Faculty Bibliography

PURPOSE: The prognosis for SHH-medulloblastoma (MB) patients with Li-Fraumeni syndrome (LFS) is poor. Due to lack of comprehensive data for these patients, it is challenging to establish effective therapeutic recommendations. We here describe the largest retrospective cohort of pediatric LFS SHH-MB patients to date and their clinical outcomes.
PATIENTS AND METHODS: N=31 patients with LFS SHH-MB were included in this retrospective multicenter study. TP53 variant type, clinical parameters including treatment modalities, event-free survival (EFS) and overall survival (OS), as well as recurrence patterns and incidence of secondary neoplasms, were evaluated.
RESULT(S): All LFS-MBs were classified as SHH subgroup, in 30/31 cases based on DNA methylation analysis. The majority of constitutional TP53 variants (72%) represented missense variants, and all except two truncating variants were located within the DNA-binding domain. 54% were large cell anaplastic, 69% gross totally resected and 81% had M0 status. The 2-(y)ear and 5-(y)ear EFS were 26% and 8,8%, respectively, and 2y- and 5y-OS 40% and 12%. Patients who received post-operative radiotherapy (RT) followed by chemotherapy (CT) showed significantly better outcomes (2y-EFS:43%) compared to patients who received CT before RT (30%) (p<0.05). The 2y-EFS and 2y-OS were similar when treated with protocols including high-dose chemotherapy (EFS:22%, OS:44%) compared to patients treated with maintenance-type chemotherapy (EFS:31%, OS:45%). Recurrence occurred in 73.3% of cases independent of resection or M-status, typically within the radiation field (75% of RT-treated patients). Secondary malignancies developed in 12.5% and were cause of death in all affected patients.
CONCLUSION(S): Patients with LFS-MBs have a dismal prognosis. This retrospective study suggests that upfront RT may increase EFS, while intensive therapeutic approaches including high-dose chemotherapy did not translate into increased survival of this patient group. To improve outcomes of LFS-MB patients, prospective collection of clinical data and development of treatment guidelines are required

Myxopapillary ependymoma (MPE) is a heterogeneous disease regarding histopathology and outcome. The underlying molecular biology is poorly understood, and markers that reliably predict the patients' clinical course are unknown. We assembled a cohort of 185 tumors classified as MPE based on DNA methylation from pediatric, adolescent, and adult patients. Methylation patterns, copy number profiles, and MGMT promoter methylation were analyzed for all tumors, 106 tumors were evaluated histomorphologically, and RNA sequencing was performed for 37 cases. Based on methylation profiling, we defined two subtypes MPE-A and MPEB, and explored associations with epidemiological, clinical, pathological, and molecular characteristics of these tumors. Tumors in the methylation class MPE were histologically diagnosed as WHO grade I (59%), WHO grade II (37%), or WHO grade III tumors (4%). 75/77 analyzed tumors expressed HOXB13, which is a diagnostic feature not detected in other spinal ependymal tumors. Based on DNA methylation, our series split into two subtypes. MPE-A occurred in younger patients (median age 27 vs. 45 years, p=7.3e-05). They were enriched with WHO grade I tumors and associated with papillary morphology and MGMT promoter hypermethylation (all p<0.001). MPE-B included most tumors initially diagnosed as WHO grade II and cases with tanycytic morphology. Copy number alterations were more common in MPE-A. RNA sequencing revealed an enrichment for extracellular matrix and immune system-related signatures in MPE-A. 15/30 MPE-A could not be totally resected compared to 1/58 MPE-B (p=6.3e-08), and progressionfree survival was significantly better for MPE-B (p=3.4e-06, 10-year relapse rate 33% vs. 85%). We unraveled the morphological and clinical heterogeneity of MPE by identifying two molecularly distinct subtypes. These subtypes significantly differed in progression-free survival and will likely need different protocols for surveillance and treatment

Ependymomas encompass multiple, clinically relevant tumor types based on localization, genetic alterations, and epigenetic and transcriptomic profiles. Tumors belonging to the methylation class of spinal ependymoma (SP-EPN) represent the most common intramedullary neoplasms in children and adults. However, molecular data of SP-EPN are scarce, and clear treatment recommendations are lacking. The only known recurrent genetic events in SP-EPN are loss of chromosome 22q and NF2 mutations. Yet, it remains unclear whether SP-EPN with germline or sporadic NF2 mutations or with NF2 wild type status differ clinically or molecularly. To provide a comprehensive molecular profile of SP-EPN, we integrated epigenetic, genomic, transcriptomic, and histological analyses of up to 237 cases. Clustering of methylation data revealed two distinct molecular SP-EPN subtypes. The distribution of NF2 mutated cases differed significantly across these subtypes (p <0.0001): The vast majority of tumors harboring either a previously known NF2 germline mutation or a sporadic mutation were assigned to subtypes A, whereas subtype B tumors mainly contained NF2 wild type sequences. In addition, subtype A tumors showed a lower frequency of MGMT promoter methylation (p= 0.018) and contained almost all pediatric patients of the cohort. Whole-exome sequencing (30 cases) identified numerous mutations in NF2 wild type and mutated tumors. Mutated genes in NF2 wild type tumors were enriched for genes associated with cell cycle and cytoskeleton. RNA sequencing revealed two distinct transcriptional groups with upregulation of proliferative genes in one group and upregulation of cilial genes in the other group. The molecular subtypes displayed subtle, but significant differences in the appearance of histopathological characteristics, such as surfaces, inflammation, and hyalinized vessels. Investigation of clinical parameters is ongoing and will complete the picture of SP-EPN heterogeneity as an important basis for future clinical decision-making

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.

Introduction: Pineal region tumors comprise a small percentage of intracranial brain malignancies and glioblastoma (GBM) in this region is extremely rare and poorly defined. Case report: We describe a rare presentation of IDH-wildtype glioblastoma arising from the pineal region in a 49-year-old female, with unusual histological and molecular findings. The patient presented with worsening headaches and diplopia, and her MRI revealed a 3.4cm heterogeneously enhancing solid and cystic pineal gland mass, causing mass effect and hydrocephalus. Results/Discussion: The resection specimen revealed a moderately cellular and highly proliferative tumor consisting of oval-to-spindled cells with astrocytic morphology, variable amounts of eosinophilic cytoplasm and nuclear pleomorphism, embedded in a myxoid matrix with distinct chondroid appearance. Atypical microvascular proliferation and brisk mitotic activity were noted, without palisading necrosis. Immunohistochemically, tumor cells were strongly GFAP positive and negative for IDH1-R132H, P53, H3K27M, and BRAFV600E. MGMT promoter methylation was detected. Next-generation sequencing uncovered CD274 (PD-L1), PDCD1LG2 (PDL2), and JAK2 amplifications; ATM, MUTYH, CDKN2C, PIK3CA mutations; and CDKN2A/B loss. The tumor was IDH and Histone H3 wildtype, and lacked common GBM-associated alterations at loci such as TERT, PTEN, or EGFR. DNA methylation analysis best classified the tumor as glioblastoma, IDH-wildtype (0.72 score), with the subclass midline (GBM-MID, 0.68 score). GBM-MID comprises tumors with the histological diagnosis of glioblastoma and midline structures location. These tumors share epigenetic similarities with the diffuse midline glioma, H3K27M-mutant methylation cluster, but lack the characteristic histone mutation. Overall, pineal region glioblastoma is a rare disease with diagnostic and therapeutic challenges. Unlike most pineal glioblastomas reported to date, this case displayed methylated MGMT status and the patient is progression-free three months after partial resection. The unique molecular alterations discovered in this rare glioblastoma, particularly PD-L1 and PD-L2 gene amplifications, offer future therapeutic considerations in this patient for potential response to immune checkpoint inhibitors

Liquid biopsy offers a noninvasive approach to monitor cancer burden during therapy and surveillance. However, in pediatric brain cancers, liquid biopsy methods from the blood have been unsuccessful due to a low tumor burden and low number of mutations in coding regions. In contrast with targeted panels, whole genome sequencing (WGS)-derived patient specific mutational signature from a matched tumor-normal WGS can provide a personalized, highly specific approach to detect mutations in circulating cell free tumor DNA (ctDNA) and provide blood-based monitoring in pediatric patients with high sensitivity. Furthermore, it can be performed on lower amount of peripheral blood since WGS requires less depth compared to targeted ctDNA panels. We have profiled a diverse cohort of brain tumors including medulloblastomas, ependymomas, low- and high-grade gliomas. Using WGS of matched tumor-normal and plasma samples, we could derive a personalized mutational pattern and used an AI-based error suppression model for quantification and ultra-sensitive detection of ctDNA in plasma samples. A patient-specific personalized genome-wide compendium of somatic mutations could be established across all tumor types and ctDNA tested at the time of diagnosis, during the therapy or surveillance period. An AI-based error suppression model is implemented to filter out the noise in the cell free DNA (cfDNA) while the personalized mutational signature was used to detect the ctDNA in the cfDNA and to amplify the somatic signal contained in it. The ctDNA Tumor Fraction (TF) is compared to the clinical status and MR-based imaging. All subtypes of pediatric brain tumors contain sufficient number of mutations to derive personalized signatures and corelate with the clinical status. Patient-specific WGS tumor signature in ctDNA from blood can be used for sensitive monitoring of children with brain tumors. However, correlation between ctDNA levels and therapeutic response need to be established for various subtypes of brain tumors

Pediatric high-grade gliomas (pHGGs), encompassing hemispheric and diffuse midline gliomas (DMGs), remain a devastating disease. The last decade has revealed oncogenic drivers including single nucleotide variants (SNVs) in histones. However, the contribution of structural variants (SVs) to gliomagenesis has not been systematically explored due to limitations in early SV analysis approaches. Using SV algorithms, we recently created, we analyzed SVs in whole-genome sequences of 179 pHGGs including a novel cohort of treatment naive samples-the largest WGS cohort assembled in adult or pediatric glioma. The most recurrent SVs targeted MYC isoforms and receptor tyrosine kinases, including a novel SV amplifying a MYC enhancer in the lncRNA CCDC26 in 12% of DMGs and revealing a more central role for MYC in these cancers than previously known. Applying de novo SV signature discovery, we identified five signatures including three (SVsig1-3) involving primarily simple SVs, and two (SVsig4-5) involving complex, clustered SVs. These SV signatures associated with genetic variants that differed from what was observed for SV signatures in other cancers, suggesting different links to underlying biology. Tumors with simple SV signatures were TP53 wild-type but were enriched with alterations in TP53 pathway members PPM1D and MDM4. Complex signatures were associated with direct aberrations in TP53, CDKN2A, and RB1 early in tumor evolution, and with extrachromosomal amplicons that likely occurred later. All pHGGs exhibited at least one simple SV signature but complex SV signatures were primarily restricted to subsets of H3.3K27M DMGs and hemispheric pHGGs. Importantly, DMGs with the complex SV signatures SVsig4-5 were associated with shorter overall survival independent of histone type and TP53 status. These data inform the role and impact of SVs in gliomagenesis and mechanisms that shape them

DNA methylation of cytosines in CpG sites throughout the genome is an epigenetic mark contributing to gene expression regulation. DNA methylation patterns are specific to tissue type, conserved throughout life and reflect changes during tumorigenesis. DNA methylation recently emerged as a diagnostic tool to classify tumors based on a combination of preserved developmental and mutation induced signatures. In addition to the tumor classification, DNA methylation data can also be used to evaluate copy number variation, assess promoter methylation status of specific genes, such as MGMT or MLH1, and deconvolute the tumor microenvironment, assessing the tumor immune infiltrate as a potential biomarker for immunotherapy. Here we review the role for DNA methylation in tumor diagnosis.

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.

We present the case of a 41-year-old man who developed worsening mid-thoracic back pain and imaging revealed a well-circumscribed intramedullary tumor in the thoracic spinal cord. Subtotal resection was performed, and histopathological analysis showed a cytologically bland, minimally proliferative glial neoplasm. Sequencing revealed H3 K27M and an activating PTPN11 mutation. Serial imaging revealed slow tumor regrowth over a three year period which prompted a second resection. The recurrent tumor displayed a similar low grade-appearing histology and harbored the same H3 K27M and PTPN11 mutations as the primary. While the prognostic importance of isolated H3 K27M in spinal gliomas is well-known, the combination of these two mutations in spinal low grade glioma has not been previously reported. Importantly, PTPN11 is a component of the MAPK signaling pathway. Thus, as building evidence shows that low grade-appearing gliomas harboring H3 K27M mutations along with BRAF or FGFR1 mutations have a relatively more favorable course compared to isolated H3 K27M-mutant midline gliomas, the present case provides new evidence for the prognostic importance of activating mutations in other components of the MAPK signaling pathway. This case further highlights the importance of clinico-radio-pathologic correlation when incorporating evolving genetic data into the integrated diagnosis of rare neuroepithelial tumors.