Faculty Bibliography

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.

BACKGROUND/UNASSIGNED:are associated with microsatellite instability and a hypermutator phenotype in numerous systemic cancers, and germline MMR mutations have been implicated in multi-organ tumor syndromes. In gliomas, MMR mutations can function as an adaptive response to alkylating chemotherapy, although there are well-documented cases of germline and sporadic mutations, with detrimental effects on patient survival. METHODS/UNASSIGNED:The clinical, pathologic, and molecular features of 18 IDH-mutant astrocytomas and 20 IDH-wild-type glioblastomas with MMR mutations in the primary tumor were analyzed in comparison to 361 IDH-mutant and 906 IDH-wild-type tumors without MMR mutations. In addition, 12 IDH-mutant astrocytomas and 18 IDH-wild-type glioblastomas that developed MMR mutations between initial presentation and tumor recurrence were analyzed in comparison to 50 IDH-mutant and 104 IDH-wild-type cases that remained MMR-wild-type at recurrence. RESULTS/UNASSIGNED: = .0022) in the IDH-mutant astrocytoma cohort. CONCLUSIONS/UNASSIGNED:These results suggest that whether present initially or in response to therapy, MMR mutations significantly affect TMB but appear to only influence the clinical outcome in IDH-mutant astrocytoma subsets.

Pleomorphic xanthoastrocytoma (PXA) poses a diagnostic challenge. The present study relies on methylation-based predictions and focuses on copy number variations (CNV) in PXA. We identified 551 tumors from patients having received the histologic diagnosis or differential diagnosis pleomorphic xanthoastrocytoma (PXA) uploaded to the web page www.molecularneuropathology.org. Of these 551 tumors, 165 received the prediction "methylation class (anaplastic) pleomorphic xanthoastrocytoma" with a calibrated score >=0.9 by the brain tumor classifier version v12.8 and, therefore, were defined the PXA reference set designated mcPXAref. In addition to these 165 mcPXAref, 767 other tumors received the prediction mcPXA with a calibrated score >=0.9 but without a histological PXA diagnosis. The total number of individual tumors predicted by histology and/or by methylome based classification as PXA, mcPXA or both was 1318, and these were designated the study cohort. The selection of a control cohort was guided by methylation-based predictions recurrently observed for the other 386/551 tumors diagnosed as histologic PXA. 131/386 received predictions for another entity besides PXA with a score >=0.9. Control tumors corresponding to the 11 most common other predictions were selected, adding up to 1100 reference cases. CNV profiles were calculated from all methylation datasets of the study and control cohorts. Special attention was given to the 7/10 signature, gene amplifications and homozygous deletion of CDKN2A/B. Comparison of CNV in the subsets of the study cohort and the control cohort were used to establish relations independent of histological diagnoses. Tumors in mcPXA were highly homogenous in regard to CNV alterations, irrespective of the histological diagnoses. The 7/10 signature commonly present in glioblastoma, IDH-wildtype, was present in 15-20% of mcPXA, whereas amplification of oncogenes (likewise common in glioblastoma) was very rare in mcPXA (<1%). In contrast, the histology-based PXA group exhibited high variance in regard to methylation classes as well as to CNVs. Our data add to the notion, that histologically defined PXA likely only represent a subset of the biological disease.

Next-generation sequencing (NGS) studies have demonstrated that co-occurring sporadic endometrioid endometrial carcinoma (EEC) and endometrioid ovarian carcinoma (EOC) are clonally related, suggesting that they originate from a single primary tumor. Despite clonality, synchronous EEC and EOC when diagnosed at early stage behave indolently, similar to isolated primary EEC or isolated primary EOC. In the present study, we compared the DNA methylation signatures of co-occurring EEC and EOC with those of isolated primary EEC and isolated primary EOC. We also performed targeted NGS to assess the clonal relatedness of 7 co-occurring EEC and EOC (4 synchronous EEC and EOC and 3 metastatic EEC based on pathologic criteria). NGS confirmed a clonal relationship in all co-occurring EEC and EOC. DNA methylation profiling showed distinct epigenetic signatures of isolated primary EEC and isolated primary EOC. Endometrial tumors from co-occurring EEC and EOC clustered with isolated primary EEC while their ovarian counterparts clustered with isolated primary EOC. Three co-occurring EEC and EOC cases with peritoneal lesions showed a closer epigenetic signature and copy number variation profile between the peritoneal lesion and EOC than EEC. In conclusion, synchronous sporadic EEC and EOC are clonally related but demonstrate a shift in DNA methylation signatures between ovarian and endometrial tumors as well as epigenetic overlap between ovarian and peritoneal tumors. Our results suggest that tumor microenvironment in the ovary may play a role in epigenetic modulation of metastatic EEC.