Faculty Bibliography

BACKGROUND:Survival for patients with high-risk neuroblastoma (HRNB) remains poor despite aggressive multimodal therapies. AIMS/OBJECTIVE:To study the feasibility and safety of incorporating a genomic-based targeted agent to induction therapy for HRNB as well as the feasibility and safety of adding difluoromethylornithine (DFMO) to anti-GD2 immunotherapy. METHODS:twice daily) was added to maintenance with dinutuximab and isotretinoin, followed by continuation of DFMO alone for 2 years. DNA methylation analysis was performed retrospectively and compared to RNA expression. RESULTS:Of the 20 subjects enrolled, 19 started targeted therapy during cycle 3 and 1 started during cycle 5. Eighty-five percent of subjects met feasibility criteria (receiving 75% of targeted agent doses). Addition of targeted agents did not result in toxicities requiring dose reduction of chemotherapy or permanent discontinuation of targeted agent. Following standard consolidation, 15 subjects continued onto immunotherapy with DFMO. This combination was well-tolerated and resulted in no unexpected adverse events related to DFMO. CONCLUSION/CONCLUSIONS:This study demonstrates the safety and feasibility of adding targeted agents to standard induction therapy and adding DFMO to immunotherapy for HRNB. This treatment regimen has been expanded to a Phase II trial to evaluate efficacy.

Sudden unexplained death in childhood (SUDC) is death of a child over 1 year of age that is unexplained after review of clinical history, circumstances of death, and complete autopsy with ancillary testing. Multiple etiologies may cause SUDC. SUDC and sudden unexpected death in epilepsy (SUDEP) share clinical and pathological features, suggesting some similarities in mechanism of death and possible abnormalities in hippocampus and cortex. To identify molecular signaling pathways, we performed label-free quantitative mass spectrometry on microdissected frontal cortex, hippocampal dentate gyrus (DG), and cornu ammonis (CA1-3) in SUDC (n = 19) and pediatric control cases (n = 19) with an explained cause of death. At a 5% false discovery rate (FDR), we found differential expression of 660 proteins in frontal cortex, 170 in DG, and 57 in CA1-3. Pathway analysis of altered proteins identified top signaling pathways associated with activated oxidative phosphorylation (p = 6.3 × 10^-15, z = 4.08) and inhibited EIF2 signaling (p = 2.0 × 10^-21, z = - 2.56) in frontal cortex, and activated acute phase response in DG (p = 8.5 × 10^-6, z = 2.65) and CA1-3 (p = 4.7 × 10^-6, z = 2.00). Weighted gene correlation network analysis (WGCNA) of clinical history indicated that SUDC-positive post-mortem virology (n = 4/17) had the most significant module in each brain region, with the top most significant associated with decreased mRNA metabolic processes (p = 2.8 × 10^-5) in frontal cortex. Additional modules were associated with clinical history, including fever within 24 h of death (top: increased mitochondrial fission in DG, p = 1.8 × 10^-3) and febrile seizure history (top: decreased small molecule metabolic processes in frontal cortex, p = 8.8 × 10^-5) in all brain regions, neuropathological hippocampal findings in the DG (top: decreased focal adhesion, p = 1.9 × 10^-3). Overall, cortical and hippocampal protein changes were present in SUDC cases and some correlated with clinical features. Our studies support that proteomic studies of SUDC cohorts can advance our understanding of the pathogenesis of these tragedies and may inform the development of preventive strategies.

PURPOSE/OBJECTIVE:-truncating mutations. Conversely, the molecular underpinnings of the rare juvenile granulosa cell tumor (JGCT) have not been well elucidated. To this end, we applied a tumor-only integrated approach to investigate the genomic, transcriptomic, and epigenomic landscape of 31 JGCTs to identify putative oncogenic drivers. EXPERIMENTAL DESIGN/METHODS:Multipronged analyses of 31 JGCTs were performed utilizing a clinically validated next-generation sequencing (NGS)-panel targeting 580 cancer-related genes for genomic interrogation, in addition to targeted RNA NGS for transcriptomic exploration. Genome-wide DNA methylation profiling was conducted using an Infinium Methylation EPIC array targeting 866,562 CpG methylation sites. RESULTS:non-rearranged JGCTs under direct promoter control. Genome-wide DNA methylation rendered a clear delineation between AGCTs and JGCTs at the epigenomic level further supporting its diagnostic utility in distinguishing among these tumors. CONCLUSIONS:rearrangements in a subset of tumors. Our findings further offer insights into possible targeted therapies in a rare entity.

Uterine perivascular epithelioid cell tumor (PEComa) is a rare mesenchymal neoplasm that occasionally shares morphologic and immunohistochemical overlap with low- and high-grade endometrial stromal sarcoma (LGESS and HGESS). In this study, we sought to characterize the clinical, morphologic, genetic, and epigenetic features of five uterine sarcomas that display histologic features of LGESS, HGESS, and PEComa. All tumors demonstrated epithelioid cells often associated with a low-grade spindled component resembling LGESS, with both regions expressing CD10, ER, PR, variable HMB45, and Melan-A immunoreactivity, and strong cathepsin K and pS6 expression. Targeted massively parallel sequencing analysis revealed the presence of somatic TSC2 mutations in all five cases, of which four harbored concurrent or consecutive JAZF1-SUZ12 gene fusions. Unsupervised hierarchical clustering analysis of methylation profiles of TSC2-mutant uterine sarcomas (n = 4), LGESS (n = 10), and HGESS (n = 12) demonstrated two clusters consisting of (1) all LGESS and TSC2-mutant uterine sarcomas and (2) all HGESS. KEGG pathway analysis detected methylation differences in genes involved in PI3K/AKT, calcium, and Rap1 signaling. TSC2-mutant uterine sarcomas were responsive to hormone suppression, and mTOR inhibition demonstrated clinical benefit in four patients with these neoplasms. Our results suggest that these tumors represent histologically distinctive LGESS with TSC2 mutations. TSC2 mutations and JAZF1-SUZ12 fusion may help diagnose these tumors and possibly direct effective treatment.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. Here, we utilize two distinct and complementary machine learning methods of analyzing whole slide images (WSI) for predicting mutated BRAF. In the first method, WSI of melanomas from 256 patients were used to train a deep convolutional neural network (CNN) in order to develop a fully automated model that first selects for tumor-rich areas (Area Under the Curve AUC=0.96) then predicts for mutated BRAF (AUC=0.71). Saliency mapping was performed and revealed that pixels corresponding to nuclei were the most relevant to network learning. In the second method, WSI were analyzed using a pathomics pipeline that first annotates nuclei and then quantifies nuclear features, demonstrating that mutated BRAF nuclei were significantly larger and rounder nuclei compared to BRAF WT nuclei. Lastly, we developed a model that combines clinical information, deep learning, and pathomics that improves the predictive performance for mutated BRAF to AUC=0.89. Not only does this provide additional insights on how BRAF mutations affect tumor structural characteristics, machine learning-based analysis of WSI has the potential to be integrated into higher order models for understanding tumor biology.

AIMS/OBJECTIVE:Hippocampal findings are implicated in the pathogenesis of sudden unexplained death in childhood (SUDC), although some studies have identified similar findings in sudden explained death in childhood (SEDC) cases. We blindly reviewed hippocampal histology in SUDC and SEDC controls. METHODS:Hippocampal H&E slides (n=67; 36 SUDC, 31 controls) from clinical and forensic collaborators were evaluated by 9 blinded reviewers: 3 board-certified forensic pathologists, 3 neuropathologists, and 3 dual-certified neuropathologist/forensic pathologists. RESULTS:Among nine reviewers, about 50% of hippocampal sections were rated as abnormal (SUDC 52.5%, controls 53.0%), with no difference by cause of death (COD) (p=0.16) or febrile seizure history (p=0.90). There was little agreement among nine reviewers on whether a slide was within normal range (Fleiss' kappa=0.014, p=0.47). Within reviewer groups, there were no findings more frequent in SUDC compared to controls, with variability in pyramidal neuron and dentate gyrus findings. Across reviewer groups, there was concordance for bilamination and granule cell loss. Neither SUDC (51.2%) nor control (55.9%) slides were considered contributory to determining COD (p=0.41). CONCLUSIONS:The lack of an association of hippocampal findings in SUDC and controls, as well as inconsistency of observations by multiple blinded reviewers, indicates discrepancy with previous studies and an inability to reliably identify hippocampal malformation associated with sudden death (HMASD). These findings underscore a need for larger studies to standardize evaluation of hippocampal findings, identify the range of normal variation and, changes unrelated to SUDC or febrile seizures. Molecular studies may help identify novel immunohistological markers that inform on COD.

BACKGROUND: DNA methylation profiling has emerged as a useful tool for robust classification of rare CNS tumors with a broad morphological spectrum. Routine diagnostic molecular profiling performed in Heidelberg and at international collaborating centers revealed a small but recurring number of CNS tumors with fusions of the PATZ1 gene coupled to either MN1 or EWSR1, displaying a distinct genome-wide methylation profile; indicating that these tumors could form a seperate biological entity. MATERIAL AND METHODS: We obtained genome-wide DNA-methylation array profiling of 68 primary CNS tumors. RNA-sequencing was perfomed on (n=23/68, 34%) of the tumor samples, including (n=6) from fresh frozen tissue used for gene expression profiling. For n=3 cases, whole exome sequencing (WES) data was generated, and gene panel sequencing data was available for n=13 cases, We systematically reevaluated the histopahthological features of 14 tumors, while immunohistochemical (IHC) staining with Ki-67, GFAP, MAP2, NeuN, Olig-2, Synaptophysin, S-100 and Vimentin was performed for (n=12) tumors. We finally collected clinical data to preliminarily characterize this novel tumor entity.
RESULT(S): A selected analysis of the tumors in this novel cohort (n=68), compared with a reference cohort consisting of 15 other low-and high-grade glial and glioneuronal tumor classes, confirmed a clearly distinct grouping. No similarity was seen with the MN1:BEND2 and MN1:CXXC5-fused CNS-tumors. Analysis of Copy number profiles derived from the DNA-methylation data showed a mostly quite genome, with (n=64/65, 98%) of tumors showing copy number variations on Chromosome 22. RNA-sequencing detected PATZ1 fusions in all tumors sequenced (n=12; MN1:PATZ1, n=11; EWSR1:PATZ1). IGF2, PAX2 and GATA2, all genes involved in brain stem cell biology, were upregulated compared to a combined reference cohort of other glioma subtypes. DNA-sequencing showed no relevant alterations at the level of point mutations or small insertions/ deletions. The tumors in our cohort showed polyphenotypic histologies along the glial spectrum, with a subset of tumors being diagnosed as Gliobastoma, WHO Grade 4 and bi-and multiphasic differentaion patterns being evident. IHC performed on tissue available did not favor a particular lineage, with most tumors showing immunopositivity to GFAP. Reverse translation of the gene expression data showed a potential role for NG2 as immunostaining marker. The median age was 11.0 years (0-80), (MN1:PATZ1 manifested at a younger age (median = 4 years) vs EWSR1:PATZ1 (median = 14 years)). Median PFS was 12 months.
CONCLUSION(S): We describe here a novel, molecularly distinct CNS tumor class with strikingly variable histopathologic morphology. We postulate that the PATZ1 fusions are a key driver of tumor initiation. Preliminary indications suggest an intermediate prognosis

DNA methylation profiling has emerged as a convincing tool to classify tumors of the central nervous system. However, for ependymomas of the lower spinal cord, neither histology nor DNA methylation can currently reliably predict progressionfree survival (PFS). To establish a clinically relevant classification, we analyzed 185 tumors classified as myxopapillary ependymoma (MPE) based on DNA methylation. Histology, global DNA methylation, copy number alterations, and global gene expression were correlated with clinical parameters and PFS. Patients with molecularly defined MPE ranged from 5-81 years of age, 58% being male. 55% of the tumors were initially diagnosed as myxopapillary ependymoma (WHO grade I), 34% as ependymoma (WHO grade II), 4% as anaplastic ependymoma (WHO grade III), and 7% with other diagnoses. 97% of the tumors with available material (n = 89) immunohistochemically expressed HOXB13, a feature that was not detected in tumors assigned to the methylation groups of spinal subependymomas (n = 4), ependymomas (n = 15), or NMYC-amplified ependymoma (n = 5). Based on DNA methylation, copy number alterations, and global gene expression, our series comprised two subgroups: MPE-A occurred in younger patients and were significantly enriched with tumors demonstrating papillary morphology and MGMT promoter methylation. These tumors occurred at lower parts of the spinal cord, could not be totally resected in many patients, and frequently relapsed. On the other hand, MPE-B included a significantly higher number of tumors with an initial diagnosis of ependymoma (WHO grade II) and tanycytic morphology. Patients within this subgroup had a significantly better outcome with a 5-year PFS of more than 90%

PURPOSE:), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma. METHODS:DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases. RESULTS:= .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively). CONCLUSION:Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction.