Immunotherapy for gliomas: shedding light on progress in preclinical and clinical development

Spatiotemporal Insights into Glioma Oncostream Dynamics: Unraveling Formation, Stability, and Disassembly Pathways

Glioblastoma (GBM) remains a challenge in Neuro-oncology, with a poor prognosis showing only a 5% survival rate beyond two years. This is primarily due to its aggressiveness and intra-tumoral heterogeneity, which limits complete surgical resection and reduces the efficacy of existing treatments. The existence of oncostreams-neuropathological structures comprising aligned spindle-like cells from both tumor and non-tumor origins- is discovered earlier. Oncostreams are closely linked to glioma aggressiveness and facilitate the spread into adjacent healthy brain tissue. A unique molecular signature intrinsic to oncostreams, with overexpression of key genes (i.e., COL1A1, ACTA2) that drive the tumor's mesenchymal transition and malignancy is also identified. Pre-clinical studies on genetically engineered mouse models demonstrated that COL1A1 inhibition disrupts oncostreams, modifies TME, reduces mesenchymal gene expression, and extends survival. An in vitro model using GFP+ NPA cells to investigate how various treatments affect oncostream dynamics is developed. Analysis showed that factors such as cell density, morphology, neurotransmitter agonists, calcium chelators, and cytoskeleton-targeting drugs influence oncostream formation. This data illuminate the patterns of glioma migration and suggest anti-invasion strategies that can improve GBM patient outcomes when combined with traditional therapies. This work highlights the potential of targeting oncostreams to control glioma invasion and enhance treatment efficacy.

Machine learning-based identification of glycosyltransferase-related mRNAs for improving outcomes and the anti-tumor therapeutic response of gliomas

Background: Glycosyltransferase participates in glycosylation modification, and glycosyltransferase alterations are involved in carcinogenesis, progression, and immune evasion, leading to poor outcomes. However, in-depth studies on the influence of glycosyltransferase on clinical outcomes and treatments are lacking. Methods: The analysis of differentially expressed genes was performed using the Gene Expression Profiling Interactive Analysis 2 database. A total of 10 machine learning algorithms were introduced, namely, random survival forest, elastic network, least absolute shrinkage and selection operator, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox, supervised principal components, generalized boosted regression modeling, and survival support vector machine. Gene Set Enrichment Analysis was performed to explore signaling pathways regulated by the signature. Cell-type identification by estimating relative subsets of RNA transcripts was used for estimating the fractions of immune cell types. Results: Here, we analyzed the genomic and expressive alterations in glycosyltransferase-related genes in gliomas. A combination of 80 machine learning algorithms was introduced to establish the glycosyltransferase-related mRNA signature (GRMS) based on 2,030 glioma samples from The Cancer Genome Atlas Program, Chinese Glioma Genome Atlas, Rembrandt, Gravendeel, and Kamoun cohorts. The GRMS was identified as an independent hazardous factor for overall survival and exhibited stable and robust performance. Notably, gliomas in the high-GRMS subgroup exhibited abundant tumor-infiltrating lymphocytes and tumor mutation burden values, increased expressive levels of hepatitis A virus cellular receptor 2 and CD274, and improved progression-free survival when subjected to anti-tumor immunotherapy. Conclusion: The GRMS may act as a powerful and promising biomarker for improving the clinical prognosis of glioma patients.

Challenges and advances for glioma therapy based on inorganic nanoparticles

Glioma is one of the most serious central nervous system diseases, with high mortality and poor prognosis. Despite the continuous development of existing treatment methods, the median survival time of glioma patients is still only 15 months. The main treatment difficulties are the invasive growth of glioma and the obstruction of the blood-brain barrier (BBB) to drugs. With rapid advancements in nanotechnology, inorganic nanoparticles (INPs) have shown favourable application prospects in the diagnosis and treatment of glioma. Due to their extraordinary intrinsic features, INPs can be easily fabricated, while doping with other elements and surface modification by biological ligands can be used to enhance BBB penetration, targeted delivery and biocompatibility. Guided glioma theranostics with INPs can improve and enhance the efficacy of traditional methods such as chemotherapy, radiotherapy and gene therapy. New strategies, such as immunotherapy, photothermal and photodynamic therapy, magnetic hyperthermia therapy, and multifunctional inorganic nanoplatforms, have also been facilitated by INPs. This review emphasizes the current state of research and clinical applications of INPs, including glioma targeting and BBB penetration enhancement methods, in vivo and in vitro biocompatibility, and diagnostic and treatment strategies. As such, it provides insights for the development of novel glioma treatment strategies.

Molecular subtypes based on centrosome-related genes can predict prognosis and therapeutic responsiveness in patients with low-grade gliomas

Background

Abnormalities in centrosome regulatory genes can induce chromosome instability, cell differentiation errors, and tumorigenesis. However, a limited number of comprehensive analyses of centrosome-related genes have been performed in low-grade gliomas (LGG).

Methods

LGG data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. The ConsensusClusterPlus” R package was used for unsupervised clustering. We constructed a centrosome-related genes (CRGs) signature using a random forest model, lasso Cox model, and multivariate Cox model, and quantified the centrosome-related risk score (centS). The prognostic prediction efficacy of centS was evaluated using a Receiver Operating Characteristic (ROC) curve. Immune cell infiltration and genomic mutational landscapes were evaluated using the ESTIMATE algorithm, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm, and “maftools” R package, respectively. Differences in clinical features, isocitrate dehydrogenase (IDH) mutation, 1p19q codeletion, O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation, and response to antitumor therapy between the high- and low-centS groups were explored. “pRRophetic” R packages were used for temozolomide (TMZ) sensitivity analysis. qRT-PCR verified the differential expression of the centrosomal gene team, the core of which is CEP135, between LGG cells and normal cells.

Results

Two distinct CRG-based clusters were identified using consensus unsupervised clustering analysis. The prognosis, biological characteristics, and immune cell infiltration of the two clusters differed significantly. A well-performing centS signature was developed to predict the prognosis of patients with LGG based on 12 potential CRGs. We found that patients in the high-centS group showed poorer prognosis and lower proportion of IDH mutation and 1p19q codeletion compared to those in the low-centS group. Furthermore, patients in the high-centS group showed higher sensitivity to TMZ, higher tumor mutation burden, and immune cell infiltration. Finally, we identified a centrosomal gene team whose core was CEP135, and verified their differential expression between LGG cells and normal glial cells.

Conclusion

Our findings reveal a novel centrosome-related signature for predicting the prognosis and therapeutic responsiveness of patients with LGG. This may be helpful for the accurate clinical treatment of LGG.

A prognostic NAD+ metabolism-related gene signature for predicting response to immune checkpoint inhibitor in glioma

Background

Nicotinamide adenine dinucleotide (NAD+) metabolism is involved in a series of cancer pathogenesis processes, and is considered a promising therapeutic target for cancer treatment. However, a comprehensive analysis of NAD+ metabolism events on immune regulation and cancer survival has not yet been conducted. Here, we constructed a prognostic NAD+ metabolism-related gene signature (NMRGS) associated with immune checkpoint inhibitor (ICI) efficacy in glioma.

Methods

40 NAD+ metabolism-related genes (NMRGs) were obtained from the Reactome database and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Glioma cases with transcriptome data and clinical information were obtained from Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). NMRGS was constructed based on the calculated risk score using univariate analysis, Kaplan-Meier analysis, multivariate Cox regression, and nomogram. This NMRGS was verified in training (CGGA693) and validation (TCGA and CGGA325) cohorts. The immune characteristics, mutation profile, and response to ICI therapy were subsequently analyzed for different NMRGS subgroups.

Results

Six NAD+ metabolism-related genes, including CD38, nicotinamide adenine dinucleotide kinase (NADK), nicotinate phosphoribosyltransferase (NAPRT), nicotinamide/nicotinic acid mononucleotide adenylyltransferase 3 (NMNAT3), poly(ADP-Ribose) polymerase family member 6 (PARP6), and poly(ADP-Ribose) polymerase family member 9 (PARP9), were ultimately used to construct a comprehensive risk model for glioma patients. Patients in the NMRGS-high group showed a poorer survival outcome than those in the NMRGS-low group. The area under curve (AUC) indicated that NMRGS has good potential in glioma prognostic prediction. A nomogram with improved accuracy was established based on independent prognostic factors (NMRGS score, 1p19q codeletion status, and WHO grade). Furthermore, patients in the NMRGS-high group showed a more immunosuppressive microenvironment, higher tumor mutation burden (TMB), higher human leucocyte antigen (HLA) expression and a more therapeutic response to ICI therapy.

Conclusions

This study constructed a prognostic NAD+ metabolism-related signature associated with the immune landscape in glioma, which can be used for guiding individualized ICI therapy.

The complex interactions between the cellular and non-cellular components of the brain tumor microenvironmental landscape and their therapeutic implications

Glioblastoma (GBM), an aggressive high-grade glial tumor, is resistant to therapy and has a poor prognosis due to its universal recurrence rate. GBM cells interact with the non-cellular components in the tumor microenvironment (TME), facilitating their rapid growth, evolution, and invasion into the normal brain. Herein we discuss the complexity of the interactions between the cellular and non-cellular components of the TME and advances in the field as a whole. While the stroma of non-central nervous system (CNS) tissues is abundant in fibrillary collagens, laminins, and fibronectin, the normal brain extracellular matrix (ECM) predominantly includes proteoglycans, glycoproteins, and glycosaminoglycans, with fibrillary components typically found only in association with the vasculature. However, recent studies have found that in GBMs, the microenvironment evolves into a more complex array of components, with upregulated collagen gene expression and aligned fibrillary ECM networks. The interactions of glioma cells with the ECM and the degradation of matrix barriers are crucial for both single-cell and collective invasion into neighboring brain tissue. ECM-regulated mechanisms also contribute to immune exclusion, resulting in a major challenge to immunotherapy delivery and efficacy. Glioma cells chemically and physically control the function of their environment, co-opting complex signaling networks for their own benefit, resulting in radio- and chemo-resistance, tumor recurrence, and cancer progression. Targeting these interactions is an attractive strategy for overcoming therapy resistance, and we will discuss recent advances in preclinical studies, current clinical trials, and potential future clinical applications. In this review, we also provide a comprehensive discussion of the complexities of the interconnected cellular and non-cellular components of the microenvironmental landscape of brain tumors to guide the development of safe and effective therapeutic strategies against brain cancer.

Development of immunotherapy for high-grade gliomas: Overcoming the immunosuppressive tumor microenvironment

The preclinical and clinical development of novel immunotherapies for the treatment of central nervous system (CNS) tumors is advancing at a rapid pace. High-grade gliomas (HGG) are aggressive tumors with poor prognoses in both adult and pediatric patients, and innovative and effective therapies are greatly needed. The use of cytotoxic chemotherapies has marginally improved survival in some HGG patient populations. Although several challenges exist for the successful development of immunotherapies for CNS tumors, recent insights into the genetic alterations that define the pathogenesis of HGG and their direct effects on the tumor microenvironment (TME) may allow for a more refined and targeted therapeutic approach. This review will focus on the TME in HGG, the genetic drivers frequently found in these tumors and their effect on the TME, the development of immunotherapy for HGG, and the practical challenges in clinical trials employing immunotherapy for HGG. Herein, we will discuss broadly the TME and immunotherapy development in HGG, with a specific focus on glioblastoma multiforme (GBM) as well as additional discussion in the context of the pediatric HGG diagnoses of diffuse midline glioma (DMG) and diffuse hemispheric glioma (DHG).

Inhibition of D-2HG leads to upregulation of a proinflammatory gene signature in a novel HLA-A2/HLA-DR1 transgenic mouse model of IDH1R132H-expressing glioma

BACKGROUND

Long-term prognosis of WHO grade II, isocitrate dehydrogenase (IDH)-mutated low-grade glioma (LGG) is poor due to high risks of recurrence and malignant transformation into high-grade glioma. Immunotherapy strategies are attractive given the relatively intact immune system of patients with LGG and the slow tumor growth rate. However, accumulation of the oncometabolite D-2-hydroxyglutarate (D-2HG) in IDH-mutated gliomas leads to suppression of inflammatory pathways in the tumor microenvironment, thereby contributing to the 'cold' tumor phenotype. Inhibiting D-2HG production presents an opportunity to generate a robust antitumor response following tumor antigen vaccination and immune checkpoint blockade.

METHODS

An IDH1R132H glioma model was created in syngeneic HLA-A2/HLA-DR1-transgenic mice, allowing us to evaluate the vaccination with the human leukocyte antigens (HLA)-DR1-restricted, IDH1R132H mutation-derived neoepitope. The effects of an orally available inhibitor of mutant IDH1 and IDH2, AG-881, were evaluated as monotherapy and in combination with the IDH1R132H peptide vaccination or anti-PD-1 immune checkpoint blockade.

RESULTS

The HLA-A2/HLA-DR1-syngeneic IDH1R132H cell line expressed the IDH1 mutant protein and formed D-2HG producing orthotopic gliomas in vivo. Treatment of tumor-bearing mice with AG-881 resulted in a reduction of D-2HG levels in IDH1R132H glioma cells (10 fold) and tumor-associated myeloid cells, which demonstrated high levels of intracellular D-2HG in the IDH1R132H gliomas. AG-881 monotherapy suppressed the progression of IDH1R132H gliomas in a CD4+ and CD8+ cell-dependent manner, enhanced proinflammatory IFNγ-related gene expression, and increased the number of CD4+ tumor-infiltrating T-cells. Prophylactic vaccination with the HLA-DR1-restricted IDH1R132H peptide or tumor-associated HLA-A2-restricted peptides did not enhance survival of tumor-bearing animals; however, vaccination with both HLA-A2-IDH1R132H and DR1-IDH1R132H peptides in combination with the IDH inhibitor significantly prolonged survival. Finally, tumor-bearing mice treated with both AG-881 and a PD-1 blocking antibody demonstrated improved survival when compared with either treatment alone.

CONCLUSION

The development of effective IDH1R132H-targeting vaccine may be enhanced by integration with HLA class I-restricted cytotoxic T cell epitopes and AG-881. Our HLA-A2/HLA-DR1-syngeneic IDH1R132H glioma model should allow us to evaluate key translational questions related to the development of novel strategies for patients with IDH-mutant glioma.

G-CSF secreted by mutant IDH1 glioma stem cells abolishes myeloid cell immunosuppression and enhances the efficacy of immunotherapy

Mutant isocitrate-dehydrogenase 1 (mIDH1) synthesizes the oncometabolite 2-hydroxyglutarate (2HG), which elicits epigenetic reprogramming of the glioma cells’ transcriptome by inhibiting DNA and histone demethylases. We show that the efficacy of immune-stimulatory gene therapy (TK/Flt3L) is enhanced in mIDH1 gliomas, due to the reprogramming of the myeloid cells’ compartment infiltrating the tumor microenvironment (TME). We uncovered that the immature myeloid cells infiltrating the mIDH1 TME are mainly nonsuppressive neutrophils and preneutrophils. Myeloid cell reprogramming was triggered by granulocyte colony-stimulating factor (G-CSF) secreted by mIDH1 glioma stem/progenitor-like cells. Blocking G-CSF in mIDH1 glioma–bearing mice restores the inhibitory potential of the tumor-infiltrating myeloid cells, accelerating tumor progression. We demonstrate that G-CSF reprograms bone marrow granulopoiesis, resulting in noninhibitory myeloid cells within mIDH1 glioma TME and enhancing the efficacy of immune-stimulatory gene therapy.

Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.

T-Cell Exhaustion Status Under High and Low Levels of Hypoxia-Inducible Factor 1α Expression in Glioma

Background: Hypoxia-inducible factor 1α (HIF1A), the principal regulator of hypoxia, is involved in the suppression of antitumor immunity. We aimed to describe the T-cell exhaustion status of gliomas under different levels of HIF1A expression. Methods: In this study, 692 patients, whose data were collected from the Chinese Glioma Genome Atlas (CGGA) database, and 669 patients, whose data were collected from The Cancer Genome Atlas database, were enrolled. We further screened the data of a cohort of paired primary and recurrent patients from the CGGA dataset (n = 50). The abundance of immune cells was calculated using the transcriptome data. The association between HIF1A and T-cell exhaustion-related genes and immune cells was investigated. Results: According to the median value of HIF1A expression, gliomas were classified into low-HIF1A-expression and high-HIF1A-expression groups. The expression levels of PDL1 (CD274), FOXO1, and PRDM1 in the high-HIF1A-expression group were significantly higher in both glioblastoma (GBM) and lower-grade glioma. The abundance of exhausted T cells and B cells was significantly higher in the high-HIF1A-expression group, while that of macrophage, monocyte, and natural killer cell was significantly higher in the low-HIF1A-expression group in both GBM and lower-grade glioma. After tumor recurrence, the expression of HIF1A significantly increased, and the correlation between HIF1A expression levels and exhausted T cells and induced regulatory T cells became stronger. Conclusion: In diffuse gliomas, the levels of T-cell exhaustion-associated genes and the abundance of immune cells were elevated under high HIF1A expression. Reversing hypoxia may improve the efficacy of immunotherapy.

Genetic Alterations in Gliomas Remodel the Tumor Immune Microenvironment and Impact Immune-Mediated Therapies

High grade gliomas are malignant brain tumors that arise in the central nervous system, in patients of all ages. Currently, the standard of care, entailing surgery and chemo radiation, exhibits a survival rate of 14-17 months. Thus, there is an urgent need to develop new therapeutic strategies for these malignant brain tumors. Currently, immunotherapies represent an appealing approach to treat malignant gliomas, as the pre-clinical data has been encouraging. However, the translation of the discoveries from the bench to the bedside has not been as successful as with other types of cancer, and no long-lasting clinical benefits have been observed for glioma patients treated with immune-mediated therapies so far. This review aims to discuss our current knowledge about gliomas, their molecular particularities and the impact on the tumor immune microenvironment. Also, we discuss several murine models used to study these therapies pre-clinically and how the model selection can impact the outcomes of the approaches to be tested. Finally, we present different immunotherapy strategies being employed in clinical trials for glioma and the newest developments intended to harness the immune system against these incurable brain tumors.

Targeting Neuroinflammation in Brain Cancer: Uncovering Mechanisms, Pharmacological Targets, and Neuropharmaceutical Developments

Gliomas are one of the most lethal types of cancers accounting for ∼80% of all central nervous system (CNS) primary malignancies. Among gliomas, glioblastomas (GBM) are the most aggressive, characterized by a median patient survival of fewer than 15  months. Recent molecular characterization studies uncovered the genetic signatures and methylation status of gliomas and correlate these with clinical prognosis. The most relevant molecular characteristics for the new glioma classification are IDH mutation, chromosome 1p/19q deletion, histone mutations, and other genetic parameters such as ATRX loss, TP53, and TERT mutations, as well as DNA methylation levels. Similar to other solid tumors, glioma progression is impacted by the complex interactions between the tumor cells and immune cells within the tumor microenvironment. The immune system’s response to cancer can impact the glioma’s survival, proliferation, and invasiveness. Salient characteristics of gliomas include enhanced vascularization, stimulation of a hypoxic tumor microenvironment, increased oxidative stress, and an immune suppressive milieu. These processes promote the neuro-inflammatory tumor microenvironment which can lead to the loss of blood-brain barrier (BBB) integrity. The consequences of a compromised BBB are deleteriously exposing the brain to potentially harmful concentrations of substances from the peripheral circulation, adversely affecting neuronal signaling, and abnormal immune cell infiltration; all of which can lead to disruption of brain homeostasis. In this review, we first describe the unique features of inflammation in CNS tumors. We then discuss the mechanisms of tumor-initiating neuro-inflammatory microenvironment and its impact on tumor invasion and progression. Finally, we also discuss potential pharmacological interventions that can be used to target neuro-inflammation in gliomas.