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Journal of Neuro-oncology Aug 2022Gliomas are the most common primary tumors of the central nervous system and are categorized by the World Health Organization into either low-grade (grades 1 and 2) or... (Review)
Review
PURPOSE
Gliomas are the most common primary tumors of the central nervous system and are categorized by the World Health Organization into either low-grade (grades 1 and 2) or high-grade (grades 3 and 4) gliomas. A subset of patients with glioma may experience no tumor-related symptoms and be incidentally diagnosed. These incidental low-grade gliomas (iLGG) maintain controversial treatment course despite scientific advancements. Here we highlight the recent advancements in classification, neuroimaging, and surgical management of these tumors.
METHODS
A review of the literature was performed. The authors created five subtopics of focus: histological criteria, diagnostic imaging, surgical advancements, correlation of surgical resection and survival outcomes, and clinical implications.
CONCLUSIONS
Alternating studies suggest that these tumors may experience higher mutational rates than their counterparts. Significant progress in management of gliomas, regardless of the grade, has been made through modern neurosurgical treatment modalities, diagnostic neuroimaging, and a better understanding of the genetic composition of these tumors. An optimal treatment approach for patients with newly diagnosed iLGG remains ill-defined despite multiple studies arguing in favor of safe maximal resection. Our review emphasizes the not so benign nature of incidental low grade glioma and further supports the need for future studies to evaluate survival outcomes following surgical resection.
Topics: Brain Neoplasms; Glioma; Humans; Neurosurgical Procedures; Treatment Outcome
PubMed: 35704158
DOI: 10.1007/s11060-022-04045-0 -
CNS Neuroscience & Therapeutics Aug 2023Gliomas are the most common primary malignant tumors in the central nervous system. However, conventional treatments, such as surgical resection and postoperative... (Review)
Review
Gliomas are the most common primary malignant tumors in the central nervous system. However, conventional treatments, such as surgical resection and postoperative combined chemo- and radio-therapy, are ineffective in improving patients' long-term survival. The tumor microenvironment (TME) consists of stromal cells, tumor components, and innate and acquired immune cells, and these cells, along with the extracellular matrix, regulate and communicate intercellularly to promote TME formation. The immune microenvironment plays a vital role in the development of glioma. Exosomes, which are extracellular vesicles (EVs), facilitate intercellular communication and regulation within the TME. Tumor cells can release exosomes to transmit messages, induce macrophage polarization, and inhibit immune cell activity, ultimately promoting metastasis and immune evasion. Moreover, immune cells can regulate tumorigenesis and progression through exosomes. This review summarized the biological properties of exosomes and their effects on the tumor microenvironment and provides an overview of the interactions between glioma cells and immune cells.
Topics: Humans; Exosomes; Tumor Microenvironment; Glioma; Extracellular Vesicles; Cell Communication; Neoplasms
PubMed: 37170647
DOI: 10.1111/cns.14239 -
Cells Mar 2021Despite advances in understanding of the molecular pathogenesis of glioma, outcomes remain dismal. Developing successful treatments for glioma requires faithful in vivo... (Review)
Review
Despite advances in understanding of the molecular pathogenesis of glioma, outcomes remain dismal. Developing successful treatments for glioma requires faithful in vivo disease modeling and rigorous preclinical testing. Murine models, including xenograft, syngeneic, and genetically engineered models, are used to study glioma-genesis, identify methods of tumor progression, and test novel treatment strategies. Since the discovery of highly recurrent isocitrate dehydrogenase (IDH) mutations in lower-grade gliomas, there is increasing emphasis on effective modeling of IDH mutant brain tumors. Improvements in preclinical models that capture the phenotypic and molecular heterogeneity of gliomas are critical for the development of effective new therapies. Herein, we explore the current status, advancements, and challenges with contemporary murine glioma models.
Topics: Animals; Biomedical Research; Disease Models, Animal; Genetic Engineering; Glioma; Mice; Mutation; Xenograft Model Antitumor Assays
PubMed: 33806933
DOI: 10.3390/cells10030712 -
Experimental Cell Research Mar 2023Glioma is a common type of brain tumor with high incidence and mortality rates. Iron plays an important role in various physiological and pathological processes. Iron... (Review)
Review
Glioma is a common type of brain tumor with high incidence and mortality rates. Iron plays an important role in various physiological and pathological processes. Iron entry into the cell is promoted by binding the transferrin receptor 2 (TFR2) to the iron-transferrin complex. This study was designed to assess the association between TFR2 and ferroptosis in glioma. Lipid peroxidation levels in glioma cells were assessed by determination of lipid reactive oxygen species (ROS), glutathione content, and mitochondrial membrane potential. The effect of TFR2 on TMZ sensitivity was examined by cell viability assays, flow cytometry, and colony formation assays. We found that Low TFR2 expression predicted a better prognosis for glioma patients. And overexpression of TFR2 promoted the production of reactive oxygen species and lipid peroxidation in glioma cells, thereby further promoting ferroptosis. This could be reversed by the ferroptosis inhibitors Fer-1 and DFO (both inhibitors of ferroptosis). Moreover, TFR2 potentiated the cytotoxic effect of TMZ (temozolomide) via activating ferroptosis. In conclusion, we found that TFR2 induced ferroptosis and enhanced TMZ sensitivity in gliomas. Our findings might provide a new treatment strategy for glioma patients and improve their prognosis.
Topics: Humans; Temozolomide; Ferroptosis; Reactive Oxygen Species; Apoptosis; Cell Line, Tumor; Glioma; Iron; Receptors, Transferrin
PubMed: 36702193
DOI: 10.1016/j.yexcr.2023.113474 -
Current Oncology (Toronto, Ont.) Jun 2023Immunotherapy is a promising therapeutic domain for the treatment of gliomas. However, clinical trials of various immunotherapeutic modalities have not yielded... (Review)
Review
Immunotherapy is a promising therapeutic domain for the treatment of gliomas. However, clinical trials of various immunotherapeutic modalities have not yielded significant improvements in patient survival. Preclinical models for glioma research should faithfully represent clinically observed features regarding glioma behavior, mutational load, tumor interactions with stromal cells, and immunosuppressive mechanisms. In this review, we dive into the common preclinical models used in glioma immunology, discuss their advantages and disadvantages, and highlight examples of their utilization in translational research.
Topics: Humans; Glioma; Immunotherapy
PubMed: 37366911
DOI: 10.3390/curroncol30060428 -
Clinical Radiology Jan 2020To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring. (Review)
Review
AIM
To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring.
MATERIALS AND METHODS
The PubMed and MEDLINE databases were searched for articles published before September 2018 using relevant search terms. The search strategy focused on articles applying ML to high-grade glioma biomarkers for treatment response monitoring, prognosis, and prediction.
RESULTS
Magnetic resonance imaging (MRI) is typically used throughout the patient pathway because routine structural imaging provides detailed anatomical and pathological information and advanced techniques provide additional physiological detail. Using carefully chosen image features, ML is frequently used to allow accurate classification in a variety of scenarios. Rather than being chosen by human selection, ML also enables image features to be identified by an algorithm. Much research is applied to determining molecular profiles, histological tumour grade, and prognosis using MRI images acquired at the time that patients first present with a brain tumour. Differentiating a treatment response from a post-treatment-related effect using imaging is clinically important and also an area of active study (described here in one of two Special Issue publications dedicated to the application of ML in glioma imaging).
CONCLUSION
Although pioneering, most of the evidence is of a low level, having been obtained retrospectively and in single centres. Studies applying ML to build neuro-oncology monitoring biomarker models have yet to show an overall advantage over those using traditional statistical methods. Development and validation of ML models applied to neuro-oncology require large, well-annotated datasets, and therefore multidisciplinary and multi-centre collaborations are necessary.
Topics: Biomarkers; Brain Neoplasms; Glioma; Humans; Image Interpretation, Computer-Assisted; Machine Learning; Magnetic Resonance Imaging; Neoplasm Grading; Prognosis
PubMed: 31371027
DOI: 10.1016/j.crad.2019.07.001 -
Neurology India 2020Are we witnessing the end of the biopsy as we know it? Is this the start of a revolution in cancer diagnostics and treatment where analysis of somatic mutations present... (Review)
Review
BACKGROUND
Are we witnessing the end of the biopsy as we know it? Is this the start of a revolution in cancer diagnostics and treatment where analysis of somatic mutations present in the blood, CSF, or urine followed by targeted therapy replaces the traditional surgery followed by chemo-radiation? Since 2016, molecular markers are an integral part of the 'glioma' treatment decision-making process- diagnostic, prognostic, and therapeutic. A lot of these somatic mutations that identify and prognosticate tumors are also detected in the adjoining bio-fluids in serum or CSF- the sampling of which is known as liquid biopsy.
OBJECTIVE
The objective of this study is to review the advancement of scientific techniques that now allows the investigation of these bio-fluids, to diagnose, prognosticate and treat gliomas.
MATERIAL AND METHODS
This review article is an exhaustive review of the literature that summarises the role of the three main liquid biopsy modalities- Circulating Tumor Cells, Cell-free Tumor DNA and Exosomes in the detection of known diagnostic and prognostic markers in gliomas.
RESULTS
The current review highlights the strengths and weaknesses of the diffrerent modalities in use, and their potential use in the clinical setting.
CONCLUSION
Liquid biopsies hold tremendous potential in the diagnosis and management of gliomas in the future.
Topics: Biomarkers, Tumor; Glioma; Humans; Liquid Biopsy; Neoplastic Cells, Circulating; Prognosis
PubMed: 33342856
DOI: 10.4103/0028-3886.304105 -
Frontiers in Immunology 2023Among all types of central nervous system cancers, glioma remains the most frequent primary brain tumor in adults. Despite significant advances in immunomodulatory...
INTRODUCTION
Among all types of central nervous system cancers, glioma remains the most frequent primary brain tumor in adults. Despite significant advances in immunomodulatory therapies, notably immune checkpoint inhibitors, their effectiveness remains constrained due to glioma resistance. The discovery of TMIGD2 (Transmembrane and Immunoglobulin Domain Containing 2) as an immuno-stimulatory receptor, constitutively expressed on naive T cells and most natural killer (NK) cells, has emerged as an attractive immunotherapy target in a variety of cancers. The expression profile of TMIGD2 and its significance in the overall survival of glioma patients remains unknown.
METHODS
In the present study, we first assessed TMIGD2 mRNA expression using the Cancer Genome Atlas (TCGA) glioma transcriptome dataset (667 patients), followed by validation with the Chinese Glioma Genome Atlas (CGGA) cohort (693 patients). Secondly, we examined TMIGD2 protein staining in a series of 25 paraffin-embedded blocks from Moroccan glioma patients. The statistical analysis was performed using GraphPad Prism 8 software.
RESULTS
TMIGD2 expression was found to be significantly higher in astrocytoma, IDH-1 mutations, low-grade, and young glioma patients. TMIGD2 was expressed on immune cells and, surprisingly, on tumor cells of glioma patients. Interestingly, our study demonstrated that TMIGD2 expression was negatively correlated with angiogenesis, hypoxia, G2/M checkpoint, and epithelial to mesenchymal transition signaling pathways. We also demonstrated that dendritic cells, monocytes, NK cells, gd T cells, and naive CD8 T cell infiltration correlates positively with TMIGD2 expression. On the other hand, Mantel-Cox analysis demonstrated that increased expression of TMIGD2 in human gliomas is associated with good overall survival. Cox multivariable analysis revealed that TMIGD2 is an independent predictor of a good prognosis in glioma patients.
DISCUSSION
Taken together, our results highlight the tight implication of TMIGD2 in glioma progression and show its promising therapeutic potential as a stimulatory target for immunotherapy.
Topics: Humans; Astrocytoma; Epithelial-Mesenchymal Transition; Glioma; Prognosis; Transcriptome
PubMed: 37261362
DOI: 10.3389/fimmu.2023.1173518 -
Frontiers in Immunology 2023Glioma is a mixed solid tumor composed of neoplastic and non-neoplastic components. Glioma-associated macrophages and microglia (GAMs) are crucial elements of the glioma... (Review)
Review
Glioma is a mixed solid tumor composed of neoplastic and non-neoplastic components. Glioma-associated macrophages and microglia (GAMs) are crucial elements of the glioma tumor microenvironment (TME), regulating tumor growth, invasion, and recurrence. GAMs are also profoundly influenced by glioma cells. Recent studies have revealed the intricate relationship between TME and GAMs. In this updated review, we provide an overview of the interaction between glioma TME and GAMs based on previous studies. We also summarize a series of immunotherapies targeting GAMs, including clinical trials and preclinical studies. Specifically, we discuss the origin of microglia in the central nervous system and the recruitment of GAMs in the glioma background. We also cover the mechanisms through which GAMs regulate various processes associated with glioma development, such as invasiveness, angiogenesis, immunosuppression, recurrence, etc. Overall, GAMs play a significant role in the tumor biology of glioma, and a better understanding of the interaction between GAMs and glioma could catalyze the development of new and effective immunotherapies for this deadly malignancy.
Topics: Humans; Glioblastoma; Microglia; Tumor Microenvironment; Brain Neoplasms; Glioma; Macrophages; Immunotherapy; Immunity
PubMed: 36969167
DOI: 10.3389/fimmu.2023.1123853 -
Cancer Letters May 2020High-grade glioma (HGG), and particularly Glioblastoma (GBM), can exhibit pronounced intratumoral heterogeneity that confounds clinical diagnosis and management. While... (Review)
Review
High-grade glioma (HGG), and particularly Glioblastoma (GBM), can exhibit pronounced intratumoral heterogeneity that confounds clinical diagnosis and management. While conventional contrast-enhanced MRI lacks the capability to resolve this heterogeneity, advanced MRI techniques and PET imaging offer a spectrum of physiologic and biophysical image features to improve the specificity of imaging diagnoses. Published studies have shown how integrating these advanced techniques can help better define histologically distinct targets for surgical and radiation treatment planning, and help evaluate the regional heterogeneity of tumor recurrence and response assessment following standard adjuvant therapy. Application of texture analysis and machine learning (ML) algorithms has also enabled the emerging field of radiogenomics, which can spatially resolve the regional and genetically distinct subpopulations that coexist within a single GBM tumor. This review focuses on the latest advances in neuro-oncologic imaging and their clinical applications for the assessment of intratumoral heterogeneity.
Topics: Algorithms; Brain Neoplasms; Contrast Media; Glioma; Humans; Machine Learning; Magnetic Resonance Imaging; Neoplasm Recurrence, Local; Positron-Emission Tomography; Therapy, Computer-Assisted
PubMed: 32112907
DOI: 10.1016/j.canlet.2020.02.025