Faculty Bibliography

BACKGROUND:Isocitrate dehydrogenase (IDH) mutant astrocytoma grading, until recently, has been entirely based on morphology. The 5th edition of the Central Nervous System World Health Organization (WHO) introduces CDKN2A/B homozygous deletion as a biomarker of grade 4. We sought to investigate the prognostic impact of DNA methylation-derived molecular biomarkers for IDH mutant astrocytoma. METHODS:We analyzed 98 IDH mutant astrocytomas diagnosed at NYU Langone Health between 2014 and 2022. We reviewed DNA methylation subclass, CDKN2A/B homozygous deletion, and ploidy and correlated molecular biomarkers with histological grade, progression free (PFS), and overall (OS) survival. Findings were confirmed using 2 independent validation cohorts. RESULTS:There was no significant difference in OS or PFS when stratified by histologic WHO grade alone, copy number complexity, or extent of resection. OS was significantly different when patients were stratified either by CDKN2A/B homozygous deletion or by DNA methylation subclass (P value = .0286 and .0016, respectively). None of the molecular biomarkers were associated with significantly better PFS, although DNA methylation classification showed a trend (P value = .0534). CONCLUSIONS:The current WHO recognized grading criteria for IDH mutant astrocytomas show limited prognostic value. Stratification based on DNA methylation shows superior prognostic value for OS.

Gliomas are the most common adult and pediatric primary brain tumors. Molecular studies have identified features that can enhance diagnosis and provide biomarkers. IDH1/2 mutation with ATRX and TP53 mutations defines diffuse astrocytomas, whereas IDH1/2 mutations with 1p19q loss defines oligodendroglioma. Focal amplifications of receptor tyrosine kinase genes, TERT promoter mutation, and loss of chromosomes 10 and 13 with trisomy of chromosome 7 are characteristic features of glioblastoma and can be used for diagnosis. BRAF gene fusions and mutations in low-grade gliomas and histone H3 mutations in high-grade gliomas also can be used for diagnostics.

BACKGROUND:Medulloblastomas are the most common malignant brain tumors in the pediatric population. Based on the idea that tumors with identical radio-genomic features should behave similarly, the 4 molecular subtypes are now widely accepted as a guide for the management and prognosis. The radiological features of medulloblastomas can predict the molecular subtype; thus, anticipating the subsequent disease progression. However, this has not been evaluated comprehensively. We aim to thoroughly study the association between the molecular subtypes and radiological features of medulloblastomas. Moreover, we aim to investigate the efficacy of this correlation with the use of progression-free survival and 5-year survival rates. METHODS:A retrospective analysis was conducted for all histopathological confirmed medulloblastomas in pediatric patients (<16 years old) that were operated on in Kuwait over the past ten years (n = 44). The radiological, histological, and molecular characteristics were justifiably evaluated and analyzed in our sample. RESULTS:The overall progression-free survival after one year was noticed among 27 cases (≈44%) and the nonspecific 5-year survival was seen in 31 cases (≈70%) after a 5-year follow-up. Sonic Hedgehog and Wingless had the best outcomes, while group 3 showed the worst outcomes. CONCLUSIONS:Our findings did not support the association between most of the typical magnetic resonance imaging characteristics and survival rate. We further established that Sonic Hedgehog and Wingless biological types have a better prognosis. There was no association observed between the radiographic features, specifically the location, and the molecular subtype.

The morphological patterns leading to the diagnosis of glioblastoma may also commonly be observed in several other distinct tumor entities, which can result in a mixed bag of tumors subsumed under this diagnosis. The 2021 WHO Classification of CNS Tumors has separated several of these entities from the diagnosis of glioblastoma, IDH-wildtype. This study determines the DNA methylation classes most likely receiving the diagnosis glioblastoma, IDH wildtype according to the definition by the WHO 2021 Classification and provides comparative copy number analyses. We identified 10782 methylome datasets uploaded to the web page www.molecularneuropathology.org with a calibrated score of ≥0.9 by the Heidelberg Brain Tumor Classifier version v12.8. These methylation classes were characterized by the diagnosis glioblastoma being the most frequent classification encountered in each of the classes according to the WHO 2021 definition. Further, methylation classes selected for this study predominantly contained adult patients. Unsupervised clustering confirmed the presence of nine methylation classes containing tumors most likely receiving the diagnosis glioblastoma, IDH-wildtype according to the WHO 2021 definition. Copy number analysis and a focus on genes with typical numerical alterations in glioblastoma revealed clear differences between the nine methylation classes. Although great progress in diagnostic precision has been achieved over the last decade, our data clearly demonstrate that glioblastoma, IDH-wildtype still is a heterogeneous group in need of further stratification.

UNLABELLED:DNA methylation is an essential molecular assay for central nervous system (CNS) tumor diagnostics. While some fusions define specific brain tumors, others occur across many different diagnoses. We performed a retrospective analysis of 219 primary CNS tumors with whole genome DNA methylation and RNA next-generation sequencing. DNA methylation profiling results were compared with RNAseq detected gene fusions. We detected 105 rare fusions involving 31 driver genes, including 23 fusions previously not implicated in brain tumors. In addition, we identified 6 multi-fusion tumors. Rare fusions and multi-fusion events can impact the diagnostic accuracy of DNA methylation by decreasing confidence in the result, such as BRAF, RAF, or FGFR1 fusions, or result in a complete mismatch, such as NTRK, EWSR1, FGFR, and ALK fusions. IMPLICATIONS/UNASSIGNED:DNA methylation signatures need to be interpreted in the context of pathology and discordant results warrant testing for novel and rare gene fusions.

Ependymomas encompass multiple clinically relevant tumor types based on localization and molecular profiles. Tumors of the methylation class "spinal ependymoma" (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, their developmental origin is ill-defined, molecular data are scarce, and the potential heterogeneity within SP-EPN remains unexplored. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations, but neither types and frequency of these alterations nor their clinical relevance have been described in a large, epigenetically defined series. Transcriptomic (n = 72), epigenetic (n = 225), genetic (n = 134), and clinical data (n = 112) were integrated for a detailed molecular overview on SP-EPN. Additionally, we mapped SP-EPN transcriptomes to developmental atlases of the developing and adult spinal cord to uncover potential developmental origins of these tumors. The integration of transcriptomic ependymoma data with single-cell atlases of the spinal cord revealed that SP-EPN display the highest similarities to mature adult ependymal cells. Unsupervised hierarchical clustering of transcriptomic data together with integrated analysis of methylation profiles identified two molecular SP-EPN subtypes. Subtype A tumors primarily carried previously known germline or sporadic NF2 mutations together with 22q loss (bi-allelic NF2 loss), resulting in decreased NF2 expression. Furthermore, they more often presented as multilocular disease and demonstrated a significantly reduced progression-free survival as compared to SP-EP subtype B. In contrast, subtype B predominantly contained samples without NF2 mutation detected in sequencing together with 22q loss (monoallelic NF2 loss). These tumors showed regular NF2 expression but more extensive global copy number alterations. Based on integrated molecular profiling of a large multi-center cohort, we identified two distinct SP-EPN subtypes with important implications for genetic counseling, patient surveillance, and drug development priorities.

BACKGROUND:There are no effective medical therapies for patients with meningioma who progress beyond surgical and radiotherapeutic interventions. Somatostatin receptor Type 2 (SSTR2) represents a promising treatment target in meningiomas. In this multicenter, single-arm phase II clinical study (NCT03971461), the SSTR2-targeting radiopharmaceutical 177Lu-DOTATATE is evaluated for its feasibility, safety, and therapeutic efficacy in these patients. PATIENTS AND METHODS/METHODS:Adult patients with progressive intracranial meningiomas received 177Lu-DOTATATE at a dose of 7.4 GBq (200 mCi) every eight weeks for four cycles. 68Ga-DOTATATE PET-MRI was performed before and six months after begin of treatment. The primary endpoint was progression-free survival (PFS) at 6 months (PFS-6). Secondary endpoints were safety and tolerability, overall survival (OS) at 12 months (OS-12), median PFS, and median OS. RESULTS:Fourteen patients (F=11, M=3) with progressive meningiomas (WHO 1=3, 2=10, 3=1) were enrolled. Median age was 63.1 (range 49.7-78) years. All patients previously underwent tumor resection and at least one course of radiation. Treatment with 177Lu-DOTATATE was well tolerated. Seven patients (50%) achieved PFS-6. Best radiographic response by modified Macdonald criteria was stable disease (SD) in all seven patients. A >25% reduction in 68Ga-DOTATATE (PET) was observed in five meningiomas and two patients. In one lesion, this corresponded to >50% reduction in bidirectional tumor measurements (MRI). CONCLUSIONS:Treatment with 177Lu-DOTATATE was well tolerated. The predefined PFS-6 threshold was met in this interim analysis, thereby allowing this multicenter clinical trial to continue enrollment. 68Ga-DOTATATE PET may be a useful imaging biomarker to assess therapeutic outcome in patients with meningioma.

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma (n = 153) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of 93.3 ± 1.6%. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.

BACKGROUND:Plexiform neurofibromas can transform into atypical neurofibromas (ANF) and then further progress to aggressive malignant peripheral nerve sheath tumors (MPNST). ANF have been described to harbor distinct histological features and frequent loss of CDKN2A/B. However, histological evaluation may be rater-dependent, and detailed knowledge about the molecular mechanisms of malignant transformation is scarce. In general, malignant transformation can be accompanied by significant epigenetic changes, and global DNA methylation profiling is able to differentiate relevant tumor subgroups. Therefore, epigenetic profiling might provide a valuable tool to distinguish and characterize ANF with differing extent of histopathological atypia from neurofibromas and MPNST. METHODS:We investigated 40 tumors histologically diagnosed as ANF and compared their global methylation profile to other peripheral nerve sheath tumors. RESULTS:Unsupervised class discovery and t-SNE analysis indicated that 36/40 ANF cluster with benign peripheral nerve sheath tumors with clear separation from MPNST. 21 ANF formed a molecularly distinct cluster in proximity to schwannomas. Tumors in this cluster had a frequent heterozygous or homozygous loss of CDKN2A/B and significantly more lymphocyte infiltration than MPNST, schwannomas, and NF. Few ANF clustered closely with neurofibromas, schwannomas, or MPNST, raising the question, whether diagnosis based on histological features alone might pose a risk to both over- and underestimate the aggressiveness of these lesions. CONCLUSIONS:Our data suggest that ANF with varying histological morphology show distinct epigenetic similarities and cluster in proximity to benign peripheral nerve sheath tumor entities. Future investigations should pay special respect to correlating this methylation pattern to clinical outcomes.