and mesenchymal (ME) subtypes. Bioinformatic prediction and IHC analysis revealed that GMFG expression obviously correlated with the macrophage marker CD163 in gliomas. Moreover, both lower grade glioma (LGG) and glioblastoma multiforme (GBM) patients with high GMFG expression had shorter overall survival than those with low GMFG expression. These results indicate that GMFG may be a therapeutic target for the treatment of such patients. Patients with low GMFG expression who received chemotherapy had a longer survival time than those with high GMFG expression. For patients who received ion radiotherapy (IR) only, the GMFG expression level had no effect on the overall survival neither in CGGA and TCGA datasets.

Conclusion

The GMFG is a novel prognostic biomarker for patients with both LGG and GBM. Increased GMFG expression is associated with tumor-associated macrophages (TAMs) infiltration and with a bad response to TMZ treatment.

Glioblastoma Treatment: State-of-the-Art and Future Perspectives

(1) Background: Glioblastoma is the most frequent and lethal primary tumor of the central nervous system. Through many years, research has brought various advances in glioblastoma treatment. At this time, glioblastoma management is based on maximal safe surgical resection, radiotherapy, and chemotherapy with temozolomide. Recently, bevacizumab has been added to the treatment arsenal for the recurrent scenario. Nevertheless, patients with glioblastoma still have a poor prognosis. Therefore, many efforts are being made in different clinical research areas to find a new alternative to improve overall survival, free-progression survival, and life quality in glioblastoma patients. (2) Methods: Our objective is to recap the actual state-of-the-art in glioblastoma treatment, resume the actual research and future perspectives on immunotherapy, as well as the new synthetic molecules and natural compounds that represent potential future therapies at preclinical stages. (3) Conclusions: Despite the great efforts in therapeutic research, glioblastoma management has suffered minimal changes, and the prognosis remains poor. Combined therapeutic strategies and delivery methods, including immunotherapy, synthetic molecules, natural compounds, and glioblastoma stem cell inhibition, may potentiate the standard of care therapy and represent the next step in glioblastoma management research.

Modulation of the Gal-9/TIM-3 Immune Checkpoint with α-Lactose. Does Anomery of Lactose Matter?

Simple Summary

The disaccharide lactose is a common excipient in pharmaceutical products. In addition, the two anomers α- and β-lactose can exert immuno-modulatory effects. α-Lactose functions as a major regulator of the T-cell immunoglobulin mucin-3 (Tim-3)/Galectin-9 (Gal-9) immune checkpoint, through direct binding to the β-galactoside-binding lectin galectin-9. The blockade of TIM-3 with monoclonal antibodies or small molecules represents a promising approach to combat onco-hematological diseases, in particular myelodysplastic syndromes, and acute myeloid leukemia. Alternatively, the activity of the checkpoint can be modulated via targeting of Gal-9 with both α- and β-lactose. In fact, lactose is a quasi-pan-galectin ligand, capable of modulating the functions of most of the 16 galectin molecules. This review discusses the capacity of lactose and Gal-9 to modulate the TIM-3/Gal-9 and PD-1/PD-L1 immune checkpoints in oncology. The immuno-regulatory roles of lactose and Gal-9 are highlighted.

Abstract

The disaccharide lactose is an excipient commonly used in pharmaceutical products. The two anomers, α- and β-lactose (α-L/β-L), differ by the orientation of the C-1 hydroxyl group on the glucose unit. In aqueous solution, a mutarotation process leads to an equilibrium of about 40% α-L and 60% β-L at room temperature. Beyond a pharmaceutical excipient in solid products, α-L has immuno-modulatory effects and functions as a major regulator of TIM-3/Gal-9 immune checkpoint, through direct binding to the β-galactoside-binding lectin galectin-9. The blockade of the co-inhibitory checkpoint TIM-3 expressed on T cells with anti-TIM-3 antibodies represents a promising approach to combat different onco-hematological diseases, in particular myelodysplastic syndromes and acute myeloid leukemia. In parallel, the discovery and development of anti-TIM-3 small molecule ligands is emerging, including peptides, RNA aptamers and a few specifically designed heterocyclic molecules. An alternative option consists of targeting the different ligands of TIM-3, notably Gal-9 recognized by α-lactose. Modulation of the TIM-3/Gal-9 checkpoint can be achieved with both α- and β-lactose. Moreover, lactose is a quasi-pan-galectin ligand, capable of modulating the functions of most of the 16 galectin molecules. The present review provides a complete analysis of the pharmaceutical and galectin-related biological functions of (α/β)-lactose. A focus is made on the capacity of lactose and Gal-9 to modulate both the TIM-3/Gal-9 and PD-1/PD-L1 immune checkpoints in oncology. Modulation of the TIM-3/Gal-9 checkpoint is a promising approach for the treatment of cancers and the role of lactose in this context is discussed. The review highlights the immuno-regulatory functions of lactose, and the benefit of the molecule well beyond its use as a pharmaceutical excipient.

Efferocytosis in the Central Nervous System

The effective clearance of apoptotic cells is essential for maintaining central nervous system (CNS) homeostasis and restoring homeostasis after injury. In most cases of physiological apoptotic cell death, efferocytosis prevents inflammation and other pathological conditions. When apoptotic cells are not effectively cleared, destruction of the integrity of the apoptotic cell membrane integrity, leakage of intracellular contents, and secondary necrosis may occur. Efferocytosis is the mechanism by which efferocytes quickly remove apoptotic cells from tissues before they undergo secondary necrosis. Cells with efferocytosis functions, mainly microglia, help to eliminate apoptotic cells from the CNS. Here, we discuss the impacts of efferocytosis on homeostasis, the mechanism of efferocytosis, the associations of efferocytosis failure and CNS diseases, and the current clinical applications of efferocytosis. We also identify efferocytosis as a novel potential target for exploring the causes and treatments of CNS diseases.

BSA-MnO2-SAL multifunctional nanoparticle-mediated M1 macrophages polarization for glioblastoma therapy

Glioblastoma (GBM) is a type of brain tumour with a very high fatality rate. Owing to the presence of the blood-brain barrier (BBB), it is difficult for drugs to reach the tumour site; thus, there has been little progress in GBM chemotherapeutics. Furthermore, the malignant growth of tumours largely depends on the tumour microenvironment. GBM is especially prevalent in slightly acidic, hydrogen peroxide (H₂O₂)-rich, hypoxic, and immunosuppressive microenvironments. Tumour-supporting macrophages (M₂ macrophages) are a type of immune cell that promote tumour growth. Therefore, targeting M₂ macrophages and repolarizing them into tumour-suppressor macrophages (M₁ macrophages) are important strategies for GBM treatment. Salinomycin (SAL) is an anti-tumour drug that can improve the tumour immune microenvironment. Interestingly, we found that SAL promoted the expression of M₁ macrophages in vitro, but its ability was limited in vivo because of the presence of the BBB. In this study, we combined SAL and MnO₂ to design bovine serum albumin-MnO₂-SAL (BMS), a nanoparticle that responds to acidic and H₂O₂-rich microenvironments. Our experimental results showed that BMS reduced GBM growth efficiency and had the ability to penetrate the BBB. It also enhanced the repolarization ability of SAL owing to the production of Mn²⁺ after decomposition, which could be applied in Magnetic Resonance Imaging (MRI). This study demonstrated that the multifunctional nanoparticle BMS is of great significance in inhibiting orthotopic GBM growth and improving immunosuppressive microenvironments.