Cranial radiotherapy improves survival of the most common childhood cancers, including brain tumors and leukemia. Unfortunately, long-term survivors are faced with consequences of secondary neoplasia, including radiation-induced meningiomas (RIMs). We characterized 31 RIMs with exome/NF2 intronic sequencing, RNA sequencing and methylation profiling, and found NF2 gene rearrangements in 12/31 of RIMs, an observation previously unreported in sporadic meningioma (SM). Additionally, known recurrent mutations characteristic of SM, including AKT1, KLF4, TRAF7 and SMO, were not observed in RIMs. Combined losses of chromosomes 1p and 22q were common in RIMs (16/18 cases) and overall, chromosomal aberrations were more complex than that observed in SM. Patterns of DNA methylation profiling supported similar cell of origin between RIMs and SMs. The findings indicate that the mutational landscape of RIMs is distinct from SMs, and have significant therapeutic implications for survivors of childhood cranial radiation and the elucidation of the molecular pathogenesis of meningiomas.Radiation-induced meningiomas are often more aggressive than sporadic ones. In this study, the authors perform an exome, methylation and RNA-seq analysis of 31 cases of radiation-induced meningioma and show NF2 rearrangement, an observation previously unreported in the sporadic tumors.

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.

Both the perivascular niche (PVN) and the integration into multicellular networks by tumor microtubes (TMs) have been associated with progression and resistance to therapies in glioblastoma, but their specific contribution remained unknown. By long-term tracking of tumor cell fate and dynamics in the live mouse brain, differential therapeutic responses in both niches are determined. Both the PVN, a preferential location of long-term quiescent glioma cells, and network integration facilitate resistance against cytotoxic effects of radiotherapy and chemotherapy-independently of each other, but with additive effects. Perivascular glioblastoma cells are particularly able to actively repair damage to tumor regions. Population of the PVN and resistance in it depend on proficient NOTCH1 expression. In turn, NOTCH1 downregulation induces resistant multicellular networks by TM extension. Our findings identify NOTCH1 as a central switch between the PVN and network niche in glioma, and demonstrate robust cross-compensation when only one niche is targeted.

Long-term complications such as radiation-induced second malignancies occur in a subset of patients following radiation-therapy, particularly relevant in pediatric patients due to the long follow-up period in case of survival. Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies such as acute lymphoblastic leukemia (ALL) and medulloblastoma (MB). We perform comprehensive (epi-) genetic and expression profiling of RIGs arising after cranial irradiation for MB (n = 23) and ALL (n = 9). Our study reveals a unifying molecular signature for the majority of RIGs, with recurrent PDGFRA amplification and loss of CDKN2A/B and an absence of somatic hotspot mutations in genes encoding histone 3 variants or IDH1/2, uncovering diagnostic markers and potentially actionable targets.

Capicua (CIC) is a transcriptional repressor that counteracts activation of genes downstream of receptor tyrosine kinase (RTK)/Ras/ERK signaling. It is well-established that tumorigenesis, especially in glioblastoma (GBM), is attributed to hyperactive RTK/Ras/ERK signaling. While CIC is mutated in other tumors, here we show that CIC has a tumor suppressive function in GBM through an alternative mechanism. We find that CIC protein levels are negligible in GBM due to continuous proteasome-mediated degradation, which is mediated by the E3 ligase PJA1 and show that this occurs through binding of CIC to its DNA target and phosphorylation on residue S173. PJA1 knockdown increased CIC stability and extended survival using in-vivo models of GBM. Deletion of the ERK binding site resulted in stabilization of CIC and increased therapeutic efficacy of ERK inhibition in GBM models. Our results provide a rationale to target CIC degradation in Ras/ERK-driven tumors, including GBM, to increase efficacy of ERK inhibitors.

Intrinsic malignant brain tumors, such as glioblastomas are frequently resistant to immune checkpoint blockade (ICB) with few hypermutated glioblastomas showing response. Modeling patient-individual resistance is challenging due to the lack of predictive biomarkers and limited accessibility of tissue for serial biopsies. Here, we investigate resistance mechanisms to anti-PD-1 and anti-CTLA-4 therapy in syngeneic hypermutated experimental gliomas and show a clear dichotomy and acquired immune heterogeneity in ICB-responder and non-responder tumors. We made use of this dichotomy to establish a radiomic signature predicting tumor regression after pseudoprogression induced by ICB therapy based on serial magnetic resonance imaging. We provide evidence that macrophage-driven ICB resistance is established by CD4 T cell suppression and Treg expansion in the tumor microenvironment via the PD-L1/PD-1/CD80 axis. These findings uncover an unexpected heterogeneity of response to ICB in strictly syngeneic tumors and provide a rationale for targeting PD-L1-expressing tumor-associated macrophages to overcome resistance to ICB.

DICER1 syndrome is a tumor predisposition syndrome that is associated with up to 30 different neoplastic lesions, usually affecting children and adolescents. Here we identify a group of mesenchymal tumors which is highly associated with DICER1 syndrome, and molecularly distinct from other DICER1-associated tumors. This group of DICER1-associated mesenchymal tumors encompasses multiple well-established clinicopathological tumor entities and can be further divided into three clinically meaningful classes designated "low-grade mesenchymal tumor with DICER1 alteration" (LGMT DICER1), "sarcoma with DICER1 alteration" (SARC DICER1), and primary intracranial sarcoma with DICER1 alteration (PIS DICER1). Our study not only provides a combined approach to classify DICER1-associated neoplasms for improved clinical management but also suggests a role for global hypomethylation and other recurrent molecular events in sarcomatous differentiation in mesenchymal tumors with DICER1 alteration. Our results will facilitate future investigations into prognostication and therapeutic approaches for affected patients.

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.

Mass spectrometry imaging vows to enable simultaneous spatially resolved investigation of hundreds of metabolites in tissues, but it primarily relies on traditional ion images for non-data-driven metabolite visualization and analysis. The rendering and interpretation of ion images neither considers nonlinearities in the resolving power of mass spectrometers nor does it yet evaluate the statistical significance of differential spatial metabolite abundance. Here, we outline the computational framework moleculaR ( https://github.com/CeMOS-Mannheim/moleculaR ) that is expected to improve signal reliability by data-dependent Gaussian-weighting of ion intensities and that introduces probabilistic molecular mapping of statistically significant nonrandom patterns of relative spatial abundance of metabolites-of-interest in tissue. moleculaR also enables cross-tissue statistical comparisons and collective molecular projections of entire biomolecular ensembles followed by their spatial statistical significance evaluation on a single tissue plane. It thereby fosters the spatially resolved investigation of ion milieus, lipid remodeling pathways, or complex scores like the adenylate energy charge within the same image.

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.

Pediatric high-grade gliomas of the subclass MYCN (HGG-MYCN) are highly aggressive tumors frequently carrying MYCN amplifications, TP53 mutations, or both alterations. Due to their rarity, such tumors have only recently been identified as a distinct entity, and biological as well as clinical characteristics have not been addressed specifically. To gain insights into tumorigenesis and molecular profiles of these tumors, and to ultimately suggest alternative treatment options, we generated a genetically engineered mouse model by breeding hGFAP-cre::Trp53Fl/Fl::lsl-MYCN mice. All mice developed aggressive forebrain tumors early in their lifetime that mimic human HGG-MYCN regarding histology, DNA methylation, and gene expression. Single-cell RNA sequencing revealed a high intratumoral heterogeneity with neuronal and oligodendroglial lineage signatures. High-throughput drug screening using both mouse and human tumor cells finally indicated high efficacy of Doxorubicin, Irinotecan, and Etoposide as possible therapy options that children with HGG-MYCN might benefit from.