Faculty Bibliography

Chromosomal structural variants (SVs) are major contributors to cancer development. Although multiple methods exist for detecting SVs, they are limited in throughput, such as fluorescent in situ hybridization and targeted panels, and use RNA, which degrades in formalin-fixed, paraffin-embedded (FFPE) blocks and is unable to detect SVs that do not produce a fusion transcript. High-throughput chromosome conformation capture (Hi-C) is a DNA-based next-generation sequencing (NGS) method that preserves the spatial conformation of the genome, capturing long-range genetic interactions and SVs. Herein, a retrospective study analyzing 71 FFPE specimens from 10 different solid tumors was performed. Results showed high concordance (98%) with clinical fluorescent in situ hybridization and RNA NGS in detecting known SVs. Furthermore, Hi-C provided insight into the mechanism of SV formation, including chromothripsis and extrachromosomal DNA, and detected rearrangements between genes and regulatory regions, all of which are undetectable by RNA NGS. Lastly, SVs were detected in 71% of cases in which previous clinical methods failed to identify a driver. Of these, 14% were clinically actionable based on current medical guidelines, and an additional 14% were not in medical guidelines but involve targetable biomarkers. Current data suggest that Hi-C is a robust and accurate method for genome-wide SV analyses from FFPE tissue and can be incorporated into current clinical NGS workflows.

BACKGROUND:Pituitary neuroendocrine tumors (PitNETs) are the most common intracranial neuroendocrine tumors. PitNETs can be challenging to classify, and current recommendations include a large immunohistochemical panel to differentiate among 14 WHO-recognized categories. METHODS:In this study, we analyzed clinical, immunohistochemical and DNA methylation data of 118 PitNETs to develop a clinico-molecular approach to classifying PitNETs and identify epigenetic classes. RESULTS:CNS DNA methylation classifier has an excellent performance in recognizing PitNETs and distinguishing the three lineages when the calibrated score is ≥0.3. Unsupervised DNA methylation analysis separated PitNETs into two major clusters. The first was composed of silent gonadotrophs, which form a biologically distinct group of PitNETs characterized by clinical silencing, weak hormonal expression on immunohistochemistry, and simple copy number profile. The second major cluster was composed of corticotrophs and Pit1 lineage PitNETs, which could be further classified using DNA methylation into distinct subclusters that corresponded to clinically functioning and silent tumors and are consistent with transcription factor expression. Analysis of promoter methylation patterns correlated with lineage for corticotrophs and Pit1 lineage subtypes. However, the gonadotrophic genes did not show a distinct promoter methylation pattern in gonadotroph tumors compared to other lineages. Promoter of the NR5A1 gene, which encodes SF1, was hypermethylated across all PitNETs clinical and molecular subtypes including gonadotrophs with strong SF1 protein expression indicating alternative epigenetic regulation. CONCLUSION/CONCLUSIONS:Our findings suggest that classification of PitNETs may benefit from DNA methylation for clinicopathological stratification.

BACKGROUND:Meningiomas are the most common primary intracranial neoplasms, with highly variable patient outcomes. While most meningiomas are benign, a significant subset recurs postoperatively, presenting substantial treatment challenges. BAP1 gene inactivation has been suggested as a marker for aggressive meningiomas, although its precise molecular and clinical roles remain poorly understood. METHODS:To comprehensively investigate BAP1-altered meningiomas, we used six meningiomas with known BAP1 alterations as a discovery set. Genome-wide DNA methylation profiling of these samples, along 11,151 reference meningiomas, identified a distinct molecular cluster (n = 42) using unsupervised visualization approaches. These tumors were further characterized by DNA/RNA sequencing, histopathological examination, and a retrospective review of clinical data, compared to reference meningioma cohorts, providing a thorough characterization of this rare tumor subtype. RESULTS:Our integrative analysis revealed BAP1-altered meningiomas as a distinct CNS tumor subtype, characterized by recurrent loss of chromosome 3p21 and driven by various BAP1-inactivating alterations. Although rhabdoid morphology is present in some cases, it is not exclusive and should not be used as a grading criterion. Progression-free survival analysis showed a median of 21 months (95% CI: 12-NA), with a 2-year overall survival rate of 79% (95% CI: 60%-100%), highlighting the aggressive nature of these tumors. Gene expression profiling revealed upregulation of PRC target genes, dysregulated Polycomb signaling, and elevated expression in several cellular and growth factor pathways. CONCLUSIONS:BAP1-altered meningiomas represent a distinct and aggressive CNS tumor subtype associated with PRC dysregulation and recurrent 3p chromosome loss. These findings support the designation "meningioma, BAP1-altered."

Somatic-type malignancies (SMs) arising in germ cell tumors (GCTs) are aggressive neoplasms resistant to systemic treatment. Most are diagnosed in metastatic sites after chemotherapy; however, they have also been well-documented in primary testicular GCTs. Historically, SMs were thought to originate in components of teratoma that acquire molecular alterations equivalent to those that characterize their true somatic counterparts. However, recent studies have shown that SMs typically lack the hallmark molecular alterations seen in similar somatic tumors. Additionally, clinicopathologic and molecular data suggest that a subset may derive from yolk sac tumor (YST) rather than teratoma. In this study, we evaluated the relationship between conventional histological types of GCTs and SMs by comparing expression of microRNA (miR)-371-373 and genomic methylation profiles. A total of 96 samples (including multiple paired conventional GCT-SM samples from individual tumors) were assessed for miR-371-373 expression by RT-qPCR and genomic DNA methylation using a clinically validated assay. Expression of miR-371-373 was higher in conventional GCTs than in SMs (considered as a single category encompassing all histological subtypes). However, miR-371-373 expression was heterogeneous among SMs, with significantly higher levels in sarcomatoid YST (SYST) and glandular neoplasms than in other SMs. Genomic DNA methylation analysis showed that SMs (considered as a single category) did not form a distinct cluster. Instead, they grouped into multiple clusters that did not show perfect correspondence with histology and often included conventional GCTs. Genome-wide methylation assessment showed a higher abundance of hypermethylated regions in SMs than in conventional GCTs. Analysis of paired conventional GCT and 'somatic-type' components that did not meet size criteria for SMs dissected from individual tumors demonstrated separation according to histology, suggesting that epigenetic processes play a role in the transition from conventional GCT to 'somatic-type' phenotypes. Gene-level and pathway-level analyses identified MAPK/RAS signaling, mitosis/proliferation, differentiation towards neural tissue/neuroectoderm, epithelial-to-mesenchymal transition, and DNA repair as key differentially regulated processes in components with somatic-type histology, suggesting mechanisms of progression from conventional to 'somatic' phenotypes in GCT. These results support the hypothesis that a subset of SMs derive from YST and suggest that some subtypes (such as SYST) may represent 'intermediate' phenotypes. Additionally, analysis of differentially methylated promoter regions in SM identified genes and biologic processess that may underlie 'somatic tranformation' in GCTs. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Gliomas are the most common primary brain tumors and a major source of mortality and morbidity in adults and children. Recent genomic studies have identified multiple molecular subtypes; however metabolic characterization of these tumors has thus far been limited. We performed metabolic profiling of 114 adult and pediatric primary gliomas and integrated metabolomic data with transcriptomics and DNA methylation classes. We identified that pediatric tumors have higher levels of glucose and reduced lactate compared to adult tumors regardless of underlying genetics or grade, suggesting differences in availability of glucose and/or utilization of glucose for downstream pathways. Differences in glucose utilization in pediatric gliomas may be facilitated through overexpression of SLC2A4, which encodes the insulin-stimulated glucose transporter GLUT4. Transcriptomic comparison of adult and pediatric tumors suggests that adult tumors may have limited access to glucose and experience more hypoxia, which is supported by enrichment of lactate, 2-hydroxyglutarate (2-HG), even in isocitrate dehydrogenase (IDH) wild-type tumors, and 3-hydroxybutyrate, a ketone body that is produced by oxidation of fatty acids and ketogenic amino acids during periods of glucose scarcity. Our data support adult tumors relying more on fatty acid oxidation, as they have an abundance of acyl carnitines compared to pediatric tumors and have significant enrichment of transcripts needed for oxidative phosphorylation. Our findings suggest striking differences exist in the metabolism of pediatric and adult gliomas, which can provide new insight into metabolic vulnerabilities for therapy.

IMPORTANCE/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED:Routine advanced multidimensional molecular profiling is now required to provide optimal standard of care for patients with CNS tumors.

BACKGROUND:The diagnosis and treatment of tumors often depend on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. METHODS:Here, we introduce Ultra-Rapid droplet digital PCR (UR-ddPCR), a technology that achieves the fastest measurement, to date, of mutation burdens in tissue samples, from tissue to result in 15 min. Our workflow substantially reduces the time from tissue biopsy to molecular diagnosis and provides a highly accurate means of quantifying residual tumor infiltration at surgical margins. FINDINGS/RESULTS: = 0.995). CONCLUSIONS:The technology and workflow developed here enable intraoperative molecular-genetic assays with unprecedented speed and sensitivity. We anticipate that our method will facilitate novel point-of-care diagnostics and molecularly guided surgeries that improve clinical outcomes. FUNDING/BACKGROUND:This study was funded by the National Institutes of Health and NYU Grossman School of Medicine institutional funds. Reagents and instruments were provided in kind by Bio-Rad.

IDH-mutant astrocytomas are diffuse gliomas that are defined by characteristic mutations in IDH1 or IDH2 and do not have complete 1p/19q co-deletion. The established grading criteria include histological features of brisk mitotic activity (grade 3) and necrosis and/or microvascular proliferation (grade 4). In addition, homozygous deletion of the CDKN2A/B locus has recently been implemented as a molecular marker for grade 4 IDH-mutant astrocytomas. Here, we describe a subgroup of high-grade IDH-mutant astrocytomas characterised by a primitive neuronal component based on histology and a distinct DNA methylation profile (n = 51, ASTRO PNC). Misinterpretation as carcinoma metastasis was common, since GFAP expression was absent in the primitive neuronal component, whereas TTF-1 expression was detected in 15/19 cases (79%) based on immunohistochemistry. Apart from mutations in IDH1, TP53, and ATRX, we observed enrichment for alterations in RB1 (n = 19/51, 37%) and MYCN (n = 14/51, 27%). Homozygous CDKN2A/B deletion (n = 1/51, 2%) and CDK4 amplification (n = 3/51, 6%) were relatively rare events. Clinical (n = 31 patients) and survival data (n = 23 patients) indicate a clinical behaviour similar to other CNS WHO grade 4 IDH-mutant astrocytomas, however with an increased risk for leptomeningeal (n = 7) and extra-axial (n = 2) spread. Taken together, ASTRO PNC is defined by a distinct molecular and histological appearance that can mimic metastatic disease and typically follows an aggressive clinical course.

Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the most common causes of cancer death in the United States. Brain metastases are often the first clinical presentation of CUP; despite extensive pathological and imaging studies, 20%-45% of CUP are never assigned a primary site. DNA methylation array profiling is a reliable method for tumor classification but tumor-type-specific classifier development requires many reference samples. This is difficult to accomplish for CUP as many cases are never assigned a specific diagnosis. Recent studies identified subsets of methylation quantitative trait loci (mQTLs) unique to specific organs, which could help increase classifier accuracy while requiring fewer samples. We performed a retrospective genome-wide methylation analysis of 759 carcinoma samples from formalin-fixed paraffin-embedded tissue samples using Illumina EPIC array. Utilizing mQTL specific for breast, lung, ovarian/gynecologic, colon, kidney, or testis (BLOCKT) (185k total probes), we developed a deep learning-based methylation classifier that achieved 93.12% average accuracy and 93.04% average F1-score across a 10-fold validation for BLOCKT organs. Our findings indicate that our organ-based DNA methylation classifier can assist pathologists in identifying the site of origin, providing oncologists insight on a diagnosis to administer appropriate therapy, improving patient outcomes.