Classification Of Medulloblastoma Research Articles

MB-98ANALYSIS OF A FRIENDLY PANEL FOR MOLECULAR CLASSIFICATION OF MEDULLOBLASTOMA (MB) IN WNT, SHH AND NON-WNT/SHH GROUPS TO CLINICAL PRACTICE AND CLINICAL TRIALS

MB-98. ANALYSIS OF A FRIENDLY PANEL FOR MOLECULAR CLASSIFICATION OF MEDULLOBLASTOMA (MB) IN WNT, SHH AND NON-WNT/SHH GROUPS TO CLINICAL PRACTICE AND CLINICAL TRIALS Raphael Medeiros, Sidnei Epelman, and Filipe Bernei; Department of Paediatric Oncology, Hospital Santa Marcelina, Sao Paulo, SP, Brazil INTRODUCTION: The International MB Working Group suggested an algorithm for molecular classification based primarily on genomic methods. These techniques are laborious, expensive and unreliable on formalin-fixed paraffin embedded (FFPE) tissue. A few recent studies have attempted to classify MBs into three molecular subgroups using pathologist-friendly techniques. OBJECTIVE: Our goal is to validate 9 IHC biomarkers and two FISH probes panels according to recent published results in a Brazilian cohort of pediatric patients. METHODS: We retrospectively retrieved all clinical data of 76 patients from 2005 to 2015. The pathological evaluation was central review, histological classification, IHC panel for beta-catenin, DKK1, GAB1, SFRP1, GLI-1, NPR3, KCNA1, YAP1 and GLI-3 and FISH for c-MYC and N-myc. RESULTS: There was performed IHC and FISH in 46 samples. 21%, 34% and 45% was classified to group Wnt, SHH and non-Wnt/SHH respectively. Classic (89%), desmoplastic/MBEN (50%) and large cell/anaplastic (40%) types belong to Wnt, SHH and non-Wnt/ SHH groups respectively. 52% of patients were alive and 48% was dead of disease progression. 64% got complete response and 38% had recurrence. Molecular classification and recurrence was correlated with OS and PFS. Non-Wnt/SHH, c-MYC positive, large cell/anaplastic type MB and recurrence had dismal outcome. CONCLUSION: Only four IHC markers (betacatenin, YAP1, GAB1 and GLI-3) and c-MYC FISH probe were effective for molecular classification of MB. Large cell/ anaplastic type and c-MYC may predict worse survival and be allocated to more aggressive therapy. These results support to expand the availability of the panel for patients from other institutions in Brazil. Neuro-Oncology 18:iii97–iii122, 2016. doi:10.1093/neuonc/now076.93 #The Author(s) 2016. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

MM2S: personalized diagnosis of medulloblastoma patients and model systems.

BackgroundMedulloblastoma (MB) is a highly malignant and heterogeneous brain tumour that is the most common cause of cancer-related deaths in children. Increasing availability of genomic data over the last decade had resulted in improvement of human subtype classification methods, and the parallel development of MB mouse models towards identification of subtype-specific disease origins and signaling pathways. Despite these advances, MB classification schemes remained inadequate for personalized prediction of MB subtypes for individual patient samples and across model systems. To address this issue, we developed the Medullo-Model to Subtypes (MM2S) classifier, a new method enabling classification of individual gene expression profiles from MB samples (patient samples, mouse models, and cell lines) against well-established molecular subtypes [Genomics 106:96-106, 2015]. We demonstrated the accuracy and flexibility of MM2S in the largest meta-analysis of human patients and mouse models to date. Here, we present a new functional package that provides an easy-to-use and fully documented implementation of the MM2S method, with additional functionalities that allow users to obtain graphical and tabular summaries of MB subtype predictions for single samples and across sample replicates. The flexibility of the MM2S package promotes incorporation of MB predictions into large Medulloblastoma-driven analysis pipelines, making this tool suitable for use by researchers.ResultsThe MM2S package is applied in two case studies involving human primary patient samples, as well as sample replicates of the GTML mouse model. We highlight functions that are of use for species-specific MB classification, across individual samples and sample replicates. We emphasize on the range of functions that can be used to derive both singular and meta-centric views of MB predictions, across samples and across MB subtypes.ConclusionsOur MM2S package can be used to generate predictions without having to rely on an external web server or additional sources. Our open-source package facilitates and extends the MM2S algorithm in diverse computational and bioinformatics contexts. The package is available on CRAN, at the following URL: https://cran.r-project.org/web/packages/MM2S/, as well as on Github at the following URLs: https://github.com/DGendoo and https://github.com/bhklab.Electronic supplementary materialThe online version of this article (doi:10.1186/s13029-016-0053-y) contains supplementary material, which is available to authorized users.

Molecular Classification of Medulloblastoma.

Medulloblastoma (MB) is one of the most frequent malignant brain tumors in children. The current standard treatment regimen consists of surgical resection, craniospinal irradiation, and adjuvant chemotherapy. Although these treatments have the potential to increase the survival of 70–80% of patients with MB, they are also associated with serious treatment-induced morbidity. The current risk stratification of MB is based on clinical factors, including age at presentation, metastatic status, and the presence of residual tumor following resection. In addition, recent genomic studies indicate that MB consists of at least four distinct molecular subgroups: WNT, sonic hedgehog (SHH), Group 3, and Group 4. WNT and SHH MBs are characterized by aberrations in the WNT and SHH signaling pathways, respectively. WNT MB has the best prognosis compared to the other MBs, while SHH MB has an intermediate prognosis. The underlying signaling pathways associated with Group 3 and 4 MBs have not been identified. Group 3 MB is frequently associated with metastasis, resulting in a poor prognosis, while Group 4 is sometimes associated with metastasis and has an intermediate prognosis. Group 4 is the most frequent MB and represents 35% of all MBs. These findings suggest that MB is a heterogeneous disease, and that MB subgroups have distinct molecular, demographic, and clinical characteristics. The molecular classification of MBs is redefining the risk stratification of patients with MB, and has the potential to identify new therapeutic strategies for the treatment of MB.

Integrating Molecular Subclassification of Medulloblastomas into Routine Clinical Practice: A Simplified Approach.

Medulloblastoma (MB) is composed of four molecular subgroups viz. WNT, SHH, groups 3 and 4, identified using various high-throughput methods. Translation of this molecular data into pathologist-friendly techniques that would be applicable in laboratories all over the world is a major challenge. Ninety-two MBs were analyzed using a panel of 10 IHC markers, real-time PCR for mRNA and miRNA expression, and FISH for MYC amplification. β-catenin, GAB1 and YAP1 were the only IHC markers of utility in classification of MBs into three subgroups viz. WNT (9.8%), SHH (45.6%) and non-WNT/SHH (44.6%). mRNA expression could further classify some non-WNT/SHH tumors into groups 3 and 4. This, however, was dependent on integrity of RNA extracted from FFPE tissue. MYC amplification was seen in 20% of non-WNT/SHH cases and was associated with the worst prognosis. For routine diagnostic practice, we recommend classification of MBs into three subgroups: WNT, SHH and non-WNT/SHH, with supplementation by prognostic markers like MYC for non-WNT/SHH tumors. Using this panel, we propose a new three-tier risk stratification system for MBs. Molecular subgrouping with this limited panel is rapid, economical, works well on FFPE tissue and is reliable as it correlates significantly with clinicopathological parameters and patient survival.

Personalized diagnosis of medulloblastoma subtypes across patients and model systems

Molecular subtyping is instrumental towards selection of model systems for fundamental research in tumor pathogenesis, and clinical patient assessment. Medulloblastoma (MB) is a highly heterogeneous, malignant brain tumor that is the most common cause of cancer-related deaths in children. Current MB classification schemes require large sample sizes, and standard reference samples, for subtype predictions. Such approaches are impractical in clinical settings with limited tumor biopsies, and unsuitable for model system predictions where standard reference samples are unavailable. Our developed Medullo-Model To Subtype (MM2S) classifier stratifies single MB gene expression profiles without reference samples or replicates. Our pathway-centric approach facilitates subtype predictions of patient samples, and model systems including cell lines and mouse models. MM2S demonstrates >96% accuracy for patients of well-characterized normal cerebellum, WNT, or SHH subtypes, and the less-characterized Group 4 (86%) and Group 3 (78.2%). MM2S also enables classification of MB cell lines and mouse models into their human counterparts.

MB-31 * MicroRNA EXPRESSION PATTERNS IN TISSUE AND CEREBROSPINAL FLUID AID IN MOLECULAR CLASSIFICATION OF PEDIATRIC MEDULLOBLASTOMA

BACKGROUND: Recent progress in medulloblastoma biology has confirmed the presence of 4 clinically and molecularly distinct subgroups. MicroRNAs are dysregulated in cancer, including pediatric central nervous system tumors. We aim to determine if microRNA expression can aid in the molecular classification of medulloblastoma in tissue and cerebrospinal fluid (CSF). METHODS: RNA purification from 41 formalin-fixed paraffin embedded primary medulloblastoma samples was performed. TaqMan® miRNA assays were used to quantify the levels of 762 mature miRNAs from each sample using the Applied Biosystems 7900HT Fast Real-Time PCR system. Molecular subgrouping using established gene sets was performed using the Nanostring® platform. Clinical, pathologic and outcome data was collected on all patients. In a separate cohort of patients with medulloblastoma, expression of circulating miRNA was quantified in CSF at the time of diagnosis. RESULTS: Molecular subgrouping by gene expression classified tumors into WNT (n = 6), Shh (n = 5), Group 3 (n = 11) and Group 4 (n = 19) tumors. Clinical and outcome data was consistent with previously published cohorts. Consensus clustering by microRNA expression is not sufficient for molecular subgrouping. Independent of subgroup, the presence of metastatic disease at diagnosis was associated with high levels of miR-373 (p = 0.003) and miR-213 (p = 0.003) and expression of miR-497 was associated with poor overall survival (p = <.001). Highly expressed, subgroup specific miRNAs including miR-9 and miR-409-3p (WNT), miR-10a and miR-10b (Shh), miR-497 (Group 3) and miR 181a-2 (Group 4) were identified. CSF of newly diagnosed patients with medulloblastoma (n = 7) revealed high expression of tumor specific microRNAs. CONCLUSIONS: MicroRNA expression patterns alone are not sufficient for molecular subgrouping in pediatric medulloblastoma. However, over-expression of individual microRNAs are associated with presence of metastatic disease and overall survival. Subgroup specific microRNAs may aid in classification and serve as circulating biomarkers of disease.

MB-20 * EVALUATING THE ONCOGENIC POTENTIAL OF TSC1/2 MUTATIONS AND EFFICACY OF MTOR INHIBITORS IN HIGH RISK PEDIATRIC MEDULLOBLASTOMA

Medulloblastoma is the most common malignant pediatric brain tumor. Molecular profiling recently enabled the classification of medulloblastoma into four distinct subgroups, of which Group 3 patients have the worst prognosis. To identify targetable molecular vulnerabilities in Group 3 medulloblastoma, we utilized a high-throughput kinase inhibitor screening assay against the Group 3-like medulloblastoma cell line D341. Comparing inhibitor sensitivities of D341 to other medulloblastoma cell lines, >400 primary leukemia samples and >100 established human cancer cell lines, we found pronounced susceptibility to inhibitors of the PI3K/AKT/MTOR pathway as reflected by nanomolar IC50 values. We found this sensitivity to be biochemically correlated with increased phospho-MTOR as well as phosphorylation of MTOR effectors in the D341 cells when compared to the medulloblastoma cell lines exhibiting weaker or no MTOR inhibitor sensitivity. Exposure of D341 cells to the FDA-approved MTOR inhibitor everolimus resulted in a dose-dependent decrease in MTOR pathway activation and increase in cell death markers. Exome sequencing of D341 revealed a TSC2 A415V point mutation, which we found has significantly diminished TSC1-interaction potential in a heterologous expression system. Loss-of-function of the TSC1:TSC2 A415V complex concomitantly increased activation of the MTOR pathway. In silico mining of previously published exome sequencing data from primary patient samples unveils a subset of medulloblastoma tumors harboring TSC1 and TSC2 mutations in regions predicted to result in loss of function. We tested the functional consequence of these mutations using a heterologous model system and found they resulted in loss of the TSC1:TSC2 complex. Taken together, these findings corroborate that a subset of high risk medulloblastoma patients may have functionally relevant mutations in the MTOR pathway leading to oncogenic addiction to the pathway and susceptibility to MTOR inhibitors. In vitro response to an FDA-approved MTOR inhibitor may suggest a potentially promising adjunct treatment for a subgroup of medulloblastoma patients.

The biologic era of childhood medulloblastoma and clues to novel therapies.

Currently, the treatment of childhood medulloblastoma (MB) is tailored to risk groups defined by clinical parameters. Growing evidence of tumoral heterogeneity is apparent as response remains varied and unpredictable based on current treatment strategies, indicating the lack of understanding of the elusive biology that drives oncogenesis of these tumors. Advances in genomic technologies are revealing newer insights into the molecular pathogenesis of MB. Utilization of the genomic machinery has enabled the definition of new molecular markers and signaling pathways, resulting in a paradigm shift in the classification of childhood MB. Recent focus into the postgenomic era has revealed varied perturbations in the epigenetic machinery in these subtypes as likely predictive biomarkers and potential therapeutic targets. Ahead lies the task and challenge in the ability to comprehensively evaluate all these data, which could provide clues to profile the next-generation clinical trials combining conventional with molecularly targeted novel therapies.

Medulloblastoma stem cells: where development and cancer cross pathways

Brain tumors are the leading cause of childhood cancer mortality, with medulloblastoma (MB) representing the most frequent malignant tumor. The recent molecular classification of MB has reconceptualized the heterogeneity that exists within pathological subtypes by giving context to the role of key developmental signaling pathways in MB pathogenesis. The identification of cancer stem cell (CSC) populations, termed brain tumor-initiating cells (BTICs), in MB has provided novel cellular targets for the study of these aberrantly activated signaling pathways, namely, Sonic hedgehog (Shh) and Wingless (Wnt), along with the identification of novel BTIC self-renewal pathways. In this review, we discuss recent evidence for the presence of a MB stem cell that drives tumorigenesis in this malignant childhood tumor. We focus on evidence from cerebellar development, the recent identification of BTICs, the presence of activated developmental signaling pathways in MB, the role of epigenetic stem cell regulatory mechanisms, and how these developmental and epigenetic pathways may be targeted for novel therapeutic options.

Hedgehogs, Flies, Wnts and MYCs: The Time Has Come for Many Things in Medulloblastoma

Medulloblastoma epitomizes the war against childhood cancer. Although this small round blue-cell tumor accounts for only 20% of all childhood brain tumors, or just fewer than 600 new cases each year in the United States, medulloblastoma has nevertheless become a paradigm for biologic study, clinical investigation, and assessment of late effects. Craniospinal irradiation historically became the mainstay of therapy for this WHO grade 4 neoplasm because of its propensity to disseminate throughout the neuraxis via the subarachnoid space. By the 1970s, 36 Gy of craniospinal radiotherapy resulted in 5-year survival of greater than 50% for better-risk patients. With cooperative group trials in the 1980s, adjuvant chemotherapy was introduced to medulloblastoma treatment protocols (SIOP I [International Society of Paediatric Oncology], CCG 942 [Children’s Cancer Group], and POG 7909 [Pediatric Oncology Group]), leading to improved survival and subsequent reduction of radiotherapy dosage for averagerisk patients in the 1990s and early part of the last decade. A decrease in craniospinal radiotherapy from 36 Gy to 23.4 Gy resulted in better neurocognitive and physical outcomes for average-risk patients, highlighting the importance of developing appropriately riskadapted therapy. Although prognosis has improved over many years, a significant fraction of children still do not respond to standard therapy. Perhaps equally disturbing, survivors are left with a multitude of sequelae attributable to chemotherapy and radiation therapy, including cognitive impairment, hearing loss, neuropathies, seizures, endocrinopathies, strokes, and second malignancies. Thus, there is an overwhelming need to refine strategies that will minimize unnecessarily aggressive therapy for patients with low-risk disease and maximize efficacious treatment for patients with high-risk disease. Such refinement can come only with better disease or risk classification. In an era of genomic profiling, risk stratification for medulloblastoma disappointingly remains strictly clinical, based solely on age, resection extent, Chang metastasis staging, and more recently anaplasia. Since the mid 1990s, a two-tiered risk stratification system has been employed for the purposes of North American cooperative group trials. Patients older than 3 years with less than 1.5 cm of residual tumor and nonmetastatic disease are considered average risk, whereas those younger than 3 years with more than 1.5 cm of residual tumor, evidence of tumor dissemination, or diffuse anaplasia are considered high risk. Multiple histopathologic, cytogenetic, and molecular factors have been found to influence prognosis, but to date, none have been incorporated into the risk-stratification system. Histopathologically, the desmoplastic variant has long been recognized as connoting better prognosis, whereas the large-cell anaplastic variant more recently has been found to be associated with reduced survival. Moreover, isochromosome 17q, loss of heterozygosity at chromosome 17p, and high-level chromosomal gain at 8q24 (locus of c-MYC) have all been associated with large-cell anaplastic variant medulloblastoma and poor prognosis. Monosomy 6 has been associated with favorable prognosis. In addition, a number of molecular markers have been identified over the past decade and have laid the groundwork for a risk-stratification system with a biologic basis. Favorable prognosis has been described for children with high TrkC expression or nucleopositivity of -catenin, an indicator of activated Wnt signaling—a pathway now known to affect embryogenesis and cancer. Poor prognosis is indicated by overexpression of calbindin-D, elevated ErbB2 expression, and elevated expression of c-MYC, a member of the MYC family of transcription factors that stimulates cell proliferation. In recent years, large-scale genomic and gene expression profile studies have begun to parse the molecular heterogeneity of medulloblastomas into clear subtypes with associated risk stratification. Initial gene expression microarray studies used a supervised approach, grouping samples on the basis of histology, metastatic status, and survival to identify differentially expressed genes in these clinical and histologic groups. More recently, unsupervised microarray studies in medulloblastoma by Kool et al (62 samples) and Thompson et al (46 samples) each identified up to five subgroups of medulloblastoma, including a subgroup characterized by activation of the Wnt signaling pathway, associated with excellent prognosis, and a subgroup characterized by activation of the Hedgehog (Hh) signaling pathway occurring primarily in infants and adults and associated with desmoplastic histology. The Hh signaling pathway is involved in organogenesis, limb formation, brain patterning, and multiple forms of cancer. There are several Hh family ligands, the best known of which is Sonic Hedgehog (SHh) for its multiple developmental roles, including in cerebellar development. The study by Kool et al also identified a molecular subtype associated with a high rate of metastatic disease, anaplastic/ large-cell histology, and poor prognosis. In this issue of Journal of Clinical Oncology, four separate studies dovetail with previous work to crystallize a molecular classification of medulloblastoma and codify a new risk-stratification model on the basis of the molecular biology of these disease subtypes. Ellison et al JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L S VOLUME 29 NUMBER 11 APRIL 1

Childhood medulloblastoma: novel approaches to the classification of a heterogeneous disease

Increasing recognition of pediatric medulloblastoma as a heterogeneous disease, with histopathological and molecular variants that have distinct biological behaviors, will impact how the disease is classified and treated. A combination of clinicopathological evaluation and assays based on molecular subgroups of disease will allow stratification of patients into risk groups and a more tailored approach to therapy. Patients with low-risk disease could be treated with de-escalated adjuvant therapy to maximize cure while reducing long-term adverse effects, and novel therapies could be sought for patients with high-risk disease. My review encompasses a brief overview of the clinical landscape, the current World Health Organization (WHO) classification of medulloblastoma, the status of molecular subgroups, and how potential stratification schemes might impact pathologists and their practice.

Abstract 233: OTX2 copy number gain is a driver event in Shh-independent medulloblastomas

Abstract Medulloblastoma is the most common malignant brain tumor in children. With the exception of the Sonic Hedgehog (Shh) and Wnt pathways, the molecular events contributing to medulloblastoma tumorigenesis are poorly understood. In this study, we performed DNA copy number analysis upon a large cohort (n=201) of primary medulloblastomas to identify recurrent copy number events of these tumors. The most commonly gained region of the medulloblastoma genome (gained in 21% of tumors) contains the single gene OTX2, which encodes a developmental transcription factor involved in regionalization of the neural tube and specification of various CNS lineages. We found that OTX2 is also commonly overexpressed (74%, n=103) in these tumors. Molecular classification of medulloblastomas identified four distinct subtypes based on gene expression signature. OTX2 overexpression and copy number gain was limited to tumors not exhibiting a signature of Shh pathway activation. We found that OTX2 is necessary for intracranial xenograft formation by medulloblastoma cells and that its expression promotes xenograft tumor formation by immortalized primary cells. Finally, we determined that OTX2 regulates the medulloblastoma oncogene MYC. As a transcription factor, targeting OTX2 function with small molecules presents a challenge. However, retinoids can reduce OTX2 expression and inhibit medulloblastoma growth in vitro, and we have demonstrated that OTX2 silencing is required for this effect. In sum, these studies identify OTX2 as a common but targetable oncogene in Shh-independent medulloblastomas. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 233.

Histologic Features and Prognosis in Pediatric Medulloblastoma

Because individual histologic features in childhood medulloblastoma alter survival likelihood, the recent 4th edition of the World Health Organization (WHO) Classification of Brain Tumors recognizes desmoplastic/nodular medulloblastoma, medulloblastoma with extensive nodularity, large cell medulloblastoma, and anaplastic medulloblastoma, in addition to medulloblastoma with no other distinguishing features. To identify features affecting survival likelihood, we investigated 33 histologic features in 556 childhood tumors diagnosed as medulloblastoma in the Childhood Brain Tumor Consortium (CBTC) database; all features have CBTC verified read-reread reliability and those features important in the classification of medulloblastoma and its WHO variants regardless of their measured reliability. Nineteen features had no effect on survival likelihood, and 8 features were too prevalent or too rare to measure their effect on survival. Nodules, balls, high cell density, and fine fibrillary stroma improved survival likelihood; necrosis and prominent nucleoli worsened survival likelihood. Of note, the presence of desmoplasia, currently a defining feature (along with nodules) for desmoplastic/nodular medulloblastoma, had no effect on survival likelihood. We conclude that the presence of nodularity in medulloblastoma is important to improved survival likelihood, particularly when combined with balls and fine fibrillary stroma. Given the "overlap" of desmoplastic/nodular medulloblastoma and nodular medulloblastoma, we suggest they be combined into a diagnosis of nodular medulloblastoma, with nodules, balls, and fine fibrillary stroma as defining criteria. We also suggest that because of the considerable overlap of anaplastic medulloblastoma and large cell medulloblastoma they be combined into 1 diagnosis of anaplastic/large cell medulloblastoma, with necrosis and prominent nucleoli among the defining criteria.

Medulloblastomas: New directions in risk stratification

Medulloblastomas (MBs) are the most common malignant brain tumors in children. Current therapeutic approaches combine surgery, radiotherapy, and chemotherapy. Although, there has been significant improvement in long-term survival rates, the tumor remains incurable in about a third of patients while cognitive deficits and other sequelae of therapy are common among long-term survivors. Hence a major challenge remains to differentiate high-from low-risk patients and to tailor therapy based on the degree of biological aggressiveness. A clinical risk-stratification system has been widely used in MBs based on age, extent of resection and the Chang staging system. However, recent reports indicate that these clinical variables are inadequate methods of defining disease risk. This has prompted search for new markers for MB stratification. Recent studies indicate that the classification of MBs according to profiles of histopathology and molecular abnormalities possibly help better risk-stratification of patients, thereby rationalizing approaches to therapy, increasing cure rate, reducing long-term side effects and developing novel therapeutic strategies. The most accurate outcome prediction till date has been obtained through microarray gene expression profiling. In this article, the current histopathological classification and the recent advances in molecular genetics of MBs are reviewed. Global efforts to translate this knowledge of disease biology into clinical practice especially as outcome predictors are highlighted.

Molecular analysis of pediatric brain tumors.

The identification of molecular genetic abnormalities in specific types of pediatric brain tumors is beginning to play a role in the stratification of patients into treatment groups. The finding of an INI1 alteration in an atypical teratoid/rhabdoid tumor or malignant neoplasm with overlapping histologic features will be required for entry onto disease-specific protocols within the Children's Oncology Group. Refinement in the classification of medulloblastoma and malignant glioma patients will likely depend on the genetic and signaling pathways that characterize these tumors. Advances in this area will depend on the ability to identify new disease genes, validate prognostic markers, and develop biologically based therapeutic strategies to tailor treatment.

Differentiation of Medulloblastoma. Studies including immunohistochemical localization of glial fibrillary acidic protein.

A series of medulloblastomas was studied by light microscopy. The tumors were variable; astrocytic, ependymal, neuronal, and probable oligodendroglial differentiation was present. Features of glioblastoma multiforme occurred in one case. Immunoperoxidase staining for glial fibrillary acidic protein (GFAP), an antigen found only in astrocytes and ependymal cells, revealed astrocytic differentiation in 11 of 13 cases. The two GFAP-negative tumors were histologically undifferentiated. A new classification of medulloblastomas is presented, based on the multiple types of differentiation of these tumors. Neuronal, astrocytic, ependymal, and small-cell types are described. Undifferentiated tumors were more frequent in younger children. The differentiation of medulloblastoma is correlated with recent experimental studies of gliogenesis and neurogenesis. A hypothesis that medulloblastoma is a stem-cell neoplasm is presented, based on these comparative data.