Classification Of Pediatric Brain Tumors Research Articles

Editorial: 2021 WHO classification of pediatric brain tumors: a final wedding between morphology and molecular biology?

Editorial: 2021 WHO classification of pediatric brain tumors: a final wedding between morphology and molecular biology?

Pediatric brain tumors

Pediatric central nervous system (CNS) tumors differ in their relative frequency, location, histology, biological behavior and prognosis from tumors in adults. Accurate neuropathological classification of CNS tumors is essential for therapeutic decisions and inclusion in therapy optimization studies. Tissue samples are analyzed by standardized conventional histological, immunohistological and molecular pathological methods and diagnosed according to the current World Health Organization (WHO) classification for CNS tumors (2021). By identifying characteristic genetic alterations and specific epigenetic signatures, the precision in the classification of pediatric brain tumors has significantly improved in recent years. The WHO classification allows aworldwide uniform, standardized classification of brain tumors and forms the basis for comparability of international epidemiological and clinical data. In some tumor types, such as childhood gliomas and embryonal tumors, key molecules and signaling pathways have been identified in recent years that represent starting points for new mechanism-based therapeutic modalities in the treatment of these patients.

BIOL-11. PRECLINICAL MODELLING OF PEDIATRIC BRAIN TUMORS USING ORGANOID TECHNOLOGY

Abstract Molecular characterization has resulted in improved classification of pediatric brain tumors, leading to many novel (sub)types with distinct oncodriving events. To study tumor biology and to perform translational research on each of these tumors, preclinical models are essential. However, we are currently lacking sufficient models, especially in vitro, to represent each (sub)type and their heterogeneity. To generate large series of preclinical in vitro models for pediatric brain tumors, we are using organoid technology. Cells from patient samples and patient-derived xenograft samples have been taken into culture to establish 3D organoids using tumor type specific culture conditions. These organoid lines retain the molecular characteristics of the original tumor tissue. They can be used to perform high-throughput drug screens, genetic manipulations, and co-cultures with, for instance, immune cells. Viable tissue is not always available for all tumor (sub)types and specific oncodrivers. To circumvent this lack of tissue, we can also induce tumors in vitro. Therefore, we generate cerebral and cerebellar brain organoids from human pluripotent stem cells. These organoids mimic human developing brain cells and can be genetically manipulated to model different brain tumor types. These genetically engineered brain tumor models allow us to study the cellular origins of pediatric brain tumors and the different tumor driving mechanisms. Tumors induced in the brain organoids histologically and molecularly resemble human patient samples based on (single cell) transcriptomic analyses. Moreover, the tumor cells are able to establish xenografts in mouse brains. In summary, organoid technology provides a novel avenue to establish in vitro models for pediatric brain tumors. At the meeting we will present data for various new ependymoma, medulloblastoma and embryonal brain tumor organoid models.

P04.03.B Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens

Abstract Background Cavitating ultrasonic aspirator (CUSA) devices are commonly used in neurosurgical procedures to carefully debulk tumor from adjacent healthy brain tissue. Here, we explore the feasibility of using ultrasonic minced tumor tissue to classify otherwise discarded sample material by DNA methylation according to the respective World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) using low pass nanopore whole genome sequencing. Material and Methods 21 ultrasonic aspirated specimens from patients undergoing surgery in the department of pediatric neurosurgery at the Charité-Universitätsmedizin Berlin with either newly diagnosed cerebral lesions or pre-treated lesions were processed by nanopore sequencing to generate copy number profiles and ad-hoc random forest classification. Results were compared to microarray-based routine profiling. Tumor purity was assessed. Results In 19/21 (90.5 %) samples the minimum amount of 1,000 CpG sites were sequenced. In 20/21 (95.2 %) cases copy number variation profiles could be generated and matched microarray derived copy number profiles, allowing for identification of diagnostically or therapeutically relevant pathognomonic alterations. 12/17 (70.6 %) samples were concordantly classified to the corresponding microarray-based diagnosis by routine neuropathological workup. Applying recently defined thresholds for nanopore-based classification resulted in sensitivity of 64.7 % and specificity of 100 %. Conclusion CUSA referred sample material of pediatric brain tumors allows for methylation-based classification according to the respective WHO classification of CNS tumors with acceptable sensitivity and high specificity. Hereby, a promising opportunity for accurate classification of pediatric brain tumors by a time- and cost-efficient advanced molecular technique is offered using otherwise discarded tumor tissue.

HGG-59. Pediatric high-grade gliomas and the WHO classification on CNS Tumors - Different perspectives of pediatric neuro-oncologists and neuropathologists in the light of recent updates

Abstract BACKGROUND: The WHO Classification of Tumors of the Central Nervous System has undergone major restructuring following rapid advances in brain tumor genomics and epigenomics. The most significant changes resulted from the introduction of molecularly defined diagnostic criteria in 2016 (revised 4th edition). In 2021 (5th edition), further essential molecular criteria were incorporated. In the present study, we sought to investigate potential differences between specialists in perception of these newly defined molecular subtypes of pediatric high-grade gliomas (pedHGG). METHODS: We designed a 22-question survey studying the impact of the revised 4th edition of the WHO classification on pedHGG. Data were collected and statistically analyzed to capture the spectrum of viewpoints and possible differences among neuro-oncologists and neuropathologists. RESULTS: 465 participants from 53 countries responded, of which 187 pediatric neuro-oncologists (40%), 160 neuropathologists (34%) and 118 experts in other related fields (neurosurgeons, radiotherapists, neuroradiologists and others; 26%). Neuro-oncologists reported having issues with the introduction of new molecular entities, such as the abolishment and renaming of established tumor entities. Neuropathologists did not define these problems to the same extent. However, both groups felt that in the 2016 version, less relevant or insufficient diagnostic definitions were available for pedHGG. Within the 2021 WHO classification, a substantial improvement was perceived regarding the definition of pedHGG entities. However, some issues of high clinical relevance, like the definition of clinical phenotypes such as diffuse intrinsic pontine glioma (DIPG) and gliomatosis cerebri, are yet to be addressed. CONCLUSIONS: Within the WHO classification of pediatric brain tumors, such as high-grade gliomas, rapid changes in nomenclature have been introduced because of substantial improvement in molecular characterization. This study highlights that ongoing cross-talk between advancing classification of pedHGG subtypes and its biological relevance and clinical impact is essential.

Pediatric high-grade gliomas and the WHO CNS Tumor Classification-Perspectives of pediatric neuro-oncologists and neuropathologists in light of recent updates.

BackgroundThe WHO Classification of Tumors of the Central Nervous System has undergone major restructuring. Molecularly defined diagnostic criteria were introduced in 2016 (revised 4th edition) and expanded in 2021 (5th edition) to incorporate further essential diagnostic molecular parameters. We investigated potential differences between specialists in perception of these molecularly defined subtypes for pediatric high-grade gliomas (pedHGG).MethodsWe designed a 22-question survey studying the impact of the revised 4th edition of the WHO classification on pedHGG. Data were collected and statistically analyzed to examine the spectrum of viewpoints and possible differences between neuro-oncologists and neuropathologists.Results465 participants from 53 countries were included; 187 pediatric neuro-oncologists (40%), 160 neuropathologists (34%), and 118 additional experts (26%). Neuro-oncologists reported issues with the introduction of molecularly defined tumor types, as well as the abolishment or renaming of established tumor entities, while neuropathologists did not to the same extent. Both groups indicated less relevant or insufficient diagnostic definitions were available in 2016. Reported issues were classified and assessed in the 2021 WHO classification and a substantial improvement was perceived. However, issues of high clinical relevance remain to be addressed, including the definition of clinical phenotypes for diffuse intrinsic pontine glioma and gliomatosis cerebri.ConclusionsWithin the WHO classification of pediatric brain tumors, such as pedHGG, rapid changes in molecular characterization have been introduced. This study highlights the ongoing need for cross talk between pathologist and oncologist to advance the classification of pedHGG subtypes and ensure biological relevance and clinical impact.

Neuropathology of Pediatric Brain Tumors: A Concise Review.

Pediatric brain tumors are an incredibly diverse group of neoplasms and neuropathological tumor classification is an essential part of patient care. Classification of pediatric brain tumors has changed considerably in recent years as molecular diagnostics have become incorporated with routine histopathology in the diagnostic process. This article will focus on the fundamental major histologic, immunohistochemical, and molecular features that neuropathologists use to make an integrated diagnosis of pediatric brain tumors. This concise review will focus on tumors that are integral to the central nervous system in pediatric patients including: embryonal tumors, low and high grade gliomas, glioneuronal tumors, ependymomas, and choroid plexus tumors.

Advances in the molecular classification of pediatric brain tumors: a guide to the galaxy.

Central nervous system (CNS) tumors are the most common solid tumor in pediatrics, accounting for approximately 25% of all childhood cancers, and the second most common pediatric malignancy after leukemia. CNS tumors can be associated with significant morbidity, even those classified as low grade. Mortality from CNS tumors is disproportionately high compared to other childhood malignancies, although surgery, radiation, and chemotherapy have improved outcomes in these patients over the last few decades. Current therapeutic strategies lead to a high risk of side effects, especially in young children. Pediatric brain tumor survivors have unique sequelae compared to age-matched patients who survived other malignancies. They are at greater risk of significant impairment in cognitive, neurological, endocrine, social, and emotional domains, depending on the location and type of the CNS tumor. Next-generation genomics have shed light on the broad molecular heterogeneity of pediatric brain tumors and have identified important genes and signaling pathways that serve to drive tumor proliferation. This insight has impacted the research field by providing potential therapeutic targets for these diseases. In this review, we highlight recent progress in understanding the molecular basis of common pediatric brain tumors, specifically low-grade glioma, high-grade glioma, ependymoma, embryonal tumors, and atypical teratoid/rhabdoid tumor (ATRT). © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Involvement of Heparan Sulfate and Heparanase in Neural Development and Pathogenesis of Brain Tumors.

Brain tumors are aggressive and devastating diseases. The most common type of brain tumor, glioblastoma (GBM), is incurable and has one of the worst five-year survival rates of all human cancers. GBMs are invasive and infiltrate healthy brain tissue, which is one main reason they remain fatal despite resection, since cells that have already migrated away lead to rapid regrowth of the tumor. Curative therapy for medulloblastoma (MB), the most common pediatric brain tumor, has improved, but the outcome is still poor for many patients, and treatment causes long-term complications. Recent advances in the classification of pediatric brain tumors reveal distinct subgroups, allowing more targeted therapy for the most aggressive forms, and sparing children with less malignant tumors the side-effects of massive treatment. Heparan sulfate proteoglycans (HSPGs), main components of the neurogenic niche, interact specifically with a large number of physiologically important molecules and vital roles for HS biosynthesis and degradation in neural stem cell differentiation have been presented. HSPGs are composed of a core protein with attached highly charged, sulfated disaccharide chains. The major enzyme that degrades HS is heparanase (HPSE), an important regulator of extracellular matrix (ECM) remodeling which has been suggested to promote the growth and invasion of other types of tumors. This is of clinical interest because GBM are highly invasive and children with metastatic MB at the time of diagnosis exhibit a worse outcome. Here we review the involvement of HS and HPSE in development of the nervous system and some of its most malignant brain tumors, glioblastoma and medulloblastoma.

Advances in the classification of pediatric brain tumors through DNA methylation profiling: From research tool to frontline diagnostic.

Despite significant improvements in pediatric brain tumor therapy and outcome, too many children still die of disease, and too many survivors experience significant sequelae as a result of conventional therapies. The molecular characterization of pediatric brain tumors has afforded tremendous insight into the basic biology and clinical management of these deadly childhood diseases. Genomic, epigenomic, and transcriptional profiling have facilitated the identification of significant heterogeneity among previously uniform disease entities. In particular, DNA methylation profiling has emerged as a robust tool for identifying key disease-specific subgroups that can exhibit distinct clinical outcomes. These approaches, which also complement classic histologic techniques, can suggest key mechanistic underpinnings of tumorigenesis and open the door for better informed and more tailored therapy. By leveraging the results of large-scale classifications of disease cohorts, novel driver mutations and pathways can be uncovered, enabling the generation of faithful animal models, promoting targeted drug design, informing developmental biology, and ultimately translating into improved clinical management. In this review, progress in the epigenetic classification of common malignant pediatric brain tumors, namely medulloblastoma, ependymoma, high-grade glioma, atypical teratoid/rhabdoid tumor, and central nervous system embryonal tumors, will be discussed, and the potential role of DNA methylation profiling as a frontline diagnostic modality will be emphasized.

Abstract 5109: Somatic CRISPR/Cas9-mediated gene editing enables versatile brain tumor modeling

Abstract Despite substantial advances in the molecular classification of pediatric brain tumors over the last decade, many tumors are still incurable, have a poor prognosis or therapy-related detrimental long term effects. To develop innovative and modern therapy approaches, sophisticated mouse models, faithfully reflecting the human disease are urgently needed. However, the development of transgenic mouse lines is a time consuming process that is confronted with an increasing number of candidate genes resulting from next generation sequencing of tumor specimens. To cope with this discrepancy, more adaptable animal models are needed. Using somatic gene transfer to manipulate cells in situ holds great advantages in terms of speed and flexibility. We therefore established a system in which we are using the CRISPR/Cas9 system for somatic disruption of candidate tumor suppressor genes (TSGs) in combination with transposon-mediated overexpression of candidate oncogenes to induce murine brain tumors. By deleting Ptch1 in murine cerebella, we induced Sonic Hedgehog (SHH) subgroup medulloblastoma with high penetrance and short latency. We characterized the induced mutations in depth and did not detect recurrent off-targets using unsupervised whole genome sequencing. We further demonstrated that this method is suited to induce other brain tumor entities by targeting multiple TSGs at the same time or by combining TSG targeting with overexpression of certain oncogenes. To date we established five novel mouse models using this system. Two of these resulted from simultaneous deletion of Nf1, Pten and Trp53 or from combining overexpression of a MET fusion with a loss of Trp53, respectively. Both of these combinations led to efficient glioblastoma induction in the murine forebrain. Our results demonstrate a fast and flexible system for validating novel candidate genes and for generating faithful animal models of human cancer. Citation Format: Marc Zuckermann, Britta Ismer, Volker Hovestadt, Christiane B. Knobbe-Thomsen, Marc Zapatka, Paul A. Northcott, Martine F. Roussel, Guido Reifenberger, Peter Lichter, Stefan M. Pfister, Daisuke Kawauchi, Jan Gronych, David T. Jones. Somatic CRISPR/Cas9-mediated gene editing enables versatile brain tumor modeling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5109.

Multiparametric Analysis of Permeability and ADC Histogram Metrics for Classification of Pediatric Brain Tumors by Tumor Grade

Accurate tumor grading is essential for treatment planning of pediatric brain tumors. We hypothesized that multiparametric analyses of a combination of permeability metrics and ADC histogram metrics would differentiate high- and low-grade tumors with high accuracy. DTI and dynamic contrast-enhanced MR imaging using T1-mapping with flip angles of 2°, 5°, 10°, and 15°, followed by a 0.1-mmol/kg body weight gadolinium-based bolus was performed on all patients in addition to standard MR imaging. Permeability data were processed and transfer constant from the blood plasma into the extracellular extravascular space, rate constant from the extracellular extravascular space back into blood plasma, extravascular extracellular volume fraction, and fractional blood plasma volume were calculated from 3D tumor volumes. Apparent diffusion coefficient histogram metrics were calculated for 3 separate tumor volumes derived from T2-FLAIR sequences, T1 contrast-enhanced sequences, and permeability maps, respectively. Results from 41 patients (0.3-16.76 years of age; mean, 6.22 years) with newly diagnosed contrast-enhancing brain tumors (16 low-grade; 25 high-grade) were included in the institutional review board-approved retrospective analysis. Wilcoxon tests showed a higher transfer constant from blood plasma into extracellular extravascular space and rate constant from extracellular extravascular space back into blood plasma, and lower extracellular extravascular volume fraction (P < .001) in high-grade tumors. The mean ADCs of FLAIR and enhancing tumor volumes were significantly lower in high-grade tumors (P < .001). ROC analysis showed that a combination of extravascular volume fraction and mean ADC of FLAIR volume differentiated high- and low-grade tumors with high accuracy (area under receiver operating characteristic curve = 0.918). ADC histogram metrics combined with permeability metrics differentiate low- and high-grade pediatric brain tumors with high accuracy.

Application of pattern recognition techniques for classification of pediatric brain tumors by in vivo 3T 1H‐MR spectroscopy—A multi‐center study

Purpose3T magnetic resonance scanners have boosted clinical application of 1H‐MR spectroscopy (MRS) by offering an improved signal‐to‐noise ratio and increased spectral resolution, thereby identifying more metabolites and extending the range of metabolic information. Spectroscopic data from clinical 1.5T MR scanners has been shown to discriminate between pediatric brain tumors by applying machine learning techniques to further aid diagnosis. The purpose of this multi‐center study was to investigate the discriminative potential of metabolite profiles obtained from 3T scanners in classifying pediatric brain tumors.MethodsA total of 41 pediatric patients with brain tumors (17 medulloblastomas, 20 pilocytic astrocytomas, and 4 ependymomas) were scanned across four different hospitals. Raw spectroscopy data were processed using TARQUIN. Borderline synthetic minority oversampling technique was used to correct for the data skewness. Different classifiers were trained using linear discriminative analysis, support vector machine, and random forest techniques.ResultsSupport vector machine had the highest balanced accuracy for discriminating the three tumor types. The balanced accuracy achieved was higher than the balanced accuracy previously reported for similar multi‐center dataset from 1.5T magnets with echo time 20 to 32 ms alone.ConclusionThis study showed that 3T MRS can detect key differences in metabolite profiles for the main types of childhood tumors. Magn Reson Med 79:2359–2366, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Multiclass imbalance learning: Improving classification of pediatric brain tumors from magnetic resonance spectroscopy.

PurposeClassification of pediatric brain tumors from 1H‐magnetic resonance spectroscopy (MRS) can aid diagnosis and management of brain tumors. However, varied incidence of the different tumor types leads to imbalanced class sizes and introduces difficulties in classifying rare tumor groups. This study assessed different imbalanced multiclass learning techniques and compared the use of complete spectra and quantified metabolite profiles for classification of three main childhood brain tumor types.MethodsSingle‐voxel, Short echo time MRS data were collected from 90 patients with pilocytic astrocytoma (n = 42), medulloblastoma (n = 38), or ependymoma (n = 10). Both spectra and metabolite profiles were used to develop the learning algorithms. The borderline synthetic minority oversampling technique and AdaboostM1 were used to correct for the skewed distribution. Classifiers were trained using five different pattern recognition algorithms.ResultsUse of imbalanced learning techniques improved the balanced accuracy rate (BAR) of all classification methods (average BAR over all classification methods for spectra: oversampled data = 0.81, original = 0.63, P < 0.001; metabolite concentration: oversampled‐data = 0.91, original = 0.75, P < 0.0001). Performance of all classifiers in discriminating ependymomas increased when oversampled data were used compared with original data for both complete spectra (F‐measure P < 0.01) and metabolite profile (F‐measure P < 0.001).ConclusionImbalanced learning techniques improve the classification accuracy of childhood brain tumors from MRS where group sizes differ and facilitate the inclusion of rarer tumor types into clinical decision support systems. Magn Reson Med 77:2114–2124, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Advances in the biology and treatment of pediatric central nervous system tumors.

Central nervous system tumors represent the most common solid tumors in children and are a leading cause of cancer-related fatalities in this age group. Here, we provide an update on insights gained through molecular profiling of the most common malignant childhood brain tumors. Genomic profiling studies of medulloblastoma, ependymoma, and diffuse intrinsic pontine glioma (diffuse midline glioma, with H3-K27M mutation), have refined, if not redefined, the diagnostic classification and therapeutic stratification of patients with these tumors. They detail the substantial genetic heterogeneity across each disease type and, importantly, link genotypic information to clinical course. The most aggressive, treatment-resistant (and also treatment-sensitive) forms within each disease entity are identified, and their potentially actionable targets. Molecularly based classification of pediatric brain tumors provides a critical framework for the more precise stratification and treatment of children with brain tumors.

Next generation sequencing as an aid to diagnosis and treatment of an unusual pediatric brain cancer.

Classification of pediatric brain tumors with unusual histologic and clinical features may be a diagnostic challenge to the pathologist. We present a case of a 12-year-old girl with a primary intracranial tumor. The tumor classification was not certain initially, and the site of origin and clinical behavior were unusual. Genomic characterization of the tumor using a Clinical Laboratory Improvement Amendment (CLIA)-certified next-generation sequencing assay assisted in the diagnosis and translated into patient benefit, albeit transient. Our case argues that next generation sequencing may play a role in the pathological classification of pediatric brain cancers and guiding targeted therapy, supporting additional studies of genetically targeted therapeutics.

MicroRNA expression profiling for Molecular Classification of pediatric brain tumors

MicroRNA expression profiling for Molecular Classification of pediatric brain tumors

The "ideal" classification of pediatric central nervous system neoplasms.

The "ideal" classification of pediatric brain tumors will depend on a full characterization of pathologic variables and their influence on prognosis. Currently available information about these variables remains incomplete, even for traditional histologic and cytologic features, and certainly for those studied by the newer methods that will continue to appear. In light of the multiplicity and specialized nature of some of the techniques that are or will become available, it is suggested that specific pediatric central nervous system neoplasms be targeted for study by groups of pathologists according to a protocol that delegates specific studies to specific individuals. In light of the large number of cases required, as well as the need to control for effects of different treatments, such studies are most readily done within the framework of large cooperative clinical trials. Such organizations provide the mechanism to test the biologic significance of pathologic findings that can then be used in the ideal classification.