The role of meningioma epigenetics in routine clinical practice

The role of meningioma epigenetics in routine clinical practice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The role of meningioma epigenetics in routine clinical practice Lydia Karamani, Wolf Müller, Max Braune, Peter Baumgarten, Christian Senft This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6218017/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The methylation profile of meningiomas is a promising predictive tool, potentially offering greater accuracy in assessing tumor behavior compared to WHO grading. This study aimed to evaluate the clinical relevance of routine epigenetic testing in meningioma management. Methods: We retrospectively analyzed patients undergoing meningioma resection between January 2021 and December 2023. Histopathological grading (WHO) and methylation profiling (MC) with the 850k Illumina chip were performed by an independent neuropathologist. Results: A total of 106 patients were included, with 81 (76%) classified as HO grade 1, 20 (19%) as grade 2, and 5 (5%) as grade 3. Epigenetically, 55 tumors (52%) were classified as benign, 18 (17%) as intermediate, 2 (2%) as malignant and 31 (29%) as unclassified. Discordances between WHO grading and methylation profiling were observed in 18 of 74 cases. Notably, 8 WHO grade 1 tumors (16%) displayed MC-intermediate, while 9 WHO grade 2 tumors were classified as intermediate, and 1 as malignant. Tumor board decisions were made in a median of 8 days postoperatively, guided by WHO grading; however, the epigenetic report was only available after a median of 22 days. During follow-up, 15 patients experienced tumor progression. Progression was significantly associated with the meningioma classifier (r = 0.3, p = 0.0102) and tumor volume (r = 0.4, p = 0.0005), but not with WHO grading (r = 0.17, p = 0.084). PFS in MC-unclassified tumors mirrored that of the intermediate group. Conclusion: Methylation profiling demonstrates superior predictive accuracy for meningioma progression and complements WHO grading, especially in identifying malignant maningiomas. Meningioma Methylation profile MC-Classifier CNV profile Illumina Human Methylation 850k array Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Meningioma, originating from the arachnoid layer of the meninges in the brain and spinal cord, is the most common non-malignant brain tumor [ 1 ]. The WHO Classification of tumors of the central nervous system (WHO CNS 5) uses a grading system that categorizes meningiomas into three grades, comprising a total of 15 subtypes. Grade 1 meningiomas are typically associated with a benign clinical course and a low risk of recurrence, while grade 2 meningiomas have a moderate clinical behavior and a higher likelihood of recurrence. Grade 3 meningiomas, on the other hand, demonstrate malignant characteristics. In part, the WHO CNS 5 grading of meningiomas is still based on histopathological features such as mitotic activity and the presence of brain invasion, which can introduce subjectivity and inter-observer variability [ 2 ]. Despite this, the integration of molecular features into the WHO CNS5 classification reflects their increasing significance in the evaluation of meningiomas. Contemporary guidelines now recommend incorporating molecular analyses alongside histological assessments to achieve a more comprehensive evaluation of meningiomas and to guide clinical decision-making [ 3 – 5 ]. For example, the most recent cIMPACT now Update 8 proposes to assign CNS WHO grade 2 for cases with CNS WHO grade 1 morphology but chromosomal arm 1p deletion in combination with 22q deletion [ 5 ]. Combining single molecular markers and histopathological features only partially captures the full spectrum of meningioma behavior. In a multicenter retrospective study by Sahm et al., the DNA epigenome wide methylation profiling of meningiomas led to the identification of six distinct methylation classes: Methylation Class (MC) benign 1, MC benign 2, MC benign 3, MC intermediate A, MC intermediate B and MC malignant [ 6 ]. Based on the observed clinical behavior, progression rates, and prognostic accuracy, the authors proposed that the DNA methylation profile is a robust predictive factor, potentially outperforming the current WHO classification. As such, incorporating of methylation profiling into meningioma classification holds significant promise for improving prognostic accuracy, refining treatment strategies, and predicting tumor progression. The European Association of Neuro – Oncology (EANO) guidelines recommend radiotherapy for CNS WHO Grade 3 meningiomas and advocate for adjuvant radiotherapy following subtotal resection (Simpson grade IV-V) of CNS WHO grade 2 meningiomas. Additionally, palliative radiotherapy may be considered for inoperable CNS WHO grade 1 meningiomas [ 7 ]. Special attention is given to CNS WHO grade 2 meningiomas due to their heterogeneity, as these tumors can range from benign to intermediate, or even malignant in their clinical course. Optimal management following surgical resection of these tumors remains unclear, and the role of radiation is still debated [ 8 ]. A combined assessment using histopathological, molecular and methylation profiles may lead to better stratification of patients, enabling more tailored therapeutic strategies and minimizing the risk of over – or undertreatment [ 9 ]. While the prognostic value of the meningioma methylation classifier has been established, its clinical utility and relevance in modern neurooncology practice are still being explored. The integration of epigenetic markers into clinical practice is in its early stages and further refinement is needed. It remains uncertain whether the clinical implications of methylome based classification and copy number profiling will lead to definitive therapeutic decisions or whether the methylation profile will directly influence clinical management. The aim of this study is to elucidate the clinical relevance and practical application of epigenome wide methylation profiling including the MC classifier and copy number variations in routine clinical practice. Material and methods Data sources We performed a retrospective analysis of patients treated at our institution between January 2021 and December 2023. The study cohort was identified by querying the hospital’s registry using the ICD-10 codes D32.0, D32.1, D32.9, D42.0, D42.1, D42.9, C70.0, C70.1, and C70.9. Patient data were extracted from clinical charts and electronic medical records. All patients included in the study underwent surgical resection and received postoperative follow-up care, primarily at our outpatient clinic. For those who continued follow-up at external facilities, we contacted these centers to retrieve relevant follow-up data. Histological examinations were performed at a single certified institute to ensure consistency and accuracy of diagnoses. Tumor volumes were measured using the BrainLab Elements software with the Smartbrush algorithm (Version 4.5). A single author conducted all volumetric analyses to minimize variability and ensure measurements consistency. Inclusion and exclusion criteria The study included patients diagnosed with meningioma, who underwent surgery at our neurosurgical clinic between January 2021 and December 2023. Both cerebral and spinal meningiomas were analyzed. Exclusion criteria encompassed patients managed conservatively or under a “watch-and-wait” approach. Patients with sporadic multiple meningiomas as well as those with familial tumor syndromes, such as Li-Fraumeni syndrome and neurofibromatosis type 2 (NF-2), were included. Progression and follow-up Our standard follow-up protocol includes MRI imaging with and/or without contrast, at 3, and 12 months during the first postoperative year. Afterward, patients are assessed annually for three years, followed by biennial imaging. Patients with CNS WHO grade 3 malignant meningiomas or grade 2 meningiomas and residual tumor are offered radiotherapy, followed by close monitoring with follow – up visits every 3 months initially. The follow-up schedule is tailored based on several factors, including histological findings, residual tumor presence, radiotherapy status, and patient preferences. All patients are reviewed by the interdisciplinary neuro - oncology tumor board pre -, postoperatively and upon radiological detection of tumor recurrence or progression. Based on this interdisciplinary neuro - oncology tumor board treatment recommendations are given. Tumor progression was defined as radiological evidence of contrast – enhancing tissue at the tumor resection margin on MRI when tumors had been resected completely or when there was evident increase of any postoperative residual contrast enhancement. Progression-free survival (PFS) was defined as the time from surgery to either tumor progression, death, or the last recorded follow – up. Neuropathological evaluation Histological analyses were performed by independent neuropathologists, generating two separate reports. The first histological report provided details on microscopic and immunohistochemical characteristics of the tumor, including WHO grading, meningioma subtype, proliferation index, mitotic activity, brain infiltration, atypical features, and specific markers such as epithelial membrane antigen (EMA), Phosphohistone H3 (PHH3), Somatostatin receptor (SSTR), proliferation index, and progesterone receptor status. A subsequent molecular report focused on the molecular characteristics of the tumor, utilizing the Illumina Methylation EPIC v1.0 (850K) Array[ 10 ]. The methylation profile of the tumor tissues was compared to previously defined methylation classes using the publicly available database of the German Center for Cancer Research (DKFZ) based on Capper et al 2018 available via www.molecularneuropathology.org [ 11 ]. This included analysis of the brain tumor methylation classifier (versions V11b4 and V12.5) and the meningioma classifier (version V2.4) [ 12 ]. Each classifier generated a score ranging from 0 to 1, representing the tumor’s similarity to established reference groups. Copy number variation (CNV) profiles including whole chromosome arms as well as single marked genes as CDKN2A/B were also assessed. In cases of histopathologically diagnosed atypical meningiomas, next generation sequencing (NGS) was performed for the detection of TERT-promoter mutations. Statistical analysis All statistical analyses were performed using GraphPad Prism 10 software (Version 10.2.3). Categorical variables were presented as medians. Comparative analyses were conducted using the chi – square test for categorical variables and the Mann – Whitney U test for non – parametric variables. Correlation analysis was performed using the Spearman test for non-parametric variables, with p values ≤ 0.05 considered statistically significant. Kaplan – Meier survival analysis was used to evaluate progression – free survival. Results were presented in APA format. Results Demographics We analyzed data from 106 consecutive patients with meningioma who underwent surgery at our institution between January 2021 and December 2023. The median age was 65 years (range: 13 to 89 years), with a clear female predominance, yielding a female – to – male ratio of 3:1. Among the cohort, 12 patients presented with recurrent meningiomas, while 94 patients were newly diagnosed. Anatomical Distribution Of the 106 meningiomas, 17 were located along the spine, and 89 were intracranial. Among the intracranial meningiomas, 77 were confined to supratentorial regions, 9 were infratentorial, and 3 involved both supra- and infratentorial compartments. Regarding tumor location, 34 meningiomas were found on the left hemisphere, 38 on the right hemisphere, and 2 cases presented with multiple meningiomas affecting both hemispheres. Additionally, 15 meningiomas were midline lesions. Solitary meningiomas were observed in 95 cases, while 11 patients exhibited multiple meningioma – like lesions. 41 tumors were in contact with large cerebral vessels, while 60 tumors showed no association with major vascular structures. In terms of skull base involvement, 36 tumors infiltrated the skull base, whereas 62 did not. The most common tumor location was the convexity (n = 29), followed by the sphenoid wing (n = 27), falx/parasagittal region (n = 10), and the suprasellar and olfactory groove regions (n = 8). Additionally, 5 tumors were in the posterior fossa, 4 in the cerebellopontine angle, 3 in the intraorbital region and along the optic nerve sheath, 3 at the foramen magnum, 1 was intraventricular, and 1 was tentorial. Among the spinal meningiomas, the thoracic region was the most common location (n = 11), followed by the lumbar (n = 1) and cervical (n = 1) regions. Tumor Volume and Characteristics Tumor volume was calculated based on preoperative imaging for cranial meningiomas. Due to the absence of navigational preoperative imaging for spinal meningiomas, these cases were excluded from volume analysis. In cases of multiple cranial meningiomas, tumor volume was measured only for the lesion scheduled for surgery. The median volume of intracranial meningiomas was 22.75 cm³ (range: 0.14 to 205.3cm³). Peritumoral edema was present in 47 tumors (52%), while 44 tumors (48%) showed no evidence of an edematous reaction. Partial calcification was observed in 25 meningiomas (27%), whereas 66 tumors (73%) exhibited no calcification. Grading Histopathological analysis revealed that most tumors were classified as CNS WHO grade 1 (n = 81, 76%), followed by CNS WHO grade 2 (n = 20, 19%) and CNS WHO grade 3 (n = 5, 5%). The most common subtype was meningothelial (n = 27), followed by transitional (n = 19), fibroblastic (n = 16), psammomatous (n = 8), secretory (n = 3), angiomatous (n = 3), microcystic (n = 2), metaplastic (n = 1), and rhabdoid (n = 1). One CNS WHO grade 1 tumor was not further subtyped. Among the CNS WHO grade 2 meningiomas, 18 were classified as atypical, 1 as chordoid and 1 as clear cell. 5 tumors were graded as CNS WHO grade 3 tumor, e.g. anaplastic meningiomas. In addition to histology, immunohistochemical markers have been analyzed. EMA was expressed in 94% of tumors (60 positive, 40 faint positive, and 6 negative). Low mitotic activity ( 20 mitoses/10 HPF) in 3 tumors. A high proliferation index (> 20%) was found in 1 tumor, while 63 tumors (59%) had a low Ki – 67 index (< 4%) and 42 (40%) had an intermediate index (4–20%). SSTR2 was positive in 103 cases (73 strong positive, 30 faint positive), with 3 negative cases. Low PHH3 expression (0–2 cells/10HPF) was found in 63 tumors, intermediate expression (3–4 cells/10 HPF) in 12, and high expression (≥ 5 cells/10HPF) in 17. Progesterone receptor positivity was detected in 9 tumors. Additional markers such as AE1/3, STAT6, CD34, SOX10, S – 100, GFAP and Desmin were assessed in select cases. NGS was performed for markers such AKT1, ALK, TP53, EGFR in selected cases. TERT promoter mutation was tested in cases with aggressive histological features via NGS and was identified in two tumors (one tumor with histopathological criteria of CNS WHO grade 3 and one tumor with histopathological criteria of CNS WHO grade 2, both not unequivocally classifiable using DNA methylation-based classification, e.g. MC Score (Summary in Table 1 ). Table 1 Summary of immunohistochemical markers Immunohistochemical markers EMA 60 positive 40 faint positive 6 negative Mitotic count (mitosis/10HPF) 89 20 Proliferation index (Ki - 67) 63 20 % SSTR2 73 positive 30 faint positive 3 negative pHH3 (cells/10HPF) 63 0 - 2 12 3 - 4 17 ≥ 5 EMA: epithelial membrane antigen, SSTR2: somatostatin receptor 2, pHH3: phosphohistone H3 The meningioma classifier analysis categorized 55 tumors (52%) as benign, 18 (17%) as intermediate and 2 (2%) as malignant. 31 tumors (29%) could not be classified unequivocally. Assignment to a MC was most likely not reached due to either technical limitations or tumor – related complexities. In 5 out of 31 tumors without a match to a MC (16%), overt technical issues such as poor tissue composition, low DNA quality, and decalcification processes prevented classification, while in the remaining 26 cases (84%), the meningioma classifier (v2.4) yielded lower classification scores of < 0,5 without overt technical limitations. Tumors with an MC – Classifier < 0.3 are by definition unclassified. In our cohort, no tumors had a score < 0,3, e.g. were unclassifiable. However, 5 tumors exhibited a very low MC – Classifier score < 0.5 (with scores 0.49, 0.5, 0.45, 0.43, 0.46). In the remaining 21 cases, a mismatch was observed between the MC – Classifier (v2.4) and the tumor – classifier (v12.5). In mismatch cases, the highest score in 8 cases met the criteria for MC – intermediate, all of which were detected in v2.4 (scores: 0.58, 0.86, 0.83, 0.84, 0.88, 0.55, 0.8, 0.7. In the remaining 13 cases, the highest score was MC – benign, detected mostly (12/13) in v12.5 (scores 0.98, 0.98, 0.99, 0.83, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.93, 0.89, 0.98) When separating cranial and spinal meningiomas, cranial tumors were classified as 49 benign, 15 intermediate, 2 malignant, and 23 unclassified. Spinal tumors included 6 benign, 3 intermediate, and 8 unclassified cases. There was no statistically significant difference in classifier distribution between spinal and cerebral tumors (p = .0884, Mann-Whitney test). No tumors with MC malignant were found in spinal tumors. Further analysis of CNS WHO grade 1 tumors based on classifier score showed 50 MC benign, 8 MC intermediate and 23 tumors with no match, with no MC malignant. Among CNS WHO grade 2 meningiomas, 4 were benign, 9 intermediate, 6 unclassified, and 1 malignant. Methylation analysis of CNS WHO grade 3 tumors revealed 1 benign, 1 intermediate, 2 unclassified and 1 malignant case (Fig. 1 ). Of particular interest was a case of CNS WHO grade 3 tumor and MC benign profile. Histopathological evaluation characterized this tumor as anaplastic based on the high mitotic activity (> 20 mitoses/ 10HPF), which was supported by elevated pHH3 expression with 23 cells/10HPF in metaphase. Further molecular analysis revealed no mutations in TERT. Patients with a malignant classifier score were categorized within the CNS WHO grading system as either grade 2 or grade 3. All patients with a match for the MC malignant, as well as those with CNS WHO grade 3 tumors regardless of the MC, were offered radiotherapy. Among CNS WHO grade 1 tumors, no tumors with MC malignant were identified, although a significant proportion (28%, 23 tumors) remained without a match. Copy number variation (CNV) CNV was neutral in 38 cases, while 68 cases showed chromosomal aberrations. The most common chromosomal alteration appeared on chromosome 22 (60 loss, 2 gain, 44 neutral), followed by changes on chromosomes 1 and 14. Two cases exhibited deletions in CDKN2A/B gene, both of which were classified as CNS WHO grade 3, with one displaying a malignant profile and the other remaining unclassified, according to the classifier. Tumors with neutral CNV did not demonstrate a survival advantage compared to those exhibiting chromosomal aberrations (p .583, Log – rank test). The median survival time for both groups remained undefined, reflecting limitations of our study, likely due to the short follow – up period or the small sample size. Additionally, no significant difference in survival as observed among tumors with different types of chromosomal alterations (p .458, Log – rank test) (Fig. 2 ). When analyzing MC-intermediate tumors, we identified that 3 tumors (17%) exhibited a neutral CNV profile, while 15 tumors (83%) displayed chromosomal alterations. All tumors with altered CNV showed aberrations involving chromosome 22. No statistically significant difference in PFS was observed between MC – intermediate tumors with neutral and altered CNV profiles (p .345, Log – rank test). The median PFS for tumors with neutral CNV was 481 days, whereas it remained undefined for tumors with altered CNV. Similarly, among CNS WHO grade 2 meningiomas, 4 tumors (20%) exhibited a neutral CNV profile, and 16 (80%) demonstrated chromosomal alterations. Chromosome 22 was the most frequently affected, with aberrations detected in 15 cases. PFS analysis revealed no statistically significant difference between tumors with neutral and altered CNV profiles (p .989, Log – rank test). The median PFS for both groups remained undefined. In the group of tumor with no match, 8 tumors (26%) exhibited a neutral CNV profile, whereas 23 tumors (74%) showed chromosomal alterations, with chromosome 22 being the most commonly affected (21 cases). Similar to the other groups, no statistically significant difference in PFS was observed between tumors with neutral and altered CNV profiles in this group. The median PFS for both groups remained undefined. When comparing CNV profiles between MC-intermediate and MC- tumors with no match to a MC, no statistically significant difference was observed (p .507, Mann – Whitney test). Clinical routine All cases were thoroughly reviewed in internal interdisciplinary tumor board, which convened a median of 8 days after surgery. This timeline coincided with the availability of histopathological results, including CNS WHO grading, which were typically obtained within 5 days post – surgery. In contrast, epigenetic analysis took a median of 23 days to be finalized. Consequently, the epigenetic profile could not be taken into account in the decision-making process during the tumor board discussions, but only afterwards during the follow-up process. Patient’s clinical performance was evaluated preoperatively and postoperatively, as well as at each follow-up visit. Preoperatively, 98 patients (92%) had a Karnofsky Performance Status (KPS) score of ≥ 70%, while 8 patients (8%) had a score < 70%. No significant difference was observed between pre- and postoperative KPS scores (p = 0.9980, Mann Whitney test), indicating that surgery did not negatively impact the patient’s overall clinical status. Progression All patients were followed up regularly in the outpatient clinic, with a median follow – up duration of 502 days (range: 5–1213 days). Radiologically confirmed tumor progression occurred in 15 patients (14%) during this period. Among these cases, 9 patients (60%) had CNS WHO grade 1 meningiomas, 5 patients (33%) had CNS WHO grade 2 tumors, and 1 patient (7%) had a CNS WHO grade 3 tumor (Fig. 1 A). Repeat tumor resection was performed in 7 patients due to progression, while 13 patients received adjuvant radiotherapy. Patients with grade 2 meningiomas and residual tumor have been consulted by radiotherapists. Of the patients who ultimately received radiotherapy, 3 had grade 1 meningioma (1 MC – benign, and 2 MC – unclassified), all with residual tumors. Additionally, 7 patients had grade 2 meningiomas (5 MC – intermediate, and 2 MC – unclassified), with 3 of these having residual tumors. Lastly, 3 patients had grade 3 meningiomas (1 MC – intermediate, 1 MC – malignant, and 1 MC – unclassified), with one of these patients also having a residual tumor (Table 2 ). The median progression – free survival (PFS) for each CNS WHO grade could not be determined due to the short follow – up duration and the limited number of progression cases. Epigenetic analysis of the progressive tumors revealed that 1 patient (7%) had a benign classifier status, 4 patients (27%) had an intermediate status, 1 patient (7%) had a malignant profile, and 9 patients (60%) were unclassified. Among the patients with unclassified tumors and documented progression, none underwent revision surgery due to progression. Of these, 4 out of 9 patients (44%) had residual tumors based on RANO criteria. Histologically, 6 of the unclassified tumors (67%) were CNS WHO grade 1, while 3 tumors (33%) were CNS WHO grade 2. Chromosomal aberrations were identified in 6 cases (67%), while 3 cases exhibited a neutral CNV profile. The most frequent chromosomal alteration, found in 6 cases (67%), involved chromosome 22. Multiple chromosomal alterations – including chromosome 22- were detected in 3 cases (33%). One tumor remained unclassified due to technical problems, whereas the remainder demonstrated scoring mismatches between MC (v2.4) and tumor classifier (v12.5), with higher score for MC-benign in v12.5 (0.99, 0.99, 0.99, 0.89) and in v2.4 (0.84, 0.8, 0.88). PFS analysis based on epigenetic profiling demonstrated that tumors with MC malignant had a median survival of 122 days, while the median PFS for benign, intermediate and unclassified tumors remained undefined. A statistically significant difference in PFS was observed between as malignant classified tumors and non – malignant tumors (benign, intermediate, unclassified) (p = .004, Chi square, Fig. 3 a). Further analysis excluding unclassified meningiomas reinforced the significance of PFS differences between malignant tumors and non – malignant ones (benign, intermediate) (p < .001, Chi square) (Fig. 3 b). These results suggest that although as malignant classified tumors are rare, they are associated with early progression and predict significantly poorer outcomes compared to non – malignant tumors. Similar results were observed when analyzing PFS of other MC, with intermediate and unclassified tumors showing comparable survival curves but still a significant difference in PFS (p < .001, Chi square) (Fig. 3 c). Correlation analysis using the Spearman’s rank correlation coefficient identified a significant positive correlation between classifier status (benign, intermediate, malignant) and the occurrence of progression (r − .3910, p < .001). In contrast, no significant correlation was observed between classifier score and the conventional CNS WHO grading system (p .117). A negative correlation was noted between classifier score and PFS (r − .2337, p .044), suggesting that as classifier status advances from benign to malignant, PFS is significantly reduced. Similarly, a negative correlation was found between classifier status and the KPS at the last follow – up visit (r − .3447, p .0004), indicating that tumors with a MC malignant tend to be associated with worse clinical performance. These results support the predictive value of the classifier in clinical outcomes. Further analysis showed no significant correlation between classifier score and radiological features such as calcification (p .255) or edema (p .401). However, a moderate positive correlation was observed between classifier score and tumor volume (r .3964, p < .001), indicating that higher classifier scores are associated with larger tumor volume. In summary, the epigenetic profiling using classification algorithms with defined MC is strongly associated with tumor progression, PFS, KPS at the last patient contact, and tumor volume. However, it does not correlate with WHO grading or radiological characteristics like calcification and edema. Discussion Given the challenges of accurately predicting meningioma behavior and recurrence based solely on histopathological criteria, there has been increasing interest in exploring molecular markers to improve classification models [ 13 ]. The WHO CNS 5 classification has incorporated TERT-promoter mutations and loss of CDKN2A/B as molecular markers for grading of anaplastic meningioma CNS WHO grade 3. This is based on their strong associations with recurrence, offering promising advancements in prognostication. For instance, mutations in the TERT promoter have been linked to a shorter time to progression, highlighting their potential utility as prognostic indicators [ 14 ]. Similarly, the identification of activating mutations in the AKT1 gene has paved the way for targeted therapies using AKT inhibitors, underscoring the growing importance of molecular analysis in individualized treatment approaches for meningioma patients [ 15 ]. However, it is important to note that molecular markers are still infrequently detected in meningiomas, limiting their current role to supplementary tools rather than primary prognostic criteria. The epigenetic profiling of meningiomas, particularly the MC, has emerged as a reliable predictor of prognosis [ 6 ]. Our findings are consistent with existing literature, confirming that the MC has a higher predictive value and accuracy compared to the CNS WHO grading system [ 16 ]. In our cohort, a statistically significant correlation was observed between MC status and both tumor progression and clinical outcomes, underscoring its potential as an efficient prognostic tool, notably even after relatively short follow-up times Interestingly, tumors with no match to a MC displayed PFS curves similar to those of intermediate tumors, suggesting that this group encompasses tumors with a broad range of behaviors, from benign to malignant and a possibly heterogenous tissue composition of benign and intermediate fractions complicating unequivocal assignment to a MC. This heterogeneity complicates clinical management, often leading to treatment dilemmas. In our cohort, tumors with no match frequently exhibited high risk markers, such as TERT promoter mutations and CDKN2A/B deletions, which are known to be associated with more aggressive clinical behavior and criteria for grading as CNS WHO grade 3 [ 14 ] [ 17 ]. However, other unclassified tumors exhibited benign molecular profiles. In our cohort both mismatch as well as technical issues, such as artifacts in genomic analysis or the inability to determine the CNV profile, contributed to the unclassified results. Additionally, discrepancies between the available classifiers led to mismatches in classification. In this study, tumors were analyzed using the Illumina Human Methylation EPIC v1.0 (850k) array. The data were processed and evaluating with the publicly available database of the German Center for Cancer Research (DKFZ) (Capper et al 2018) accessible via www.molecularneuropathology.org [ 11 ]. This database employed until recently the meningioma classifier v2.4, as well as the tumor methylation classifier v11b4 and v12.5. MC scores > 0.5 were considered sufficient for classification, whereas MC scores < 0.5, or scores lower than those of the tumor methylation classifier, indicated a mismatch and resulted in unclassified tumors. Such mismatches have been reported previously [ 9 ]. Updated technologies, such as the Illumina Human Methylation EPIC v2.0 (935k) methylation array as well as updated classification algorithms may reduce the number of unclassified cases [ 18 ]. Furthermore, tumor biology heterogeneity, atypia and large tumor volume may all separately lead to mismatch resulting in unclassified tumors. In these cases, combining CNS WHO grading with molecular markers may provide a more comprehensive understanding of tumor behavior and assist in treatment decision – making. With respect to radiotherapy, patients with CNS WHO grade 1 meningiomas did not regularly receive any form of adjuvant treatment, except in cases of subtotal resection or significant residual tumor, where radiotherapy may be considered. CNS WHO grade 2 meningioma, however, remains a particularly heterogenous group. Traditionally, radiation has been offered to patients with incomplete resections or multiple meningiomas, while those with complete resections are typically followed without immediate postoperative radiotherapy [ 7 ]. Radiotherapy was recommended for all patients with CNS WHO grade 3 meningiomas, also in those which were not graded malignant according to MC. We did not feel safe for patients to refrain from adjuvant therapy once CNS WHO grade 3 was assigned, as there are no prospective data for this subgroup of patients. Apart from the extent of resection, other clinical or pathological markers such as MC may offer additional guidance in treatment decisions for CNS WHO grade 2 meningiomas. Specifically, MC may help clinicians to decide whether to intensify therapy or adjust follow – up intervals. Ehret et al. have also recommended incorporating molecular markers, CNV and the MC into the clinical management of grade 2 meningiomas to predict tumor aggressiveness and tailor personalized treatment strategies [ 9 ]. In addition to the CNS WHO classification, several alternative classification systems have been proposed, each emphasizing distinct tumor characteristics. For instance, Nassiri et al. developed a molecularly integrated classification, categorizing meningiomas into four groups (M1 – MG4) based on molecular markers [ 19 ]. Another approach by Patel et al., which leverages RNA sequencing and whole – exome sequencing, categorizes meningiomas into three groups with unique molecular profiles [ 20 ]. Choudhury et al. further expanded on this approach, using a comprehensive analysis including DNA methylation, genetic alterations, transcriptional profiles, biochemical markers, proteomics, and single – cell profiling to classify meningiomas into three groups [ 21 ] Driver et al. proposed an integrated score using CNV-alterations, mitotic activity and CDKN2A/B-deletions [ 22 ]. Each classification system seeks to provide a framework that reliably predicts tumor behavior and progression potential. However, to be widely adopted, a classification system must also be practical, accessible and applicable across clinical settings without complicating the decision – making process. These various approaches reflect distinct perspectives on meningioma pathology, yet it remains unclear which classification system is superior in terms of predictive accuracy and clinical utility. While the prognostic value of the MC has been well established, routine clinical practice continues to rely heavily on the traditional CNS WHO grading system for guiding treatment decisions and aftercare in meningiomas. Our data also show that “classical” histopathological grading remains indispensable, as it continues to provide crucial information that cannot be fully replaced by molecular or epigenetic analysis. Although epigenetic analysis is standard procedure at our institution for every patient with a confirmed meningioma, its labor – intensive nature presents challenges. Specifically, the molecularpathological report from this analysis is typically not available for initial postoperative tumor board discussions and is instead considered during later follow – up visits. In that respect, however, none of the other proposed classification systems appears superior to the MC based grading system we have been using. In the updated WHO CNS 5 Classification, albeit histopathological and molecular markers are included, methylation profiling has not yet been incorporated into the grading score. Consequently, the integration of the MC into routine clinical practice remains uncertain, with criticisms regarding its practicability and clinical relevance. However, the most recent cIMPACT 8 update recommends further molecular testing in histological borderline cases, suggesting similar adjustments in an updated WHO CNS classification[ 5 ]. There is a growing emphasis on personalized treatment approaches, especially in neuro-oncology. The development of individualized treatment concepts that incorporate histological features, molecular markers, and epigenetic profiling, is gaining momentum. These advancements aim to tailor therapeutic strategies for each patient, improving outcomes and minimizing unnecessary treatments. However, the financial implications of epigenetic analysis cannot be overlooked. Conducting these analyses incurs costs that are 3–4 times higher than those of conventional histopathological examination. At our institution, the costs for standard histological examination are around 200€ per case, whereas costs of epigenetic analysis amounts to approximately 680€ per case. In public healthcare systems, where cost – efficiency is a key consideration, the uncertain clinical implications of routine epigenetic testing must be carefully weighed against its benefits. We believe that the additional costs for epigenetic testing are worthwhile to avoid under- or overtreatment in terms of either omitting radiotherapy or performing follow-up MRI in unnecessarily short intervals, which in result could level out or be even cost – effective. Limitations The primary limitations of our study include the small size and the relatively short follow – up period. Given the typically slow growth rate and long progression course of meningiomas, extended follow – up is essential for accurately predicting PFS and overall survival (OS) [ 23 ]. As meningiomas are often benign and indolent, longer observation periods are required to capture meaningful clinical outcomes. Additionally, the classification of unclassified tumors poses a challenge, as their clinical behavior remains difficult to predict. Emerging and updated technologies, such as the EPIC v2.0 (935k) methylation array and further advances in classifier algorithms could help improving classifier accuracy and ideally provide a single, definitive score. These advancements may improve classification accuracy and reduce the number of unclassified cases, leading to clearer prognostic insights. Declarations Funding : The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests : The authors have no relevant financial or non-financial interests to disclose. Author Contribution: All authors contribute to the conception and design of the study, and all reviewed and approved the final version submitted. L.K drafted the main manuscript and conducted the overall work W.M and M.B conducted all laboratory analyses, and provided all histopathalogical and epigenetically reports P.B contribute to manuscript preparation C.S supervised the overall work and coordinated the entire team Ethics approval : This study received ethical approval from the local ethics committee of Friedrich – Schiller University Jena, under registration number Reg. – Nr.: 2024 – 3409 – Daten. This study protocol adhered to the principles outlined in the Declaration of Helsinki, specifically points 22 and 23. Consent to participate: informed consent was obtained from all individual participants included in the study. No personal or identifiable data were collected, and individuals cannot be distinguished. We confirm complete anonymity in our retrospective analysis. This submission does not include any images that could lead to the identification of individuals. Consent to publish: not necessary, as all information remains anonymized and all the procedures being performed were part of the routine care. Human Ethics and Consent to Participate: not applicable Clinical trial number: not applicable Clinical trial number: not applicable References Alruwaili AA, De Jesus O. Meningioma. StatPearls , Treasure Island (FL) ineligible companies. Disclosure: Orlando De Jesus declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC.; 2024. Torp SH, Solheim O, Skjulsvik AJ. The WHO 2021 Classification of Central Nervous System tumours: a practical update on what neurosurgeons need to know-a minireview, Acta neurochirurgica . 2022; 164(9): 2453-2464. Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, Hawkins C, Ng HK, Pfister SM, Reifenberger G, Soffietti R, von Deimling A, Ellison DW. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary, Neuro Oncol . 2021; 23(8): 1231-1251. Gritsch S, Batchelor TT, Gonzalez Castro LN. Diagnostic, therapeutic, and prognostic implications of the 2021 World Health Organization classification of tumors of the central nervous system, Cancer . 2022; 128(1): 47-58. Sahm F, Aldape KD, Brastianos PK, Brat DJ, Dahiya S, von Deimling A, Giannini C, Gilbert MR, Louis DN, Raleigh DR, Reifenberger G, Santagata S, Sarkar C, Zadeh G, Wesseling P, Perry A. cIMPACT-NOW Update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas, Neuro-oncology . 2024. Sahm F, Schrimpf D, Stichel D, Jones DTW, Hielscher T, Schefzyk S, Okonechnikov K, Koelsche C, Reuss DE, Capper D, Sturm D, Wirsching HG, Berghoff AS, Baumgarten P, Kratz A, Huang K, Wefers AK, Hovestadt V, Sill M, Ellis HP, Kurian KM, Okuducu AF, Jungk C, Drueschler K, Schick M, Bewerunge-Hudler M, Mawrin C, Seiz-Rosenhagen M, Ketter R, Simon M, Westphal M, Lamszus K, Becker A, Koch A, Schittenhelm J, Rushing EJ, Collins VP, Brehmer S, Chavez L, Platten M, Hänggi D, Unterberg A, Paulus W, Wick W, Pfister SM, Mittelbronn M, Preusser M, Herold-Mende C, Weller M, von Deimling A. DNA methylation-based classification and grading system for meningioma: a multicentre, retrospective analysis, Lancet Oncol . 2017; 18(5): 682-694. Goldbrunner R, Stavrinou P, Jenkinson MD, Sahm F, Mawrin C, Weber DC, Preusser M, Minniti G, Lund-Johansen M, Lefranc F, Houdart E, Sallabanda K, Le Rhun E, Nieuwenhuizen D, Tabatabai G, Soffietti R, Weller M. EANO guideline on the diagnosis and management of meningiomas, Neuro Oncol . 2021; 23(11): 1821-1834. Jenkinson MD, Javadpour M, Haylock BJ, Young B, Gillard H, Vinten J, Bulbeck H, Das K, Farrell M, Looby S, Hickey H, Preusser M, Mallucci CL, Hughes D, Gamble C, Weber DC. The ROAM/EORTC-1308 trial: Radiation versus Observation following surgical resection of Atypical Meningioma: study protocol for a randomised controlled trial, Trials . 2015; 16(519. Ehret F, Perez E, Teichmann D, Meier S, Geiler C, Zeus C, Franke H, Roohani S, Wasilewski D, Onken J, Vajkoczy P, Schweizer L, Kaul D, Capper D. Correction: Clinical implications of DNA methylation-based integrated classification of histologically defined grade 2 meningiomas, Acta neuropathologica communications . 2024; 12(1): 96. Moran S, Arribas C, Esteller M. Validation of a DNA methylation microarray for 850,000 CpG sites of the human genome enriched in enhancer sequences, Epigenomics . 2016; 8(3): 389-99. Capper D, Jones DTW, Sill M, Hovestadt V, Schrimpf D, Sturm D, Koelsche C, Sahm F, Chavez L, Reuss DE, Kratz A, Wefers AK, Huang K, Pajtler KW, Schweizer L, Stichel D, Olar A, Engel NW, Lindenberg K, Harter PN, Braczynski AK, Plate KH, Dohmen H, Garvalov BK, Coras R, Hölsken A, Hewer E, Bewerunge-Hudler M, Schick M, Fischer R, Beschorner R, Schittenhelm J, Staszewski O, Wani K, Varlet P, Pages M, Temming P, Lohmann D, Selt F, Witt H, Milde T, Witt O, Aronica E, Giangaspero F, Rushing E, Scheurlen W, Geisenberger C, Rodriguez FJ, Becker A, Preusser M, Haberler C, Bjerkvig R, Cryan J, Farrell M, Deckert M, Hench J, Frank S, Serrano J, Kannan K, Tsirigos A, Brück W, Hofer S, Brehmer S, Seiz-Rosenhagen M, Hänggi D, Hans V, Rozsnoki S, Hansford JR, Kohlhof P, Kristensen BW, Lechner M, Lopes B, Mawrin C, Ketter R, Kulozik A, Khatib Z, Heppner F, Koch A, Jouvet A, Keohane C, Mühleisen H, Mueller W, Pohl U, Prinz M, Benner A, Zapatka M, Gottardo NG, Driever PH, Kramm CM, Müller HL, Rutkowski S, von Hoff K, Frühwald MC, Gnekow A, Fleischhack G, Tippelt S, Calaminus G, Monoranu CM, Perry A, Jones C, Jacques TS, Radlwimmer B, Gessi M, Pietsch T, Schramm J, Schackert G, Westphal M, Reifenberger G, Wesseling P, Weller M, Collins VP, Blümcke I, Bendszus M, Debus J, Huang A, Jabado N, Northcott PA, Paulus W, Gajjar A, Robinson GW, Taylor MD, Jaunmuktane Z, Ryzhova M, Platten M, Unterberg A, Wick W, Karajannis MA, Mittelbronn M, Acker T, Hartmann C, Aldape K, Schüller U, Buslei R, Lichter P, Kool M, Herold-Mende C, Ellison DW, Hasselblatt M, Snuderl M, Brandner S, Korshunov A, von Deimling A, Pfister SM. DNA methylation-based classification of central nervous system tumours, Nature . 2018; 555(7697): 469-474. Hielscher T, Sill M, Sievers P, Stichel D, Brandner S, Jones DTW, von Deimling A, Sahm F, Maas SLN. Clinical implementation of integrated molecular-morphologic risk prediction for meningioma, Brain pathology (Zurich, Switzerland) . 2023; 33(3): e13132. Roehrkasse AM, Peterson JEG, Fung KM, Pelargos PE, Dunn IF. The Discrepancy Between Standard Histologic WHO Grading of Meningioma and Molecular Profile: A Single Institution Series, Front Oncol . 2022; 12(846232. Sahm F, Schrimpf D, Olar A, Koelsche C, Reuss D, Bissel J, Kratz A, Capper D, Schefzyk S, Hielscher T, Wang Q, Sulman EP, Adeberg S, Koch A, Okuducu AF, Brehmer S, Schittenhelm J, Becker A, Brokinkel B, Schmidt M, Ull T, Gousias K, Kessler AF, Lamszus K, Debus J, Mawrin C, Kim YJ, Simon M, Ketter R, Paulus W, Aldape KD, Herold-Mende C, von Deimling A. TERT Promoter Mutations and Risk of Recurrence in Meningioma, J Natl Cancer Inst . 2016; 108(5). Weller M, Roth P, Sahm F, Burghardt I, Schuknecht B, Rushing EJ, Regli L, Lindemann JP, von Deimling A. Durable Control of Metastatic AKT1-Mutant WHO Grade 1 Meningothelial Meningioma by the AKT Inhibitor, AZD5363, J Natl Cancer Inst . 2017; 109(3): 1-4. Shen E, Leclair NK, Herlth K, Soucy M, Renzette N, Zhuo X, Kelly K, Omerza G, Onyiuke H, McNeill I, Wolansky L, Becker K, Li L, Wu Q, Bulsara KR. DNA methylation provides diagnostic value for meningioma recurrence in clinical practice, Acta neurochirurgica . 2023; 165(5): 1323-1331. Sievers P, Hielscher T, Schrimpf D, Stichel D, Reuss DE, Berghoff AS, Neidert MC, Wirsching HG, Mawrin C, Ketter R, Paulus W, Reifenberger G, Lamszus K, Westphal M, Etminan N, Ratliff M, Herold-Mende C, Pfister SM, Jones DTW, Weller M, Harter PN, Wick W, Preusser M, von Deimling A, Sahm F. CDKN2A/B homozygous deletion is associated with early recurrence in meningiomas, Acta Neuropathol . 2020; 140(3): 409-413. Kaur D, Lee SM, Goldberg D, Spix NJ, Hinoue T, Li HT, Dwaraka VB, Smith R, Shen H, Liang G, Renke N, Laird PW, Zhou W. Comprehensive Evaluation of The Infinium Human MethylationEPIC v2 BeadChip, Epigenetics communications . 2023; 3(1). Nassiri F, Liu J, Patil V, Mamatjan Y, Wang JZ, Hugh-White R, Macklin AM, Khan S, Singh O, Karimi S, Corona RI, Liu LY, Chen CY, Chakravarthy A, Wei Q, Mehani B, Suppiah S, Gao A, Workewych AM, Tabatabai G, Boutros PC, Bader GD, de Carvalho DD, Kislinger T, Aldape K, Zadeh G. A clinically applicable integrative molecular classification of meningiomas, Nature . 2021; 597(7874): 119-125. Patel AJ, Wan YW, Al-Ouran R, Revelli JP, Cardenas MF, Oneissi M, Xi L, Jalali A, Magnotti JF, Muzny DM, Doddapaneni H, Sebastian S, Heck KA, Goodman JC, Gopinath SP, Liu Z, Rao G, Plon SE, Yoshor D, Wheeler DA, Zoghbi HY, Klisch TJ. Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors, Proceedings of the National Academy of Sciences of the United States of America . 2019; 116(43): 21715-21726. Choudhury A, Magill ST, Eaton CD, Prager BC, Chen WC, Cady MA, Seo K, Lucas CG, Casey-Clyde TJ, Vasudevan HN, Liu SJ, Villanueva-Meyer JE, Lam TC, Pu JK, Li LF, Leung GK, Swaney DL, Zhang MY, Chan JW, Qiu Z, Martin MV, Susko MS, Braunstein SE, Bush NAO, Schulte JD, Butowski N, Sneed PK, Berger MS, Krogan NJ, Perry A, Phillips JJ, Solomon DA, Costello JF, McDermott MW, Rich JN, Raleigh DR. Meningioma DNA methylation groups identify biological drivers and therapeutic vulnerabilities, Nature genetics . 2022; 54(5): 649-659. Driver J, Hoffman SE, Tavakol S, Woodward E, Maury EA, Bhave V, Greenwald NF, Nassiri F, Aldape K, Zadeh G, Choudhury A, Vasudevan HN, Magill ST, Raleigh DR, Abedalthagafi M, Aizer AA, Alexander BM, Ligon KL, Reardon DA, Wen PY, Al-Mefty O, Ligon AH, Dubuc AM, Beroukhim R, Claus EB, Dunn IF, Santagata S, Bi WL. A molecularly integrated grade for meningioma, Neuro-oncology . 2022; 24(5): 796-808. Zeidman LA, Ankenbrandt WJ, Du H, Paleologos N, Vick NA. Growth rate of non-operated meningiomas, Journal of neurology . 2008; 255(6): 891-5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Karamani","email":"data:image/png;base64,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","orcid":"","institution":"Jena University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Lydia","middleName":"","lastName":"Karamani","suffix":""},{"id":439914271,"identity":"df6352d6-56d3-4a33-b78d-8644545c3a2a","order_by":1,"name":"Wolf Müller","email":"","orcid":"","institution":"Leipzig University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wolf","middleName":"","lastName":"Müller","suffix":""},{"id":439914272,"identity":"a9663cfa-4944-473f-ac56-f369290ae15c","order_by":2,"name":"Max Braune","email":"","orcid":"","institution":"Leipzig University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Max","middleName":"","lastName":"Braune","suffix":""},{"id":439914273,"identity":"98536555-d0f8-452d-956d-ec27c5efb046","order_by":3,"name":"Peter Baumgarten","email":"","orcid":"","institution":"Jena University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Baumgarten","suffix":""},{"id":439914274,"identity":"88a4506d-8464-4d62-a0ba-ddba4e251dc9","order_by":4,"name":"Christian Senft","email":"","orcid":"","institution":"Jena University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Senft","suffix":""}],"badges":[],"createdAt":"2025-03-13 08:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6218017/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6218017/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80585154,"identity":"9fd34719-0f01-4404-b062-a82a2123bac7","added_by":"auto","created_at":"2025-04-15 00:29:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62780,"visible":true,"origin":"","legend":"\u003cp\u003eSankey diagram showing the distribution of Meningioma Classifier across CNS WHO grading\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6218017/v1/42f71aefd2aa442bcd7f5a60.png"},{"id":80583776,"identity":"e40ab9f2-1832-4441-9efb-52f3296263c8","added_by":"auto","created_at":"2025-04-15 00:13:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126723,"visible":true,"origin":"","legend":"\u003cp\u003ea) Violin Plot showing all chromosomal aberrations identified in epigenetic analysis, b) Kaplan – Meier survival curve estimates PFS in tumors with neutral vs. altered CNV, c) Kaplan – Meier survival curve estimates PFS for each chromosomal alteration\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6218017/v1/4b9c9da8acd459b4e96695c7.png"},{"id":80584216,"identity":"686e39fa-8767-4991-b535-666815789ecc","added_by":"auto","created_at":"2025-04-15 00:21:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":82477,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan – Meier survival estimates a) PFS according to WHO grade, b) PFS according to methylation classes, MC-malignant, MC-non malignant, MC-unclassified, c) PFS for each classifier class\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6218017/v1/30c58fbc2814d96face7fb75.png"},{"id":80583780,"identity":"3787d0ec-fbf4-4c08-a4bc-645f33d78ba6","added_by":"auto","created_at":"2025-04-15 00:13:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12318,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTable 2 \u003c/em\u003ePatients characteristics for those receiving radiotherapy by CNS WHO grade, residual tumor and MC – classifier\u003c/p\u003e","description":"","filename":"table2.png","url":"https://assets-eu.researchsquare.com/files/rs-6218017/v1/d32d67a1dd8ca0f3f7353467.png"},{"id":83733712,"identity":"09f5a018-9ea9-41ae-ad37-549ff48ec99d","added_by":"auto","created_at":"2025-06-01 15:17:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":777822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6218017/v1/f1bcffe8-6ca0-47a0-8eec-cd243477d08c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The role of meningioma epigenetics in routine clinical practice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMeningioma, originating from the arachnoid layer of the meninges in the brain and spinal cord, is the most common non-malignant brain tumor [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The WHO Classification of tumors of the central nervous system (WHO CNS 5) uses a grading system that categorizes meningiomas into three grades, comprising a total of 15 subtypes. Grade 1 meningiomas are typically associated with a benign clinical course and a low risk of recurrence, while grade 2 meningiomas have a moderate clinical behavior and a higher likelihood of recurrence. Grade 3 meningiomas, on the other hand, demonstrate malignant characteristics. In part, the WHO CNS 5 grading of meningiomas is still based on histopathological features such as mitotic activity and the presence of brain invasion, which can introduce subjectivity and inter-observer variability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this, the integration of molecular features into the WHO CNS5 classification reflects their increasing significance in the evaluation of meningiomas. Contemporary guidelines now recommend incorporating molecular analyses alongside histological assessments to achieve a more comprehensive evaluation of meningiomas and to guide clinical decision-making [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For example, the most recent cIMPACT now Update 8 proposes to assign CNS WHO grade 2 for cases with CNS WHO grade 1 morphology but chromosomal arm 1p deletion in combination with 22q deletion [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCombining single molecular markers and histopathological features only partially captures the full spectrum of meningioma behavior. In a multicenter retrospective study by Sahm et al., the DNA epigenome wide methylation profiling of meningiomas led to the identification of six distinct methylation classes: Methylation Class (MC) benign 1, MC benign 2, MC benign 3, MC intermediate A, MC intermediate B and MC malignant [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Based on the observed clinical behavior, progression rates, and prognostic accuracy, the authors proposed that the DNA methylation profile is a robust predictive factor, potentially outperforming the current WHO classification. As such, incorporating of methylation profiling into meningioma classification holds significant promise for improving prognostic accuracy, refining treatment strategies, and predicting tumor progression.\u003c/p\u003e \u003cp\u003e The European Association of Neuro \u0026ndash; Oncology (EANO) guidelines recommend radiotherapy for CNS WHO Grade 3 meningiomas and advocate for adjuvant radiotherapy following subtotal resection (Simpson grade IV-V) of CNS WHO grade 2 meningiomas. Additionally, palliative radiotherapy may be considered for inoperable CNS WHO grade 1 meningiomas [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Special attention is given to CNS WHO grade 2 meningiomas due to their heterogeneity, as these tumors can range from benign to intermediate, or even malignant in their clinical course. Optimal management following surgical resection of these tumors remains unclear, and the role of radiation is still debated [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A combined assessment using histopathological, molecular and methylation profiles may lead to better stratification of patients, enabling more tailored therapeutic strategies and minimizing the risk of over \u0026ndash; or undertreatment [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile the prognostic value of the meningioma methylation classifier has been established, its clinical utility and relevance in modern neurooncology practice are still being explored. The integration of epigenetic markers into clinical practice is in its early stages and further refinement is needed. It remains uncertain whether the clinical implications of methylome based classification and copy number profiling will lead to definitive therapeutic decisions or whether the methylation profile will directly influence clinical management.\u003c/p\u003e \u003cp\u003eThe aim of this study is to elucidate the clinical relevance and practical application of epigenome wide methylation profiling including the MC classifier and copy number variations in routine clinical practice.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eWe performed a retrospective analysis of patients treated at our institution between January 2021 and December 2023. The study cohort was identified by querying the hospital\u0026rsquo;s registry using the ICD-10 codes D32.0, D32.1, D32.9, D42.0, D42.1, D42.9, C70.0, C70.1, and C70.9. Patient data were extracted from clinical charts and electronic medical records.\u003c/p\u003e \u003cp\u003e All patients included in the study underwent surgical resection and received postoperative follow-up care, primarily at our outpatient clinic. For those who continued follow-up at external facilities, we contacted these centers to retrieve relevant follow-up data. Histological examinations were performed at a single certified institute to ensure consistency and accuracy of diagnoses.\u003c/p\u003e \u003cp\u003eTumor volumes were measured using the BrainLab Elements software with the Smartbrush algorithm (Version 4.5). A single author conducted all volumetric analyses to minimize variability and ensure measurements consistency.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eThe study included patients diagnosed with meningioma, who underwent surgery at our neurosurgical clinic between January 2021 and December 2023. Both cerebral and spinal meningiomas were analyzed. Exclusion criteria encompassed patients managed conservatively or under a \u0026ldquo;watch-and-wait\u0026rdquo; approach. Patients with sporadic multiple meningiomas as well as those with familial tumor syndromes, such as Li-Fraumeni syndrome and neurofibromatosis type 2 (NF-2), were included.\u003c/p\u003e\n\u003ch3\u003eProgression and follow-up\u003c/h3\u003e\n\u003cp\u003eOur standard follow-up protocol includes MRI imaging with and/or without contrast, at 3, and 12 months during the first postoperative year. Afterward, patients are assessed annually for three years, followed by biennial imaging. Patients with CNS WHO grade 3 malignant meningiomas or grade 2 meningiomas and residual tumor are offered radiotherapy, followed by close monitoring with follow \u0026ndash; up visits every 3 months initially. The follow-up schedule is tailored based on several factors, including histological findings, residual tumor presence, radiotherapy status, and patient preferences.\u003c/p\u003e \u003cp\u003eAll patients are reviewed by the interdisciplinary neuro - oncology tumor board pre -, postoperatively and upon radiological detection of tumor recurrence or progression. Based on this interdisciplinary neuro - oncology tumor board treatment recommendations are given.\u003c/p\u003e \u003cp\u003eTumor progression was defined as radiological evidence of contrast \u0026ndash; enhancing tissue at the tumor resection margin on MRI when tumors had been resected completely or when there was evident increase of any postoperative residual contrast enhancement. Progression-free survival (PFS) was defined as the time from surgery to either tumor progression, death, or the last recorded follow \u0026ndash; up.\u003c/p\u003e\n\u003ch3\u003eNeuropathological evaluation\u003c/h3\u003e\n\u003cp\u003eHistological analyses were performed by independent neuropathologists, generating two separate reports. The first histological report provided details on microscopic and immunohistochemical characteristics of the tumor, including WHO grading, meningioma subtype, proliferation index, mitotic activity, brain infiltration, atypical features, and specific markers such as epithelial membrane antigen (EMA), Phosphohistone H3 (PHH3), Somatostatin receptor (SSTR), proliferation index, and progesterone receptor status.\u003c/p\u003e\n\u003cp\u003eA subsequent molecular report focused on the molecular characteristics of the tumor, utilizing the Illumina Methylation EPIC v1.0 (850K) Array[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]. The methylation profile of the tumor tissues was compared to previously defined methylation classes using the publicly available database of the German Center for Cancer Research (DKFZ) based on Capper et al 2018 available via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.molecularneuropathology.org\u003c/span\u003e\u003c/span\u003e [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. This included analysis of the brain tumor methylation classifier (versions V11b4 and V12.5) and the meningioma classifier (version V2.4) [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. Each classifier generated a score ranging from 0 to 1, representing the tumor\u0026rsquo;s similarity to established reference groups. Copy number variation (CNV) profiles including whole chromosome arms as well as single marked genes as CDKN2A/B were also assessed. In cases of histopathologically diagnosed atypical meningiomas, next generation sequencing (NGS) was performed for the detection of TERT-promoter mutations.\u003c/p\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eAll statistical analyses were performed using GraphPad Prism 10 software (Version 10.2.3). Categorical variables were presented as medians. Comparative analyses were conducted using the chi \u0026ndash; square test for categorical variables and the Mann \u0026ndash; Whitney U test for non \u0026ndash; parametric variables. Correlation analysis was performed using the Spearman test for non-parametric variables, with p values\u0026thinsp;\u0026le;\u0026thinsp;0.05 considered statistically significant. Kaplan \u0026ndash; Meier survival analysis was used to evaluate progression \u0026ndash; free survival. Results were presented in APA format.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographics\u003c/h2\u003e\n \u003cp\u003eWe analyzed data from 106 consecutive patients with meningioma who underwent surgery at our institution between January 2021 and December 2023. The median age was 65 years (range: 13 to 89 years), with a clear female predominance, yielding a female \u0026ndash; to \u0026ndash; male ratio of 3:1. Among the cohort, 12 patients presented with recurrent meningiomas, while 94 patients were newly diagnosed.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAnatomical Distribution\u003c/h3\u003e\n\u003cp\u003eOf the 106 meningiomas, 17 were located along the spine, and 89 were intracranial. Among the intracranial meningiomas, 77 were confined to supratentorial regions, 9 were infratentorial, and 3 involved both supra- and infratentorial compartments. Regarding tumor location, 34 meningiomas were found on the left hemisphere, 38 on the right hemisphere, and 2 cases presented with multiple meningiomas affecting both hemispheres. Additionally, 15 meningiomas were midline lesions. Solitary meningiomas were observed in 95 cases, while 11 patients exhibited multiple meningioma \u0026ndash; like lesions.\u003c/p\u003e\n\u003cp\u003e41 tumors were in contact with large cerebral vessels, while 60 tumors showed no association with major vascular structures. In terms of skull base involvement, 36 tumors infiltrated the skull base, whereas 62 did not.\u003c/p\u003e\n\u003cp\u003eThe most common tumor location was the convexity (n\u0026thinsp;=\u0026thinsp;29), followed by the sphenoid wing (n\u0026thinsp;=\u0026thinsp;27), falx/parasagittal region (n\u0026thinsp;=\u0026thinsp;10), and the suprasellar and olfactory groove regions (n\u0026thinsp;=\u0026thinsp;8). Additionally, 5 tumors were in the posterior fossa, 4 in the cerebellopontine angle, 3 in the intraorbital region and along the optic nerve sheath, 3 at the foramen magnum, 1 was intraventricular, and 1 was tentorial. Among the spinal meningiomas, the thoracic region was the most common location (n\u0026thinsp;=\u0026thinsp;11), followed by the lumbar (n\u0026thinsp;=\u0026thinsp;1) and cervical (n\u0026thinsp;=\u0026thinsp;1) regions.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eTumor Volume and Characteristics\u003c/h2\u003e\n \u003cp\u003eTumor volume was calculated based on preoperative imaging for cranial meningiomas. Due to the absence of navigational preoperative imaging for spinal meningiomas, these cases were excluded from volume analysis. In cases of multiple cranial meningiomas, tumor volume was measured only for the lesion scheduled for surgery. The median volume of intracranial meningiomas was 22.75 cm\u0026sup3; (range: 0.14 to 205.3cm\u0026sup3;).\u003c/p\u003e\n \u003cp\u003ePeritumoral edema was present in 47 tumors (52%), while 44 tumors (48%) showed no evidence of an edematous reaction. Partial calcification was observed in 25 meningiomas (27%), whereas 66 tumors (73%) exhibited no calcification.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eGrading\u003c/h2\u003e\n \u003cp\u003eHistopathological analysis revealed that most tumors were classified as CNS WHO grade 1 (n\u0026thinsp;=\u0026thinsp;81, 76%), followed by CNS WHO grade 2 (n\u0026thinsp;=\u0026thinsp;20, 19%) and CNS WHO grade 3 (n\u0026thinsp;=\u0026thinsp;5, 5%). The most common subtype was meningothelial (n\u0026thinsp;=\u0026thinsp;27), followed by transitional (n\u0026thinsp;=\u0026thinsp;19), fibroblastic (n\u0026thinsp;=\u0026thinsp;16), psammomatous (n\u0026thinsp;=\u0026thinsp;8), secretory (n\u0026thinsp;=\u0026thinsp;3), angiomatous (n\u0026thinsp;=\u0026thinsp;3), microcystic (n\u0026thinsp;=\u0026thinsp;2), metaplastic (n\u0026thinsp;=\u0026thinsp;1), and rhabdoid (n\u0026thinsp;=\u0026thinsp;1). One CNS WHO grade 1 tumor was not further subtyped. Among the CNS WHO grade 2 meningiomas, 18 were classified as atypical, 1 as chordoid and 1 as clear cell. 5 tumors were graded as CNS WHO grade 3 tumor, e.g. anaplastic meningiomas.\u003c/p\u003e\n \u003cp\u003eIn addition to histology, immunohistochemical markers have been analyzed. EMA was expressed in 94% of tumors (60 positive, 40 faint positive, and 6 negative). Low mitotic activity (\u0026lt;\u0026thinsp;4 mitoses/10 HPF) was identified in 89 tumors, intermediate mitotic count (4\u0026ndash;20 mitoses/10 HPF) in 14, and high mitotic activity (\u0026gt;\u0026thinsp;20 mitoses/10 HPF) in 3 tumors. A high proliferation index (\u0026gt;\u0026thinsp;20%) was found in 1 tumor, while 63 tumors (59%) had a low Ki \u0026ndash; 67 index (\u0026lt;\u0026thinsp;4%) and 42 (40%) had an intermediate index (4\u0026ndash;20%). SSTR2 was positive in 103 cases (73 strong positive, 30 faint positive), with 3 negative cases. Low PHH3 expression (0\u0026ndash;2 cells/10HPF) was found in 63 tumors, intermediate expression (3\u0026ndash;4 cells/10 HPF) in 12, and high expression (\u0026ge;\u0026thinsp;5 cells/10HPF) in 17. Progesterone receptor positivity was detected in 9 tumors.\u003c/p\u003e\n \u003cp\u003eAdditional markers such as AE1/3, STAT6, CD34, SOX10, S \u0026ndash; 100, GFAP and Desmin were assessed in select cases. NGS was performed for markers such AKT1, ALK, TP53, EGFR in selected cases. TERT promoter mutation was tested in cases with aggressive histological features via NGS and was identified in two tumors (one tumor with histopathological criteria of CNS WHO grade 3 and one tumor with histopathological criteria of CNS WHO grade 2, both not unequivocally classifiable using DNA methylation-based classification, e.g. MC Score (Summary in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 1\u003c/em\u003e Summary of immunohistochemical markers\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"326\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 326px;\"\u003e\n \u003cp\u003eImmunohistochemical markers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003eEMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e60 \u0026nbsp; \u0026nbsp; \u0026nbsp; positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e40 \u0026nbsp; \u0026nbsp; \u0026nbsp; faint positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e6 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; negative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003eMitotic count (mitosis/10HPF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e89 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e14 \u0026nbsp; \u0026nbsp; \u0026nbsp; 4 - 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e3 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003eProliferation index (Ki - 67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e63 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt; 4 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e42 \u0026nbsp; \u0026nbsp; \u0026nbsp; 4 - 20 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt; 20 %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003eSSTR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e73 \u0026nbsp; \u0026nbsp; \u0026nbsp; positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e30 \u0026nbsp; \u0026nbsp; \u0026nbsp; faint positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e3 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; negative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003epHH3 \u0026nbsp; \u0026nbsp;(cells/10HPF)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e63 \u0026nbsp; \u0026nbsp; \u0026nbsp; 0 - 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e12 \u0026nbsp; \u0026nbsp; \u0026nbsp; 3 - 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e17 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026ge; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eEMA: epithelial membrane antigen, SSTR2: somatostatin receptor 2, pHH3: phosphohistone H3\u003c/p\u003e\n \u003cp\u003eThe meningioma classifier analysis categorized 55 tumors (52%) as benign, 18 (17%) as intermediate and 2 (2%) as malignant. 31 tumors (29%) could not be classified unequivocally. Assignment to a MC was most likely not reached due to either technical limitations or tumor \u0026ndash; related complexities. In 5 out of 31 tumors without a match to a MC (16%), overt technical issues such as poor tissue composition, low DNA quality, and decalcification processes prevented classification, while in the remaining 26 cases (84%), the meningioma classifier (v2.4) yielded lower classification scores of \u0026lt;\u0026thinsp;0,5 without overt technical limitations. Tumors with an MC \u0026ndash; Classifier\u0026thinsp;\u0026lt;\u0026thinsp;0.3 are by definition unclassified. In our cohort, no tumors had a score\u0026thinsp;\u0026lt;\u0026thinsp;0,3, e.g. were unclassifiable. However, 5 tumors exhibited a very low MC \u0026ndash; Classifier score\u0026thinsp;\u0026lt;\u0026thinsp;0.5 (with scores 0.49, 0.5, 0.45, 0.43, 0.46). In the remaining 21 cases, a mismatch was observed between the MC \u0026ndash; Classifier (v2.4) and the tumor \u0026ndash; classifier (v12.5). In mismatch cases, the highest score in 8 cases met the criteria for MC \u0026ndash; intermediate, all of which were detected in v2.4 (scores: 0.58, 0.86, 0.83, 0.84, 0.88, 0.55, 0.8, 0.7. In the remaining 13 cases, the highest score was MC \u0026ndash; benign, detected mostly (12/13) in v12.5 (scores 0.98, 0.98, 0.99, 0.83, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.93, 0.89, 0.98)\u003c/p\u003e\n \u003cp\u003eWhen separating cranial and spinal meningiomas, cranial tumors were classified as 49 benign, 15 intermediate, 2 malignant, and 23 unclassified. Spinal tumors included 6 benign, 3 intermediate, and 8 unclassified cases. There was no statistically significant difference in classifier distribution between spinal and cerebral tumors (p\u0026thinsp;=\u0026thinsp;.0884, Mann-Whitney test). No tumors with MC malignant were found in spinal tumors.\u003c/p\u003e\n \u003cp\u003eFurther analysis of CNS WHO grade 1 tumors based on classifier score showed 50 MC benign, 8 MC intermediate and 23 tumors with no match, with no MC malignant. Among CNS WHO grade 2 meningiomas, 4 were benign, 9 intermediate, 6 unclassified, and 1 malignant. Methylation analysis of CNS WHO grade 3 tumors revealed 1 benign, 1 intermediate, 2 unclassified and 1 malignant case (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Of particular interest was a case of CNS WHO grade 3 tumor and MC benign profile. Histopathological evaluation characterized this tumor as anaplastic based on the high mitotic activity (\u0026gt;\u0026thinsp;20 mitoses/ 10HPF), which was supported by elevated pHH3 expression with 23 cells/10HPF in metaphase. Further molecular analysis revealed no mutations in TERT.\u003c/p\u003e\n \u003cp\u003ePatients with a malignant classifier score were categorized within the CNS WHO grading system as either grade 2 or grade 3. All patients with a match for the MC malignant, as well as those with CNS WHO grade 3 tumors regardless of the MC, were offered radiotherapy. Among CNS WHO grade 1 tumors, no tumors with MC malignant were identified, although a significant proportion (28%, 23 tumors) remained without a match.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eCopy number variation (CNV)\u003c/h2\u003e\n \u003cp\u003eCNV was neutral in 38 cases, while 68 cases showed chromosomal aberrations. The most common chromosomal alteration appeared on chromosome 22 (60 loss, 2 gain, 44 neutral), followed by changes on chromosomes 1 and 14. Two cases exhibited deletions in CDKN2A/B gene, both of which were classified as CNS WHO grade 3, with one displaying a malignant profile and the other remaining unclassified, according to the classifier. Tumors with neutral CNV did not demonstrate a survival advantage compared to those exhibiting chromosomal aberrations (p .583, Log \u0026ndash; rank test). The median survival time for both groups remained undefined, reflecting limitations of our study, likely due to the short follow \u0026ndash; up period or the small sample size. Additionally, no significant difference in survival as observed among tumors with different types of chromosomal alterations (p .458, Log \u0026ndash; rank test) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eWhen analyzing MC-intermediate tumors, we identified that 3 tumors (17%) exhibited a neutral CNV profile, while 15 tumors (83%) displayed chromosomal alterations. All tumors with altered CNV showed aberrations involving chromosome 22. No statistically significant difference in PFS was observed between MC \u0026ndash; intermediate tumors with neutral and altered CNV profiles (p .345, Log \u0026ndash; rank test). The median PFS for tumors with neutral CNV was 481 days, whereas it remained undefined for tumors with altered CNV.\u003c/p\u003e\n \u003cp\u003eSimilarly, among CNS WHO grade 2 meningiomas, 4 tumors (20%) exhibited a neutral CNV profile, and 16 (80%) demonstrated chromosomal alterations. Chromosome 22 was the most frequently affected, with aberrations detected in 15 cases. PFS analysis revealed no statistically significant difference between tumors with neutral and altered CNV profiles (p .989, Log \u0026ndash; rank test). The median PFS for both groups remained undefined.\u003c/p\u003e\n \u003cp\u003eIn the group of tumor with no match, 8 tumors (26%) exhibited a neutral CNV profile, whereas 23 tumors (74%) showed chromosomal alterations, with chromosome 22 being the most commonly affected (21 cases). Similar to the other groups, no statistically significant difference in PFS was observed between tumors with neutral and altered CNV profiles in this group. The median PFS for both groups remained undefined. When comparing CNV profiles between MC-intermediate and MC- tumors with no match to a MC, no statistically significant difference was observed (p .507, Mann \u0026ndash; Whitney test).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eClinical routine\u003c/h2\u003e\n \u003cp\u003eAll cases were thoroughly reviewed in internal interdisciplinary tumor board, which convened a median of 8 days after surgery. This timeline coincided with the availability of histopathological results, including CNS WHO grading, which were typically obtained within 5 days post \u0026ndash; surgery. In contrast, epigenetic analysis took a median of 23 days to be finalized. Consequently, the epigenetic profile could not be taken into account in the decision-making process during the tumor board discussions, but only afterwards during the follow-up process.\u003c/p\u003e\n \u003cp\u003ePatient\u0026rsquo;s clinical performance was evaluated preoperatively and postoperatively, as well as at each follow-up visit. Preoperatively, 98 patients (92%) had a Karnofsky Performance Status (KPS) score of \u0026ge;\u0026thinsp;70%, while 8 patients (8%) had a score\u0026thinsp;\u0026lt;\u0026thinsp;70%. No significant difference was observed between pre- and postoperative KPS scores (p\u0026thinsp;=\u0026thinsp;0.9980, Mann Whitney test), indicating that surgery did not negatively impact the patient\u0026rsquo;s overall clinical status.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eProgression\u003c/h2\u003e\n \u003cp\u003eAll patients were followed up regularly in the outpatient clinic, with a median follow \u0026ndash; up duration of 502 days (range: 5\u0026ndash;1213 days).\u003c/p\u003e\n \u003cp\u003eRadiologically confirmed tumor progression occurred in 15 patients (14%) during this period. Among these cases, 9 patients (60%) had CNS WHO grade 1 meningiomas, 5 patients (33%) had CNS WHO grade 2 tumors, and 1 patient (7%) had a CNS WHO grade 3 tumor (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Repeat tumor resection was performed in 7 patients due to progression, while 13 patients received adjuvant radiotherapy. Patients with grade 2 meningiomas and residual tumor have been consulted by radiotherapists. Of the patients who ultimately received radiotherapy, 3 had grade 1 meningioma (1 MC \u0026ndash; benign, and 2 MC \u0026ndash; unclassified), all with residual tumors. Additionally, 7 patients had grade 2 meningiomas (5 MC \u0026ndash; intermediate, and 2 MC \u0026ndash; unclassified), with 3 of these having residual tumors. Lastly, 3 patients had grade 3 meningiomas (1 MC \u0026ndash; intermediate, 1 MC \u0026ndash; malignant, and 1 MC \u0026ndash; unclassified), with one of these patients also having a residual tumor (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The median progression \u0026ndash; free survival (PFS) for each CNS WHO grade could not be determined due to the short follow \u0026ndash; up duration and the limited number of progression cases.\u003c/p\u003e\n \u003cp\u003eEpigenetic analysis of the progressive tumors revealed that 1 patient (7%) had a benign classifier status, 4 patients (27%) had an intermediate status, 1 patient (7%) had a malignant profile, and 9 patients (60%) were unclassified. Among the patients with unclassified tumors and documented progression, none underwent revision surgery due to progression. Of these, 4 out of 9 patients (44%) had residual tumors based on RANO criteria. Histologically, 6 of the unclassified tumors (67%) were CNS WHO grade 1, while 3 tumors (33%) were CNS WHO grade 2. Chromosomal aberrations were identified in 6 cases (67%), while 3 cases exhibited a neutral CNV profile. The most frequent chromosomal alteration, found in 6 cases (67%), involved chromosome 22. Multiple chromosomal alterations \u0026ndash; including chromosome 22- were detected in 3 cases (33%). One tumor remained unclassified due to technical problems, whereas the remainder demonstrated scoring mismatches between MC (v2.4) and tumor classifier (v12.5), with higher score for MC-benign in v12.5 (0.99, 0.99, 0.99, 0.89) and in v2.4 (0.84, 0.8, 0.88).\u003c/p\u003e\n \u003cp\u003ePFS analysis based on epigenetic profiling demonstrated that tumors with MC malignant had a median survival of 122 days, while the median PFS for benign, intermediate and unclassified tumors remained undefined. A statistically significant difference in PFS was observed between as malignant classified tumors and non \u0026ndash; malignant tumors (benign, intermediate, unclassified) (p\u0026thinsp;=\u0026thinsp;.004, Chi square, Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea). Further analysis excluding unclassified meningiomas reinforced the significance of PFS differences between malignant tumors and non \u0026ndash; malignant ones (benign, intermediate) (p\u0026thinsp;\u0026lt;\u0026thinsp;.001, Chi square) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb). These results suggest that although as malignant classified tumors are rare, they are associated with early progression and predict significantly poorer outcomes compared to non \u0026ndash; malignant tumors. Similar results were observed when analyzing PFS of other MC, with intermediate and unclassified tumors showing comparable survival curves but still a significant difference in PFS (p\u0026thinsp;\u0026lt;\u0026thinsp;.001, Chi square) (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e\n \u003cp\u003eCorrelation analysis using the Spearman\u0026rsquo;s rank correlation coefficient identified a significant positive correlation between classifier status (benign, intermediate, malignant) and the occurrence of progression (r \u0026minus;\u0026thinsp;.3910, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). In contrast, no significant correlation was observed between classifier score and the conventional CNS WHO grading system (p .117). A negative correlation was noted between classifier score and PFS (r \u0026minus;\u0026thinsp;.2337, p .044), suggesting that as classifier status advances from benign to malignant, PFS is significantly reduced.\u003c/p\u003e\n \u003cp\u003eSimilarly, a negative correlation was found between classifier status and the KPS at the last follow \u0026ndash; up visit (r \u0026minus;\u0026thinsp;.3447, p .0004), indicating that tumors with a MC malignant tend to be associated with worse clinical performance. These results support the predictive value of the classifier in clinical outcomes.\u003c/p\u003e\n \u003cp\u003eFurther analysis showed no significant correlation between classifier score and radiological features such as calcification (p .255) or edema (p .401). However, a moderate positive correlation was observed between classifier score and tumor volume (r .3964, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), indicating that higher classifier scores are associated with larger tumor volume. In summary, the epigenetic profiling using classification algorithms with defined MC is strongly associated with tumor progression, PFS, KPS at the last patient contact, and tumor volume. However, it does not correlate with WHO grading or radiological characteristics like calcification and edema.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGiven the challenges of accurately predicting meningioma behavior and recurrence based solely on histopathological criteria, there has been increasing interest in exploring molecular markers to improve classification models [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]. The WHO CNS 5 classification has incorporated TERT-promoter mutations and loss of CDKN2A/B as molecular markers for grading of anaplastic meningioma CNS WHO grade 3. This is based on their strong associations with recurrence, offering promising advancements in prognostication. For instance, mutations in the TERT promoter have been linked to a shorter time to progression, highlighting their potential utility as prognostic indicators [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eSimilarly, the identification of activating mutations in the AKT1 gene has paved the way for targeted therapies using AKT inhibitors, underscoring the growing importance of molecular analysis in individualized treatment approaches for meningioma patients [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, it is important to note that molecular markers are still infrequently detected in meningiomas, limiting their current role to supplementary tools rather than primary prognostic criteria.\u003c/p\u003e\n\u003cp\u003eThe epigenetic profiling of meningiomas, particularly the MC, has emerged as a reliable predictor of prognosis [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. Our findings are consistent with existing literature, confirming that the MC has a higher predictive value and accuracy compared to the CNS WHO grading system [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our cohort, a statistically significant correlation was observed between MC status and both tumor progression and clinical outcomes, underscoring its potential as an efficient prognostic tool, notably even after relatively short follow-up times\u003c/p\u003e\n\u003cp\u003eInterestingly, tumors with no match to a MC displayed PFS curves similar to those of intermediate tumors, suggesting that this group encompasses tumors with a broad range of behaviors, from benign to malignant and a possibly heterogenous tissue composition of benign and intermediate fractions complicating unequivocal assignment to a MC. This heterogeneity complicates clinical management, often leading to treatment dilemmas. In our cohort, tumors with no match frequently exhibited high risk markers, such as TERT promoter mutations and CDKN2A/B deletions, which are known to be associated with more aggressive clinical behavior and criteria for grading as CNS WHO grade 3 [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, other unclassified tumors exhibited benign molecular profiles. In our cohort both mismatch as well as technical issues, such as artifacts in genomic analysis or the inability to determine the CNV profile, contributed to the unclassified results.\u003c/p\u003e\n\u003cp\u003eAdditionally, discrepancies between the available classifiers led to mismatches in classification. In this study, tumors were analyzed using the Illumina Human Methylation EPIC v1.0 (850k) array. The data were processed and evaluating with the publicly available database of the German Center for Cancer Research (DKFZ) (Capper et al 2018) accessible via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.molecularneuropathology.org\u003c/span\u003e\u003c/span\u003e [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. This database employed until recently the meningioma classifier v2.4, as well as the tumor methylation classifier v11b4 and v12.5. MC scores\u0026thinsp;\u0026gt;\u0026thinsp;0.5 were considered sufficient for classification, whereas MC scores\u0026thinsp;\u0026lt;\u0026thinsp;0.5, or scores lower than those of the tumor methylation classifier, indicated a mismatch and resulted in unclassified tumors. Such mismatches have been reported previously [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. Updated technologies, such as the Illumina Human Methylation EPIC v2.0 (935k) methylation array as well as updated classification algorithms may reduce the number of unclassified cases [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, tumor biology heterogeneity, atypia and large tumor volume may all separately lead to mismatch resulting in unclassified tumors.\u003c/p\u003e\n\u003cp\u003eIn these cases, combining CNS WHO grading with molecular markers may provide a more comprehensive understanding of tumor behavior and assist in treatment decision \u0026ndash; making.\u003c/p\u003e\n\u003cp\u003eWith respect to radiotherapy, patients with CNS WHO grade 1 meningiomas did not regularly receive any form of adjuvant treatment, except in cases of subtotal resection or significant residual tumor, where radiotherapy may be considered. CNS WHO grade 2 meningioma, however, remains a particularly heterogenous group. Traditionally, radiation has been offered to patients with incomplete resections or multiple meningiomas, while those with complete resections are typically followed without immediate postoperative radiotherapy [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. Radiotherapy was recommended for all patients with CNS WHO grade 3 meningiomas, also in those which were not graded malignant according to MC. We did not feel safe for patients to refrain from adjuvant therapy once CNS WHO grade 3 was assigned, as there are no prospective data for this subgroup of patients.\u003c/p\u003e\n\u003cp\u003eApart from the extent of resection, other clinical or pathological markers such as MC may offer additional guidance in treatment decisions for CNS WHO grade 2 meningiomas. Specifically, MC may help clinicians to decide whether to intensify therapy or adjust follow \u0026ndash; up intervals. Ehret et al. have also recommended incorporating molecular markers, CNV and the MC into the clinical management of grade 2 meningiomas to predict tumor aggressiveness and tailor personalized treatment strategies [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eIn addition to the CNS WHO classification, several alternative classification systems have been proposed, each emphasizing distinct tumor characteristics. For instance, Nassiri et al. developed a molecularly integrated classification, categorizing meningiomas into four groups (M1 \u0026ndash; MG4) based on molecular markers [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. Another approach by Patel et al., which leverages RNA sequencing and whole \u0026ndash; exome sequencing, categorizes meningiomas into three groups with unique molecular profiles [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]. Choudhury et al. further expanded on this approach, using a comprehensive analysis including DNA methylation, genetic alterations, transcriptional profiles, biochemical markers, proteomics, and single \u0026ndash; cell profiling to classify meningiomas into three groups [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e] Driver et al. proposed an integrated score using CNV-alterations, mitotic activity and CDKN2A/B-deletions [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eEach classification system seeks to provide a framework that reliably predicts tumor behavior and progression potential. However, to be widely adopted, a classification system must also be practical, accessible and applicable across clinical settings without complicating the decision \u0026ndash; making process. These various approaches reflect distinct perspectives on meningioma pathology, yet it remains unclear which classification system is superior in terms of predictive accuracy and clinical utility.\u003c/p\u003e\n\u003cp\u003eWhile the prognostic value of the MC has been well established, routine clinical practice continues to rely heavily on the traditional CNS WHO grading system for guiding treatment decisions and aftercare in meningiomas. Our data also show that \u0026ldquo;classical\u0026rdquo; histopathological grading remains indispensable, as it continues to provide crucial information that cannot be fully replaced by molecular or epigenetic analysis.\u003c/p\u003e\n\u003cp\u003eAlthough epigenetic analysis is standard procedure at our institution for every patient with a confirmed meningioma, its labor \u0026ndash; intensive nature presents challenges. Specifically, the molecularpathological report from this analysis is typically not available for initial postoperative tumor board discussions and is instead considered during later follow \u0026ndash; up visits. In that respect, however, none of the other proposed classification systems appears superior to the MC based grading system we have been using.\u003c/p\u003e\n\u003cp\u003eIn the updated WHO CNS 5 Classification, albeit histopathological and molecular markers are included, methylation profiling has not yet been incorporated into the grading score. Consequently, the integration of the MC into routine clinical practice remains uncertain, with criticisms regarding its practicability and clinical relevance. However, the most recent cIMPACT 8 update recommends further molecular testing in histological borderline cases, suggesting similar adjustments in an updated WHO CNS classification[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThere is a growing emphasis on personalized treatment approaches, especially in neuro-oncology. The development of individualized treatment concepts that incorporate histological features, molecular markers, and epigenetic profiling, is gaining momentum. These advancements aim to tailor therapeutic strategies for each patient, improving outcomes and minimizing unnecessary treatments.\u003c/p\u003e\n\u003cp\u003eHowever, the financial implications of epigenetic analysis cannot be overlooked. Conducting these analyses incurs costs that are 3\u0026ndash;4 times higher than those of conventional histopathological examination. At our institution, the costs for standard histological examination are around 200\u0026euro; per case, whereas costs of epigenetic analysis amounts to approximately 680\u0026euro; per case. In public healthcare systems, where cost \u0026ndash; efficiency is a key consideration, the uncertain clinical implications of routine epigenetic testing must be carefully weighed against its benefits.\u003c/p\u003e\n\u003cp\u003eWe believe that the additional costs for epigenetic testing are worthwhile to avoid under- or overtreatment in terms of either omitting radiotherapy or performing follow-up MRI in unnecessarily short intervals, which in result could level out or be even cost \u0026ndash; effective.\u003c/p\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eLimitations\u003c/h2\u003e\n \u003cp\u003eThe primary limitations of our study include the small size and the relatively short follow \u0026ndash; up period. Given the typically slow growth rate and long progression course of meningiomas, extended follow \u0026ndash; up is essential for accurately predicting PFS and overall survival (OS) [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. As meningiomas are often benign and indolent, longer observation periods are required to capture meaningful clinical outcomes.\u003c/p\u003e\n \u003cp\u003eAdditionally, the classification of unclassified tumors poses a challenge, as their clinical behavior remains difficult to predict. Emerging and updated technologies, such as the EPIC v2.0 (935k) methylation array and further advances in classifier algorithms could help improving classifier accuracy and ideally provide a single, definitive score. These advancements may improve classification accuracy and reduce the number of unclassified cases, leading to clearer prognostic insights.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e:\u003cem\u003e\u0026nbsp;\u003c/em\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e: The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor Contribution:\u003c/em\u003e All authors contribute to the conception and design of the study, and all reviewed and approved the final version submitted.\u003c/p\u003e\n\u003cp\u003eL.K drafted the main manuscript and conducted the overall work\u003c/p\u003e\n\u003cp\u003eW.M and M.B conducted all laboratory analyses, and provided all histopathalogical and epigenetically reports\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;P.B contribute to manuscript preparation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eC.S supervised the overall work and coordinated the entire team\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval\u003c/em\u003e: \u0026nbsp;This study received ethical approval from the local ethics committee of Friedrich \u0026ndash; Schiller University Jena, under registration number Reg. \u0026ndash; Nr.: 2024 \u0026ndash; 3409 \u0026ndash; Daten. This study protocol adhered to the principles outlined in the Declaration of Helsinki, specifically points 22 and 23.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to participate:\u0026nbsp;\u003c/em\u003einformed consent was obtained from all individual participants included in the study. No personal or identifiable data were collected, and individuals cannot be distinguished. We confirm complete anonymity in our retrospective analysis. This submission does not include any images that could lead to the identification of individuals.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to publish:\u0026nbsp;\u003c/em\u003enot necessary, as all information remains anonymized and all the procedures being performed were part of the routine care.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHuman Ethics and Consent to Participate:\u003c/em\u003e not applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical trial number:\u003c/em\u003e not applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical trial number:\u003c/em\u003e not applicable\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlruwaili AA, De Jesus O. Meningioma. \u003cem\u003eStatPearls\u003c/em\u003e, Treasure Island (FL) ineligible companies. 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Molecular profiling predicts meningioma recurrence and reveals loss of DREAM complex repression in aggressive tumors, \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e. 2019; 116(43): 21715-21726.\u003c/li\u003e\n\u003cli\u003eChoudhury A, Magill ST, Eaton CD, Prager BC, Chen WC, Cady MA, Seo K, Lucas CG, Casey-Clyde TJ, Vasudevan HN, Liu SJ, Villanueva-Meyer JE, Lam TC, Pu JK, Li LF, Leung GK, Swaney DL, Zhang MY, Chan JW, Qiu Z, Martin MV, Susko MS, Braunstein SE, Bush NAO, Schulte JD, Butowski N, Sneed PK, Berger MS, Krogan NJ, Perry A, Phillips JJ, Solomon DA, Costello JF, McDermott MW, Rich JN, Raleigh DR. Meningioma DNA methylation groups identify biological drivers and therapeutic vulnerabilities, \u003cem\u003eNature genetics\u003c/em\u003e. 2022; 54(5): 649-659.\u003c/li\u003e\n\u003cli\u003eDriver J, Hoffman SE, Tavakol S, Woodward E, Maury EA, Bhave V, Greenwald NF, Nassiri F, Aldape K, Zadeh G, Choudhury A, Vasudevan HN, Magill ST, Raleigh DR, Abedalthagafi M, Aizer AA, Alexander BM, Ligon KL, Reardon DA, Wen PY, Al-Mefty O, Ligon AH, Dubuc AM, Beroukhim R, Claus EB, Dunn IF, Santagata S, Bi WL. A molecularly integrated grade for meningioma, \u003cem\u003eNeuro-oncology\u003c/em\u003e. 2022; 24(5): 796-808.\u003c/li\u003e\n\u003cli\u003eZeidman LA, Ankenbrandt WJ, Du H, Paleologos N, Vick NA. Growth rate of non-operated meningiomas, \u003cem\u003eJournal of neurology\u003c/em\u003e. 2008; 255(6): 891-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Meningioma, Methylation profile, MC-Classifier, CNV profile, Illumina Human Methylation 850k array","lastPublishedDoi":"10.21203/rs.3.rs-6218017/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6218017/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eThe methylation profile of meningiomas is a promising predictive tool, potentially offering greater accuracy in assessing tumor behavior compared to WHO grading. This study aimed to evaluate the clinical relevance of routine epigenetic testing in meningioma management.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed patients undergoing meningioma resection between January 2021 and December 2023. Histopathological grading (WHO) and methylation profiling (MC) with the 850k Illumina chip were performed by an independent neuropathologist.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eA total of 106 patients were included, with 81 (76%) classified as HO grade 1, 20 (19%) as grade 2, and 5 (5%) as grade 3. Epigenetically, 55 tumors (52%) were classified as benign, 18 (17%) as intermediate, 2 (2%) as malignant and 31 (29%) as unclassified. Discordances between WHO grading and methylation profiling were observed in 18 of 74 cases. Notably, 8 WHO grade 1 tumors (16%) displayed MC-intermediate, while 9 WHO grade 2 tumors were classified as intermediate, and 1 as malignant. Tumor board decisions were made in a median of 8 days postoperatively, guided by WHO grading; however, the epigenetic report was only available after a median of 22 days. During follow-up, 15 patients experienced tumor progression. Progression was significantly associated with the meningioma classifier (r\u0026thinsp;=\u0026thinsp;0.3, p\u0026thinsp;=\u0026thinsp;0.0102) and tumor volume (r\u0026thinsp;=\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;0.0005), but not with WHO grading (r\u0026thinsp;=\u0026thinsp;0.17, p\u0026thinsp;=\u0026thinsp;0.084). PFS in MC-unclassified tumors mirrored that of the intermediate group.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eMethylation profiling demonstrates superior predictive accuracy for meningioma progression and complements WHO grading, especially in identifying malignant maningiomas.\u003c/p\u003e","manuscriptTitle":"The role of meningioma epigenetics in routine clinical practice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 00:12:58","doi":"10.21203/rs.3.rs-6218017/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"73ebaead-66c5-4ae8-b831-a6b532f7e148","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-01T15:08:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-15 00:12:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6218017","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6218017","identity":"rs-6218017","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}