Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes

Cancer-specific epigenome identifies oncogenic hijacking by nuclear factor I family proteins for medulloblastoma progression

Normal cells coordinate proliferation and differentiation by precise tuning of gene expression based on the dynamic shifts of the epigenome throughout the developmental timeline. Although non-mutational epigenetic reprogramming is an emerging hallmark of cancer, the epigenomic shifts that occur during the transition from normal to malignant cells remain elusive. Here, we capture the epigenomic changes that occur during tumorigenesis in a prototypic embryonal brain tumor, medulloblastoma. By comparing the epigenomes of the different stages of transforming cells in mice, we identify nuclear factor I family of transcription factors, known to be cell fate determinants in development, as oncogenic regulators in the epigenomes of precancerous and cancerous cells. Furthermore, genetic and pharmacological inhibition of NFIB validated a crucial role of this transcription factor by disrupting the cancer epigenome in medulloblastoma. Thus, this study exemplifies how epigenomic changes contribute to tumorigenesis via non-mutational mechanisms involving developmental transcription factors.

Survival-Related Genes on Chromosomes 6 and 17 in Medulloblastoma

Survival of Medulloblastoma (MB) depends on various factors, including the gene expression profiles of MB tumor tissues. In this study, we identified 967 MB survival-related genes (SRGs) using a gene expression dataset and the Cox proportional hazards regression model. Notably, the SRGs were over-represented on chromosomes 6 and 17, known for the abnormalities monosomy 6 and isochromosome 17 in MB. The most significant SRG was HMGA1 (high mobility group AT-hook 1) on chromosome 6, which is a known oncogene and a histone H1 competitor. High expression of HMGA1 was associated with worse survival, primarily in the Group 3γ subtype. The high expression of HMGA1 was unrelated to any known somatic copy number alteration. Most SRGs on chromosome 17p were associated with low expression in Group 4β, the MB subtype, with 93% deletion of 17p and 98% copy gain of 17q. GO enrichment analysis showed that both chromosomes 6 and 17 included SRGs related to telomere maintenance and provided a rationale for testing telomerase inhibitors in Group 3 MBs. We conclude that HMGA1, along with other SRGs on chromosomes 6 and 17, warrant further investigation as potential therapeutic targets in selected subgroups or subtypes of MB.

scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network

Cells respond divergently to drugs due to the heterogeneity among cell populations. Thus, it is crucial to identify drug-responsive cell populations in order to accurately elucidate the mechanism of drug action, which is still a great challenge. Here, we address this problem with scRank, which employs a target-perturbed gene regulatory network to rank drug-responsive cell populations via in silico drug perturbations using untreated single-cell transcriptomic data. We benchmark scRank on simulated and real datasets, which shows the superior performance of scRank over existing methods. When applied to medulloblastoma and major depressive disorder datasets, scRank identifies drug-responsive cell types that are consistent with the literature. Moreover, scRank accurately uncovers the macrophage subpopulation responsive to tanshinone IIA and its potential targets in myocardial infarction, with experimental validation. In conclusion, scRank enables the inference of drug-responsive cell types using untreated single-cell data, thus providing insights into the cellular-level impacts of therapeutic interventions.

EYA2 tyrosine phosphatase inhibition reduces MYC and prevents medulloblastoma progression

BACKGROUND

Medulloblastoma is the most common pediatric brain malignancy. Patients with the Group 3 subtype of medulloblastoma (MB) often exhibit MYC amplification and/or overexpression and have the poorest prognosis. While Group 3 MB is known to be highly dependent on MYC, direct targeting of MYC remains elusive.

METHODS

Patient gene expression data were used to identify highly expressed EYA2 in Group 3 MB samples, assess the correlation between EYA2 and MYC, and examine patient survival. Genetic and pharmacological studies were performed on EYA2 in Group 3 derived MB cell models to assess MYC regulation and viability in vitro and in vivo.

RESULTS

EYA2 is more highly expressed in Group 3 MB than other MB subgroups and is essential for Group 3 MB growth in vitro and in vivo. EYA2 regulates MYC expression and protein stability in Group 3 MB, resulting in global alterations of MYC transcription. Inhibition of EYA2 tyrosine phosphatase activity, using a novel small molecule inhibitor (NCGC00249987, or 9987), significantly decreases Group 3 MB MYC expression in both flank and intracranial growth in vivo. Human MB RNA-seq data show that EYA2 and MYC are significantly positively correlated, high EYA2 expression is significantly associated with a MYC transcriptional signature, and patients with high EYA2 and MYC expression have worse prognoses than those that do not express both genes at high levels.

CONCLUSIONS

Our data demonstrate that EYA2 is a critical regulator of MYC in Group 3 MB and suggest a novel therapeutic avenue to target this highly lethal disease.

DUBing Primary Tumors of the Central Nervous System: Regulatory Roles of Deubiquitinases

The ubiquitin proteasome system (UPS) utilizes an orchestrated enzymatic cascade of E1, E2, and E3 ligases to add single or multiple ubiquitin-like molecules as post-translational modification (PTM) to proteins. Ubiquitination can alter protein functions and/or mark ubiquitinated proteins for proteasomal degradation but deubiquitinases (DUBs) can reverse protein ubiquitination. While the importance of DUBs as regulatory factors in the UPS is undisputed, many questions remain on DUB selectivity for protein targeting, their mechanism of action, and the impact of DUBs on the regulation of diverse biological processes. Furthermore, little is known about the expression and role of DUBs in tumors of the human central nervous system (CNS). In this comprehensive review, we have used publicly available transcriptional datasets to determine the gene expression profiles of 99 deubiquitinases (DUBs) from five major DUB families in seven primary pediatric and adult CNS tumor entities. Our analysis identified selected DUBs as potential new functional players and biomarkers with prognostic value in specific subtypes of primary CNS tumors. Collectively, our analysis highlights an emerging role for DUBs in regulating CNS tumor cell biology and offers a rationale for future therapeutic targeting of DUBs in CNS tumors.

Correcting batch effects in large-scale multiomics studies using a reference-material-based ratio method

BACKGROUND

Batch effects are notoriously common technical variations in multiomics data and may result in misleading outcomes if uncorrected or over-corrected. A plethora of batch-effect correction algorithms are proposed to facilitate data integration. However, their respective advantages and limitations are not adequately assessed in terms of omics types, the performance metrics, and the application scenarios.

RESULTS

As part of the Quartet Project for quality control and data integration of multiomics profiling, we comprehensively assess the performance of seven batch effect correction algorithms based on different performance metrics of clinical relevance, i.e., the accuracy of identifying differentially expressed features, the robustness of predictive models, and the ability of accurately clustering cross-batch samples into their own donors. The ratio-based method, i.e., by scaling absolute feature values of study samples relative to those of concurrently profiled reference material(s), is found to be much more effective and broadly applicable than others, especially when batch effects are completely confounded with biological factors of study interests. We further provide practical guidelines for implementing the ratio based approach in increasingly large-scale multiomics studies.

CONCLUSIONS

Multiomics measurements are prone to batch effects, which can be effectively corrected using ratio-based scaling of the multiomics data. Our study lays the foundation for eliminating batch effects at a ratio scale.

KCTD1 is a new modulator of the KCASH family of Hedgehog suppressors

The Sonic Hedgehog (Hh) signal transduction pathway plays a critical role in many developmental processes and, when deregulated, may contribute to several cancers, including basal cell carcinoma, medulloblastoma, colorectal, prostate, and pancreatic cancer. In recent years, several Hh inhibitors have been developed, mainly acting on the Smo receptor. However, drug resistance due to Smo mutations or non-canonical Hh pathway activation highlights the need to identify further mechanisms of Hh pathway modulation. Among these, deacetylation of the Hh transcription factor Gli1 by the histone deacetylase HDAC1 increases Hh activity. On the other end, the KCASH family of oncosuppressors binds HDAC1, leading to its ubiquitination and subsequent proteasomal degradation, leaving Gli1 acetylated and not active. It was recently demonstrated that the potassium channel containing protein KCTD15 is able to interact with KCASH2 protein and stabilize it, enhancing its effect on HDAC1 and Hh pathway. KCTD15 and KCTD1 proteins share a high homology and are clustered in a specific KCTD subfamily. We characterize here KCTD1 role on the Hh pathway. Therefore, we demonstrated KCTD1 interaction with KCASH1 and KCASH2 proteins, and its role in their stabilization by reducing their ubiquitination and proteasome-mediated degradation. Consequently, KCTD1 expression reduces HDAC1 protein levels and Hh/Gli1 activity, inhibiting Hh dependent cell proliferation in Hh tumour cells. Furthermore, analysis of expression data on publicly available databases indicates that KCTD1 expression is reduced in Hh dependent MB samples, compared to normal cerebella, suggesting that KCTD1 may represent a new putative target for therapeutic approaches against Hh-dependent tumour.

Using evolutionary constraint to define novel candidate driver genes in medulloblastoma

Current knowledge of cancer genomics remains biased against noncoding mutations. To systematically search for regulatory noncoding mutations, we assessed mutations in conserved positions in the genome under the assumption that these are more likely to be functional than mutations in positions with low conservation. To this end, we use whole-genome sequencing data from the International Cancer Genome Consortium and combined it with evolutionary constraint inferred from 240 mammals, to identify genes enriched in noncoding constraint mutations (NCCMs), mutations likely to be regulatory in nature. We compare medulloblastoma (MB), which is malignant, to pilocytic astrocytoma (PA), a primarily benign tumor, and find highly different NCCM frequencies between the two, in agreement with the fact that malignant cancers tend to have more mutations. In PA, a high NCCM frequency only affects the BRAF locus, which is the most commonly mutated gene in PA. In contrast, in MB, >500 genes have high levels of NCCMs. Intriguingly, several loci with NCCMs in MB are associated with different ages of onset, such as the HOXB cluster in young MB patients. In adult patients, NCCMs occurred in, e.g., the WASF-2/AHDC1/FGR locus. One of these NCCMs led to increased expression of the SRC kinase FGR and augmented responsiveness of MB cells to dasatinib, a SRC kinase inhibitor. Our analysis thus points to different molecular pathways in different patient groups. These newly identified putative candidate driver mutations may aid in patient stratification in MB and could be valuable for future selection of personalized treatment options.

Role of Ubiquitin Ligases and Conjugases in Targeted Cancer Therapy

The ubiquitin proteasome system regulates the activity of many short-lived proteins in cells [...].

Dissecting molecular, pathological, and clinical features associated with tumor neural/neuroendocrine heterogeneity

Lineage plasticity, especially transdifferentiation between neural/neuroendocrine (NE) and non-NE lineage, has been observed in multiple cancer types and linked to increased tumor aggressiveness. However, existing NE/non-NE subtype classifications in various cancer types were established through ad hoc approaches in different studies, making it difficult to align findings across cancer types and extend investigations to new datasets. To address this issue, we developed a generalized strategy to generate quantitative NE scores and a web application to facilitate its implementation. We applied this method to nine datasets covering seven cancer types, including two neural cancers, two neuroendocrine cancers, and three non-NE cancers. Our analysis revealed significant NE inter-tumoral heterogeneity and identified strong associations between NE scores and molecular, histological, and clinical features, including prognosis in different cancer types. These results support the translational utility of NE scores. Overall, our work demonstrated a broadly applicable strategy for determining the NE properties of tumors.

Leveraging base-pair mammalian constraint to understand genetic variation and human disease

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

ARF suppression by MYC but not MYCN confers increased malignancy of aggressive pediatric brain tumors

Medulloblastoma, the most common malignant pediatric brain tumor, often harbors MYC amplifications. Compared to high-grade gliomas, MYC-amplified medulloblastomas often show increased photoreceptor activity and arise in the presence of a functional ARF/p53 suppressor pathway. Here, we generate an immunocompetent transgenic mouse model with regulatable MYC that develop clonal tumors that molecularly resemble photoreceptor-positive Group 3 medulloblastoma. Compared to MYCN-expressing brain tumors driven from the same promoter, pronounced ARF silencing is present in our MYC-expressing model and in human medulloblastoma. While partial Arf suppression causes increased malignancy in MYCN-expressing tumors, complete Arf depletion promotes photoreceptor-negative high-grade glioma formation. Computational models and clinical data further identify drugs targeting MYC-driven tumors with a suppressed but functional ARF pathway. We show that the HSP90 inhibitor, Onalespib, significantly targets MYC-driven but not MYCN-driven tumors in an ARF-dependent manner. The treatment increases cell death in synergy with cisplatin and demonstrates potential for targeting MYC-driven medulloblastoma.

A neurodevelopmental epigenetic programme mediated by SMARCD3-DAB1-Reelin signalling is hijacked to promote medulloblastoma metastasis

How abnormal neurodevelopment relates to the tumour aggressiveness of medulloblastoma (MB), the most common type of embryonal tumour, remains elusive. Here we uncover a neurodevelopmental epigenomic programme that is hijacked to induce MB metastatic dissemination. Unsupervised analyses of integrated publicly available datasets with our newly generated data reveal that SMARCD3 (also known as BAF60C) regulates Disabled 1 (DAB1)-mediated Reelin signalling in Purkinje cell migration and MB metastasis by orchestrating cis-regulatory elements at the DAB1 locus. We further identify that a core set of transcription factors, enhancer of zeste homologue 2 (EZH2) and nuclear factor I X (NFIX), coordinates with the cis-regulatory elements at the SMARCD3 locus to form a chromatin hub to control SMARCD3 expression in the developing cerebellum and in metastatic MB. Increased SMARCD3 expression activates Reelin-DAB1-mediated Src kinase signalling, which results in a MB response to Src inhibition. These data deepen our understanding of how neurodevelopmental programming influences disease progression and provide a potential therapeutic option for patients with MB.

Drug Resistance in Medulloblastoma Is Driven by YB-1, ABCB1 and a Seven-Gene Drug Signature

Therapy resistance represents an unmet challenge in the treatment of medulloblastoma. Accordingly, the identification of targets that mark drug-resistant cell populations, or drive the proliferation of resistant cells, may improve treatment strategies. To address this, we undertook a targeted approach focused on the multi-functional transcription factor YB-1. Genetic knockdown of YB-1 in Group 3 medulloblastoma cell lines diminished cell invasion in 3D in vitro assays and increased sensitivity to standard-of-care chemotherapeutic vincristine and anti-cancer agents panobinostat and JQ1. For vincristine, this occurred in part by YB-1-mediated transcriptional regulation of multi-drug resistance gene ABCB1, as determined by chromatin immunoprecipitation. Whole transcriptome sequencing of YB-1 knockdown cells identified a role for YB-1 in the regulation of tumourigenic processes, including lipid metabolism, cell death and survival and MYC and mTOR pathways. Stable cisplatin- and vincristine-tolerant Group 3 and SHH cell lines were generated to identify additional mechanisms driving resistance to standard-of-care medulloblastoma therapy. Next-generation sequencing revealed a vastly different transcriptomic landscape following chronic drug exposure, including a drug-tolerant seven-gene expression signature, common to all sequenced drug-tolerant cell lines, representing therapeutically targetable genes implicated in the acquisition of drug tolerance. Our findings provide significant insight into mechanisms and genes underlying therapy resistance in medulloblastoma.

Normalization of Large-Scale Transcriptome Data Using Heuristic Methods

In this study, we introduce an artificial intelligent method for addressing the batch effect of a transcriptome data. The method has several clear advantages in comparison with the alternative methods presently in use. Batch effect refers to the discrepancy in gene expression data series, measured under different conditions. While the data from the same batch (measurements performed under the same conditions) are compatible, combining various batches into 1 data set is problematic because of incompatible measurements. Therefore, it is necessary to perform correction of the combined data (normalization), before performing biological analysis. There are numerous methods attempting to correct data set for batch effect. These methods rely on various assumptions regarding the distribution of the measurements. Forcing the data elements into pre-supposed distribution can severely distort biological signals, thus leading to incorrect results and conclusions. As the discrepancy between the assumptions regarding the data distribution and the actual distribution is wider, the biases introduced by such “correction methods” are greater. We introduce a heuristic method to reduce batch effect. The method does not rely on any assumptions regarding the distribution and the behavior of data elements. Hence, it does not introduce any new biases in the process of correcting the batch effect. It strictly maintains the integrity of measurements within the original batches.

Whole-genome sequencing of extrachromosomal circular DNA of cerebrospinal fluid of medulloblastoma

BACKGROUND

Medulloblastoma (MB) is a malignant tumor associated with a poor prognosis in part due to a lack of effective detection methods. Extrachromosomal circular DNA (eccDNA) has been associated with multiple tumors. Nonetheless, little is currently known on eccDNA in MB.

METHODS

Genomic features of eccDNAs were identified in MB tissues and matched cerebrospinal fluid (CSF) and compared with corresponding normal samples using Circle map. The nucleotides on both sides of the eccDNAs' breakpoint were analyzed to understand the mechanisms of eccDNA formation. Bioinformatics analysis combined with the Gene Expression Omnibus (GEO) database identified features of eccDNA-related genes in MB. Lasso Cox regression model, univariate and multivariate Cox regression analysis, time-dependent ROC, and Kaplan-Meier curve were used to assess the potential diagnostic and prognostic value of the hub genes.

RESULTS

EccDNA was profiled in matched tumor and CSF samples from MB patients, and control, eccDNA-related genes enriched in MB were identified. The distribution of eccDNAs in the genome was closely related to gene density and the mechanism of eccDNA formation was evaluated. EccDNAs in CSF exhibited similar distribution with matched MB tissues but were differentially expressed between tumor and normal. Ten hub genes prominent in both the eccDNA dataset and the GEO database were selected to classify MB patients to either high- or low-risk groups, and a prognostic nomogram was thus established.

CONCLUSIONS

This study provides preliminary evidence of the characteristics and formation mechanism of eccDNAs in MB and CSF. Importantly, eccDNA-associated hub genes in CSF could be used as diagnostic and prognostic biomarkers for MB.

Intratumoral heterogeneity of MYC drives medulloblastoma metastasis and angiogenesis

BACKGROUND

Intratumoral heterogeneity is crucially involved in metastasis, resistance to therapy, and cancer relapse. Amplifications of the proto-oncogene MYC display notable heterogeneity at the single-cell level and are associated with a particularly dismal prognosis in high-risk medulloblastomas (MBs). The aim of this study was to establish the relevance of interclonal cross-talk between MYC-driven and non-MYC-driven MB cells.

METHODS

We used fluorescence in situ hybridization, single-cell transcriptomics, and immunohistochemistry, in vitro isogenic cell models, non-targeted proteomics, mass spectrometry-based metabolite quantification, HUVECs tube formation assay, and orthotopic in vivo experiments to investigate interclonal cross-talk in MB.

RESULTS

We found that the release of lactate dehydrogenase A (LDHA) from MYC-driven cells facilitates metastatic seeding and outgrowth, while secretion of dickkopf WNT signaling pathway inhibitor 3 from non-MYC-driven cells promotes tumor angiogenesis. This tumor-supporting interaction between both subclones was abrogated by targeting the secretome through pharmacological and genetic inhibition of LDHA, which significantly suppressed tumor cell migration.

CONCLUSION

Our study reveals the functional relevance of clonal diversity and highlights the therapeutic potential of targeting the secretome to interrupt interclonal communication and progression in high-risk MB.

Gene Expression Monotonicity across Bladder Cancer Stages Informs on the Molecular Pathogenesis and Identifies a Prognostic Eight-Gene Signature

Despite advancements in molecular classification, tumor stage and grade still remain the most relevant prognosticators used by clinicians to decide on patient management. Here, we leverage publicly available data to characterize bladder cancer (BLCA)’s stage biology based on increased sample sizes, identify potential therapeutic targets, and extract putative biomarkers. A total of 1135 primary BLCA transcriptomes from 12 microarray studies were compiled in a meta-cohort and analyzed for monotonal alterations in pathway activities, gene expression, and co-expression patterns with increasing stage (Ta–T1–T2–T3–T4), starting from the non-malignant tumor-adjacent urothelium. The TCGA-2017 and IMvigor-210 RNA-Seq data were used to validate our findings. Wnt, MTORC1 signaling, and MYC activity were monotonically increased with increasing stage, while an opposite trend was detected for the catabolism of fatty acids, circadian clock genes, and the metabolism of heme. Co-expression network analysis highlighted stage- and cell-type-specific genes of potentially synergistic therapeutic value. An eight-gene signature, consisting of the genes AKAP7, ANLN, CBX7, CDC14B, ENO1, GTPBP4, MED19, and ZFP2, had independent prognostic value in both the discovery and validation sets. This novel eight-gene signature may increase the granularity of current risk-to-progression estimators.

Automatic Segmentation of Magnetic Resonance Images of Severe Patients with Advanced Liver Cancer and the Molecular Mechanism of Emodin-Induced Apoptosis of HepG2 Cells under the Deep Learning

To improve the accuracy of clinical diagnosis of severe patients with advanced liver cancer and enhance the effect of chemotherapy treatment, the U-Net model was optimized by introducing the batch normalization (BN) layer and the dropout layer, and the segmentation training and verification of the optimized model were realized by the magnetic resonance (MR) image data. Subsequently, HepG2 cells were taken as the research objects and treated with 0, 10, 20, 40, 60, 80, and 100 μmol/L emodin (EMO), respectively. The methyl thiazolyl tetrazolium (MTT) method was used to explore the changes in cell viability, the acridine orange (AO)/ethidium bromide (EB) and 4',6-diamidino-2-phenylindole (DAPI) were used for staining, the Annexin V fluorescein isothiocyanate (FITC)/propidium iodide (PI) (Annexin V-FITC/PI) was adopted to detect the apoptosis after EMO treatment, and the Western blot (WB) method was used with the purpose of exploring the changes in protein expression levels of PARP, Bcl-2, and p53 in the cells after treatment. It was found that compared with the original U-Net model, the introduction of the BN layer and the dropout layer can improve the robustness of the U-Net model, and the optimized U-Net model had the highest dice similarity coefficient (DSC) (98.45%) and mean average precision (MAP) (0.88) for the liver tumor segmentation.

Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

Background

Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB.

Methods

A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣log fold change | >1 and P < 0.05. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network.

Results

Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

MiR-212-3p functions as a tumor suppressor gene in group 3 medulloblastoma via targeting nuclear factor I/B (NFIB)

Haploinsufficiency of chromosome 17p and c-Myc amplification distinguish group 3 medulloblastomas which are associated with early metastasis, rapid recurrence, and swift mortality. Tumor suppressor genes on this locus have not been adequately characterized. We elucidated the role of miR-212-3p in the pathophysiology of group 3 tumors. First, we learned that miR-212-3p undergoes epigenetic silencing by histone modifications in group 3 tumors. Restoring its expression reduced cancer cell proliferation, migration, colony formation, and wound healing in vitro and attenuated tumor burden and improved survival in vivo. MiR-212-3p also triggered c-Myc destabilization and degradation, leading to elevated apoptosis. We then isolated an oncogenic target of miR-212-3p, i.e. NFIB, a nuclear transcription factor implicated in metastasis and recurrence in various cancers. Increased expression of NFIB was confirmed in group 3 tumors and associated with poor survival. NFIB silencing reduced cancer cell proliferation, migration, and invasion. Concurrently, reduced medullosphere formation and stem cell markers (Nanog, Oct4, Sox2, CD133) were noted. These results substantiate the tumor-suppressive role of miR-212-3p in group 3 MB and identify a novel oncogenic target implicated in metastasis and tumor recurrence.

Co-activation of Sonic hedgehog and Wnt signaling in murine retinal precursor cells drives ocular lesions with features of intraocular medulloepithelioma

Intraocular medulloepithelioma (IO-MEPL) is a rare embryonal ocular neoplasm, prevalently occurring in children. IO-MEPLs share histomorphological features with CNS embryonal tumors with multilayered rosettes (ETMRs), referred to as intracranial medulloepitheliomas. While Sonic hedgehog (SHH) and WNT signaling pathways are crucial for ETMR pathogenesis, the impact of these pathways on human IO-MEPL development is unclear. Gene expression analyses of human embryonal tumor samples revealed similar gene expression patterns and significant overrepresentation of SHH and WNT target genes in both IO-MEPL and ETMR. In order to unravel the function of Shh and Wnt signaling for IO-MEPL pathogenesis in vivo, both pathways were activated in retinal precursor cells in a time point specific manner. Shh and Wnt co-activation in early Sox2- or Rax-expressing precursor cells resulted in infiltrative ocular lesions that displayed extraretinal expansion. Histomorphological, immunohistochemical, and molecular features showed a strong concordance with human IO-MEPL. We demonstrate a relevant role of WNT and SHH signaling in IO-MEPL and report the first mouse model to generate tumor-like lesions with features of IO-MEPL. The presented data may be fundamental for comprehending IO-MEPL initiation and developing targeted therapeutic approaches.

Single-cell spatial transcriptomic analysis reveals common and divergent features of developing postnatal granule cerebellar cells and medulloblastoma

BACKGROUND

Cerebellar neurogenesis involves the generation of large numbers of cerebellar granule neurons (GNs) throughout development of the cerebellum, a process that involves tight regulation of proliferation and differentiation of granule neuron progenitors (GNPs). A number of transcriptional regulators, including Math1, and the signaling molecules Wnt and Shh have been shown to have important roles in GNP proliferation and differentiation, and deregulation of granule cell development has been reported to be associated with the pathogenesis of medulloblastoma. While the progenitor/differentiation states of cerebellar granule cells have been broadly investigated, a more detailed association between developmental differentiation programs and spatial gene expression patterns, and how these lead to differential generation of distinct types of medulloblastoma remains poorly understood. Here, we provide a comparative single-cell spatial transcriptomics analysis to better understand the similarities and differences between developing granule and medulloblastoma cells.

RESULTS

To acquire an enhanced understanding of the precise cellular states of developing cerebellar granule cells, we performed single-cell RNA sequencing of 24,919 murine cerebellar cells from granule neuron-specific reporter mice (Math1-GFP; Dcx-DsRed mice). Our single-cell analysis revealed that there are four major states of developing cerebellar granule cells, including two subsets of granule progenitors and two subsets of differentiating/differentiated granule neurons. Further spatial transcriptomics technology enabled visualization of their spatial locations in cerebellum. In addition, we performed single-cell RNA sequencing of 18,372 cells from Patched+/- mutant mice and found that the transformed granule cells in medulloblastoma closely resembled developing granule neurons of varying differentiation states. However, transformed granule neuron progenitors in medulloblastoma exhibit noticeably less tendency to differentiate compared with cells in normal development.

CONCLUSION

In sum, our study revealed the cellular and spatial organization of the detailed states of cerebellar granule cells and provided direct evidence for the similarities and discrepancies between normal cerebellar development and tumorigenesis.

Loss of 5-Hydroxymethylcytosine as an Epigenetic Signature That Correlates With Poor Outcomes in Patients With Medulloblastoma

Medulloblastoma, as the most common malignant brain tumor in children, exhibits highly dysregulated DNA methylation. The novel epigenetic marker—5-hydroxymethylcytosine (5hmC) plays essential role in gene regulation during brain development and in brain tumors. However, the biological and clinical implications of 5hmC in medulloblastoma are still unclear. Here, we detected global 5hmC levels in two independent medulloblastoma patient cohorts (discovery cohort: n = 81; validation cohort: n = 171) using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. Immunohistochemistry was used to identify the cell proliferation and expression of Ten-eleven translocation 1 and 2 (TET1/2). The prognostic impacts of covariates on progression-free survival (PFS) and overall survival (OS) were evaluated using multivariate Cox hazards regression models. We observed that global 5hmC levels were decreased in medulloblastomas compared to normal cerebellums (P < 0.001). Multivariate analysis showed that low global 5hmC levels correlated with poor PFS and OS rates (discovery cohort: PFS: P = 0.003, OS: P = 0.002; validation cohort: PFS: P = 0.0002, OS: P = 0.001). Immunohistochemistry showed an inverse correlation between 5hmC score and Ki-67 index (r = -0.747, P < 0.0001). Moreover, 5hmC score in MB samples was associated with nuclear expression of TET1 (r = -0.419, P = 0.003) and TET2 (r = -0.399, P = 0.005) proteins. Our study demonstrates that loss of 5hmC is an epigenetic biomarker in medulloblastomas. Our results indicate that 5hmC could be a candidate prognostic indicator for improving survival prediction of risk stratification in patients with medulloblastoma.

Proteomic profiling of medulloblastoma reveals novel proteins differentially expressed within each molecular subgroup

OBJECTIVES

The objective of the study was to identify novel medulloblastoma (MB) biomarkers through proteomic profiling, correlate it with the molecular subgroups of MB and assess the clinical significance.

METHODS

Archived paraffin embedded tumor tissue blocks from 118 MB patients, operated at our institute were retrieved. Clinical information was documented from the hospital database. Tumours were stratified into molecular subgroups using the IHC markers- β Catenin, GAB-1, YAP-1 and p53. Six fresh MB tumour tissues and two control cerebellar tissues were subjected to proteomic profiling to study differential protein expression in molecular subgroups using high resolution mass spectrometry. Prominent signalling pathways activated in each subgroup were identified using the Panther pathway software.

RESULTS

Non WNT/SHH group was the most common (61.1 %), followed by SHH and WNT. p53 immunopositivity did not correlate with prognosis in any subgroup. Proteomic profiling revealed several novel proteins differentially expressed between MB molecular subgroups. Signalling pathways exclusively enriched in each molecular subgroup were also identified. The top upregulated proteins were PMEL and FBN2 in the WNT subgroup, SYNGR2 in the SHH subgroup and GFAP, IMPG2 and MAGEA10 in the Non WNT/Non SHH group. We validated GFAP by immunohistochemistry on the archived samples (n = 118) and noted two types of staining pattern in MBs - reactive (stellate) astrocytes and tumour cell staining. GFAP immunopositivity in tumor cells of SHH subgroup correlated with a better prognosis.

CONCLUSIONS

Proteomic profile identified several novel proteins differentially regulated within the molecular subgroups that could serve as potential diagnostic /prognostic biomarkers. Notably, GFAP, which was derived from proteomics data, when validated by IHC, revealed a variable staining pattern in MB tumours. The prognostic significance of GFAP in SHH tumor patients further points at the heterogeneity of this subgroup. The study also throws light on the signaling pathways activated in MB and in turn its plausible role in the tumorigenesis.

Nuclear Receptor Binding Protein 2 Is Downregulated in Medulloblastoma, and Reduces Tumor Cell Survival upon Overexpression

Pseudokinases, comprising 10% of the human kinome, are emerging as regulators of canonical kinases and their functions are starting to be defined. We previously identified the pseudokinase Nuclear Receptor Binding Protein 2 (NRBP2) in a screen for genes regulated during neural differentiation. During mouse brain development, NRBP2 is expressed in the cerebellum, and in the adult brain, mainly confined to specific neuronal populations. To study the role of NRBP2 in brain tumors, we stained a brain tumor tissue array for NRPB2, and find its expression to be low, or absent, in a majority of the tumors. This includes medulloblastoma (MB), a pediatric tumor of the cerebellum. Using database mining of published MB data sets, we also find that NRBP2 is expressed at a lower level in MB than in the normal cerebellum. Recent studies indicate that MB exhibits frequent epigenetic alternations and we therefore treated MB cell lines with drugs inhibiting DNA methylation or histone deacetylation, which leads to an upregulation of NRBP2 mRNA expression, showing that it is under epigenetic regulation in cultured MB cells. Furthermore, forced overexpression of NRBP2 in MB cell lines causes a dramatic decrease in cell numbers, increased cell death, impaired cell migration and inhibited cell invasion in vitro. Taken together, our data indicate that downregulation of NRBP2 may be a feature by which MB cells escape growth regulation.

Cell-free microRNAs in Parkinson's disease: potential biomarkers that provide new insights into disease pathogenesis

MicroRNAs (miRNAs) are master post-transcriptional regulators of gene expression and their specific footprints reflect disease conditions. Over the last few years, several primary reports have described the deregulation of cell-free miRNAs in Parkinson's disease (PD), however, results have been rather inconsistent due to preanalytical and analytical challenges. This study integrated the data across twenty-four reports to identify steadily deregulated miRNAs that may assist in the path towards biomarker development and molecular characterization of the underlying pathology. Stringent KEGG pathway analysis of the miRNA targets revealed FoxO, Prolactin, TNF, and ErbB signaling pathways as the most significantly enriched categories while Gene Ontology analysis revealed that the protein targets are mostly associated with transcription. Chromosomal location of the consistently deregulated miRNAs revealed that over a third of them were clustered at the same location at Chr14q32 suggesting that they are co-regulated by specific transcription factors. This genomic region is inherently unstable due to expanded TGG repeats and responsible for human abnormalities. Stringent analysis of transcription factor sites surrounding the deregulated miRNAs revealed that CREB1, CEBPB and MAZ sites existed in approximately half of the miRNAs, including all of the miRNAs located at Chr14q32. Additional studies are now needed to determine the biomarker potential of the consistently deregulated miRNAs in PD and the therapeutic implications of these bioinformatics insights.

Humanized Stem Cell Models of Pediatric Medulloblastoma Reveal an Oct4/mTOR Axis that Promotes Malignancy

Medulloblastoma (MB), the most frequent malignant childhood brain tumor, can arise from cellular malfunctions during hindbrain development. Here we generate humanized models for Sonic Hedgehog (SHH)-subgroup MB via MYCN overexpression in primary human hindbrain-derived neuroepithelial stem (hbNES) cells or iPSC-derived NES cells, which display a range of aggressive phenotypes upon xenografting. iPSC-derived NES tumors develop quickly with leptomeningeal dissemination, whereas hbNES-derived cells exhibit delayed tumor formation with less dissemination. Methylation and expression profiling show that tumors from both origins recapitulate hallmarks of infant SHH MB and reveal that mTOR activation, as a result of increased Oct4, promotes aggressiveness of human SHH tumors. Targeting mTOR decreases cell viability and prolongs survival, showing the utility of these varied models for dissecting mechanisms mediating tumor aggression and demonstrating the value of humanized models for a better understanding of pediatric cancers.

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Human iPSC-derived or primary neuroepithelial stem cells can be transformed by MYCN

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MYCN drives infant SHH medulloblastoma with clinically relevant features

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Epigenetically regulated Oct4 promotes mTOR hyperactivation in infant SHH tumors

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mTOR inhibition efficiently targets metastatic SHH medulloblastoma models and PDXs

Differential Expression of Mitochondrial Biogenesis Markers in Mouse and Human SHH-Subtype Medulloblastoma

Medulloblastoma is a brain tumor that arises predominantly in infants and children. It is the most common pediatric brain malignancy. Around 25% of medulloblastomas are driven by constitutive activation of the Hedgehog signaling pathway. Hedgehog-driven medulloblastoma is often studied in the laboratory using genetic mouse models with overactive Hedgehog signaling, which recapitulate many of the pathological features of human Hedgehog-dependent tumors. However, we show here that on a molecular level the human and mouse HH-dependent MB are quite distinct, with human, but not mouse, tumors characterized by the presence of markers of increased oxidative phosphorylation and mitochondrial biogenesis. The latter suggests that, unlike for many other types of tumors, a switch to glycolytic metabolism might not be co-opted by human SHH-MB to perpetuate their survival and growth. This needs to be taken into consideration and could potentially be exploited in the design of therapies.