Characteristics of diffuse hemispheric gliomas, H3 G34-mutant in adults

Approaches to supratentorial brain tumours in children

The differential diagnosis of supratentorial brain tumours in children can be challenging, especially considering the recent changes to the WHO classification of CNS tumours published in 2021. Many new tumour types have been proposed which frequently present in children and young adults and their imaging features are currently being described by the neuroradiology community. The purpose of this article is to provide guidance to residents and fellows new to the field of paediatric neuroradiology on how to evaluate an MRI of a patient with a newly diagnosed supratentorial tumour. Six different approaches are discussed including: 1. Tumour types, briefly discussing the main changes to the recent WHO classification of CNS tumours, 2. Patient age and its influence on incidence rates of specific tumour types, 3. Growth patterns, 4. Tumour location and how defining the correct location helps in narrowing down the differential diagnoses and 5. Imaging features of the tumour on DWI, SWI, FLAIR and post contrast sequences.

Radiomics and artificial intelligence applications in pediatric brain tumors

BACKGROUND

The study of central nervous system (CNS) tumors is particularly relevant in the pediatric population because of their relatively high frequency in this demographic and the significant impact on disease- and treatment-related morbidity and mortality. While both morphological and non-morphological magnetic resonance imaging techniques can give important information concerning tumor characterization, grading, and patient prognosis, increasing evidence in recent years has highlighted the need for personalized treatment and the development of quantitative imaging parameters that can predict the nature of the lesion and its possible evolution. For this purpose, radiomics and the use of artificial intelligence software, aimed at obtaining valuable data from images beyond mere visual observation, are gaining increasing importance. This brief review illustrates the current state of the art of this new imaging approach and its contributions to understanding CNS tumors in children.

DATA SOURCES

We searched the PubMed, Scopus, and Web of Science databases using the following key search terms: ("radiomics" AND/OR "artificial intelligence") AND ("pediatric AND brain tumors"). Basic and clinical research literature related to the above key research terms, i.e., studies assessing the key factors, challenges, or problems of using radiomics and artificial intelligence in pediatric brain tumors management, was collected.

RESULTS

A total of 63 articles were included. The included ones were published between 2008 and 2024. Central nervous tumors are crucial in pediatrics due to their high frequency and impact on disease and treatment. MRI serves as the cornerstone of neuroimaging, providing cellular, vascular, and functional information in addition to morphological features for brain malignancies. Radiomics can provide a quantitative approach to medical imaging analysis, aimed at increasing the information obtainable from the pixels/voxel grey-level values and their interrelationships. The "radiomic workflow" involves a series of iterative steps for reproducible and consistent extraction of imaging data. These steps include image acquisition for tumor segmentation, feature extraction, and feature selection. Finally, the selected features, via training predictive model (CNN), are used to test the final model.

CONCLUSIONS

In the field of personalized medicine, the application of radiomics and artificial intelligence (AI) algorithms brings up new and significant possibilities. Neuroimaging yields enormous amounts of data that are significantly more than what can be gained from visual studies that radiologists can undertake on their own. Thus, new partnerships with other specialized experts, such as big data analysts and AI specialists, are desperately needed. We believe that radiomics and AI algorithms have the potential to move beyond their restricted use in research to clinical applications in the diagnosis, treatment, and follow-up of pediatric patients with brain tumors, despite the limitations set out.

Midline invasion predicts poor prognosis in diffuse hemispheric glioma, H3 G34-mutant: an individual participant data review

INTRODUCTION

Diffuse hemispheric glioma, H3 G34-mutant (DHGs), is a newly categorized tumor in pediatric-type diffuse high-grade gliomas, World Health Organization grade 4, with a poor prognosis. Although prognostic factors associated with genetic abnormalities have been reported, few reports have examined the clinical presentation of DHGs, especially from the viewpoint of imaging findings. In this study, we investigated the relationship between clinical factors, including imaging findings, and prognosis in patients with DHGs.

METHODS

We searched Medline through the PubMed database using two search terms: "G34" and "glioma", between 1 April 2012 and 1 July 2023. We retrieved articles that described imaging findings and overall survival (OS), and added one DHG case from our institution. We defined midline invasion (MI) as invasion to the contralateral cerebrum, brainstem, corpus callosum, thalamus, and basal ganglia on magnetic resonance imaging. The primary outcome was 12-month survival, estimated using Kaplan-Meier curves and logistic regression.

RESULTS

A total of 96 patients were included in this study. The median age was 22 years, and the proportion of male patients was 48.4%. Lesions were most frequently located in the frontal lobe (52.6%). MI was positive in 39.6% of all patients. The median OS was 14.4 months. Univariate logistic regression analysis revealed that OS was significantly worse in the MI-positive group compared with the MI-negative group. Multivariate logistic regression analysis revealed that MI was an independent prognostic factor in DHGs.

CONCLUSIONS

In this study, MI-positive cases had a worse prognosis compared with MI-negative cases.

PREVIOUS PRESENTATIONS

No portion of this study has been presented or published previously.

Algorithmic approach utilizing histology and immunohistochemistry for the current classification of diffuse glioma

INTRODUCTION

Diffuse glioma constitutes 28% of primary brain tumors. Until recently morphologic appearance was the only criterion for classifying these tumors. However, WHO 2016 incorporates molecular information in the primary diagnosis of gliomas such as Isocitrate dehydrogenase 1 (IDH1), Alpha thalassemia/mental retardation syndrome X inked (ATRX) as well as 1p/19q codeletion on FISH. In a resource-limited setup where FISH is not available, Alpha internexin (INA) has been suggested as a surrogate IHC marker.

MATERIAL AND METHODS

Cross-sectional study conducted in the Department of Pathology for two years. Tissue blocks and clinical as well as radiological details were obtained from departmental archives. After assessing the morphologic details, routine IHC markers such as GFAP, Ki67 and P53 along with molecular markers like IDH-1, ATRX, and lNA were applied.

RESULTS

Out of 55 cases of diffuse glioma, 23 cases of astrocytoma and 32 cases of oligodendroglioma with an overall mean age of presentation of 41.49 ± 12.47 years. IDH-1 expression among diffuse glioma was 89.1% in our study. Alteration in the ATRX gene expression was observed in 95.7% of astrocytomas. 75% of oligodendrogliomas expressed INA with no significant difference in expression between the two grades. Based on the algorithmic approach using molecular surrogate markers, diffuse gliomas were categorized into six distinct groups. IDH-mutant, ATRX loss of expression astrocytoma and IDH-mutant, INA positive oligodendroglioma are two categories that do not require further molecular testing. This comprises 72.7% of the cases and these do not warrant further workup.

CONCLUSION

Implementation of combined phenotypic-genotypic diagnosis with the use of histomorphology and immunohistochemical surrogates for molecular genetic alterations will yield more homogeneous and narrowly defined diagnostic entities which will provide better prognostication and definitive treatment. It also is cost-effective in a resource-limited setup.

Adult-type and Pediatric-type Diffuse Gliomas : What the Neuroradiologist Should Know

The classification of diffuse gliomas into the adult type and the pediatric type is the new basis for the diagnosis and clinical evaluation. The knowledge for the neuroradiologist should not remain limited to radiological aspects but should be based additionally on the current edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS). This classification defines the 11 entities of diffuse gliomas, which are included in the 3 large groups of adult-type diffuse gliomas, pediatric-type diffuse low-grade gliomas, and pediatric-type diffuse high-grade gliomas. This article provides a detailed overview of important molecular, morphological, and clinical aspects for all 11 entities, such as typical genetic alterations, age distribution, variability of the tumor localization, variability of histopathological and radiological findings within each entity, as well as currently available statistical information on prognosis and outcome. Important differential diagnoses are also discussed.

H3G34-Mutant Gliomas-A Review of Molecular Pathogenesis and Therapeutic Options

The 2021 World Health Organization Classification of Tumors of the Central Nervous System reflected advances in understanding of the roles of oncohistones in gliomagenesis with the introduction of the H3.3-G34R/V mutant glioma to the already recognized H3-K27M altered glioma, which represent the diagnoses of pediatric-type diffuse hemispheric glioma and diffuse midline glioma, respectively. Despite advances in research regarding these disease entities, the prognosis remains poor. While many studies and clinical trials focus on H3-K27M-altered-glioma patients, those with H3.3-G34R/V mutant gliomas represent a particularly understudied population. Thus, we sought to review the current knowledge regarding the molecular mechanisms underpinning the gliomagenesis of H3.3-G34R/V mutant gliomas and the diagnosis, treatment, long-term outcomes, and possible future therapeutics.

Newly Recognized CNS Tumors in the 2021 World Health Organization Classification: Imaging Overview with Histopathologic and Genetic Correlation

In 2021, the World Health Organization released an updated classification of CNS tumors. This update reflects the growing understanding of the importance of genetic alterations related to tumor pathogenesis, prognosis, and potential targeted treatments and introduces 22 newly recognized tumor types. Herein, we review these 22 newly recognized entities and emphasize their imaging appearance with correlation to histologic and genetic features.

H3 G34-mutant high-grade gliomas: integrated clinical, imaging and pathological characterisation of a single-centre case series

BACKGROUND

Diffuse hemispheric glioma, H3 G34-mutant, is a novel paediatric tumour type in the fifth edition of the WHO classification of CNS tumours associated with an invariably poor outcome. We present a comprehensive clinical, imaging and pathological review of this entity.

METHODS

Patients with confirmed H3 G34R-mutant high-grade glioma were included in a single-centre retrospective cohort study and examined for clinical, radiological and histo-molecular data.

RESULTS

Twelve patients were enrolled in the study - 7 males/5 females; the mean age was 17.5 years (10-57 years). Most patients presented with signs of raised intracranial pressure (8/12). The frontal lobe (60%) was the prevalent location, with a mixed cystic-nodular appearance (10/12) and presence of vascular flow voids coursing through/being encased by the mass (8/12), and all tumours showed cortical invasion. Nine patients had subtotal resection limited by functional margins, two patients underwent supra-total resection, and one patient had biopsy only. 5-ALA was administered to 6 patients, all of whom showed positive fluorescence. Histologically, the tumours showed a marked heterogeneity and aggressive spread along pre-existing brain structures and leptomeninges. In addition to the diagnostic H3 G34R/V mutation, pathogenic variants in TP53 and ATRX genes were found in most cases. Potential targetable mutations in PDGFRA and PIK3CA genes were detected in five cases. The MGMT promoter was highly methylated in half of the samples. Methylation profiling was a useful diagnostic tool and highlighted recurrent structural chromosome abnormalities, such as PDGFRA amplification, CDKN2A/B deletion, PTEN loss and various copy number changes in the cyclin D-CDK4/Rb pathway. Radiochemotherapy was the most common adjuvant treatment (9/12), and the average survival was 19.3 months.

CONCLUSIONS

H3 G34R-mutant hemispheric glioma is a distinct entity with characteristic imaging and pathological features. Genomic landscaping of individual tumours can offer an opportunity to adapt individual therapies and improve patient management.

Dissecting the tumor microenvironment of epigenetically driven gliomas: Opportunities for single-cell and spatial multiomics

Malignant gliomas are incurable brain neoplasms with dismal prognoses and near-universal fatality, with minimal therapeutic progress despite billions of dollars invested in research and clinical trials over the last 2 decades. Many glioma studies have utilized disparate histologic and genomic platforms to characterize the stunning genomic, transcriptomic, and immunologic heterogeneity found in gliomas. Single-cell and spatial omics technologies enable unprecedented characterization of heterogeneity in solid malignancies and provide a granular annotation of transcriptional, epigenetic, and microenvironmental states with limited resected tissue. Heterogeneity in gliomas may be defined, at the broadest levels, by tumors ostensibly driven by epigenetic alterations (IDH- and histone-mutant) versus non-epigenetic tumors (IDH-wild type). Epigenetically driven tumors are defined by remarkable transcriptional programs, immunologically distinct microenvironments, and incompletely understood topography (unique cellular neighborhoods and cell-cell interactions). Thus, these tumors are the ideal substrate for single-cell multiomic technologies to disentangle the complex intra-tumoral features, including differentiation trajectories, tumor-immune cell interactions, and chromatin dysregulation. The current review summarizes the applications of single-cell multiomics to existing datasets of epigenetically driven glioma. More importantly, we discuss future capabilities and applications of novel multiomic strategies to answer outstanding questions, enable the development of potent therapeutic strategies, and improve personalized diagnostics and treatment via digital pathology.

The clinicopathological features and prognosis of multifocal high-grade gliomas in adults with H3F3A mutation

OBJECTIVES

To explore the clinicopathological features and prognosis of multifocal high-grade gliomas (M-HGGs) with H3F3A mutation in adults.

METHODS

Four adult patients with H3F3A-mutant M-HGGs who were treated at our institution from August 2020 to December 2021 were reviewed, including clinical, pathological and radiologic data. A series of 16 adult patients with M-HGGs without H3F3A mutation was used as a comparative group. Progression-free survival (PFS) and overall survival (OS) were compared between the groups using the Kaplan-Meier method.

RESULTS

All patients were IDH wild-type and TERT wild-type, and P53 was overexpressed. A patient with the H3 G34R mutation and 1 of 3 patients with the H3 K27 M mutation had MGMT promoter methylation. The lesions with the H3 G34R mutation were located in the cerebral hemisphere; the lesions with H3 K27 alterations were mainly in the midline structure, and the cerebral hemisphere could also be involved. One patient underwent subtotal resection (STR), and 3 patients underwent biopsy. All patients received radiotherapy, and the median PFS and OS were 9.5 months and 14.5 months, respectively. The clinical outcomes were similar to those of non-H3F3A-mutated M-HGGs patients (median PFS and OS were 7.0 months and 18.0 months, respectively).

CONCLUSION

We describe the clinicopathological features and outcomes of 4 adult M-HGGs patients with H3F3A mutation, and found this mutation doesn't appear to have a negative outcome with the administration of current therapies.

Adult type diffuse gliomas in the new 2021 WHO Classification

Adult-type diffuse gliomas represent a group of highly infiltrative central nervous system tumors with a prognosis that significantly varies depending on the specific subtype and histological grade. Traditionally, adult-type diffuse gliomas have been classified based on their morphological features with a great interobserver variability and discrepancy in patient survival even within the same histological grade. Over the last few decades, advances in molecular profiling have drastically changed the diagnostic approach and classification of brain tumors leading to the development of an integrated morphological and molecular classification endowed with a more clinically relevant value. These concepts were largely anticipated in the revised fourth-edition of WHO classification of central nervous system tumors published in 2016. The fifth-edition (WHO 2021) moved molecular diagnostics forward into a full integration of molecular parameters with the histological features into an integrative diagnostic approach. Diagnosis of adult type diffuse gliomas, IDH mutant and IDH-wildtype has been simplified by introducing revised diagnostic and grading criteria. In this review, we will discuss the most recent updates to the classification of adult-type diffuse gliomas and summarize the essential diagnostic keys providing a practical guidance to pathologists.

Conventional MRI-Derived Biomarkers of Adult-Type Diffuse Glioma Molecular Subtypes: A Comprehensive Review

The introduction of molecular criteria into the classification of diffuse gliomas has added interesting practical implications to glioma management. This has created a new clinical need for correlating imaging characteristics with glioma genotypes, also known as radiogenomics or imaging genomics. Although many studies have primarily focused on the use of advanced magnetic resonance imaging (MRI) techniques for radiogenomics purposes, conventional MRI sequences remain the reference point in the study and characterization of brain tumors. A summary of the conventional imaging features of glioma molecular subtypes should be useful as a tool for daily diagnostic brain tumor management. Hence, this article aims to summarize the conventional MRI features of glioma molecular subtypes in light of the recent literature.

Molecular testing for adolescent and young adult central nervous system tumors: A Canadian guideline

The 2021 World Health Organization (WHO) classification of CNS tumors incorporates molecular signatures with histology and has highlighted differences across pediatric vs adult-type CNS tumors. However, adolescent and young adults (AYA; aged 15–39), can suffer from tumors across this spectrum and is a recognized orphan population that requires multidisciplinary, specialized care, and often through a transition phase. To advocate for a uniform testing strategy in AYAs, pediatric and adult specialists from neuro-oncology, radiation oncology, neuropathology, and neurosurgery helped develop this review and testing framework through the Canadian AYA Neuro-Oncology Consortium. We propose a comprehensive approach to molecular testing in this unique population, based on the recent tumor classification and within the clinical framework of the provincial health care systems in Canada.

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).