Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis

Previously undescribed prognostic subclasses of high-grade astrocytoma are identified and discovered to resemble stages in neurogenesis. One tumor class displaying neuronal lineage markers shows longer survival, while two tumor classes enriched for neural stem cell markers display equally short survival. Poor prognosis subclasses exhibit markers either of proliferation or of angiogenesis and mesenchyme. Upon recurrence, tumors frequently shift toward the mesenchymal subclass. Chromosomal locations of genes distinguishing tumor subclass parallel DNA copy number differences between subclasses. Functional relevance of tumor subtype molecular signatures is suggested by the ability of cell line signatures to predict neurosphere growth. A robust two-gene prognostic model utilizing PTEN and DLL3 expression suggests that Akt and Notch signaling are hallmarks of poor prognosis versus better prognosis gliomas, respectively.

International Classification of Childhood Cancer, third edition

BACKGROUND

The third edition of the International Classification of Diseases for Oncology (ICD-O-3), which was published in 2000, introduced major changes in coding and classification of neoplasms, notably for leukemias and lymphomas, which are important groups of cancer types that occur in childhood. This necessitated a third revision of the 1996 International Classification of Childhood Cancer (ICCC-3).

METHODS

The tumor categories for the ICCC-3 were designed to respect several principles: agreement with current international standards, integration of the entities defined by newly developed diagnostic techniques, continuity with previous childhood classifications, and exhaustiveness.

RESULTS

The ICCC-3 classifies tumors coded according to the ICD-O-3 into 12 main groups, which are split further into 47 subgroups. These 2 levels of the ICCC-3 allow standardized comparisons of the broad categories of childhood neoplasms in continuity with the previous classifications. The 16 most heterogeneous subgroups are broken down further into 2-11 divisions to allow study of important entities or homogeneous collections of tumors characterized at the cytogenetic or molecular level. Some divisions may be combined across the higher-level categories, such as the B-cell neoplasms within leukemias and lymphomas.

CONCLUSIONS

The ICCC-3 respects currently existing international standards and was designed for use in international, population-based, epidemiological studies and cancer registries. The use of an international classification system is especially important in the field of pediatric oncology, in which the low frequency of cases requires rigorous procedures to ensure data comparability.

The new WHO classification of brain tumours

The new edition of the World Health Organization (WHO) book on 'Histological Typing of Tumours of the Central Nervous System' reflects the progress in brain tumour classification which has been achieved since publication of the first edition in 1979. Several new tumour entities have been added, including the pleomorphic xanthoastrocytoma, central neurocytoma, the infantile desmoplastic astrocytoma/ganglioglioma, and the dysembryoplastic neuroepithelial tumour. The list of histological variants has also been expanded. In line with recent morphological and molecular data on glioma progression, the glioblastoma is now grouped together with astrocytic tumours. The classification of childhood tumours has been largely retained, the diagnosis primitive neuroectodermal tumour (PNET) only being recommended as a generic term for cerebellar medulloblastomas and neoplasms that are histologically indistinguishable from medulloblastoma but located in the CNS at sites other than the cerebellum. The WHO grading scheme was revised and adapted to new entities but its use, as before, remains optional.

Primary brain tumours in adults

Primary CNS tumours refer to a heterogeneous group of tumours arising from cells within the CNS, and can be benign or malignant. Malignant primary brain tumours remain among the most difficult cancers to treat, with a 5 year overall survival no greater than 35%. The most common malignant primary brain tumours in adults are gliomas. Recent advances in molecular biology have improved understanding of glioma pathogenesis, and several clinically significant genetic alterations have been described. A number of these (IDH, 1p/19q codeletion, H3 Lys27Met, and RELA-fusion) are now combined with histology in the revised 2016 WHO classification of CNS tumours. It is likely that understanding such molecular alterations will contribute to the diagnosis, grading, and treatment of brain tumours. This progress in genomics, along with significant advances in cancer and CNS immunology, has defined a new era in neuro-oncology and holds promise for diagntic and therapeutic improvement. The challenge at present is to translate these advances into effective treatments. Current efforts are focused on developing molecular targeted therapies, immunotherapies, gene therapies, and novel drug-delivery technologies. Results with single-agent therapies have been disappointing so far, and combination therapies seem to be required to achieve a broad and durable antitumour response. Biomarker-targeted clinical trials could improve efficiencies of therapeutic development.

Outcomes and prognostic factors in recurrent glioma patients enrolled onto phase II clinical trials

PURPOSE

To determine aggregate outcomes and prognostic covariates in patients with recurrent glioma enrolled onto phase II chemotherapy trials.

PATIENTS AND METHODS

Patients from eight consecutive phase II trials included 225 with recurrent glioblastoma multiforme (GBM) and 150 with recurrent anaplastic astrocytoma (AA). Their median age was 45 years (range, 15 to 82 years) and their median Karnofsky performance score was 80 (range, 60 to 100). Prognostic covariates were analyzed with respect to tumor response, progression-free survival (PFS), and overall survival (OS) by multivariate logistic and Cox proportional hazards regression analyses.

RESULTS

Overall, 34 (9%) had complete or partial response, whereas 80 (21%) were alive and progression-free at 6 months (APF6). The median PFS was 10 weeks and median OS was 30 weeks. Histology was a robust prognostic factor across all outcomes. GBM patients had significantly poorer outcomes than AA patients. The APF6 proportion was 15% for GBM and 31% for AA, whereas the median PFS was 9 weeks for GBM and 13 weeks for AA. Results were also significantly poorer for patients with more than two prior surgeries or chemotherapy regimens.

CONCLUSION

Histology is a dominant factor in determining outcome in patients with recurrent glioma enrolled onto phase II trials. Future trials should be designed with separate histology strata.

Grading of astrocytomas. A simple and reproducible method

This study determines the effectiveness and reproducibility of a previously published method of grading gliomas. The method under study is for use on "ordinary astrocytoma" cell types, i.e., fibrillary, protoplasmic, gemistocytic, anaplastic astrocytomas and glioblastomas, and is based upon the recognition of the presence or absence of four morphologic criteria: nuclear atypia, mitoses, endothelial proliferation, and necrosis. The method results in a summary score which is translated into a grade as follows: 0 criteria = grade 1, 1 criterion = grade 2, 2 criteria = grade 3, 3 or 4 criteria = grade 4. The histologic material and clinical data were derived from a previously reported series of patients with astrocytomas, radiotherapeutically treated at Mayo Clinic between the years 1960 and 1969. From this series, initially graded 1 to 4, according to the Kernohan system, 287 "ordinary astrocytomas" were entered into the study; 51 pilocytic astrocytomas and microcystic cerebellar-type astrocytomas also were included for comparison. Among ordinary astrocytomas, the grading method under study distinguished 0.7% of grade 1, 17% of grade 2, 18% of grade 3, and 65.3% of grade 4. A 15-year period of follow-up was available on all surviving patients. Statistical analysis showed that in ordinary astrocytomas, each of the four histologic criteria, as well as the resultant grade, were strongly correlated to survival (P less than 0.0001). Median survival was 4 years in grade 2, 1.6 years in grade 3, and 0.7 years in grade 4 tumors. Of the two patients with grade 1 ordinary astrocytomas, 1 had 11 years of survival, and the other was alive at 15 years. Furthermore, based upon the Cox Model, grade was found to be the major prognostic factor, superceding the effects of age, sex, and location. Among ordinary astrocytomas, the grading system under consideration clearly distinguished four distinct grades of malignancy, whereas, the Kernohan grading system accurately distinguished only two major groups of patients. Survival curve of patients with our grade 2 tumors coincided with the grade 1 and 2 Kernohan survival curves. Similarly, our grade 4 survival curve coincided with the Kernohan grade 3 and 4 survival curves. As a result, our proposed grading method generated an individualized curve corresponding to grade 3 tumors. Double-blind grading between two independent observers was concordant in 94% of ordinary astrocytomas; reproducibility was 81% in low-grade (grades 1 and 2) and 96% in high-grade (grades 3 and 4) astrocytomas of ordinary type.(ABSTRACT TRUNCATED AT 400 WORDS)

Targeting brain cancer: advances in the molecular pathology of malignant glioma and medulloblastoma

Malignant brain tumours continue to be the cause of a disproportionate level of morbidity and mortality across a wide range of individuals. The most common variants in the adult and paediatric populations - malignant glioma and medulloblastoma, respectively - have been the subject of increasingly intensive research over the past two decades that has led to considerable advances in the understanding of their basic biology and pathogenesis. This Review summarizes these developments in the context of the evolving notion of molecular pathology and discusses the implications that this work has on the design of new treatment regimens.

Primary brain tumours in adults

The most frequent primary brain tumours in adults are gliomas and primary CNS lymphomas. In gliomas, molecular genetic analysis plays an increasing part in classification and treatment planning, a feature well illustrated by the chemosensitive oligodendrogliomas. Unfortunately, management of glioblastoma is still mainly palliative. Incidence of primary CNS lymphoma has increased strikingly in the past 20 years; substantial progress has been achieved in patients who are immunocompetent with the addition of methotrexate-based chemotherapy to radiotherapy, but the potential neurotoxic effects of this combination in elderly patients is worrisome.

Glioma Subclassifications and Their Clinical Significance

The impact of targeted therapies in glioma has been modest. All the therapies that have demonstrated a significant survival benefit for gliomas in Phase III trials, including radiation, chemotherapy (temozolomide and PCV [procarbazine, lomustine, vincristine]), and tumor-treating fields, are based on nonspecific targeting of proliferating cells. Recent advances in the molecular understanding of gliomas suggest some potential reasons for the failure of more targeted therapies in gliomas. Specifically, the histologic-based glioma classification is composed of multiple different molecular subtypes with distinct biology, natural history, and prognosis. As a result of these insights, the diagnosis and classification of gliomas have recently been updated by the World Health Organization. However, these changes and other novel observations regarding glioma biomarkers and subtypes highlight several clinical challenges. First, the field is faced with the difficulty of reinterpreting the results of prior studies and retrospective data using the new classifications to clarify prognostic assessments and treatment recommendations for patients. Second, the new classifications and insights require rethinking the design and stratification of future clinical trials. Last, these observations provide the essential framework for the development and testing of new specific targeted therapies for particular glioma subtypes. This review aims to summarize the current literature regarding glioma subclassifications and their clinical relevance in this evolving field.

Brain and other central nervous system tumor statistics, 2021

Brain and other central nervous system (CNS) tumors are among the most fatal cancers and account for substantial morbidity and mortality in the United States. Population-based data from the Central Brain Tumor Registry of the United States (a combined data set of the National Program of Cancer Registries [NPCR] and Surveillance, Epidemiology, and End Results [SEER] registries), NPCR, National Vital Statistics System and SEER program were analyzed to assess the contemporary burden of malignant and nonmalignant brain and other CNS tumors (hereafter brain) by histology, anatomic site, age, sex, and race/ethnicity. Malignant brain tumor incidence rates declined by 0.8% annually from 2008 to 2017 for all ages combined but increased 0.5% to 0.7% per year among children and adolescents. Malignant brain tumor incidence is highest in males and non-Hispanic White individuals, whereas the rates for nonmalignant tumors are highest in females and non-Hispanic Black individuals. Five-year relative survival for all malignant brain tumors combined increased between 1975 to 1977 and 2009 to 2015 from 23% to 36%, with larger gains among younger age groups. Less improvement among older age groups largely reflects a higher burden of glioblastoma, for which there have been few major advances in prevention, early detection, and treatment the past 4 decades. Specifically, 5-year glioblastoma survival only increased from 4% to 7% during the same time period. In addition, important survival disparities by race/ethnicity remain for childhood tumors, with the largest Black-White disparities for diffuse astrocytomas (75% vs 86% for patients diagnosed during 2009-2015) and embryonal tumors (59% vs 67%). Increased resources for the collection and reporting of timely consistent data are critical for advancing research to elucidate the causes of sex, age, and racial/ethnic differences in brain tumor occurrence, especially for rarer subtypes and among understudied populations.

Genetic and molecular epidemiology of adult diffuse glioma

The WHO 2007 glioma classification system (based primarily on tumour histology) resulted in considerable interobserver variability and substantial variation in patient survival within grades. Furthermore, few risk factors for glioma were known. Discoveries over the past decade have deepened our understanding of the molecular alterations underlying glioma and have led to the identification of numerous genetic risk factors. The advances in molecular characterization of glioma have reframed our understanding of its biology and led to the development of a new classification system for glioma. The WHO 2016 classification system comprises five glioma subtypes, categorized by both tumour morphology and molecular genetic information, which led to reduced misclassification and improved consistency of outcomes within glioma subtypes. To date, 25 risk loci for glioma have been identified and several rare inherited mutations that might cause glioma in some families have been discovered. This Review focuses on the two dominant trends in glioma science: the characterization of diagnostic and prognostic tumour markers and the identification of genetic and other risk factors. An overview of the many challenges still facing glioma researchers is also included.

Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas

Mutations in the critical chromatin modifier ATRX and mutations in CIC and FUBP1, which are potent regulators of cell growth, have been discovered in specific subtypes of gliomas, the most common type of primary malignant brain tumors. However, the frequency of these mutations in many subtypes of gliomas, and their association with clinical features of the patients, is poorly understood. Here we analyzed these loci in 363 brain tumors. ATRX is frequently mutated in grade II-III astrocytomas (71%), oligoastrocytomas (68%), and secondary glioblastomas (57%), and ATRX mutations are associated with IDH1 mutations and with an alternative lengthening of telomeres phenotype. CIC and FUBP1 mutations occurred frequently in oligodendrogliomas (46% and 24%, respectively) but rarely in astrocytomas or oligoastrocytomas ( more than 10%). This analysis allowed us to define two highly recurrent genetic signatures in gliomas: IDH1/ATRX (I-A) and IDH1/CIC/FUBP1 (I-CF). Patients with I-CF gliomas had a significantly longer median overall survival (96 months) than patients with I-A gliomas (51 months) and patients with gliomas that did not harbor either signature (13 months). The genetic signatures distinguished clinically distinct groups of oligoastrocytoma patients, which usually present a diagnostic challenge, and were associated with differences in clinical outcome even among individual tumor types. In addition to providing new clues about the genetic alterations underlying gliomas, the results have immediate clinical implications, providing a tripartite genetic signature that can serve as a useful adjunct to conventional glioma classification that may aid in prognosis, treatment selection, and therapeutic trial design.

Validation of the RTOG recursive partitioning analysis (RPA) classification for brain metastases

PURPOSE

The Radiation Therapy Oncology Group (RTOG) previously developed three prognostic classes for brain metastases using recursive partitioning analysis (RPA) of a large database. These classes were based on Karnofsky performance status (KPS), primary tumor status, presence of extracranial system metastases, and age. An analysis of RTOG 91-04, a randomized study comparing two dose-fractionation schemes with a comparison to the established RTOG database, was considered important to validate the RPA classes.

METHODS AND MATERIALS

A total of 445 patients were randomized on RTOG 91-04, a Phase III study of accelerated hyperfractionation versus accelerated fractionation. No difference was observed between the two treatment arms with respect to survival. Four hundred thirty-two patients were included in this analysis. The majority of the patients were under age 65, had KPS 70-80, primary tumor controlled, and brain-only metastases. The initial RPA had three classes, but only patients in RPA Classes I and II were eligible for RTOG 91-04.

RESULTS

For RPA Class I, the median survival time was 6. 2 months and 7.1 months for 91-04 and the database, respectively. The 1-year survival was 29% for 91-04 versus 32% for the database. There was no significant difference in the two survival distributions (p = 0.72). For RPA Class II, the median survival time was 3.8 months for 91-04 versus 4.2 months for the database. The 1-year survival was 12% and 16% for 91-04 and the database, respectively (p = 0.22).

CONCLUSION

This analysis indicates that the RPA classes are valid and reliable for historical comparisons. Both the RTOG and other clinical trial organizers should currently utilize this RPA classification as a stratification factor for clinical trials.

Delineation of two clinically and molecularly distinct subgroups of posterior fossa ependymoma

Despite the histological similarity of ependymomas from throughout the neuroaxis, the disease likely comprises multiple independent entities, each with a distinct molecular pathogenesis. Transcriptional profiling of two large independent cohorts of ependymoma reveals the existence of two demographically, transcriptionally, genetically, and clinically distinct groups of posterior fossa (PF) ependymomas. Group A patients are younger, have laterally located tumors with a balanced genome, and are much more likely to exhibit recurrence, metastasis at recurrence, and death compared with Group B patients. Identification and optimization of immunohistochemical (IHC) markers for PF ependymoma subgroups allowed validation of our findings on a third independent cohort, using a human ependymoma tissue microarray, and provides a tool for prospective prognostication and stratification of PF ependymoma patients.

Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by genetic instability, intratumoral histopathological variability, and unpredictable clinical behavior. We investigated global gene expression in surgical samples of brain tumors. Gene expression profiling revealed large differences between normal brain samples and tumor tissues and between GBMs and lower-grade oligodendroglial tumors. Extensive differences in gene expression were found among GBMs, particularly in genes involved in angiogenesis, immune cell infiltration, and extracellular matrix remodeling. We found that the gene expression patterns in paired specimens from the same GBM invariably were more closely related to each other than to any other tumor, even when the paired specimens had strikingly divergent histologies. Survival analyses revealed a set of approximately 70 genes more highly expressed in rapidly progressing tumors that stratified GBMs into two groups that differed by >4-fold in median duration of survival. We further investigated one gene from the group, FABP7, and confirmed its association with survival in two unrelated cohorts totaling 105 patients. Expression of FABP7 enhanced the motility of glioma-derived cells in vitro. Our analyses thus identify and validate a prognostic marker of both biologic and clinical significance and provide a series of putative markers for additional evaluation.

Primary and secondary glioblastomas: from concept to clinical diagnosis

Glioblastomas may develop de novo (primary glioblastomas) or through progression from low-grade or anaplastic astrocytomas, (secondary glioblastomas). These subtypes of glioblastoma constitute distinct disease entities that evolve through different genetic pathways, affect patients at different ages, and are likely to differ in prognosis and response to therapy. Primary glioblastomas develop in older patients and typically show EGFR overexpression, PTEN (MMAC1) mutations, CDKN2A (p16) deletions, and less frequently, MDM2 amplification. Secondary glioblastomas develop in younger patients and often contain TP53 mutations as the earliest detectable alteration. These characteristics are derived largely from patients selected on the basis of clinical history and sequential biopsies. Currently available data are insufficient for a substitution of histologic classification and grading of astrocytic tumors by genetic typing alone. More subtypes of glioblastomas may exist with intermediate clinical and genetic profiles, a factor exemplified by the giant-cell glioblastoma that clinically and genetically occupies a hybrid position between primary (de novo) and secondary glioblastomas. Future research should aim at the identification of criteria for a combined clinical, histologic, and genetic classification of astrocytic tumors.

Relationship of glioblastoma multiforme to neural stem cell regions predicts invasive and multifocal tumor phenotype

Neural stem cells with astrocyte-like characteristics exist in the human brain subventricular zone (SVZ), and these cells may give rise to glioblastoma multiforme (GBM). We therefore analyzed MRI features of GBMs in specific relation to the SVZ. We reviewed the preoperative and serial postoperative MR images of 53 patients with newly diagnosed GBM. The spatial relationship of the contrast-enhancing lesion (CEL) with the SVZ and cortex was determined preoperatively. Classification was as follows: group I, CEL contacting SVZ and infiltrating cortex; group II, CEL contacting SVZ but not involving cortex; group III, CEL not contacting SVZ but involving cortex; and group IV, CEL neither contacting SVZ nor infiltrating cortex. Patients with group I GBMs (n = 16) were most likely to have multifocal disease at diagnosis (9 patients, 56%, p = 0.001). In contrast, group IV GBMs (n = 14) were never multifocal. Group II (n = 14) and group III (n = 9) GBMs were multifocal in 11% and 29% of cases, respectively. Group I GBMs always had tumor recurrences noncontiguous with the initial lesion(s), while group IV GBM recurrences were always bordering the primary lesion. Group I GBMs may be most related to SVZ stem cells; these tumors were in intimate contact with the SVZ, were most likely to be multifocal at diagnosis, and recurred at great distances to the initial lesion(s). In contrast, group IV GBMs were always solitary lesions; these may arise from non-SVZ, white matter glial progenitors. Our MRI-based classification of GBMs may further our understanding of GBM histogenesis and help predict tumor recurrence pattern.

The oligodendroglial lineage marker OLIG2 is universally expressed in diffuse gliomas

Astrocytomas, oligodendrogliomas, and oligoastrocytomas, collectively referred to as diffuse gliomas, are the most common primary brain tumors. These tumors are classified by histologic similarity to differentiated astrocytes and oligodendrocytes, but this approach has major limitations in guiding modern treatment and research. Lineage markers represent a potentially useful adjunct to morphologic classification. The murine bHLH transcription factors Olig1 and Olig2 are expressed in neural progenitors and oligodendroglia and are essential for oligodendrocyte development. High OLIG expression alone has been proposed to distinguish oligodendrogliomas from astrocytomas, so we critically evaluated OLIG2 as a marker by immunohistochemical and oligonucleotide microarray analysis. OLIG2 protein is faithfully restricted to normal oligodendroglia and their progenitors in human brain. Immunohistochemical analysis of 180 primary, metastatic, and non-neural human tumors shows OLIG2 is highly expressed in all diffuse gliomas. Immunohistochemistry and microarray analyses demonstrate higher OLIG2 in anaplastic oligodendrogliomas versus glioblastomas, which are heterogeneous with respect to OLIG2 levels. OLIG2 protein expression is present but inconsistent and generally lower in most other brain tumors and is absent in non-neuroectodermal tumors. Overall, OLIG2 is a useful marker of diffuse gliomas as a class. However, expression heterogeneity of OLIG2 in astrocytomas precludes immunohistochemical classification of individual gliomas by OLIG2 alone.

Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy

Although conventional proton magnetic resonance imaging has increased our ability to detect brain tumors, it has not enhanced to nearly the same degree our ability to diagnose tumor type. Proton magnetic resonance spectroscopy is a safe, noninvasive means of performing biochemical analysis in vivo. Using this technique, we characterized and classified tissue from normal brains, as well as tissue from the five most common types of adult supratentorial brain tumors. These six tissue types differed in their pattern across the six metabolites measured. 'Leaving-one-out' linear discriminant analyses based on these resonance profiles correctly classified 104 of 105 spectra, and, whereas conventional preoperative clinical diagnosis misclassified 20 of 91 tumors, the linear discriminant analysis approach missed only 1. Thus, we have found that a pattern-recognition analysis of the biochemical information obtained from proton magnetic resonance spectroscopy can enable accurate, noninvasive diagnosis of the most prevalent types of supratentorial brain tumors.

Integrated Molecular and Clinical Analysis of 1,000 Pediatric Low-Grade Gliomas

Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS-mitogen-activated protein kinase (RAS/MAPK) pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. Eighty-four percent of cases harbored a driver alteration, while those without an identified alteration also often exhibited upregulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared with SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status

The methylation status of the O⁶-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.