The glioblastoma multiforme tumor site promotes the commitment of tumor-infiltrating lymphocytes to the TH17 lineage in humans

The role of IL-17 in the pathogenesis and treatment of glioblastoma-an update on the state of the art and future perspectives

Glioblastoma (GBM) is the most common malignant brain tumor, which, despite significant progress made in the last years in the field of neuro-oncology, remains an incurable disease. GBM has a poor prognosis with a median survival of 12-15 months, and its aggressive clinical course is related to rapid growth, extensive infiltration of adjacent tissues, resistance to chemotherapy, radiotherapy and immunotherapy, and frequent relapse. Currently, several molecular biomarkers are used in clinical practice to predict patient prognosis and response to treatment. However, due to the overall unsatisfactory efficacy of standard multimodal treatment and the remaining poor prognosis, there is an urgent need for new biomarkers and therapeutic strategies for GBM. Recent evidence suggests that GBM tumorigenesis is associated with crosstalk between cancer, immune and stromal cells mediated by various cytokines. One of the key factors involved in this process appears to be interleukin-17 (IL-17), a pro-inflammatory cytokine that is significantly upregulated in the serum and tissue of GBM patients. IL-17 plays a key role in tumorigenesis, angiogenesis, and recurrence of GBM by activating pro-oncogenic signaling pathways and promoting cell survival, proliferation, and invasion. IL-17 facilitates the immunomodulation of the tumor microenvironment by promoting immune cells infiltration and cytokine secretion. In this article we review the latest scientific reports to provide an update on the role of IL-17 role in tumorigenesis, tumor microenvironment, diagnosis, prognosis, and treatment of GBM.

Non-Tumor Cells within the Tumor Microenvironment-The "Eminence Grise" of the Glioblastoma Pathogenesis and Potential Targets for Therapy

Glioblastoma (GBM) is the most common malignancy of the central nervous system in adults. GBM has high levels of therapy failure and its prognosis is usually dismal. The phenotypic heterogeneity of the tumor cells, dynamic complexity of non-tumor cell populations within the GBM tumor microenvironment (TME), and their bi-directional cross-talk contribute to the challenges of current therapeutic approaches. Herein, we discuss the etiology of GBM, and describe several major types of non-tumor cells within its TME, their impact on GBM pathogenesis, and molecular mechanisms of such an impact. We also discuss their value as potential therapeutic targets or prognostic biomarkers, with reference to the most recent works on this subject. We conclude that unless all "key player" populations of non-tumor cells within the TME are considered, no breakthrough in developing treatment for GBM can be achieved.

Basic Science of Neuroinflammation and Involvement of the Inflammatory Response in Disorders of the Nervous System

Neuroinflammation is a key immune response observed in many neurologic diseases. Although an appropriate immune response can be beneficial, aberrant activation of this response recruits excessive proinflammatory cells to cause damage. Because the central nervous system is separated from the periphery by the blood-brain barrier (BBB) that creates an immune-privileged site, it has its own unique immune cells and immune response. Moreover, neuroinflammation can compromise the BBB causing an influx of peripheral immune cells and factors. Recent advances have brought a deeper understanding of neuroinflammation that can be leveraged to develop more potent therapies and improve patient selection.

Radiogenomic biomarkers for immunotherapy in glioblastoma: A systematic review of magnetic resonance imaging studies

Background

Immunotherapy is an effective "precision medicine" treatment for several cancers. Imaging signatures of the underlying genome (radiogenomics) in glioblastoma patients may serve as preoperative biomarkers of the tumor-host immune apparatus. Validated biomarkers would have the potential to stratify patients during immunotherapy clinical trials, and if trials are beneficial, facilitate personalized neo-adjuvant treatment. The increased use of whole genome sequencing data, and the advances in bioinformatics and machine learning make such developments plausible. We performed a systematic review to determine the extent of development and validation of immune-related radiogenomic biomarkers for glioblastoma.

Methods

A systematic review was performed following PRISMA guidelines using the PubMed, Medline, and Embase databases. Qualitative analysis was performed by incorporating the QUADAS 2 tool and CLAIM checklist. PROSPERO registered: CRD42022340968. Extracted data were insufficiently homogenous to perform a meta-analysis.

Results

Nine studies, all retrospective, were included. Biomarkers extracted from magnetic resonance imaging volumes of interest included apparent diffusion coefficient values, relative cerebral blood volume values, and image-derived features. These biomarkers correlated with genomic markers from tumor cells or immune cells or with patient survival. The majority of studies had a high risk of bias and applicability concerns regarding the index test performed.

Conclusions

Radiogenomic immune biomarkers have the potential to provide early treatment options to patients with glioblastoma. Targeted immunotherapy, stratified by these biomarkers, has the potential to allow individualized neo-adjuvant precision treatment options in clinical trials. However, there are no prospective studies validating these biomarkers, and interpretation is limited due to study bias with little evidence of generalizability.

Targeting immunogenic cell death for glioma immunotherapy

Immunogenic cell death (ICD) arouses great interest in targeting glioma, the most common primary brain tumor, to achieve boosted immunotherapy. We discuss the unexpected findings on the induction of Th17 immunity by ICD and propose the best design for dendritic cell (DC)-based vaccines loaded with whole glioma lysates obtained after ICD inducers.

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology

INTRODUCTION

Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming.

OBJECTIVE

To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level.

METHODS

We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically.

RESULTS

The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level.

CONCLUSIONS

This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Cellular Cancer Immunotherapy Development and Manufacturing in the Clinic

The transfusion of naturally derived or modified cellular therapies, referred to as adoptive cell therapy (ACT), has demonstrated clinical efficacy in the treatment of hematologic malignancies and metastatic melanoma. In addition, cellular vaccination, such as dendritic cell-based cancer vaccines, continues to be actively explored. The manufacturing of these therapies presents a considerable challenge to expanding the use of ACT as a viable treatment modality, particularly at academic production facilities. Furthermore, the expanding commercial interest in ACT presents new opportunities as well as strategic challenges for the future vision of cellular manufacturing in academic centers. Current trends in the production of ACT at tertiary care centers and prospects for improved manufacturing practices that will foster further clinical benefit are reviewed herein.

The Prognostic Impact of Gender, Therapeutic Strategies, Molecular Background, and Tumor-Infiltrating Lymphocytes in Glioblastoma: A Still Unsolved Jigsaw

Despite the adoption of novel therapeutical approaches, the outcomes for glioblastoma (GBM) patients remain poor. In the present study, we investigated the prognostic impact of several clinico-pathological and molecular features as well as the role of the cellular immune response in a series of 59 GBM. CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) were digitally assessed on tissue microarray cores and their prognostic role was investigated. Moreover, the impact of other clinico-pathological features was evaluated. The number of CD4+ and CD8+ is higher in GBM tissue compared to normal brain tissue (p < 0.0001 and p = 0.0005 respectively). A positive correlation between CD4+ and CD8+ in GBM is present (rs = 0.417-p = 0.001). CD4+ TILs are inversely related to overall survival (OS) (HR = 1.79, 95% CI 1.1-3.1, p = 0.035). The presence of low CD4+ TILs combined with low CD8+ TILs is an independent predictor of longer OS (HR 0.38, 95% CI 0.18-0.79, p = 0.014). Female sex is independently related to longer OS (HR 0.42, 95% CI 0.22-0.77, p = 0.006). Adjuvant treatment, methylguanine methyltransferase (MGMT) promoter methylation, and age remain important prognostic factors but are influenced by other features. Adaptive cell-mediated immunity can affect the outcomes of GBM patients. Further studies are needed to elucidate the commitment of the CD4+ cells and the effects of different TILs subpopulations in GBM.

DC vaccines loaded with glioma cells killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a four-gene signature for glioma prognosis

Gliomas, the most frequent type of primary tumor of the central nervous system in adults, results in significant morbidity and mortality. Despite the development of novel, complex, multidisciplinary, and targeted therapies, glioma therapy has not progressed much over the last decades. Therefore, there is an urgent need to develop novel patient-adjusted immunotherapies that actively stimulate antitumor T cells, generate long-term memory, and result in significant clinical benefits. This work aimed to investigate the efficacy and molecular mechanism of dendritic cell (DC) vaccines loaded with glioma cells undergoing immunogenic cell death (ICD) induced by photosens-based photodynamic therapy (PS-PDT) and to identify reliable prognostic gene signatures for predicting the overall survival of patients. Analysis of the transcriptional program of the ICD-based DC vaccine led to the identification of robust induction of Th17 signature when used as a vaccine. These DCs demonstrate retinoic acid receptor-related orphan receptor-γt dependent efficacy in an orthotopic mouse model. Moreover, comparative analysis of the transcriptome program of the ICD-based DC vaccine with transcriptome data from the TCGA-LGG dataset identified a four-gene signature (CFH, GALNT3, SMC4, VAV3) associated with overall survival of glioma patients. This model was validated on overall survival of CGGA-LGG, TCGA-GBM, and CGGA-GBM datasets to determine whether it has a similar prognostic value. To that end, the sensitivity and specificity of the prognostic model for predicting overall survival were evaluated by calculating the area under the curve of the time-dependent receiver operating characteristic curve. The values of area under the curve for TCGA-LGG, CGGA-LGG, TCGA-GBM, and CGGA-GBM for predicting five-year survival rates were, respectively, 0.75, 0.73, 0.9, and 0.69. These data open attractive prospects for improving glioma therapy by employing ICD and PS-PDT-based DC vaccines to induce Th17 immunity and to use this prognostic model to predict the overall survival of glioma patients.