Updates on the 2016 World Health Organization Classification of Pediatric Tumors of the Central Nervous System - a systematic review.
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ABSTRACT:
SUBMITTER: Cosnarovici MM
PROVIDER: S-EPMC8357361 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The latest World Health Organization (WHO) classification of tumors of the central nervous system (CNS) integrates both histological and molecular features in the definition of diagnostic entities. This new approach enrolls novel entities of gliomas. In this study, we aimed to reveal the epidemiological characteristics, including age at diagnosis, gender ratio, tumor distribution and survival, of these new entities. We retrospectively reclassified 1210 glioma samples according to the 2016 CNS WHO diagnostic criteria. In our cohort, glioblastoma multiforme (GBM) with wildtype isocitrate dehydrogenase (IDH) was the most common malignant tumor in the brain. Almost all gliomas were more prevalent in males, especially in the cluster of WHO grade III gliomas and IDH-wildtype GBM. Age at diagnosis was directly proportional to tumor grade. With respect to the distribution by histology, we found that gliomas concurrent with IDH-mutant and 1p/19q-codeleted or with single IDH-mutant were mainly distributed in frontal lobe, while those with IDH-wildtype were dominant in temporal lobe. Lesions located in insular lobe were more likely to be IDH-mutant astrocytoma. In summary, our results elucidated the epidemiological characteristics as well as the regional constituents of these new gliomas entities, which could bring insights into tumorigenesis and personalized treatment of Chinese glioma population.
| S-EPMC5386767 | biostudies-literature
Project description:Central nervous system (CNS) tumors are the second most common type of cancer and the most common cause of cancer death in pediatric patients. New therapies are desperately needed for some of the most malignant of all cancers. Immunotherapy has emerged in the past two decades as an additional avenue to augment/replace traditional therapies (such as chemotherapy, surgery, and radiation therapy). This article first discusses the unique nature of the pediatric CNS immune system and how it interacts with the systemic immune system. It then goes on to review three important and widely studied types of immune therapies: checkpoint inhibitors, vaccines, and radiation therapy, and touches on early studies of antibody-mediated immunogenic therapies, Finally, the article discusses the importance of combination immunotherapy for pediatric CNS tumors, and addresses the neurologic toxicities associated with immunotherapies.
| S-EPMC10598668 | biostudies-literature
Project description:Introduction The 2021 World Health Organization (WHO) classification of tumors of the central nervous system (CNS) has introduced significant changes to tumor taxonomy. One of the most significant changes in the isolation of isocitrate dehydrogenase (IDH) mutant forms of glioblastoma multiforme (GBM) into separate entities, as well as no longer allowing for entries to be classified as not otherwise specified (NOS). As a result, this entity now includes only the most aggressive adult-type tumors. As such, established prognostic factors no longer apply, as they now form the criteria of different disease entries or have been established based on a mixed cohort. Herein, we aimed to reclassify glioblastoma cases diagnosed per the 2016 WHO tumors of the CNS classification into the 2021 WHO tumors of the CNS classification and establish a patient survival pattern based on age, gender, tumor location, and size as well as tumor O-6-methylguanine-DNA methyltransferase (MGMT) mutation. Materials and methods A retrospective, non-clinical approach was utilized. Biopsy specimens of adults diagnosed with GBM, WHO grade 4, NOS in the period February 2018-February 2021 were reevaluated. The data regarding the patient's gender and age were withdrawn from the medical documentation. Immunohistochemistry was performed with mouse monoclonal anti-IDH R132H and rabbit polyclonal anti-MGMT. Radiology data on tumor location and size were pulled from the radiology repository. Data were statistically analyzed for significance, using Kaplan-Meier survival analysis, with a 95% confidence interval and p<0.05 defined as significant. Results A total of 58 cases fit the set criteria, with eight of them (13.7%) harboring an IDH R132H mutation and were hence reclassified as diffuse astrocytoma IDH-mutant, WHO CNS grade 4. The cases that retained their GBM classification included n=28 males and n=22 females, a male to female ratio of 1.27:1, and a mean age of 65.3 years (range 43-86 years). The MGMT mutational status revealed a total of n=17 positive cases (35%), while the remaining cases were negative. No hemispheric predilection could be established. Lobar predilection was as follows: temporal (37.78%), parietal (28.89%), frontal (24.44%), and occipital (8.89%). The mean tumor size measured on neuroradiology across the cohort was 50.51 mm (range 20-76 mm). The median survival across cases was 255.96 days (8.41 months), with a range of 18-1150 days (0.59-37.78 months). No statistical correlation could be established between patient survival and gender, hemispheric location, lobar location, and tumor size. A significant difference in survival was established only when comparing the 41-50 age groups to the 71-80 and 81-90 age groups and MGMT positive versus negative tumors (p=0.0001). Conclusion From a practical standpoint, the changes implemented in the new classification of CNS tumors define GBM as the most aggressive adult type of tumor. Based on their significantly more favorable prognosis, the reclassification of IDH mutant forms of astrocytomas has had little epidemiological impact on this relatively common malignancy but has significantly underlined the dismal prognosis. The changes have also led to MGMT promoter methylation status being the only significant prognostic factor for patient survival in clinical use, based on its prediction for response to temozolomide therapy in this nosological unit clinically presenting when it has already reached immense size.
| S-EPMC8896839 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-01-18 | GSE109381 | GEO
Project description:Purpose of reviewPrimary central nervous system lymphoma (PCNSL) is an aggressive malignancy confined to the brain, spinal cord, leptomeninges, and eyes. Due to its rarity, there is a paucity of randomized trials and a varied approach to its management in the oncologic community. This review summarizes recent literature guiding current clinical practice.Recent findingsThe presentation, work up, and management of PCNSL are discussed. Induction therapy incorporates a methotrexate-based chemotherapy regimen and is generally followed by a consolidation regimen including high dose chemotherapy (with or without autologous stem cell rescue). Whole brain radiation therapy (WBRT) is a potential additional consolidation strategy. Management of relapsed and refractory disease poses a special challenge due to poor outcomes. Immunotherapy and targeted treatments are promising novel strategies for recurrent/refractory patients. Currently, there is little consensus in the management of PCNSL. Treatment recommendations should be tailored to the individual patient, with consideration for risk of neurotoxicity. New, exciting strategies are in development and when feasible, enrollment in a clinical trial should be considered.
| S-EPMC6636316 | biostudies-literature
Project description: Not available
| S-EPMC10670190 | biostudies-literature
Project description:Background: Modern neuropathology is challenged by an increasing number of clinically-relevant CNS tumor subgroups that require assessment of a multitude of molecular markers for classification, as well a highly trained medical staff. Failure to meet this challenge leads to tumor misclassification, which can have severe consequences for affected patients. Methods: We compiled a cohort of genome-wide DNA methylation profiles of 2,682 tumors from 82 histologically and/or molecularly distinct CNS tumor classes across all ages and histologies that served as reference for a Random Forest-based diagnostic classifier. This classifier was used to prospectively investigate a further 1,104 CNS tumor samples in order to determine its clinical utility. Results: The classifier was able to reliably assign tumor samples to a given diagnostic category with a misclassification rate of less than 2%. The system functioned robustly across laboratories and using different DNA methylation profiling techniques. Prospective application to clinical samples resulted in a reclassification of 12% of tumors compared with standard practice alone. A further 12% could not be classified by methylation profiling – this subset was highly enriched for unusual syndrome-associated tumors and likely novel entities. Conclusion: This study represents a proof-of-concept for the application of machine learning approaches in molecular diagnostics using a single, easy-to-use assay. The reference cohort and Random Forest-based classifier are available online as a valuable community tool for improving precision in brain tumor diagnostics. We expect that approaches similar to the one presented herein will rapidly restructure diagnostic practice in neurooncology and across tumor pathology.
2018-01-18 | GSE109379 | GEO
Project description:Background: Modern neuropathology is challenged by an increasing number of clinically-relevant CNS tumor subgroups that require assessment of a multitude of molecular markers for classification, as well a highly trained medical staff. Failure to meet this challenge leads to tumor misclassification, which can have severe consequences for affected patients. Methods: We compiled a cohort of genome-wide DNA methylation profiles of 2,682 tumors from 82 histologically and/or molecularly distinct CNS tumor classes across all ages and histologies that served as reference for a Random Forest-based diagnostic classifier. This classifier was used to prospectively investigate a further 1,104 CNS tumor samples in order to determine its clinical utility. Results: The classifier was able to reliably assign tumor samples to a given diagnostic category with a misclassification rate of less than 2%. The system functioned robustly across laboratories and using different DNA methylation profiling techniques. Prospective application to clinical samples resulted in a reclassification of 12% of tumors compared with standard practice alone. A further 12% could not be classified by methylation profiling – this subset was highly enriched for unusual syndrome-associated tumors and likely novel entities. Conclusion: This study represents a proof-of-concept for the application of machine learning approaches in molecular diagnostics using a single, easy-to-use assay. The reference cohort and Random Forest-based classifier are available online as a valuable community tool for improving precision in brain tumor diagnostics. We expect that approaches similar to the one presented herein will rapidly restructure diagnostic practice in neurooncology and across tumor pathology.
2018-01-14 | GSE90496 | GEO
Project description: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.
| S-EPMC8451154 | biostudies-literature
Project description:Pediatric Central Nervous System (CNS) tumors are the most fatal cancer diseases in childhood. Due to their localization and infiltrative nature, some tumor resections or biopsies are not feasible. In those cases, the use of minimally invasive methods as diagnostic, molecular marker detection, prognostic or monitoring therapies are emerging. The analysis of liquid biopsies which contain genetic information from the tumor has been much more widely explored in adults than in children. We compare the detection of BRAF V600E targetable mutation by digital-PCR from cell-free-DNA and EV-derived DNA (ctDNA) in serum, plasma and cerebrospinal fluid (CSF) isolated from a cohort of 29 CNS pediatric patients. Here we demonstrate that ctDNA isolated from serum and plasma could be successfully analyzed to obtain tumor genetic information which could be used to guide critical treatment decisions.
| S-EPMC7016762 | biostudies-literature