Aldape, Kenneth

2030 Background: Brain metastases (BM) are common and arise in 30% of lung adenocarcinoma (LUAD) patients. Patients with LUAD that develop BM have significantly poorer outcomes, with a 10-16 month median overall survival. Unfortunately, current clinical practice for BM prediction is limited and so BM are typically detected after they develop and grow to cause neurological symptoms. Once BM are detected, currently neurosurgical tumor biopsies are performed to enable BM diagnosis via neuropathological evaluation. The aims of this study were to develop DNA methylation-based models that predict LUAD BM and non-invasively detect BM in blood to enable early diagnosis and treatment. Methods: DNA methylomes were acquired from 402 tumor tissue and plasma samples in a cohort of 346 LUAD and BM patients. Machine learning models were built using DNA methylation signatures that stratify BM risk in tissue and detect BM in plasma. Models were evaluated in independent validation datasets. A predictive nomogram was developed using the BM prediction model together with clinical factors to provide composite patient-specific scores reflecting BM risk. Results: The methylation-based BM predictor accurately stratified BM risk in a univariable Cox model using validation set data (HR = 5.65, 95%CI 1.85–17.2, p = 0.0023). Model utility was independent of the predictive value of clinical factors in a multivariable Cox model using validation set data (Table 1: HR = 8.92, 95%CI 1.97–40.5, p = 0.0046). The 5-year model accuracy was 0.81 and significantly higher than a similarly built cancer stage-based model (0.65), demonstrating utility over current practice. The combinatorial clinical-methylomic predictive nomogram had enhanced utility with an accuracy of 0.82 univariable Cox HR of 17.2 (95%CI 4.13–71.3, p < 0.0001), demonstrating comprehensive patient-specificity. The plasma-based model accurately classified BM from gliomas and lymphomas (AUROC=0.80), as typical clinical differential diagnoses, in validation set data. The models were validated further in additional external data. Conclusions: DNA methylation-based modeling of BM can accurately predict LUAD patients at risk for BM development and can non-invasively detect BM that develop. Future treatment approaches may tailor initial LUAD treatment and ongoing cancer surveillance to a patient’s BM risk, allowing for the potential to prevent and treat BM early. DNA methylation-based BM prediction is independent of clinical factors in a multivariable Cox proportional hazards model. Variable HR 95% CI p Methylome risk score 8.92 1.97–40.5 0.005 Age Years 0.96 0.92–1.02 0.177 Smoking Pack-years 0.99 0.95–1.03 0.496 EGFR Mutant vs wildtype 0.92 0.25–3.34 0.895 T T2 vs T1 1.58 0.41–6.04 0.505 T3−4 vs T1 1.49 0.28–7.98 0.642 N N1 vs N0 1.05 0.31–3.58 0.943 N2−3 vs N0 1.00 0.27–3.69 0.995 M M1 vs M0 145 12.2–1730 <0.001

Importance Molecular techniques, including next-generation sequencing, genomic copy number profiling, fusion transcript detection, and genomic DNA methylation arrays, are now indispensable tools for the workup of central nervous system (CNS) tumors. Yet there remains a great deal of heterogeneity in using such biomarker testing across institutions and hospital systems. This is in large part because there is a persistent reluctance among third-party payers to cover molecular testing. The objective of this Review is to describe why comprehensive molecular biomarker testing is now required for the accurate diagnosis and grading and prognostication of CNS tumors and, in so doing, to justify more widespread use by clinicians and coverage by third-party payers. Observations The 5th edition of the World Health Organization (WHO) classification system for CNS tumors incorporates specific molecular signatures into the essential diagnostic criteria for most tumor entities. Many CNS tumor types cannot be reliably diagnosed according to current WHO guidelines without molecular testing. The National Comprehensive Cancer Network also incorporates molecular testing into their guidelines for CNS tumors. Both sets of guidelines are maximally effective if they are implemented routinely for all patients with CNS tumors. Moreover, the cost of these tests is less than 5% of the overall average cost of caring for patients with CNS tumors and consistently improves management. This includes more accurate diagnosis and prognostication, clinical trial eligibility, and prediction of response to specific treatments. Each major group of CNS tumors in the WHO classification is evaluated and how molecular diagnostics enhances patient care is described. Conclusions and Relevance Routine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.

Abstract Genome-wide DNA methylation signatures correlate with and distinguish central nervous system (CNS) tumor types. Since the publication of the initial CNS tumor DNA methylation classifier in 2018, this platform has been increasingly used as a diagnostic tool for CNS tumors, with multiple studies showing the value and utility of DNA methylation-based classification of CNS tumors. A Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) Working Group was therefore convened to describe the current state of the field and to provide advice based on lessons learned to date. Here, we provide recommendations for the use of DNA methylation-based classification in CNS tumor diagnostics, emphasizing the attributes and limitations of the modality. We emphasize that the methylation classifier is one diagnostic tool to be used alongside previously established diagnostic tools in a fully integrated fashion. In addition, we provide examples of the inclusion of DNA methylation data within the layered diagnostic reporting format endorsed by the World Health Organization (WHO) and the International Collaboration on Cancer Reporting. We emphasize the need for backward compatibility of future platforms to enable accumulated data to be compatible with new versions of the array. Finally, we outline the specific connections between methylation classes and CNS WHO tumor types to aid in the interpretation of classifier results. It is hoped that this update will assist the neuro-oncology community in the interpretation of DNA methylation classifier results to facilitate the accurate diagnosis of CNS tumors and thereby help guide patient management.

Abstract Adult primary leptomeningeal gliomatosis (PLG) is a rare, rapidly progressive and fatal disease characterized by prominent leptomeningeal infiltration by a glial tumor without an identifiable parenchymal mass. The molecular profile of adult PLG has not been well‐characterized. We report the clinical, pathological, and molecular findings of six adult PLG patients (five males and one female), median age 58 years. All cases exhibited pathological leptomeningeal enhancement at presentation. Leptomeningeal biopsy was diagnostic in five (of six) cases, revealing infiltration by an astrocytic glioma with mitotic activity, lacking microvascular proliferation or necrosis. One case was diagnosed at autopsy. All tumors were IDH‐wildtype, with five harboring TERT promoter mutations. Additional mutations identified were PTEN in one case, TP53 in two cases, and NF1 in two cases. A chromosome profile with +7/−10 was found in four cases, whereas the remaining two showed either chromosome 7 or 7p gain only. Four cases showed chromosome 9p loss with CDKN2A/B homozygous deletion, one case showed hemizygous CDKN2A/B loss, and one case showed intact chromosome 9 and CDK4/GLI1 amplification. DNA methylation profiling was performed in four cases and revealed a match to glioblastoma (GBM) family and mesenchymal typical class with high confidence scores in two cases; the other two cases showed only suggestive combined scores for GBM family and mesenchymal atypical class. The molecular profile of all cases closely aligned with that of adult‐type GBM, IDH‐wildtype, CNS WHO grade 4. All patients succumbed to the disease. In five cases with extensive leptomeningeal disease at diagnosis, the course was rapid, with median survival of 24 days following palliative care. Only one case, with relatively localized disease at diagnosis, received chemoradiation therapy and survived 535 days, raising the possibility that early diagnosis and timely treatment could improve outcome. A detailed list of previously reported cases is provided in a supplementary table.

Atypical teratoid/rhabdoid tumor (ATRT) is an aggressive, malignant embryonal tumor with dismal long-term survival despite aggressive multimodal therapy. While this tumor typically presents in infancy or early childhood, there are published case reports of adult-onset ATRT. Making prognostic conclusions or therapeutic decisions for this older patient population remains challenging due to the paucity of these reports. A 25-year-old female with Down syndrome presented with dysphagia and facial droop and was found to have an avidly enhancing, cerebellopontine angle mass. Histology demonstrated sheets of rhabdoid cells with loss of INI1 expression, pathognomonic for ATRT. Further sequencing detected a frameshift SMARCB1 mutation and methylation profiling matched with high confidence to the MYC subclass of ATRT. The patient was treated with subtotal surgical resection and focal proton beam irradiation, followed by chemotherapy on a modified regimen due to concern for heightened risk of treatment-related toxicity. On most recent follow-up 22 months from diagnosis, the patient remains without evidence of disease. This report represents the first known case of ATRT in a young adult patient with Down syndrome, offering unique mechanistic insight into the tumorigenesis of ATRT. Further studies are needed to define an appropriate risk-adapted and standardized therapeutic approach for this patient population.

Abstract Most TERT promoter (TERTp) clinically relevant sequence variants in CNS tumors are the canonical C228T and C250T mutations. Non-canonical TERTp mutations have been reported mainly in non-CNS tumors. We describe 12 CNS tumors with non-canonical TERTp variants interpreted as clinically relevant. Using clinical targeted NGS panels (2020-2024), we detected c.-100_-79dup (n=2), c.-92_-91insGGCGGCCCCGCCCCTTCCTTTC (n=1), c.-118_-117insTCCCCGGCCCAGCCCCTTCCGGG (n=1), c.-123_-76dup (n=1), c.-110_-89dup (n=2), and c.-57A&gt;C (n=5). Most cases had chromosomal microarray (n=11) and/or methylation array data analyzed using the NCI/Bethesda v.2 classifier (n=9). All non-canonical TERTp variants occurred at a variant allele frequency suggestive of somatic clonal origin (mean, 34%; range, 18-46), and in adults (mean age, 60 years; range, 36-88). Except for the c.-57A&gt;C variant, all non-canonical TERTp variants occurred in tumors with histological and/or molecular diagnostic features of glioblastoma, IDH-wildtype (GBM), often epigenetically aligning to this tumor type. All five tested cases matched to superfamily glioblastoma (score ≥ 0.9), with three to class GBM_RTK_I (&gt;0.9 in 2, 0.86 in 1) and two to GBM_RTK_II (&gt;0.9). The size and sequence of such variants suggest that these may be functionally equivalent to canonical mutations or generate favorable TERTp activation motif conformations like previously reported activating duplications. The c.-57A&gt;C variant is a well-established oncogenic mutation observed in other cancer types but has not been reported in CNS tumors. We describe five cases with the c.-57A&gt;C variant: one GBM matching to methylation class GBM_MES_TYP (0.99); two oligodendroglioma, IDH-mutant and 1p/19q-codeleted, one of which had methylation data matching to class O_IDH (0.99); one diffuse glioma, IDH-mutant, which was partially 1p/19q-codeleted and matched to class O_IDH (0.99); and one anaplastic meningioma, aligning to superfamily meningioma (0.99)/MNG_MAL (0.79). Our findings show that non-canonical TERTp variants typically occur in tumor types that often harbor TERTp canonical mutations, expanding the spectrum of TERTp clinically relevant variants that are molecular biomarkers in CNS tumors.

Abstract Meningiomas are the most frequent primary intracranial tumors. Hence, they constitute a major share of diagnostic specimens in neuropathology practice. The 2021 WHO Classification of Central Nervous System Tumors (“CNS5”) has introduced the first molecular grading parameters for meningioma with oncogenic variants in the TERT promoter and homozygous deletion of CDKN2A/B as markers for CNS WHO grade 3. However, after the publication of the new classification volume, clarifications were requested, not only on novel but also on long-standing questions in meningioma grading that were beyond the scope of the WHO “blue book.” In addition, more recent research into possible new molecular grading parameters could not yet be implemented in the 2021 classification but constitutes a compelling body of literature. Hence, the consortium to inform molecular and practical approaches to CNS tumor taxonomy-not official WHO (cIMPACT-NOW) Steering Committee convened a working group to provide such clarification and assess the evidence of possible novel molecular criteria. As a result, this cIMPACT-NOW update provides guidance for more standardized morphological evaluation and interpretation, most prominently pertaining to brain invasion, identifies scenarios in which advanced molecular testing is recommended, 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 and/or NF2 oncogenic variants, and discusses areas in which the current evidence is not yet sufficient to result in new recommendations.

Abstract Background The optimal diagnosis and management of patients with brain tumors currently uses the 2021 WHO integrated diagnosis of histomorphologic and molecular features. However, neuro-oncology practice in resource-limited settings usually relies solely on histomorphology. This study aimed to classify glioma cases diagnosed in the Department of Anatomic and Molecular Pathology, Lagos University Teaching Hospital, using the 2021 WHO CNS tumor classification. Methods Fifty-six brain tumors from 55 patients diagnosed with glioma between 2013 and 2021 were reevaluated for morphologic diagnosis. Molecular features were determined from formalin-fixed paraffin-embedded (FFPE) tissue using immunohistochemistry (IHC) for IDH1-R132H, ATRX, BRAF-V600E, p53, Ki67, and H3-K27M, OncoScan chromosomal microarray for copy number, targeted next generation sequencing for mutation and fusion and methylation array profiling. Results Of 55 central nervous system tumors, 3 were excluded from histomorphologic reevaluation for not being of glial or neuroepithelial origin. Of the remaining 52 patients, the median age was 20.5 years (range: 1 to 60 years), 38(73%) were males and 14(27%) were females. Seventy-one percent of the gliomas evaluated provided adequate DNA from archival FFPE tissue blocks. After applying the 2021 WHO diagnostic criteria the initial morphologic diagnosis changed for 35% (18/52) of cases. Diagnoses of 5 (9.6%) gliomas were upgraded, and 7 (14%) were downgraded. Conclusions This study shows that the incorporation of molecular testing can considerably improve brain tumor diagnoses in Nigeria. Furthermore, this study highlights the diagnostic challenges in resource-limited settings and what is at stake in the global disparities of brain tumor diagnosis.