TGF-β Determines the Pro-migratory Potential of bFGF Signaling in Medulloblastoma

The microenvironment shapes cell behavior and determines metastatic outcomes of tumors. We addressed how microenvironmental cues control tumor cell invasion in pediatric medulloblastoma (MB). We show that bFGF promotes MB tumor cell invasion through FGF receptor (FGFR) in vitro and that blockade of FGFR represses brain tissue infiltration in vivo. TGF-β regulates pro-migratory bFGF function in a context-dependent manner. Under low bFGF, the non-canonical TGF-β pathway causes ROCK activation and cortical translocation of ERK1/2, which antagonizes FGFR signaling by inactivating FGFR substrate 2 (FRS2), and promotes a contractile, non-motile phenotype. Under high bFGF, negative-feedback regulation of FRS2 by bFGF-induced ERK1/2 causes repression of the FGFR pathway. Under these conditions, TGF-β counters inactivation of FRS2 and restores pro-migratory signaling. These findings pinpoint coincidence detection of bFGF and TGF-β signaling by FRS2 as a mechanism that controls tumor cell invasion. Thus, targeting FRS2 represents an emerging strategy to abrogate aberrant FGFR signaling

Locoregional delivery of CAR T cells to the cerebrospinal fluid for treatment of metastatic medulloblastoma and ependymoma

Recurrent medulloblastoma and ependymoma are universally lethal, with no approved targeted therapies and few candidates presently under clinical evaluation. Nearly all recurrent medulloblastomas and posterior fossa group A (PFA) ependymomas are located adjacent to and bathed by the cerebrospinal fluid, presenting an opportunity for locoregional therapy, bypassing the blood-brain barrier. We identify three cell-surface targets, EPHA2, HER2 and interleukin 13 receptor α2, expressed on medulloblastomas and ependymomas, but not expressed in the normal developing brain. We validate intrathecal delivery of EPHA2, HER2 and interleukin 13 receptor α2 chimeric antigen receptor T cells as an effective treatment for primary, metastatic and recurrent group 3 medulloblastoma and PFA ependymoma xenografts in mouse models. Finally, we demonstrate that administration of these chimeric antigen receptor T cells into the cerebrospinal fluid, alone or in combination with azacytidine, is a highly effective therapy for multiple metastatic mouse models of group 3 medulloblastoma and PFA ependymoma, thereby providing a rationale for clinical trials of these approaches in humans

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

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