scholarly journals Meningioma epigenetic grouping reveals biologic drivers and therapeutic vulnerabilities

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.

scholarly journals Meningioma epigenetic grouping reveals biologic drivers and therapeutic vulnerabilities

2020 ◽  
Author(s):  
Abrar Choudhury ◽  
Stephen T. Magill ◽  
Charlotte D. Eaton ◽  
Briana C. Prager ◽  
William C. Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Dna Methylation ◽  
Central Nervous System ◽  
Nervous System ◽  
Immune Cell ◽  
Molecular Therapy ◽  
Intermediate Outcomes ◽  
Dna Methylation Profiling ◽  
New Treatments ◽  
Methylation Profiling

SUMMARYMeningiomas 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.

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

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.

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

BMC Cancer ◽  
2009 ◽  
Vol 9 (1) ◽  
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

scholarly journals Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas

2021 ◽  
Author(s):  
Laetitia Lebrun ◽  
Martin Bizet ◽  
Barbara Melendez ◽  
Barbara Alexiou ◽  
Lara Absil ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Central Nervous System ◽  
Cns Tumors ◽  
High Grade ◽  
Wild Type ◽  
Molecular Analyses ◽  
Classification Approach ◽  
Dna Methylation Profiling ◽  
Reference Cohort ◽  
Methylation Profiling

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 &lt;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.

scholarly journals The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Shirin Karimi ◽  
Jeffrey A. Zuccato ◽  
Yasin Mamatjan ◽  
Sheila Mansouri ◽  
Suganth Suppiah ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Central Nervous System ◽  
Nervous System ◽  
Patient Care ◽  
Classification Systems ◽  
Tumor Classification ◽  
Tumor Board ◽  
Molecular Diagnostic ◽  
Cns Tumor ◽  
Methylation Profiling

Abstract Background Molecular signatures are being increasingly incorporated into cancer classification systems. DNA methylation-based central nervous system (CNS) tumor classification is being recognized as having the potential to aid in cases of difficult histopathological diagnoses. Here, we present our institutional clinical experience in integrating a DNA-methylation-based classifier into clinical practice and report its impact on CNS tumor patient diagnosis and treatment. Methods Prospective case review was undertaken at CNS tumor board discussions over a 3-year period and 55 tumors with a diagnosis that was not certain to two senior neuropathologists were recommended for methylation profiling based on diagnostic needs. Tumor classification, calibrated scores, and copy number variant (CNV) plots were obtained for all 55 cases. These results were integrated with histopathological findings to reach a final diagnosis. We retrospectively reviewed each patient's clinical course to determine final neuro-pathology diagnoses and the impact of methylation profiling on their clinical management, with a focus on changes that were made to treatment decisions. Results Following methylation profiling, 46 of the 55 (84%) challenging cases received a clinically relevant diagnostic alteration, with two-thirds having a change in the histopathological diagnosis and the other one-third obtaining clinically important molecular diagnostic or subtyping alterations. WHO grading changed by 27% with two-thirds receiving a higher grade. Patient care was directly changed in 15% of all cases with major changes in clinical decision-making being made for these patients to avoid unnecessary or insufficient treatment. Conclusions The integration of methylation-based CNS tumor classification into diagnostics has a substantial clinical benefit for patients with challenging CNS tumors while also avoiding unnecessary health care costs. The clinical impact shown here may prompt the expanded use of DNA methylation profiling for CNS tumor diagnostics within prominent neuro-oncology centers globally.

scholarly journals Blood Surrogate Epigenetic Biomarkers of Atherosclerosis Reveal Common Signature of Inflamm-Aging-Disorders

Proceedings ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 39
Author(s):  
Ken Declerck ◽  
Wim Vanden Berghe
Keyword(s):  
Dna Methylation ◽  
Immune Cell ◽  
Epigenetic Mark ◽  
Epigenetic Clock ◽  
Blood Samples ◽  
Associated Diseases ◽  
Epigenetic Biomarkers ◽  
Cardiometabolic Disorders ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

DNA methylation is the most well-known epigenetic modification of DNA. This epigenetic mark is crucial in controlling gene expression profiles, maintaining cellular identity, genomic imprinting and X-chromosome inactivation. Furthermore, DNA methylation is plastic and can adapt to environmental stimuli, acting as a cellular memory of past events. Whereas epigenetic DNA methylation profiling in cancer diagnostics is now well established, associations with other chronic age-associated diseases, including obesity, diabetes, cardiovascular and neurological diseases have recently started to be explored for prognostic, diagnostic and therapeutic applications. Upon genome-wide DNA methylation profiling of whole blood samples from atherosclerotic patients, we characterized various atherosclerosis specific differentially methylated regions (DMRs). Interestingly, similar DMRs were also observed in other age-and inflammation-associated diseases, like obesity, cancer, Alzheimer’s and Parkinson’s disease, both in blood as well as in brain and tumor tissues. This suggests that inflammaging diseases share a common epigenetic signature of the immune system, which is different from the classic epigenetic clock signature. Furthermore, a cardio-protective flavanol-rich diet intervention can partially reverse this inflammaging disease associated epigenetic pattern. We found that this methylation profile mainly reflects shifts in immune cell type composition and infiltrating immune cell populations. Upon correcting for differences in immune cell composition in blood samples, we identified BRCA1 DNA methylation as an atherosclerosis-specific methylation biomarker irrespective of variations in immune cell biomarkers. How BRCA1 DNA methylation differentially promotes cancer, neurodegeneration or atherosclerosis pathologies requires further investigation. In conclusion, atherosclerosis patient blood samples reveal inflammaging and atherosclerosis-specific DNA methylation biomarkers, which could potentially be used as lifestyle biomarkers to estimate disease risk of neurodegeneration, cardiometabolic disorders and cancer in aging populations.

Sign in / Sign up

Export Citation Format

Share Document