Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas

Abstract Intramedullary astrocytomas (IMAs) consist of a heterogeneous group of rare central nervous system (CNS) tumors associated with variable outcomes. A DNA methylation-based classification approach has recently emerged as a powerful tool to further classify CNS tumors. However, no DNA methylation-related studies specifically addressing to IMAs have been performed yet. In the present study, we analyzed 16 IMA samples subjected to morphological and molecular analyses, including DNA methylation profiling. Among the 16 samples, only 3 cases were classified in a reference methylation class (MC) with the recommended calibrated score (≥0.9). The remaining cases were either considered “no-match” cases (calibrated score <0.3, n = 7) or were classified with low calibrated scores (ranging from 0.32 to 0.53, n = 6), including inconsistent classification. To obtain a more comprehensive tool for pathologists, we used different unsupervised analyses of DNA methylation profiles, including our data and those from the Heidelberg reference cohort. Even though our cohort included only 16 cases, hypotheses regarding IMA-specific classification were underlined; a potential specific MC of PA_SPINE was identified and high-grade IMAs, probably consisting of H3K27M wild-type IMAs, were mainly associated with ANA_PA MC. These hypotheses strongly suggest that a specific classification for IMAs has to be investigated.

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PATH-21. CLINICAL UTILITY OF DNA METHYLATION PROFILING FOR DIAGNOSIS OF CHALLENGING CENTRAL NERVOUS SYSTEM TUMORS: THE TORONTO EXPERIENCE

Neuro-Oncology ◽

10.1093/neuonc/noz175.617 ◽

2019 ◽

Vol 21 (Supplement_6) ◽

pp. vi147-vi147

Author(s):

Shirin Karimi ◽

Jeffrey Zuccato ◽

Yasin Mamatjan ◽

Sheila Mansouri ◽

Suganth Suppiah ◽

...

Keyword(s):

Dna Methylation ◽

Central Nervous System ◽

Nervous System ◽

Clinical Utility ◽

Cns Tumors ◽

Cns Tumor ◽

Dna Methylation Profiling ◽

Diffuse Gliomas ◽

Methylation Profiling

Abstract The update on the WHO classification of central nervous system (CNS) tumors incorporated molecular signatures for a more accurate diagnosis. Recently, DKFZ has demonstrated the utility of DNA methylation profiling(MP) for molecular classification of CNS tumors. We performed a prospective clinical study over the last three years to evaluate the clinical utility ofDNA MP on FFPE samples of 66 challenging CNS tumor cases using online DKFZ classifier. Eleven samples were excluded due to low tumor DNA content or low calibration(predictive) scores(CS)< 0.3.DNA MP confirmed the original pathology diagnoses in 15(27%)cases. The integrated molecular diagnoses were changed in 38/55(70%) including establishment of a new diagnostic entity, change in molecular signature and subtyping. TheWHO grades were changed in 16(27%) of the tumors; about two-thirds resulted in upgrading. We detected non-canonical IDH mutations in 9 diffuse gliomas and the CNV plots revealed false positive FISH results for 1p/19q co-deletion in two diffuse gliomas. The CNV plots contributed to the final diagnosis in 40(72%) patients. The molecular subtypes of medulloblastoma, ependymoma and glioblastoma subclasses were determined in 36(65%) cases. Seventy-five percent of cases with confirmation of initial diagnosis or change in molecular diagnosis had CS > 0.5, among which 51% had a CS >0.9. The median and range CS of cases with new diagnostic entity and confirmed cases were 0.86(0.37–0.99) and 0.98(0.42–0.99), respectably. Furthermore, we detected higher CS in IDH-mutant gliomas in comparison to glioblastoma IDH-wild type(P=0.04). We also observed lower CS in mesenchymal glioblastoma in comparison to other subclasses. The MGMT promoter methylation was determined in 17/20(85%) glioblastoma cases. While the DKFZ group established CS of 0.9 as a cut-off for matching to methylation classes, our findings suggest lower threshold values in challenging CNS tumor cases. Our experience indicates clinical utility of MP of challenging CNS tumors as a reliable ancillary diagnostic tool in routine neuropathology practice.

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EPCO-17. METHYLATION ANALYSIS OF MATCHED PRIMARY AND RECURRENT IDHmt ASTROCYTOMA; AN UPDATE FROM THE GLIOMA LONGITUDINAL ANALYSIS NL (GLASS-NL) CONSORTIUM

Neuro-Oncology ◽

10.1093/neuonc/noab196.016 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi5-vi5

Author(s):

Wies Vallentgoed ◽

Anneke Niers ◽

Karin van Garderen ◽

Martin van den Bent ◽

Kaspar Draaisma ◽

...

Keyword(s):

Dna Methylation ◽

Surgical Resection ◽

Molecular Mechanisms ◽

Relative Proportion ◽

Low Grade ◽

High Grade ◽

Primary Tumors ◽

Genome Wide ◽

Dna Methylation Profiling ◽

Methylation Profiling

Abstract The GLASS-NL consortium, was initiated to gain insight into the molecular mechanisms underlying glioma evolution and to identify markers of progression in IDH-mutant astrocytomas. Here, we present the first results of genome-wide DNA-methylation profiling of GLASS-NL samples. 110 adult patients were identified with an IDH-mutant astrocytoma at first diagnosis. All patients underwent a surgical resection of the tumor at least twice, separated by at least 6 months (median 40.9 months (IQR: 24.0, 64.7). In 37% and 18% of the cases, patients were treated with radiotherapy or chemotherapy respectively, before surgical resection of the recurrent tumor. DNA-methylation profiling was done on 235 samples from 103 patients (102 1st, 101 2nd, 29 3rd, and 3 4th resection). Copy number variations were also extracted from these data. Methylation classes were determined according to Capper et al. Overall survival (OS) was measured from date of first surgery. Of all primary tumors, the methylation-classifier assigned 85 (87%) to the low grade subclass and 10 (10%) to the high grade subclass. The relative proportion of high grade tumors increased ~three-fold at tumor recurrence (32/101, 32%) and even further in the second recurrence (15/29, 52%). Methylation classes were prognostic, both in primary and recurrent tumors. The overall DNA-methylation levels of recurrent samples was lower than that of primary samples. This difference is explained by the increased number of high grade samples at recurrence, since near identical DNA-methylation levels were observed in samples that remained low grade. In an unsupervised analysis, DNA-methylation data derived from primary and first recurrence samples of individual patients mostly (79%) cluster together. Recurrent samples that do not cluster with their primary tumor, form a separate group with relatively low genome-wide DNA-methylation. Our data demonstrate that methylation profiling identifies a shift towards a higher grade at tumor progression coinciding with reduced genome-wide DNA-methylation levels.

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Array-based DNA methylation profiling of primary lymphomas of the central nervous system

BMC Cancer ◽

10.1186/1471-2407-9-455 ◽

2009 ◽

Vol 9 (1) ◽

Cited By ~ 19

Author(s):

Julia Richter ◽

Ole Ammerpohl ◽

José I Martín-Subero ◽

Manuel Montesinos-Rongen ◽

Marina Bibikova ◽

...

Keyword(s):

Dna Methylation ◽

Central Nervous System ◽

Nervous System ◽

Dna Methylation Profiling ◽

The Central Nervous System ◽

Methylation Profiling

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Dural-based atypical teratoid/rhabdoid tumor in an adult: DNA methylation profiling as a tool for the diagnosis

CNS Oncology ◽

10.2217/cns-2020-0006 ◽

2020 ◽

Vol 9 (2) ◽

pp. CNS54

Author(s):

Alzoubi Hiba ◽

Gianno Francesca ◽

Giangaspero Felice ◽

Bartolini Daniela ◽

Riccioni Luca ◽

...

Keyword(s):

Dna Methylation ◽

Differential Diagnosis ◽

Definitive Diagnosis ◽

Rhabdoid Tumor ◽

Cns Tumors ◽

Atypical Teratoid Rhabdoid Tumor ◽

Embryonal Tumor ◽

Dna Methylation Profiling ◽

Atypical Teratoid ◽

Methylation Profiling

Atypical teratoid/rhabdoid tumor (ATRT) is a malignant CNS embryonal tumor that mostly occurs in childhood, adult cases are rare. We report a case of a 23-year-old male with an extra-axial dura-based lesion in the left frontal area, previously diagnosed as gliosarcoma. After 6 years, the patient had a recurrence and the previous slides were reviewed. Tumor was positive for vimentin and negative for INI1. The differential diagnosis for this extra-axial tumor with long survival was rhabdoid meningioma with INI1 loss or ATRT. DNA methylation profiling was performed to reach the final and the most definitive diagnosis; the result was ATRT. Our case suggests the usefulness of DNA methylation profiling for diagnosing challenging CNS tumors.

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Integrated Genomic Classification of Melanocytic Tumors of the Central Nervous System Using Mutation Analysis, Copy Number Alterations, and DNA Methylation Profiling

Clinical Cancer Research ◽

10.1158/1078-0432.ccr-18-0763 ◽

2018 ◽

Vol 24 (18) ◽

pp. 4494-4504 ◽

Cited By ~ 8

Author(s):

Klaus G. Griewank ◽

Christian Koelsche ◽

Johannes A.P. van de Nes ◽

Daniel Schrimpf ◽

Marco Gessi ◽

...

Keyword(s):

Dna Methylation ◽

Central Nervous System ◽

Nervous System ◽

Copy Number ◽

Copy Number Alterations ◽

Melanocytic Tumors ◽

Dna Methylation Profiling ◽

The Central Nervous System ◽

Methylation Profiling

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Meningioma epigenetic grouping reveals biologic drivers and therapeutic vulnerabilities

10.21203/rs.3.rs-113172/v1 ◽

2020 ◽

Author(s):

David Raleigh ◽

Stephen Magill ◽

Charlotte Eaton ◽

Briana Prager ◽

William Chen ◽

...

Keyword(s):

Cell Cycle ◽

Dna Methylation ◽

Central Nervous System ◽

Nervous System ◽

Immune Cell ◽

Lymphatic Vessels ◽

Intermediate Outcomes ◽

Dna Methylation Profiling ◽

New Treatments ◽

Methylation Profiling

Abstract Meningiomas arising from the meningothelial central nervous system lining are the most common primary intracranial tumors, and a significant cause of neurologic morbidity and mortality1. There are no effective medical therapies for meningioma patients2,3, and new treatments have been encumbered by limited understanding of meningioma biology. DNA methylation profiling provides robust classification of central nervous system tumors4, and can elucidate targets for molecular therapy5. Here we use DNA methylation profiling on 565 meningiomas integrated with genetic, transcriptomic, biochemical, and single-cell approaches to show meningiomas are comprised of 3 epigenetic groups with distinct clinical outcomes and biological features informing new treatments for meningioma patients. Merlin-intact meningiomas (group A, 34%) have the best outcomes and are distinguished by a novel apoptotic tumor suppressor function of NF2/Merlin. Immune-enriched meningiomas (group B, 38%) have intermediate outcomes and are distinguished by immune cell infiltration, HLA expression, and lymphatic vessels. Hypermitotic meningiomas (group C, 28%) have the worst outcomes and are distinguished by convergent genetic mechanisms misactivating the cell cycle. Consistently, we find cell cycle inhibitors block meningioma growth in cell culture, organoids, xenografts, and patients. Our results establish a framework for understanding meningioma biology, and provide preclinical rationale for new therapies to treat meningioma patients.

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BIOM-57. PEDIATRIC TUMOR CLASSIFICATION THROUGH GENOME-WIDE METHYLATION PROFILING OF EXTRACELLULAR VESICLE DNA

Neuro-Oncology ◽

10.1093/neuonc/noaa215.054 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii14-ii14

Author(s):

Franz Ricklefs ◽

Cecile Maire ◽

Krys Fita ◽

Friederike Fritzsche ◽

Gertrud Kammler ◽

...

Keyword(s):

Dna Methylation ◽

Tumor Cells ◽

Copy Number ◽

Cns Tumors ◽

Copy Number Alterations ◽

Cns Tumor ◽

Original Tumor ◽

Genome Wide ◽

Dna Methylation Profiling ◽

Methylation Profiling

Abstract BACKGROUND Genome-wide methylation profiling reliably classifies pediatric central nervous system (CNS) tumors. Extracellular vesicles (EVs) are released by pediatric CNS tumor cells (pCC) and contain high molecular weight tumor DNA, rendering EVs a potential biomarker source to identify tumor subgroups, stratify patients and monitor therapy by liquid biopsy. We investigated whether the DNA in pCC-derived EVs reflects genome-wide tumor methylation profiles and allows tumor subtype classification. METHODS DNA was isolated from EVs secreted by pediatric CNS tumor cells (pCC) as well as from the shortly cultured tumor cells and from the original tumor samples (n=4 patients). Pediatric Fibroblasts and EVs derived thereof were used as a non-tumorous control. EVs were classified by nanoparticle analysis (NTA), immunoblotting, imaging flow cytometry (IFCM and electron microscopy. Genome-wide DNA methylation profiling was performed using an 850k Illumina EPIC array and results were classified according to the DKFZ brain tumor classifier and further analysed by t-SNE and Copy number alteration analysis (CNA). RESULTS The size range of pCC-derived EVs was 120–150 nm, as measured by NTA. The majority of secreted EVs exhibited high expression of common EV markers (i.e. CD9, CD63 and CD81), as characterized by IFCM. Genome-wide DNA methylation profiling of pCC-derived EVs correctly identified the methylation class of the original tumor (i.e. pilocytic astrocytoma, medulloblastoma). In addition, t-SNE analysis and copy number alterations matched the pattern of the parental pCC and original tumor samples. CONCLUSION EV DNA faithfully reflects the tumor methylation class and copy number alterations present in the parental cells and the original tumor. Methylation profiling of circulating tumor EV DNA could become a useful tool to detect and classify pediatric CNS tumors.

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