Faculty Bibliography

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.

BACKGROUND:Intracerebral schwannomas are rare tumors resembling their peripheral nerve sheath counterparts but localized in the CNS. They are not classified as a separate tumor type in the 2021 WHO classification. This study aimed to compile and characterize these rare neoplasms morphologically and molecularly. METHODS:We analyzed 20 tumor samples by histology, RNA Next-Generation Sequencing, DNA-methylation profiling, copy number analyses, and single nucleus RNA sequencing (snRNA-seq). Clinical data, including age, sex, and disease progression, were collected. MRI series were included when available. RESULTS:All cases with tissue available for histology review (n=13) were morphologically consistent with intracerebral schwannoma, but differed in their extent of GFAP staining. All (n=20) shared DNA-methylation profiles distinct from other CNS tumors, as well as from VGLL-altered peripheral nerve sheath tumors. Most cases (n=14/17) harbored fusions of either VGLL3 or VGLL1 (CHD7::VGLL3 (n=9/17) and EWSR1::VGLL1 (n=5/17)). In two cases the presence of a VGLL3 fusion was also confirmed by CNA analyses (n=2/17). MRI (n=4) showed well-defined, nodular tumors with strong, homogeneous enhancement and no diffusion restriction. Tumors were located throughout the neuroaxis [supratentorial (n=15), infratentorial (n=4), and spinal (n=1)]. snRNA-seq of a VGLL1-fused tumor indicated VGLL1 upregulation in 28.6% of tumor cells (n=1). During median follow-up of 1.8 years (range 3 months-9 years), none of the tumors recurred (n=10). CONCLUSIONS:We identify and define a new benign tumor class, designated VGLL-altered intraparenchymal CNS schwannomas. These tumors feature VGLL alterations and a specific DNA-methylation profile, with schwannoma-like histopathology and CNS localization, akin to previously classified intracerebral schwannomas.

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:Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. METHODS:We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS neoplastic/non-neoplastic lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. RESULTS:In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 77.77%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. CONCLUSIONS:RapidLymphoma proves reliable and valid for intraoperative PCNSL detection and differentiation from other CNS entities. It provides visual feedback within three minutes, enabling fast clinical decision-making and subsequent treatment strategy planning.

AIMS/OBJECTIVE:We investigated key signalling pathways' activity and mutational status of early-stage breast carcinomas with low and intermediate 21-gene recurrence score (RS) to identify molecular features that may predict recurrence. METHODS:This is a retrospective case-control study of 18 patients with recurrent breast carcinoma with low and intermediate 21-gene RS (<25) and control group of 15 non-recurrent breast cancer patients. DNA and mRNA were extracted from tumour tissue. mRNA expression of genes involved in oestrogen receptor (ER), androgen receptor (AR), PI3K and MAPK signalling pathways was measured by real-time quantitative reverse transcription-qPCR (OncoSIGNal G4 test, InnoSIGN). Tumour mutational landscape was assessed by targeted DNA sequencing (Oncomine Precision Assay). RESULTS:mutations, may play a role in the recurrence of early-stage breast cancer with low and intermediate 21-gene RS. Pathway analysis can help to identify high-risk patients in this setting.

Accurate intraoperative diagnosis is crucial for differentiating between primary CNS lymphoma (PCNSL) and other CNS entities, guiding surgical decision-making, but represents significant challenges due to overlapping histomorphological features, time constraints, and differing treatment strategies. We combined stimulated Raman histology (SRH) with deep learning to address this challenge. We imaged unprocessed, label-free tissue samples intraoperatively using a portable Raman scattering microscope, generating virtual H&E-like images within less than three minutes. We developed a deep learning pipeline called RapidLymphoma based on a self-supervised learning strategy to (1) detect PCNSL, (2) differentiate from other CNS entities, and (3) test the diagnostic performance in a prospective international multicenter cohort and two additional independent test cohorts. We trained on 54,000 SRH patch images sourced from surgical resections and stereotactic-guided biopsies, including various CNS tumor/non-tumor lesions. Training and test data were collected from four tertiary international medical centers. The final histopathological diagnosis served as ground-truth. In the prospective test cohort of PCNSL and non-PCNSL entities (n=160), RapidLymphoma achieved an overall balanced accuracy of 97.81% ±0.91, non-inferior to frozen section analysis in detecting PCNSL (100% vs. 78.94%). The additional test cohorts (n=420, n=59) reached balanced accuracy rates of 95.44% ±0.74 and 95.57% ±2.47 in differentiating IDH-wildtype diffuse gliomas and various brain metastasis from PCNSL. Visual heatmaps revealed RapidLymphoma's capabilities to detect class-specific histomorphological key features. RapidLymphoma is valid and reliable in detecting PCNSL and differentiating from other CNS entities within three minutes, as well as visual feedback in an intraoperative setting. This leads to fast clinical decision-making and further treatment strategy planning.

Tumors of the major and minor salivary glands histologically encompass a diverse and partly overlapping spectrum of frequent diagnostically challenging neoplasms. Despite recent advances in molecular testing and the identification of tumor-specific mutations or gene fusions, there is an unmet need to identify additional diagnostic biomarkers for entities lacking specific alterations. In this study, we collected a comprehensive cohort of 363 cases encompassing 20 different salivary gland tumor entities and explored the potential of DNA methylation to classify these tumors. We were able to show that most entities show specific epigenetic signatures and present a machine learning algorithm that achieved a mean balanced accuracy of 0.991. Of note, we showed that cribriform adenocarcinoma is epigenetically distinct from classical polymorphous adenocarcinoma, which could support risk stratification of these tumors. Myoepithelioma and pleomorphic adenoma form a uniform epigenetic class, supporting the theory of a single entity with a broad but continuous morphologic spectrum. Furthermore, we identified a histomorphologically heterogeneous but epigenetically distinct class that could represent a novel tumor entity. In conclusion, our study provides a comprehensive resource of the DNA methylation landscape of salivary gland tumors. Our data provide novel insight into disputed entities and show the potential of DNA methylation to identify new tumor classes. Furthermore, in future, our machine learning classifier could support the histopathologic diagnosis of salivary gland tumors.

Sudden unexplained death in childhood (SUDC) is death of a child ≥ 12 months old that is unexplained after autopsy and detailed analyses. Among SUDC cases, ~ 30% have febrile seizure (FS) history, versus 2-5% in the general population. SUDC cases share features with sudden unexpected death in epilepsy (SUDEP) and sudden infant death syndrome (SIDS), in which brainstem autonomic dysfunction is implicated. To understand whether brainstem protein changes are associated with FS history in SUDC, we performed label-free quantitative mass spectrometry on microdissected midbrain dorsal raphe, medullary raphe, and the ventrolateral medulla (n = 8 SUDC-noFS, n = 11 SUDC-FS). Differential expression analysis between SUDC-FS and SUDC-noFS at p < 0.05 identified 178 altered proteins in dorsal raphe, 344 in medullary raphe, and 100 in the ventrolateral medulla. These proteins were most significantly associated with increased eukaryotic translation initiation (p = 3.09 × 10^-7, z = 1.00), eukaryotic translation elongation (p = 6.31 × 10^-49, z = 6.01), and coagulation system (p = 1.32 × 10^-5, z = 1.00). The medullary raphe had the strongest enrichment for altered signaling pathways, including with comparisons to three other brain regions previously analyzed (frontal cortex, hippocampal dentate gyrus, cornu ammonus). Immunofluorescent tissue analysis of serotonin receptors identified 2.1-fold increased 5HT2A in the medullary raphe of SUDC-FS (p = 0.025). Weighted gene correlation network analysis (WGCNA) of case history indicated that longer FS history duration significantly correlated with protein levels in the medullary raphe and ventrolateral medulla; the most significant gene ontology biological processes were decreased cellular respiration (p = 9.8 × 10^-5, corr = - 0.80) in medullary raphe and decreased synaptic vesicle cycle (p = 1.60 × 10^-7, corr = - 0.90) in the ventrolateral medulla. Overall, FS in SUDC was associated with more protein differences in the medullary raphe and was related with increased translation-related signaling pathways. Future studies should assess whether these changes result from FS or may in some way predispose to FS or SUDC.

Diffuse midline gliomas are among the deadliest human cancers and have had little progress in treatment in the last 50 years. Cell cultures of these tumors have been developed recently, but the degree to which such cultures retain the characteristics of the source tumors is unknown. DNA methylation profiling offers a powerful tool to look at genome-wide epigenetic changes that are biologically meaningful and can help assess the similarity of cultured tumor cells to their in vivo progenitors. Paraffinized diagnostic tissue from three diffuse intrinsic pontine gliomas with H3 K27M mutations was compared with subsequent passages of neurosphere cell cultures from those tumors. Each cell line was passaged 3-4 times and analyzed with DNA methylation arrays and standard algorithms that provided a comparison of diagnostic classification and cluster analysis. All samples tested maintained high classifier scores and clustered within the reference group of H3 K27M-mutant diffuse midline gliomas. There was a gain of 1q in all cell lines, with two cell lines initially manifesting the gain of 1q only during culture. In vitro cell cultures of H3 K27M-mutant gliomas maintain high degrees of similarity in DNA methylation profiles to their source tumor, confirming their fidelity even with some chromosomal changes.

BACKGROUND AND OBJECTIVES/OBJECTIVE:The management of World Health Organization (WHO) grade 2 meningiomas is complicated by their diverse clinical behaviors. Stereotactic radiosurgery (SRS) can be an effective management option. Literature on SRS dose selection is limited but suggests that a higher dose is better for tumor control. We characterize the predictors of post-SRS outcomes that can help guide planning and management. METHODS:We reviewed a cohort of consecutive patients with pathologically-proven WHO grade 2 meningiomas who underwent SRS at a single institution between 2011 and 2023. RESULTS:Ninety-nine patients (median age 62 years) underwent SRS, 11 of whom received hypofractionated SRS in 5 fractions. Twenty-two patients had received previous irradiation. The median follow-up was 49 months. The median overall survival was 119 months (95% CI 92-NA) with estimated 5- and 10-year survival of 83% and 27%, respectively. The median progression-free survival (PFS) was 40 months (95% CI 32-62), with 3- and 5-year rates at 54% and 35%, respectively. The median locomarginal PFS was 63 months (95% CI 51.8-NA) with 3- and 5-year rates at 65% and 52%. Nine (9%) patients experienced adverse events, 2 Common Terminology Criteria for Adverse Events grade 3 and 7 grade 2, consisting of worsening neurologic deficit from edema. In the single-session cohort, Ki-67 significantly predicted both overall survival and intracranial PFS. Tumors with Ki-67 >10% had 2.17 times the risk of locomarginal progression compared with Ki-67 ≤10% (P = .018) adjusting for covariates. Sex, prescription dose, tumor volume, and location also predicted tumor control. In tumors with Ki-67 >10%, margin dose ≥14 Gy was associated with significantly better tumor control but not for tumors with Ki-67 ≤10%. CONCLUSION/CONCLUSIONS:The management of WHO grade 2 meningiomas requires a multimodality approach. This study demonstrates the value of a targeted SRS approach in patients with limited disease and further establishes predictive biomarkers that can guide planning through a personalized approach.