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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. Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies but their origin are still unclear. Here, the authors define the genomic, epigenetic and transcriptional landscape of 32 RIGs cases.

Kinase inhibitors are effective cancer therapies, but tumors frequently develop resistance. Current strategies to circumvent resistance target the same or parallel pathways. We report here that targeting a completely different process, autophagy, can overcome multiple BRAF inhibitor resistance mechanisms in brain tumors. BRAFV600Emutations occur in many pediatric brain tumors. We previously reported that these tumors are autophagy-dependent and a patient was successfully treated with the autophagy inhibitor chloroquine after failure of the BRAFV600E inhibitor vemurafenib, suggesting autophagy inhibition overcame the kinase inhibitor resistance. We tested this hypothesis in vemurafenib-resistant brain tumors. Genetic and pharmacological autophagy inhibition overcame molecularly distinct resistance mechanisms, inhibited tumor cell growth, and increased cell death. Patients with resistance had favorable clinical responses when chloroquine was added to vemurafenib. This provides a fundamentally different strategy to circumvent multiple mechanisms of kinase inhibitor resistance that could be rapidly tested in clinical trials in patients with BRAFV600E brain tumors. Cancers of the brain and spine are the second most common kind of tumor in children, after cancers of the blood and bone marrow. Yet brain and spine tumors kill more children than any other cancer, in part because many become resistant to treatment. Like in other cancers, cells in brain and spine tumors often use a process called autophagy to survive the treatments that are used to try and kill them. This process allows cells to recycle proteins and other things inside the cell and use them for energy when the cell is under stress. In 2014, researchers reported that brain tumors carrying a mutation called BRAFV600E rely on autophagy to survive treatment with medications that target this mutation. These findings suggested that blocking autophagy might make the medications more effective against BRAFV600Emutant tumors and overcome the resistance. Now, Mulcahy Levy et al. – who include most of the researchers involved in the 2014 study – report that blocking autophagy does indeed overcome this kind of resistance in multiple types of tumor. The experiments made use of human brain tumor cells that can be grown in the laboratory and have been widely studied, as well as samples collected from patients. Mulcahy Levy et al. were able to block autophagy in the tumor cells by using genetic methods and, importantly, by using an approved and inexpensive drug that could be rapidly translated into clinical trials. Together these findings suggest that blocking autophagy in patients might be a safe and effective strategy to improve their response to existing therapies that target the BRAFV600E mutation. Future clinical trials are now needed to test more patients and verify if this treatment plan can be broadly effective in patients with these types of brain cancers.

Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utilize large volumes of training data, which are not available in many healthcare contexts. For patients with brain tumors, non-invasive diagnosis would represent a substantial clinical advance, potentially sparing patients from the risks associated with surgical intervention on the brain. Such an approach will depend upon highly accurate models built using the limited datasets that are available. Herein, we present a novel genetic algorithm (GA) that identifies optimal architecture parameters using feature embeddings from state-of-the-art image classification networks to identify the pediatric brain tumor, adamantinomatous craniopharyngioma (ACP). We optimized classification models for preoperative Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and combined CT and MRI datasets with demonstrated test accuracies of 85.3%, 83.3%, and 87.8%, respectively. Notably, our GA improved baseline model performance by up to 38%. This work advances DL and its applications within healthcare by identifying optimized networks in small-scale data contexts. The proposed system is easily implementable and scalable for non-invasive computer-aided diagnosis, even for uncommon diseases.

Background Medulloblastoma is the most common malignant brain tumor in children and remains a therapeutic challenge due to its significant therapy-related morbidity. Polo-like kinase 1 ( PLK1 ) is highly expressed in many cancers and regulates critical steps in mitotic progression. Recent studies suggest that targeting PLK1 with small molecule inhibitors is a promising approach to tumor therapy. Methods We examined the expression of PLK1 mRNA in medulloblastoma tumor samples using microarray analysis. The impact of PLK1 on cell proliferation was evaluated by depleting expression with RNA interference (RNAi) or by inhibiting function with the small molecule inhibitor BI 2536. Colony formation studies were performed to examine the impact of BI 2536 on medulloblastoma cell radiosensitivity. In addition, the impact of depleting PLK1 mRNA on tumor-initiating cells was evaluated using tumor sphere assays. Results Analysis of gene expression in two independent cohorts revealed that PLK1 mRNA is overexpressed in some, but not all, medulloblastoma patient samples when compared to normal cerebellum. Inhibition of PLK1 by RNAi significantly decreased medulloblastoma cell proliferation and clonogenic potential and increased cell apoptosis. Similarly, a low nanomolar concentration of BI 2536, a small molecule inhibitor of PLK1, potently inhibited cell growth, strongly suppressed the colony-forming ability, and increased cellular apoptosis of medulloblastoma cells. Furthermore, BI 2536 pretreatment sensitized medulloblastoma cells to ionizing radiation. Inhibition of PLK1 impaired tumor sphere formation of medulloblastoma cells and decreased the expression of SRY (sex determining region Y)-box 2 ( SOX2 ) mRNA in tumor spheres indicating a possible role in targeting tumor inititiating cells. Conclusions Our data suggest that targeting PLK1 with small molecule inhibitors, in combination with radiation therapy, is a novel strategy in the treatment of medulloblastoma that warrants further investigation.

Plexiform neurofibroma (PN) is a leading cause of morbidity in children with the genetic condition Neurofibromatosis Type 1 (NF1), often disfiguring or threatening vital structures. During formation of PN, a complex tumor microenvironment (TME) develops, with recruitment of neoplastic and non-neoplastic cell types being critical for growth and progression. Due to the cohesive cellularity of PN, single-cell RNA-sequencing is difficult and may result in a loss of detection of critical cellular subpopulations. To bypass this barrier, we performed single-nuclei RNA-sequencing (snRNA-seq) on 8 frozen PN samples, and integrated this with spatial transcriptomics (ST) in 4 PN samples and immunohistochemistry to provide morphological context to transcriptomic data. SnRNA-seq analysis definitively charted the heterogeneous cellular subpopulations in the PN TME, with the predominant fraction being fibroblast subtypes. PN showed a remarkable amount of inter-sample homogeneity regarding cellular subpopulation proportions despite being resected from a variety of anatomical locations. ST analysis identified distinct cellular subpopulations which were annotated using snRNA-seq data and correlated with histological features. Schwann cell/fibroblast interactions were identified by receptor/ligand interaction analysis demonstrating a high probability of Neurexin 1/Neuroligin 1 (NRXN1/NLGN1) receptor-ligand cross-talk predicted between fibroblasts and non-myelinated Schwann cells (NM-SC) and subtypes, respectively. We observed aberrant expression of NRXN1 and NLGN1 in our PN snRNA-seq data compared to a normal mouse sciatic nerve single-cell RNA-seq dataset. This pathway has never been described in PN and may indicate a clear and direct communication pathway between putative NM-SC cells of origin and surrounding fibroblasts, potentially driving disease progression. SnRNA-seq integrated with spatial transcriptomics advances our understanding of the complex cellular heterogeneity of PN TME and identify potential novel communication pathways that may drive disease progression, a finding that could provide translational therapy options for patients with these devastating tumors of childhood and early adulthood.

Pediatric neoplasms in the central nervous system (CNS) show extensive clinical and molecular heterogeneity and are fundamentally different from those occurring in adults. Molecular genetic testing contributes to accurate diagnosis and enables an optimal clinical management of affected children. Here, we investigated a rare, molecularly distinct type of pediatric high-grade neuroepithelial tumor ( n  = 18), that was identified through unsupervised visualization of genome-wide DNA methylation array data, together with copy number profiling, targeted next-generation DNA sequencing, and RNA transcriptome sequencing. DNA and/or RNA sequencing revealed recurrent fusions involving the capicua transcriptional repressor ( CIC ) gene in 10/10 tumor samples analyzed, with the most common fusion being CIC::LEUTX ( n  = 9). In addition, a CIC::NUTM1 fusion was detected in one of the tumors. Apart from the detected fusion events, no additional oncogenic alteration was identified in these tumors. The histopathological review demonstrated a morphologically heterogeneous group of high-grade neuroepithelial tumors with positive immunostaining for markers of glial differentiation in combination with weak and focal expression of synaptophysin, CD56 and CD99. All tumors were located in the supratentorial compartment, occurred during childhood (median age 8.5 years) and typically showed early relapses. In summary, we expand the spectrum of pediatric-type tumors of the CNS by reporting a previously uncharacterized group of rare high-grade neuroepithelial tumors that share a common DNA methylation signature and recurrent gene fusions involving the transcriptional repressor CIC . Downstream functional consequences of the fusion protein CIC::LEUTX and potential therapeutic implications need to be further investigated.

Background Medulloblastoma is the most common type of malignant brain tumor that afflicts children. Although recent advances in chemotherapy and radiation have improved outcomes, high-risk patients do poorly with significant morbidity. Methods To identify new molecular targets, we performed an integrated genomic analysis using structural and functional methods. Gene expression profiling in 16 medulloblastoma patient samples and subsequent gene set enrichment analysis indicated that cell cycle-related kinases were associated with disease development. In addition a kinome-wide small interfering RNA (siRNA) screen was performed to identify kinases that, when inhibited, could prevent cell proliferation. The two genome-scale analyses were combined to identify key vulnerabilities in medulloblastoma. The inhibition of one of the identified targets was further investigated using RNAi and a small molecule inhibitor. Results Combining the two analyses revealed that mitosis-related kinases were critical determinants of medulloblastoma cell proliferation. RNA interference (RNAi)-mediated knockdown of WEE1 kinase and other mitotic kinases was sufficient to reduce medulloblastoma cell proliferation. These data prompted us to examine the effects of inhibiting WEE1 by RNAi and by a small molecule inhibitor of WEE1, MK-1775, in medulloblastoma cell lines. MK-1775 inhibited the growth of medulloblastoma cell lines, induced apoptosis and increased DNA damage at nanomolar concentrations. Further, MK-1775 was synergistic with cisplatin in reducing medulloblastoma cell proliferation and resulted in an associated increase in cell death. In vivo MK-1775 suppressed medulloblastoma tumor growth as a single agent. Conclusions Taken together, these findings highlight mitotic kinases and, in particular, WEE1 as a rational therapeutic target for medulloblastoma.

Members of the HDAC family are predictive biomarkers and regulate the tumorigenesis in several cancers. However, the role of these genes in the biology of intracranial ependymomas (EPNs) remains unexplored. Here, an analysis of eighteen HDACs genes in an EPN transcriptomic dataset, revealed significantly higher levels of HDAC4 in supratentorial ZFTA fusion (ST-ZFTA) compared with ST-YAP1 fusion and posterior fossa EPNs, while HDAC7 and SIRT2 were downregulated in ST-ZFTA. HDAC4 was also overexpressed in ST-ZFTA as measured by single-cell RNA-Seq, quantitative real time-polymerase chain reaction, and immunohistochemistry. Survival analyses showed a significantly worse outcome for EPNs with higher HDAC4 and SIRT1 mRNA levels. Ontology enrichment analysis showed an HDAC4-high signature consistent with viral processes while collagen-containing extracellular matrix and cell-cell junction were enriched in those with an HDAC4-low signature. Immune gene analysis demonstrated a correlation between HDAC4 expression and low levels of NK resting cells. Several small molecules compounds targeting HDAC4 and ABCG2, were predicted by in silico analysis to be effective against HDAC4-high ZFTA. Our results provide novel insights into the biology of the HDAC family in intracranial ependymomas and reveal HDAC4 as a prognostic marker and potential therapeutic target in ST-ZFTA.

It is unclear why medulloblastoma patients receiving similar treatments experience different outcomes. Transcriptomic profiling identified subgroups with different prognoses, but in each subgroup, individuals remain at risk of incurable recurrence. To investigate why similar-appearing tumors produce variable outcomes, we analyzed medulloblastomas triggered in transgenic mice by a common driver mutation expressed at different points in brain development. We genetically engineered mice to express oncogenic SmoM2, starting in multipotent glio-neuronal stem cells, or committed neural progenitors. Both groups developed medulloblastomas with similar transcriptomic profiles. We compared medulloblastoma progression, radiosensitivity, and cellular heterogeneity, determined by single-cell transcriptomic analysis (scRNA-seq). Stem cell-triggered medulloblastomas progressed faster, contained more OLIG2-expressing stem-like cells, and consistently showed radioresistance. In contrast, progenitor-triggered MBs progressed slower, down-regulated stem-like cells and were curable with radiation. Progenitor-triggered medulloblastomas also contained more diverse stromal populations, with more Ccr2+ macrophages and fewer Igf1+ microglia, indicating that developmental events affected the subsequent tumor microenvironment. Reduced mTORC1 activity in M-Smo tumors suggests that differential Igf1 contributed to differences in phenotype. Developmental events in tumorigenesis that were obscure in transcriptomic profiles thus remained cryptic determinants of tumor composition and outcome. Precise understanding of medulloblastoma pathogenesis and prognosis requires supplementing transcriptomic/methylomic studies with analyses that resolve cellular heterogeneity.Malawsky, Weir et al. compare medulloblastomas that form in mice engineered to express SmoM2, a constitutively active component of the Sonic hedgehog signaling pathway, starting in either neural progenitor or stem cells. Medulloblastomas in the two models show similar bulk transcriptomic profiles, but contain different fractions of tumor stem cells and different myeloid populations, and demonstrate different therapeutic responses.