Therapeutic Impact of Cytoreductive Surgery and Irradiation of Posterior Fossa Ependymoma in the Molecular Era: A Retrospective Multicohort Analysis

Posterior fossa ependymoma comprises two distinct molecular variants termed EPN_PFA and EPN_PFB that have a distinct biology and natural history. The therapeutic value of cytoreductive surgery and radiation therapy for posterior fossa ependymoma after accounting for molecular subgroup is not known

Cytogenetic Prognostication Within Medulloblastoma Subgroups

PURPOSE: Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. PATIENTS AND METHODS: Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. RESULTS: Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. CONCLUSION: Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials

Genome-Wide CRISPR-Cas9 Screens Expose Genetic Vulnerabilities and Mechanisms of Temozolomide Sensitivity in Glioblastoma Stem Cells

Summary: Glioblastoma therapies have remained elusive due to limitations in understanding mechanisms of growth and survival of the tumorigenic population. Using CRISPR-Cas9 approaches in patient-derived GBM stem cells (GSCs) to interrogate function of the coding genome, we identify actionable pathways responsible for growth, which reveal the gene-essential circuitry of GBM stemness and proliferation. In particular, we characterize members of the SOX transcription factor family, SOCS3, USP8, and DOT1L, and protein ufmylation as important for GSC growth. Additionally, we reveal mechanisms of temozolomide resistance that could lead to combination strategies. By reaching beyond static genome analysis of bulk tumors, with a genome-wide functional approach, we reveal genetic dependencies within a broad range of biological processes to provide increased understanding of GBM growth and treatment resistance. : MacLeod et al. describe genome-wide CRISPR-Cas9 screens identifying genetic vulnerabilities across a panel of patient-derived glioblastoma stem cell cultures. Regulators of stemness (SOX2, SOX9, DOT1L, and SOCS3) and stress response (ufmylation and ERAD pathways) govern the growth of glioblastoma stem cells. Chemogenomic screens using temozolomide identify modulators of sensitivity to chemotherapy. Keywords: glioblastoma, glioblastoma stem cells, CRISPR-Cas9, fitness genes, functional genomic

The transcriptional landscape of Shh medulloblastoma

Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention

Intertumoral Heterogeneity within Medulloblastoma Subgroups

While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials. [Display omitted] •Medulloblastoma comprises 12 subtypes; 2 WNT, 4 SHH, 3 group 3, and 3 group 4 groups•Heterogeneity within subgroups accounts for previously unexplained variation•Groups 3 and 4 medulloblastoma are molecularly distinct entities•Clinically and biologically relevant subtypes exist for each subgroup Cavalli et al. analyze 763 primary medulloblastoma samples using the similarity network fusion approach. They identify subtypes that have distinct somatic copy-number aberrations, activated pathways, and clinical outcomes within each of the four known subgroups and further delineate group 3 from group 4 MB