Classification Of Central Nervous System Tumors Research Articles

New Approaches with Precision Medicine in Adult Brain Tumors.

Simple SummaryPrimary brain tumors are rare neoplasms with limited effective systemic treatment options. Recent advances in new molecular techniques have brought about novel information about molecular markers and potential targetable molecular alterations in brain tumors. Targeted therapeutic approaches are already established in several extracranial malignancies and its application is increasingly used and studied in the management of primary brain tumors. The aim of this article is to summarize the latest progress in precision medicine approaches in primary brain tumors.Primary central nervous system (CNS) tumors represent a heterogenous group of tumors. The 2021 fifth edition of the WHO Classification of Tumors of the CNS emphasizes the advanced role of molecular diagnostics with routine implementation of molecular biomarkers in addition to histologic features in the classification of CNS tumors. Thus, novel diagnostic methods such as DNA methylome profiling are increasingly used to provide a more precise diagnostic work-up of CNS tumors. In addition to these diagnostic precision medicine advantages, molecular alterations are also addressed therapeutically with targeted therapies. Like in other tumor entities, precision medicine has therefore also arrived in the treatment of CNS malignancies as the application of targeted therapies has shown promising response rates. Nevertheless, large prospective studies are currently missing as most targeted therapies were evaluated in single arm, basket, or platform trials. In this review, we focus on the current evidence of precision medicine in the treatment of primary CNS tumors in adults. We outline the pathogenic background and prevalence of the most frequent targetable genetic alterations and summarize the existing evidence of precision medicine approaches for the treatment of primary CNS tumors.

FISH analyses for 1p and 19q status on gliomas: Reporting an 8 years' experience from a tertiary care center in the Middle East

Diffuse gliomas are the most common primary malignancies of the central nervous system (CNS). The 2016 edition of the World Health Organization (WHO) classification of CNS tumors opted to integrate current molecular data with the traditional histologic diagnosis in the definition of the disease. This integrated diagnosis offers a greater level of objectivity and helps in establishing more definitive diagnoses for tumors that may have been controversial on histology alone. The classification of gliomas may require FISH technique to identify chromosomal abnormalities. FISH is commonly used to identify 1p/19q codeletion, but many challenges are encountered in the process. In this study, we review the FISH results for 1p/19q codeletion of n = 85 diffuse glioma samples examined at a tertiary care center in the Middle East over a period of 8 years. We also conduct a literature review to study the potential role of DNA-microarray in the identification of 1p/19q deletions. Glioblastoma (GBM), WHO grade IV is the most common glioma type identified (n = 24; 29%). All oligodendrogliomas show 1p/19q codeletion (26/26) while 12.5% of GBMs have 1p/19q codeletion (3/24). Isolated 1p deletions are only identified in one case of diffuse astrocytoma, WHO grade II. Isolated 19q deletions are identified in oligoastrocytoma, anaplastic astrocytoma, and glioblastoma. FISH is the most commonly used technique to diagnose oligodendroglioma because it is a simple, effective, and accessible technique in settings with limited resources. However, the optimization process remains highly variable between laboratories. Microarray is a more objective technique that can provide more information about the genetic alterations of the tumor for better diagnosis and sub-classification of diffuse glioma types.

Clinicopathological features, imaging characteristics and surgical management in a novel tumour entity - aggressive meningiomas

Meningiomas are common neoplasms of the central nervous system, comprising between 24 and 30% of primary intracranial tumours, most commonly affecting females in their middle age or later adult life [1] [2].
 Meningiomas are classified as benign, atypical or anaplastic meningiomas depending mostly on histopathological criteria known to be associated with worse prognosis in terms of tumour progression, recurrence risk after surgery and overall survival. The 2016 edition of the World Health Organization (WHO) classification of Central Nervous System (CNS) tumours recognizes brain invasion as an independent criterion for diagnosing an atypical grade II meningioma [3]. Meningioma grading based on the WHO classification of CNS tumours thoroughly impacts therapeutic management and tumour prognosis.
 Aggressive meningiomas, a different phenotype of tumours, characterized by rapid growth and involvement of adjacent brain tissue, blood vessels and bone, was not previously listed as an independent entity in the WHO classification of meningothelial-cell tumours. 
 Regarding the increasing importance of tumour grading in meningioma treatment strategies, the authors here provide an overview of clinicopathological and radiographic features, surgical management and long-term prognosis of this novel meningothelial tumour entity, the aggressive meningioma. In particular, we aimed to describe pre-, intra- and postoperative methods for recognizing aggressive meningiomas and explore the implications of this diagnosis on both surgical strategies and adjuvant therapy.

PEDT-1 Integrated diagnoses of pediatric gliomas in our institute by cIMPACT-NOW recommendations

Purpose:Since many genetic abnormalities in glioma have been revealed in recent years, Integrated diagnoses are necessary in the updated fourth edition of the WHO Classification of Tumors of the Central Nervous System(CNS) published in 2016. The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) was established to provide a forum to evaluate and recommend proposed changes to future CNS tumor classification. We retrospectively classified pediatric gliomas in our hospital in accordance with cIMPACT-NOW recommendations. Methods: This study includes 13 consecutive glioma patients under the age of 18 who underwent surgical resection at our hospital from 2000 to 2021. Histopathological diagnoses and molecular status such as IDH, H3F3A and BRAF were analyzed. Results: There were four females and nine males, ranging in age from 0 to 17 years, median 9.0 years. Three pilocytic astrocytomas (PA) and a polymorphous low-grade neuroepithelial tumor of the young (PLNTY) had BRAF fusion. Four cases were classified as Diffuse midline glioma, H3K27M-altered. Two cases were classified as Diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype. No genetic alteration was observed in two diffuse astrocytoma cases. An anaplastic oligodendroglioma case with PDGFRA amplification could not be classified as any new entity. All three PA cases with BRAF fusion occurred in cerebellum and all four H3K27M altered cases occurred in midline location such as thalamus, brainstem and cervical spinal cord. Six cases which were classified as pediatric-type diffuse high grade gliomas had poor prognosis. Conclusion:Genetic status is associated to tumor location and patients prognosis. Integrated diagnoses are important in pediatric glioma patients.

La classification de l’OMS 2021 des tumeurs du système nerveux central

Rapid technical advances in molecular biology allowed for the identification of key genetic alterations in central nervous system (CNS) tumors. Our ever-expanding knowledge of brain tumor genetics and the development of new technologies, such as DNA-methylation profiling, required an update of the 2016 fourth edition of the WHO classification of CNS tumors. Updates were regularly published by the Consortium to Inform Molecular Practical Approaches to CNS Tumor Taxonomy-Not Official WHO (c-IMPACT-NOW) until the publication of the fifth edition of the WHO classification of CNS tumors in 2021. In that edition, new types and subtypes are introduced and criteria for histo-molecular diagnostic and grading are refined, especially for diffuse gliomas. The definition of a broad category “diffuse glioma, pediatric subtype” (low or high grade) is a major improvement of the classification. Moreover, the nomenclature was simplified and aligned with that of other blue books. The 2021 edition truly advances the role of molecular diagnostics in CNS tumor classification. Methyloma profiling may become a cornerstone of CNS tumor diagnostic. The new WHO classification will lead to better management of brain tumor patients.

BIOM-19. DECIPHERING THE METHYLATION SIGNATURE OF CIRCULATING EXTRACELLULAR VESICLE DNA FOR CNS TUMOR CLASSIFICATION

Abstract Genome-wide methylation profiling has recently been developed into a tool that allows subtype tumor classification in central nervous system (CNS) tumors. We previously showed that extracellular vesicle (EV) DNA faithfully reflects the tumor methylation class, including information on the IDH mutation and MGMT promoter methylation status. Furthermore we showed that circulating plasma EVs are elevated in CNS tumor patients in comparison to non-tumor donors (HD) controls with tumor related protein profiles. We now investigated, whether the methylation signatures of circulating DNA (both EV and cfNDA) can be used in liquid biopsy approaches for CNS tumor detection and classification. We isolated DNA from circulating EVs (n=27), cfDNA (n=27) and tumor tissue DNA (n=90) of patients with glioblastoma (GBM), meningioma (MGN) and cerebral metastases (CM). Patients undergoing epilepsy surgery as well as aneurysm clipping were used as non-tumor controls (HD, n= 7). EVs were classified by nanoparticle analysis, immunoblotting, imaging flow cytometry and electron microscopy. Isolated EV-DNA comprised many sorts of molecular weight (up tp >10Kb) in comparison to cfDNA (130-140bp). Healthy donors and tumor patients showed not differences in their DNA size profiles. We performed genome-wide methylation profiling by 850k Illumina EPIC arrays for all DNA analytes and tumor entities. Linear models and empirical Bayes methods identified significant differentially methylated CpGs (GBM vs. HD, MGN, vs HD, CM vs. HD), that revealed tumor specific signatures to detect and discriminate different CNS tumor entities. Visualization of differentially methylated CPGs by dimension reduction (PCA, t-SNE, Umap) verified tumor specific clusters. cfDNA and EV-DNA exhibited distinctive individual CpG profiles. Our study shows that the methylation signature of circulating EV DNA and cfDNA can be used to separate healthy individuals from tumor patients and could potentially complement standard-of-care imaging to improve tumor detection, classification and surveillance.

DNA methylation profiling as a model for discovery and precision diagnostics in neuro-oncology.

Recent years have witnessed a shift to more objective and biologically-driven methods for central nervous system (CNS) tumor classification. The 2016 world health organization (WHO) classification update (“blue book”) introduced molecular diagnostic criteria into the definitions of specific entities as a response to the plethora of evidence that key molecular alterations define distinct tumor types and are clinically meaningful. While in the past such diagnostic alterations included specific mutations, copy number changes, or gene fusions, the emergence of DNA methylation arrays in recent years has similarly resulted in improved diagnostic precision, increased reliability, and has provided an effective framework for the discovery of new tumor types. In many instances, there is an intimate relationship between these mutations/fusions and DNA methylation signatures. The adoption of methylation data into neuro-oncology nosology has been greatly aided by the availability of technology compatible with clinical diagnostics, along with the development of a freely accessible machine learning-based classifier. In this review, we highlight the utility of DNA methylation profiling in CNS tumor classification with a focus on recently described novel and rare tumor types, as well as its contribution to refining existing types.

Approach to integrating molecular markers for assessment of pediatric gliomas

Recent research has promoted elucidation of the diverse biological processes that occur in pediatric central nervous system (CNS) tumors. These molecular data are leading to new guidelines for the diagnosis, offering prognostic implications and novel molecular targeted therapies. The consortium to inform molecular and practical approaches to CNS tumor taxonomy-NOW have made practical recommendations using recent advances in CNS tumor classification, particularly in molecular discernment of these neoplasms as morphology-based classification of tumors is being replaced by molecular-based classification. Here, we review the specific molecular drivers that help to define the entities that fall under the umbrella of pediatric gliomas and how to effectively test them in cost-effective manner. We discuss briefly the proposed risk-based stratification system that considers both clinical and molecular parameters to aid clinicians in making treatment decisions and the availability of an increasing array of molecular-directed therapies.

Adult Diffuse Astrocytic and Oligodendroglial Tumors.

Infiltrating gliomas comprise the most common group of primary intraparenchymal brain tumors and present a level of complexity which requires careful integration of histopathology and molecular diagnostics for optimal therapy. To this end, the fourth edition of the World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) has been followed by a series of publications by cIMPACT-NOW (the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy) incorporating molecular signatures to propose updated diagnostic categories in anticipation of the upcoming fifth edition of CNS tumor classification. Integration of histopathology, immunophenotyping, and molecular findings is profoundly changing the practice of diagnostic surgical neuropathology and enabling a more personalized approach to treating patients with gliomas.

Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system.

The 2016 revised fourth edition of the World Health Organization (WHO) classification of central nervous system (CNS) tumors incorporated molecular features with histologic grading, revolutionizing how oncologists conceptualize primary brain and spinal cord tumors as well as providing new insights into their management and prognosis. The 2021 revised fifth edition of the WHO classification further integrates molecular alterations for CNS tumor categorization, updating current understanding of the pathophysiology of many of these disease entities. Here, the authors review changes in the new classification for the most common primary adult tumors-gliomas (including astrocytomas, oligodendrogliomas, and ependymomas) and meningiomas-highlighting the key genomic alterations for each group classification to help clinicians interpret them as they consider therapeutic options-including clinical trials and targeted therapies-and discuss the prognosis of these tumors with their patients. The revised, updated 2021 WHO classification also further integrates molecular alterations in the classification of pediatric CNS tumors, but those are not covered in the current review.

Work in progress: Changes to who brain tumor classification

The WHO classification of central nervous system (CNS) tumors had been revised in 2016 to include for the first time molecular biomarkers that are important for tumor classification and clinical decision making. Thereafter, the cIMPACT-NOW (Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy – not officially WHO) formed to further refine CNS tumor classification through specific recommendations that addressed issues of classification still controversial in 2016. Several cIMPACT-NOW proposals have shaped the new 2021 WHO classification of brain tumors. Mutations in the isocitrate dehydrogenase (IDH) 1 or 2 genes continue to play a major role in glioma classification beyond 2021. Among IDH-mutant gliomas, loss of ATRX expression identifies IDH-mutant astrocytomas without necessity for 1p/19q codeletion testing. Conversely, etection of a 1p/19q codeletion in an IDH-mutant glioma defines an oligodendroglial tumor. The nomenclature for IDH-mutant glioblastoma has been changed to astrocytoma, IDH-mutant, WHO grade 4, with CDKN2A homozygous deletion representing a molecular marker for these tumors. IDH-wildtype astrocytomas that lack microvascular proliferation or necrosis but exhibit telomerase reverse transcriptase promoter mutation, epidermal growth factor receptor amplification and/or a + 7/−10 genotype are now classified as IDH-wildtype glioblastoma. H3.3 G34-mutant diffuse hemispheric gliomas have been proposed as a new entity separate from IDH-wildtype glioblastoma. The new WHO classification increases the diagnostic accuracy and refines clinical care by changing treatment recommendations, e.g. for patients with IDH-wildtype astrocytomas showing molecular features of glioblastoma. It also has major implications for clinical trial design, notable inclusion and exclusion criteria for ongoing and upcoming clinical trials.

DNA 5-hydroxymethylcytosine in pediatric central nervous system tumors may impact tumor classification and is a positive prognostic marker

BackgroundNucleotide-specific 5-hydroxymethylcytosine (5hmC) remains understudied in pediatric central nervous system (CNS) tumors. 5hmC is abundant in the brain, and alterations to 5hmC in adult CNS tumors have been reported. However, traditional approaches to measure DNA methylation do not distinguish between 5-methylcytosine (5mC) and its oxidized counterpart 5hmC, including those used to build CNS tumor DNA methylation classification systems. We measured 5hmC and 5mC epigenome-wide at nucleotide resolution in glioma, ependymoma, and embryonal tumors from children, as well as control pediatric brain tissues using tandem bisulfite and oxidative bisulfite treatments followed by hybridization to the Illumina Methylation EPIC Array that interrogates over 860,000 CpG loci.ResultsLinear mixed effects models adjusted for age and sex tested the CpG-specific differences in 5hmC between tumor and non-tumor samples, as well as between tumor subtypes. Results from model-based clustering of tumors was used to test the relation of cluster membership with patient survival through multivariable Cox proportional hazards regression. We also assessed the robustness of multiple epigenetic CNS tumor classification methods to 5mC-specific data in both pediatric and adult CNS tumors. Compared to non-tumor samples, tumors were hypohydroxymethylated across the epigenome and tumor 5hmC localized to regulatory elements crucial to cell identity, including transcription factor binding sites and super-enhancers. Differentially hydroxymethylated loci among tumor subtypes tended to be hypermethylated and disproportionally found in CTCF binding sites and genes related to posttranscriptional RNA regulation, such as DICER1. Model-based clustering results indicated that patients with low 5hmC patterns have poorer overall survival and increased risk of recurrence. Our results suggest 5mC-specific data from OxBS-treated samples impacts methylation-based tumor classification systems giving new opportunities for further refinement of classifiers for both pediatric and adult tumors.ConclusionsWe identified that 5hmC localizes to super-enhancers, and genes commonly implicated in pediatric CNS tumors were differentially hypohydroxymethylated. We demonstrated that distinguishing methylation and hydroxymethylation is critical in identifying tumor-related epigenetic changes. These results have implications for patient prognostication, considerations of epigenetic therapy in CNS tumors, and for emerging molecular neuropathology classification approaches.

Investigation of the Relationship Between the Degree of Peritumoral Brain Edema and Pathological Features of Glioma Before Surgery

Background: Gliomas are the most common malignant tumors of the central nervous system (CNS). Preoperative prediction of the malignancy grade of gliomas are of particular importance. These tumors are often accompanied by peritumoral brain edema (PTBE). Previous studies have suggested that the degree of PTBE is an independent indicator of the prognosis of gliomas. Objectives: This study aimed to investigate the relationships between the degree of PTBE and the grade of glioma, isocitrate dehydrogenase 1 (IDH1) mutation status, and Ki-67 expression level in gliomas. Patients and Methods: In this retrospective cross-sectional study, a total of 82 patients were enrolled, according to the 2016 World Health Organization (WHO) classification of CNS tumors. Overall, 29 tumors were pathologically confirmed as low-grade gliomas (LGGs , grade I-II), whereas the remaining 53 tumors were classified as high-grade gliomas (HGGs, grade III-IV). The IDH1 mutations, Ki-67 expression, and magnetic resonance imaging (MRI) findings were retrospectively analyzed. The tumor and tumor + PTBE volumes were also measured, and the tumor edema index (EI) was calculated for each patient. Edema was then graded and correlated with the pathological parameters. Results: The degree of EI was higher in the HGG group compared to the LGG group, and the difference was statistically significant (z = -7.018, P < 0.05). Besides, the degree of EI was higher in the IDH1 wild-type compared with mutant groups (z = -4.116, P < 0.05). The degree of EI significantly associated with Ki-67 expression and patient’s age (P < 0.05), whereas there was no significant association between the degree of EI and gender (z = -0.497, P = 0.619). The Spearman’s correlation test revealed that the EI degree was positively correlated with the Ki-67 expression level and age, with correlation coefficients of 0.740 and 0.466, respectively. Moreover, the multivariate logistic regression analysis indicated that EI and IDH1 had significant effects on differentiating LGGs from HGGs (P < 0.05 for both). The receiver operating characteristic (ROC) curve analysis showed that EI was an optimal index for differentiating LGGs from HGGs, with an area under curve (AUC) of 0.822 (cutoff value: 1.722, sensitivity: 95.8%, specificity: 70.0%, 95% CI: 0.718 - 0.899). Conclusion: The degree of PTBE was found to be a valuable index for the differential diagnosis of LGGs from HGGs. It has a significant difference between IDH1 wild and mutation status, furthermore, it was positively correlated with the age and Ki-67 level.

Updates on the 2016 World Health Organization Classification of Pediatric Tumors of the Central Nervous System - a systematic review.

Tumors of the central nervous system (CNS) represent the main cause of death through solid tumors in children and the second most frequent neoplasm in this patient group. The poor survival rate is due to many factors, such as the large diversity of morphological features, the particular micro-environmental characteristics of the nervous tissue, the relative rareness in relation to other childhood diseases, which leads to late diagnosis and the limited effectiveness of the available treatment options. Up until 2016, brain tumors were classified according to their histologic features. The new 2016 World Health Organization (WHO) Classification of CNS tumors incorporates molecular features, alongside the immunohistology, in order to provide a more accurate understanding of the disease. The treatment consists of surgery, radiation therapy and chemotherapy. We decided to review the literature on this pathology, in order to show the importance of the recent discoveries in this field.

Abstract 457: A comparison of IDH1 R132H [H09] and [IHC132] antibodies on diffuse gliomas

Abstract Introduction In the 2016 World Health Organization Central Nervous System Tumor Classification, diffuse gliomas were reclassified to include astrocytic tumors (grade II and III), oligodendrogliomas (grade II and III), and grade IV glioblastomas with diffuse astrocytoma being distinct from the diffuse gliomas. This reclassification is due to the abundance of IDH1 mutations in many of these tumors. A much better outcome has been observed in these patients than those without this mutation. IDH1 mutation of the R132H type constitutes more than 90% of all IDH1 and IDH2 mutations. Further, IDH1 IHC is now widely applied for the differential diagnosis of these tumors. There are two distinct IDH1 R132H clones on the market, the H09 and IHC132. Comparing these markers for the IDH1 R132H mutations by IHC can help determine if one is superior for diagnostics. Materials and Methods IHC was performed on 3-5 um thick formalin-fixed, paraffin-embedded (FFPE) brain tissue arrays containing glioblastoma, astrocytoma, oligoastrocytoma, oligodendroglioma with adjacent normal tissue (US Biomax, Derwood, USA). These slides were deparaffinized, and peroxidase blocked in the usual manner. Slides were then subjected to HIER in a pressure cooker using a citrate-based buffer at 110°C for 15 minutes before being stained on a semi-automated instrument. The slides were stained with rabbit monoclonal IDH1 R132H antibody H09 (Dianova, Hamburg, Germany) and mouse monoclonal IDH1 R132H antibody IHC132 (GenomeMe, Richmond, Canada) at concentrations and protocols predetermined to match staining intensity. Results The mouse monoclonal anti-IDH1 R132H IHC132 has shown that it is analogous to the current IDH1 R132H [H09]. Upon review of the data, IHC132 marker stains a higher percentage of cases in glioblastoma compared to H09 (11%, n=36) and equal in astrocytoma (73%, n=15), oligoastrocytoma (75%, n=4), oligodendroglioma (100%, n=8). Neither clone stained normal brain tissue per negative controls. Conclusion Mouse monoclonal anti-IDH1 R132H [IHC132] compared with that of the rabbit monoclonal anti-IDH1 R132H [H09] showed equal sensitivity for astrocytoma, oligodendroglioma, and oligoastrocytomas with higher sensitivity for glioblastoma. The results provide evidence to support a higher percentage of positive staining and equal or greater intensity for clone IHC132 versus H09. Citation Format: Sara Figueroa, Joseph Vargas, Jason Ramos. A comparison of IDH1 R132H [H09] and [IHC132] antibodies on diffuse gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 457.

Deep Neural Network Analysis of Pathology Images With Integrated Molecular Data for Enhanced Glioma Classification and Grading.

Gliomas are primary brain tumors that originate from glial cells. Classification and grading of these tumors is critical to prognosis and treatment planning. The current criteria for glioma classification in central nervous system (CNS) was introduced by World Health Organization (WHO) in 2016. This criteria for glioma classification requires the integration of histology with genomics. In 2017, the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) was established to provide up-to-date recommendations for CNS tumor classification, which in turn the WHO is expected to adopt in its upcoming edition. In this work, we propose a novel glioma analytical method that, for the first time in the literature, integrates a cellularity feature derived from the digital analysis of brain histopathology images integrated with molecular features following the latest WHO criteria. We first propose a novel over-segmentation strategy for region-of-interest (ROI) selection in large histopathology whole slide images (WSIs). A Deep Neural Network (DNN)-based classification method then fuses molecular features with cellularity features to improve tumor classification performance. We evaluate the proposed method with 549 patient cases from The Cancer Genome Atlas (TCGA) dataset for evaluation. The cross validated classification accuracies are 93.81% for lower-grade glioma (LGG) and high-grade glioma (HGG) using a regular DNN, and 73.95% for LGG II and LGG III using a residual neural network (ResNet) DNN, respectively. Our experiments suggest that the type of deep learning has a significant impact on tumor subtype discrimination between LGG II vs. LGG III. These results outperform state-of-the-art methods in classifying LGG II vs. LGG III and offer competitive performance in distinguishing LGG vs. HGG in the literature. In addition, we also investigate molecular subtype classification using pathology images and cellularity information. Finally, for the first time in literature this work shows promise for cellularity quantification to predict brain tumor grading for LGGs with IDH mutations.

Spatial progression and molecular heterogeneity of IDH-mutant glioblastoma determined by DNA methylation-based mapping

Glioblastoma (GBM) is the most common malignant primary central nervous system (CNS) neoplasm in adults, and has an almost universally poor prognosis. Recently, an emphasis on genetic and epigenetic profiling has revealed a number of molecular features useful in the diagnostic and prognostic classification of GBM, advancing our understanding of the underlying features that make these tumors so aggressive and providing the rationale for the creation of better targeted therapeutics. One such method, DNA methylation profiling, has recently emerged as an important technique for the classification of CNS tumors, with diagnostic accuracy in some cases surpassing traditional methods. However, how DNA methylation profiles change with the course of the disease remains less understood. Here, we present a case of a 30-year-old male with primary IDH-mutant GBM with widespread recurrence and death two years later. Using unsupervised hierarchical clustering of methylation probes, we created a phylogenetic map to trace the tumor path as it spread from the initial biopsy site throughout the right hemisphere, across the corpus callosum to the contralateral hemisphere, and into the brainstem. We identified molecular divergence between the right and left hemisphere GBM samples marked by distinct copy number profile alterations, alterations in specific methylation sites, and regional loss of MGMT promoter methylation, providing a potential mechanism for treatment resistance in this case. In summary, this case both highlights the molecular diversity in GBM, and illustrates a novel use for methylation profiling in establishing a phylogenetic profile to allow for spatial mapping of tumor progression.

The 2021 WHO Classification of Tumors of the Central Nervous System: a summary.

The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, is the sixth version of the international standard for the classification of brain and spinal cord tumors. Building on the 2016 updated fourth edition and the work of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy, the 2021 fifth edition introduces major changes that advance the role of molecular diagnostics in CNS tumor classification. At the same time, it remains wedded to other established approaches to tumor diagnosis such as histology and immunohistochemistry. In doing so, the fifth edition establishes some different approaches to both CNS tumor nomenclature and grading and it emphasizes the importance of integrated diagnoses and layered reports. New tumor types and subtypes are introduced, some based on novel diagnostic technologies such as DNA methylome profiling. The present review summarizes the major general changes in the 2021 fifth edition classification and the specific changes in each taxonomic category. It is hoped that this summary provides an overview to facilitate more in-depth exploration of the entire fifth edition of the WHO Classification of Tumors of the Central Nervous System.

Pearls and Pitfalls of Imaging in Pediatric Brain Tumors

The central nervous system (CNS) tumors constitute the most common type of solid tumors in the pediatric population. The cerebral and cerebellar parenchyma are the most common site of pediatric CNS neoplasms. Imaging plays an important role in detection, characterization, staging and prognostication of brain tumors. The focus of the current article is pediatric brain tumor imaging with emphasis on pearls and pitfalls of conventional and advanced imaging in various pediatric brain tumor subtypes. The article also elucidates changes in brain tumor terms and entities as applicable to pediatric patients, updated as per World Health Organization (WHO) 2016 classification of primary CNS tumors. This classification introduced the genetic and/or molecular information of primary CNS neoplasms as part of comprehensive tumor pathology report in the routine clinical workflow. The concepts from 2016 classification have been further refined based on current research, by the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) group and published in the form of updates. The updates serve as guidelines in the time interval between WHO updates and expect to be broadly adopted in the subsequent WHO classification. The current review covers most pediatric brain tumors except pituitary tumors, meningeal origin tumors, nerve sheath tumors and CNS lymphoma/leukemia.

English

BACKGROUND Tumours of central nervous system (CNS) are reported to be less than 2 % of all malignancies. In India, CNS tumours constitute about 1.9 % of all tumours. The CNS space occupying lesions cause grave life-threatening outcomes irrespective of their nature as they grow in a confined space and are present close to vital structures. Hence, it is of great importance to establish the accurate diagnosis for proper and timely neurosurgical intervention. METHODS This was a retrospective study carried out in a tertiary care teaching hospital which caters as a referral unit for neurosurgical cases in Eastern India, for a duration of one and half year (January 2018 - July 2020) among 185 cases of CNS lesions collected from archives of Department of Pathology. The tumours were reclassified and graded according to the most recent World health organisation (WHO) classification of CNS tumours (2016). RESULTS Neoplastic lesions (168 cases, 91.35 %) were commoner than non-neoplastic entities and amongst the neoplastic lesions, meningioma was the commonest entity followed by diffuse astrocytic and oligodendroglial tumours while least incidence was noted for neuronal and mixed neuronal glial tumours. Out of all the tumours for which World Health Organization (WHO) grading was done, highest was WHO grade I (80 cases, 54.8 %) and least was grade III tumours (10 cases, 6.8 %). Male predominance was seen overall except in meningioma. Some rare and interesting cases like solitary fibrous tumour / hemangiopericytoma (anaplastic type), primary CNS diffuse large B cell lymphoma (DLBCL), CNS plasmacytoma which we came across are also highlighted. CONCLUSIONS The present study helps to provide information regarding the disease burden in our area. This study attempts to categorise various CNS neoplasms as per recent WHO classification (2016) which has not only diagnostic implication but also has significant prognosis and predictive value. KEYWORDS Central Nervous System, Immunohistochemistry, Eastern India, Meningioma, Solitary Fibrous Tumour / Hemangiopericytoma, Diffuse Large B Cell Lymphoma