Proteomic analysis of Medulloblastoma reveals functional biology with translational potential

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames (ORFs). To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a stepwise approach using multiple CRISPR-Cas9 screens to elucidate non-canonical ORFs and putative microproteins implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream ORFs (uORFs) exhibited selective functionality independent of main coding sequences. A microprotein encoded by one of these ORFs, ASNSD1-uORF or ASDURF, was upregulated, associated with MYC-family oncogenes, and promoted medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future studies seeking to define new cancer targets.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

INTRODUCTION

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

AREAS COVERED

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

EXPERT OPINION

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets.

Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues

Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each 'ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors.

Primary cilia contribute to the aggressiveness of atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumor (AT/RT) is a highly malignant brain tumor in infants that is characterized by loss of nuclear expression of SMARCB1 or SMARCA4 proteins. Recent studies show that AT/RTs comprise three molecular subgroups, namely AT/RT-TYR, AT/RT-MYC and AT/RT-SHH. The subgroups show distinct expression patterns of genes involved in ciliogenesis, however, little is known about the functional roles of primary cilia in the biology of AT/RT. Here, we show that primary cilia are present across all AT/RT subgroups with specific enrichment in AT/RT-TYR patient samples. Furthermore, we demonstrate that primary ciliogenesis contributes to AT/RT biology in vitro and in vivo. Specifically, we observed a significant decrease in proliferation and clonogenicity following disruption of primary ciliogenesis in AT/RT cell line models. Additionally, apoptosis was significantly increased via the induction of STAT1 and DR5 signaling, as detected by proteogenomic profiling. In a Drosophila model of SMARCB1 deficiency, concomitant knockdown of several cilia-associated genes resulted in a substantial shift of the lethal phenotype with more than 20% of flies reaching adulthood. We also found significantly extended survival in an orthotopic xenograft mouse model of AT/RT upon disruption of primary ciliogenesis. Taken together, our findings indicate that primary ciliogenesis or its downstream signaling contributes to the aggressiveness of AT/RT and, therefore, may constitute a novel therapeutic target.

Weighted Gene Co-Expression Network Analysis and Support Vector Machine Learning in the Proteomic Profiling of Cerebrospinal Fluid from Extraventricular Drainage in Child Medulloblastoma

Medulloblastoma (MB) is the most common pediatric malignant central nervous system tumor. Overall survival in MB depends on treatment tuning. There is aneed for biomarkers of residual disease and recurrence. We analyzed the proteome of waste cerebrospinal fluid (CSF) from extraventricular drainage (EVD) from six children bearing various subtypes of MB and six controls needing EVD insertion for unrelated causes. Samples included total CSF, microvesicles, exosomes, and proteins captured by combinatorial peptide ligand library (CPLL). Liquid chromatography-coupled tandem mass spectrometry proteomics identified 3560 proteins in CSF from control and MB patients, 2412 (67.7%) of which were overlapping, and 346 (9.7%) and 805 (22.6%) were exclusive. Multidimensional scaling analysis discriminated samples. The weighted gene co-expression network analysis (WGCNA) identified those modules functionally associated with the samples. A ranked core of 192 proteins allowed distinguishing between control and MB samples. Machine learning highlighted long-chain fatty acid transport protein 4 (SLC27A4) and laminin B-type (LMNB1) as proteins that maximized the discrimination between control and MB samples. Machine learning WGCNA and support vector machine learning were able to distinguish between MB versus non-tumor/hemorrhagic controls. The two potential protein biomarkers for the discrimination between control and MB may guide therapy and predict recurrences, improving the MB patients' quality of life.

TOP2A correlates with poor prognosis and affects radioresistance of medulloblastoma

Radiotherapy remains the standard treatment for medulloblastoma (MB), and the radioresistance contributes to tumor recurrence and poor clinical outcomes. Nuclear DNA topoisomerase II-alpha (TOP2A) is a key catalytic enzyme that initiates DNA replication, and studies have shown that TOP2A is closely related to the therapeutic effects of radiation. In this study, we found that TOP2A was significantly upregulated in MB, and high expression of TOP2A related to poor prognosis of MB patients. Knockdown of TOP2A inhibited MB cell proliferation, migration, and invasion, whereas overexpression of TOP2A enhanced the proliferative and invasive ability of MB cells. Moreover, si-TOP2A transfection in combination with irradiation (IR) significantly reduced the tumorigenicity of MB cells, compared with those transfected with si-TOP2A alone. Cell survival curve analysis revealed that the survival fraction of MB cells was significantly reduced upon TOP2A downregulation and that si-TOP2A-transfected cells had decreased D₀, Dq, and SF₂ values, indicating that TOP2A knockdown suppresses the resistance to radiotherapy in MB cells. In addition, western blot analysis demonstrated that the activity of Wnt/β-catenin signaling pathway was inhibited after TOP2A downregulation alone or in combination with IR treatment, whereas overexpression of TOP2A exhibited the opposite effects. Gene set enrichment analysis also revealed that Wnt/β-catenin signaling pathway is enriched in TOP2A high-expression phenotypes. Collectively, these data indicate that high expression of TOP2A leads to poor prognosis of MB, and downregulation of TOP2A inhibits the malignant behaviour as well as the radioresistance of MB cells. The Wnt/β-catenin signaling pathway may be involved in the molecular mechanisms of TOP2A mediated reduced tumorigenicity and radioresistance of MB cells.

Prognostic role of NLGN2 and PTGDS in medulloblastoma based on gene expression omnibus

BACKGROUND

Medulloblastoma (MB) is the most common intracranial malignant tumour in children, but genes and pathways involved in its pathogenesis are still under investigation. This study was designed to screen and identify biomarkers of MB to provide markers for clinical diagnosis and prognosis assessment.

METHODS

The data sets of GSE109401 and GSE42656 were acquired from Gene expression omnibus (GEO). Limma package in R was adopted to identify the differentially expressed genes (DEGs), and the GSE30074 data set was adopted to analyse their prognostic role. Children with MB (n=55) diagnosed in Affiliated Ezhou Central Hospital were enrolled and assigned to the patient group, and healthy children (n=30) who received physical examination in our hospital during the same time period were assigned to the control group. The two groups were compared in serum NLGN2 and PTGDS levels, and all patients were followed up for three years to understand the associations of Neuroligin 2 (NLGN2) and Prostaglandin D2 synthase (PTGDS) with the survival of patients.

RESULTS

With Limma, 247 DEGs were screened out. The LASSO-Cox regression analysis revealed that 6 genes were associated with MB prognosis, and the established model revealed a lower survival rate in the high-risk group. According to Cox regression analysis, NLGN2 and PTGDS may be independent prognostic factors of MB. Similar to the data sets, the Real time-quantitative polymerase chain reaction (RT-qPCR) assay revealed lowly-expressed NLGN2 and PTGDS levels in MB patients, and patients with lower expression of them showed a lower 3-year survival rate.

CONCLUSION

With low expression in MB cases, NLGN2 and PTGDS have high prognostic value for MB.

Identification of PBK as a hub gene and potential therapeutic target for medulloblastoma

Medulloblastoma (MB) is the most frequent malignant brain tumor in pediatrics. Since the current standard of care for MB consisting of surgery, cranio-spinal irradiation and chemotherapy often leads to a high morbidity rate, a number of patients suffer from long-term sequelae following treatment. Targeted therapies hold the promise of being more effective and less toxic. Therefore, the present study aimed to identify hub genes with an upregulated expression in MB and to search for potential therapeutic targets from these genes. For this purpose, gene expression profile datasets were obtained from the Gene Expression Omnibus database and processed using R 3.6.0 software to screen differentially expressed genes (DEGs) between MB samples and normal brain tissues. A total of 282 upregulated and 436 downregulated DEGs were identified. Functional enrichment analysis revealed that the upregulated DEGs were predominantly enriched in the cell cycle, DNA replication and cell division. The top 10 hub genes were identified from the protein-protein interaction network of upregulated genes, and one identified hub gene [PDZ binding kinase (PBK)] was selected for further investigation due to its possible role in the pathogenesis of MB. The aberrant expression of PBK in MB was verified in additional independent gene expression datasets. Survival analysis demonstrated that a higher expression level of PBK was significantly associated with poorer clinical outcomes in non-Wingless MBs. Furthermore, targeting PBK with its inhibitor, HI-TOPK-032, impaired the proliferation and induced the apoptosis of two MB cell lines, with the diminished phosphorylation of downstream effectors of PBK, including ERK1/2 and Akt, and the activation of caspase-3. Hence, these results suggest that PBK may be a potential prognostic biomarker and a novel candidate of targeted therapy for MB.

Cancer proteogenomics: current impact and future prospects

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep-learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules-such as gene promoter context, CpG island relationship, or user-defined groupings-and relate them to diagnostic and prognostic outcomes. We demonstrate these models' utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep-learning analyses' interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

An extracellular vesicle-related gene expression signature identifies high-risk patients in medulloblastoma

BACKGROUND

Medulloblastoma (MB) is a malignant brain tumor in childhood. It comprises 4 subgroups with different clinical behaviors. The aim of this study was to characterize the transcriptomic landscape of MB, both at the level of individual tumors as well as in large patient cohorts.

METHODS

We used a combination of single-cell transcriptomics, cell culture models and biophysical methods such as nanoparticle tracking analysis and electron microscopy to investigate intercellular communication in the MB tumor niche.

RESULTS

Tumor cells of the sonic hedgehog (SHH)-MB subgroup show a differentiation blockade. These cells undergo extensive metabolic reprogramming. The gene expression profiles of individual tumor cells show a partial convergence with those of tumor-associated glial and immune cells. One possible cause is the transfer of extracellular vesicles (EVs) between cells in the tumor niche. We were able to detect EVs in co-culture models of MB tumor cells and oligodendrocytes. We also identified a gene expression signature, EVS, which shows overlap with the proteome profile of large oncosomes from prostate cancer cells. This signature is also present in MB patient samples. A high EVS expression is one common characteristic of tumors that occur in high-risk patients from different MB subgroups or subtypes.

CONCLUSIONS

With EVS, our study uncovered a novel gene expression signature that has a high prognostic significance across MB subgroups.

A systematic view of pediatric medulloblastoma proteomics-current state of the field and future directions

Quantitative mass spectrometry (MS)-based approaches have allowed further characterization of medulloblastoma (MB) classification and clinical/biological behavior. By investigating protein expression, as well as the role of post-translational modifications in shaping cellular activity, novel avenues of research will clarify the current subgrouping, providing elements for tumor treatment-new molecular targets and signaling cascades-and introducing serum, urinary, and CSF markers of tumor growth and recurrence. We systematically searched and reviewed original research articles treating MB proteomics on PubMed. Reviews, opinion papers, and abstracts were excluded from the final work. A total of 30 novel articles treating the proteomic characterization of MB were included in our review. Research conducted on tissue samples, cell lines, CSF, and urine, as well as exosome and medullospheres, was considered, to picture a broad view of the different directions MS-based proteomic analysis is moving toward. In this review, we collect, summarize, and interpret the current literature on this topic. Significant progress has been achieved in the last decade in MB characterization, paving the way for further exploration of large biobanks of MB and other tissues that will allow a more systematic understanding of MB functioning and clinical progression.

RNA m6A Methylation Regulators Subclassify Luminal Subtype in Breast Cancer

RNA N⁶-methyladenosine (m⁶A) methylation is the most prevalent epitranscriptomic modification in mammals, with a complex and fine-tuning regulatory system. Recent studies have illuminated the potential of m⁶A regulators in clinical applications including diagnosis, therapeutics, and prognosis. Based on six datasets of breast cancer in The Cancer Genome Atlas (TCGA) database and two additional proteomic datasets, we provide a comprehensive view of all the known m⁶A regulators in their gene expression, copy number variations (CNVs), DNA methylation status, and protein levels in breast tumors and their association with prognosis. Among four breast cancer subtypes, basal-like subtype exhibits distinct expression and genomic alteration in m⁶A regulators from other subtypes. Accordingly, four representative regulators (IGF2BP2, IGF2BP3, YTHDC2, and RBM15) are identified as basal-like subtype-featured genes. Notably, luminal A/B samples are subclassified into two clusters based on the methylation status of those four genes. In line with its similarity to basal-like subtype, cluster1 shows upregulation in immune-related genes and cell adhesion molecules, as well as an increased number of tumor-infiltrating lymphocytes. Besides, cluster1 has worse disease-free and progression-free survival, especially among patients diagnosed with stage II and luminal B subtype. Together, this study highlights the potential functions of m⁶A regulators in the occurrence and malignancy progression of breast cancer. Given the heterogeneity within luminal subtype and high risk of recurrence and metastasis in a portion of patients, the prognostic stratification of luminal A/B subtypes utilizing basal-featured m⁶A regulators may help to improve the accuracy of diagnosis and therapeutics of breast cancer.

Piecing together the Pediatric Brain Tumor Puzzle

A recent study by Petralia et al. of 218 pediatric brain tumors across seven different entities applied an integrated approach incorporating proteomics, phosphoproteomics, whole-genome sequencing, and RNA sequencing. This elegant study unveiled new signaling pathways, the composition of tumor microenvironments, and functional effects of copy number variants and somatic mutations.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Effective Inhibition of MYC-Amplified Group 3 Medulloblastoma Through Targeting EIF4A1

Purpose

In medulloblastoma (MB), group 3 (G3) patients with MYC amplification tend to exhibit worse prognosis, thus creating a need for novel effective therapies. As the driver and crucial dependency for MYC-amplified G3-MB, MYC has been proven to be a prospective therapeutic target. Here, we aimed to identify novel effective therapeutic strategies against MYC-amplified G3-MB via targeting MYC translation.

Materials and Methods

Major components of translation initiation complex eIF4F were subjected to MB tumor dataset analysis, and EIF4A1 was identified to be a potential therapeutic target of MYC-amplified G3-MB. Validation was performed through genetic or pharmacological approaches with multiple patient-derived tumor models of MYC-amplified G3-MB in vitro and in vivo. Underlying mechanisms were further explored by Western blot, quantitative real-time PCR and mass spectrometry (MS) analyses.

Results

MB tumor datasets analyses showed that EIF4A1 was significantly up-regulated in G3-MB patients relative to normal cerebella, positively correlated with MYC in G3-MB at transcriptional level and a crucial cancer dependency in MYC-amplified G3-MB cells. Targeting EIF4A1 with a CRISPR/Cas9 approach or small-molecule inhibitor silvestrol effectively attenuated growth in multiple preclinical models of MYC-amplified G3-MB via blocking proliferation and inducing apoptosis. Mechanistically, EIF4A1 inhibition effectively impeded MYC expression at translational level, and its potency was positively associated with MYC level. Whole-proteome MS analysis of silvestrol-treated cells further unveiled other biological functions and pathways influenced by EIF4A1 inhibition.

Conclusion

Our investigation shows that interrupting MYC translation by EIF4A1 inhibition could be a potential effective therapeutic approach when treating patients with MYC-amplified G3-MB.

Deconstructing Sonic Hedgehog Medulloblastoma: Molecular Subtypes, Drivers, and Beyond

Medulloblastoma (MB) is a highly malignant cerebellar tumor predominantly diagnosed during childhood. Driven by pathogenic activation of sonic hedgehog (SHH) signaling, SHH subgroup MB (SHH-MB) accounts for nearly one-third of diagnoses. Extensive molecular analyses have identified biologically and clinically relevant intertumoral heterogeneity among SHH-MB tumors, prompting the recognition of novel subtypes. Beyond germline and somatic mutations promoting constitutive SHH signaling, driver alterations affect a multitude of pathways and molecular processes, including TP53 signaling, chromatin modulation, and post-transcriptional gene regulation. Here, we review recent advances in the underpinnings of SHH-MB in the context of molecular subtypes, clarify novel somatic and germline drivers, highlight cellular origins and developmental hierarchies, and describe the composition of the tumor microenvironment and its putative role in tumorigenesis.

Histone deacetylase inhibitors induce medulloblastoma cell death independent of HDACs recruited in REST repression complexes

BACKGROUND

Repressor element 1-silencing transcription factor (REST) acts as a transcriptional repressor by recruiting several chromatin modifiers, including histone deacetylase (HDAC). Elevated REST expression in medulloblastoma has been associated with tumor progression nevertheless, the tumor shows high sensitivity to HDAC inhibitors (HDACi). However, the functional implications of REST and its requirement for HDACi-induced anti-cancer effects are not well understood.

METHODS

In this study, the expression of REST was evaluated across the medulloblastoma subgroups and subtypes using published gene expression data. Further, the expression of REST was modulated using the CRISPR/Cas9 knockout and shRNA knockdown in the Daoy medulloblastoma cell line.

RESULTS

The results of this study showed that the expression of REST is elevated in most medulloblastoma subgroups compared to the non-cancerous cerebellum. Blocking of REST expression resulted in increasing the expression of REST-regulated genes, a moderate decrease in the fraction of the cells in the S-phase, and reducing the cells' migration ability. However, REST deficiency did not lead to a marked decrease in the Daoy cell viability and sensitivity to HDACi.

CONCLUSION

The findings of this study indicate that REST is not essential for sustaining the proliferation/viability of the Daoy cells. It also revealed that the anti-proliferative effect of HDACi is independent of REST expression.

The Non-coding Side of Medulloblastoma

Medulloblastoma (MB) is the most common pediatric brain tumor and a primary cause of cancer-related death in children. Until a few years ago, only clinical and histological features were exploited for MB pathological classification and outcome prognosis. In the past decade, the advancement of high-throughput molecular analyses that integrate genetic, epigenetic, and expression data, together with the availability of increasing wealth of patient samples, revealed the existence of four molecularly distinct MB subgroups. Their further classification into 12 subtypes not only reduced the well-characterized intertumoral heterogeneity, but also provided new opportunities for the design of targets for precision oncology. Moreover, the identification of tumorigenic and self-renewing subpopulations of cancer stem cells in MB has increased our knowledge of its biology. Despite these advancements, the origin of MB is still debated, and its molecular bases are poorly characterized. A major goal in the field is to identify the key genes that drive tumor growth and the mechanisms through which they are able to promote tumorigenesis. So far, only protein-coding genes acting as oncogenic drivers have been characterized in each MB subgroup. The contribution of the non-coding side of the genome, which produces a plethora of transcripts that control fundamental biological processes, as the cell choice between proliferation and differentiation, is still unappreciated. This review wants to fill this major gap by summarizing the recent findings on the impact of non-coding RNAs in MB initiation and progression. Furthermore, their potential role as specific MB biomarkers and novel therapeutic targets is also highlighted.

Identification of hub genes and small-molecule compounds in medulloblastoma by integrated bioinformatic analyses

Background

Medulloblastoma (MB) is the most common intracranial malignant tumor in children. The genes and pathways involved in the pathogenesis of MB are relatively unknown. We aimed to identify potential biomarkers and small-molecule drugs for MB.

Methods

Gene expression profile data sets were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the Limma package in R. Functional annotation, and cell signaling pathway analysis of DEGs was carried out using DAVID and Kobas. A protein-protein interaction network was generated using STRING. Potential small-molecule drugs were identified using CMap.

Result

We identified 104 DEGs (29 upregulated; 75 downregulated). Gene ontology analysis showed enrichment in the mitotic cell cycle, cell cycle, spindle, and DNA binding. Cell signaling pathway analysis identified cell cycle, HIF-1 signaling pathway, and phospholipase D signaling pathway as key pathways. SYN1, CNTN2, FAIM2, MT3, and SH3GL2 were the prominent hub genes and their expression level were verified by RT-qPCR. Vorinostat, resveratrol, trichostatin A, pyrvinium, and prochlorperazine were identified as potential drugs for MB. The five hub genes may be targets for diagnosis and treatment of MB, and the small-molecule compounds are promising drugs for effective treatment of MB.

Conclusion

In this study we obtained five hub genes of MB, SYN1, CNTN2, FAIM2, MT3, and SH3GL2 were confirmed as hub genes. Meanwhile, Vorinostat, resveratrol, trichostatin A, pyrvinium, and prochlorperazine were identified as potential drugs for MB.

Medulloblastomics revisited: biological and clinical insights from thousands of patients

Medulloblastoma, a malignant brain tumour primarily diagnosed during childhood, has recently been the focus of intensive molecular profiling efforts, profoundly advancing our understanding of biologically and clinically heterogeneous disease subgroups. Genomic, epigenomic, transcriptomic and proteomic landscapes have now been mapped for an unprecedented number of bulk samples from patients with medulloblastoma and, more recently, for single medulloblastoma cells. These efforts have provided pivotal new insights into the diverse molecular mechanisms presumed to drive tumour initiation, maintenance and recurrence across individual subgroups and subtypes. Translational opportunities stemming from this knowledge are continuing to evolve, providing a framework for improved diagnostic and therapeutic interventions. In this Review, we summarize recent advances derived from this continued molecular characterization of medulloblastoma and contextualize this progress towards the deployment of more effective, molecularly informed treatments for affected patients.

MeinteR: A framework to prioritize DNA methylation aberrations based on conformational and cis-regulatory element enrichment

DNA methylation studies have been reformed with the advent of single-base resolution arrays and bisulfite sequencing methods, enabling deeper investigation of methylation-mediated mechanisms. In addition to these advancements, numerous bioinformatics tools address important computational challenges, covering DNA methylation calling up to multi-modal interpretative analyses. However, contrary to the analytical frameworks that detect driver mutational signatures, the identification of putatively actionable epigenetic events remains an unmet need. The present work describes a novel computational framework, called MeinteR, that prioritizes critical DNA methylation events based on the following hypothesis: critical aberrations of DNA methylation more likely occur on a genomic substrate that is enriched in cis-acting regulatory elements with distinct structural characteristics, rather than in genomic “deserts”. In this context, the framework incorporates functional cis-elements, e.g. transcription factor binding sites, tentative splice sites, as well as conformational features, such as G-quadruplexes and palindromes, to identify critical epigenetic aberrations with potential implications on transcriptional regulation. The evaluation on multiple, public cancer datasets revealed significant associations between the highest-ranking loci with gene expression and known driver genes, enabling for the first time the computational identification of high impact epigenetic changes based on high-throughput DNA methylation data.

Are molecular subgroups of medulloblastomas really prognostic?

PURPOSE OF REVIEW

Medulloblastoma is no more a unique disease. Clinical and biologic classification used so far are challenged by molecular classification(s). Following the consensus article that described four molecular groups of medulloblastoma in 2012, several articles in 2017 provided more relevant classifications that may impact on further clinical trial design.

RECENT FINDINGS

Though wingless (WNT) and sonic hedgehog (SHH) are defined by the activation of their respective pathways, the age and type of activation define various subgroups with specific features and outcome. Groups 3 and 4 remain ill defined. The whole population of medulloblastoma may be divided in 12 subgroups: WNTαβ, SHHαβγδ, group 3αβγ and group 4αβγ. The paediatric population may be divided in seven subgroups: WNT, SHH of infants and children, and low-risk and high-risk groups 3 and 4. SHH of infants may be divided as iSHH-I vs. iSHH-II that have different prognosis. Moreover, specific drivers of groups 3 and 4 were reported.

SUMMARY

These findings have and will have direct implications on the conception of clinical trials. Low-risk groups will benefit from less toxic therapies, and high-risk groups will benefit from targeted therapies.

Translational control in brain pathologies: biological significance and therapeutic opportunities

Messenger RNA (mRNA) translation is the terminal step in protein synthesis, providing a crucial regulatory checkpoint for this process. Translational control allows specific cell types to respond to rapid changes in the microenvironment or to serve specific functions. For example, neurons use mRNA transport to achieve local protein synthesis at significant distances from the nucleus, the site of RNA transcription. Altered expression or functions of the various components of the translational machinery have been linked to several pathologies in the central nervous system. In this review, we provide a brief overview of the basic principles of mRNA translation, and discuss alterations of this process relevant to CNS disease conditions, with a focus on brain tumors and chronic neurological conditions. Finally, synthesizing this knowledge, we discuss the opportunities to exploit the biology of altered mRNA translation for novel therapies in brain disorders, as well as how studying these alterations can shed new light on disease mechanisms.

Principles of tumorigenesis and emerging molecular drivers of SHH-activated medulloblastomas

SHH-activated medulloblastomas (SHH-MB) account for 25-30% of all medulloblastomas (MB) and occur with a bimodal age distribution, encompassing many infant and adult, but fewer childhood cases. Different age groups are characterized by distinct survival outcomes and age-specific alterations of regulatory pathways. Here, we review SHH-specific genetic aberrations and signaling pathways. Over 95% of SHH-MBs contain at least one driver event - the activating mutations frequently affect sonic hedgehog signaling (PTCH1, SMO, SUFU), genome maintenance (TP53), and chromatin modulation (KMT2D, KMT2C, HAT complexes), while genes responsible for transcriptional regulation (MYCN) are recurrently amplified. SHH-MBs have the highest prevalence of damaging germline mutations among all MBs. TP53-mutant MBs are enriched among older children and have the worst prognosis among all SHH-MBs. Numerous genetic aberrations, including mutations of TERT, DDX3X, and the PI3K/AKT/mTOR pathway are almost exclusive to adult patients. We elaborate on the newest development within the evolution of molecular subclassification, and compare proposed risk categories across emerging classification systems. We discuss discoveries based on preclinical models and elaborate on the applicability of potential new therapies, including BET bromodomain inhibitors, statins, inhibitors of SMO, AURK, PLK, cMET, targeting stem-like cells, and emerging immunotherapeutic strategies. An enormous amount of data on the genetic background of SHH-MB have accumulated, nevertheless, subgroup affiliation does not provide reliable prediction about response to therapy. Emerging subtypes within SHH-MB offer more layered risk stratifications. Rational clinical trial designs with the incorporation of available molecular knowledge are inevitable. Improved collaboration across the scientific community will be imperative for therapeutic breakthroughs.

Molecular markers and potential therapeutic targets in non-WNT/non-SHH (group 3 and group 4) medulloblastomas

Childhood medulloblastomas (MB) are heterogeneous and are divided into four molecular subgroups. The provisional non-wingless-activated (WNT)/non-sonic hedgehog-activated (SHH) category combining group 3 and group 4 represents over two thirds of all MBs, coupled with the highest rates of metastases and least understood pathology. The molecular era expanded our knowledge about molecular aberrations involved in MB tumorigenesis, and here, we review processes leading to non-WNT/non-SHH MB formations.

The heterogeneous group 3 and group 4 MBs frequently harbor rare individual genetic alterations, yet the emerging profiles suggest that infrequent events converge on common, potentially targetable signaling pathways. A mutual theme is the altered epigenetic regulation, and in vitro approaches targeting epigenetic machinery are promising. Growing evidence indicates the presence of an intermediate, mixed signature group along group 3 and group 4, and future clarifications are imperative for concordant classification, as misidentifying patient samples has serious implications for therapy and clinical trials.

To subdue the high MB mortality, we need to discern mechanisms of disease spread and recurrence. Current preclinical models do not represent the full scale of group 3 and group 4 heterogeneity: all of existing group 3 cell lines are MYC-amplified and most mouse models resemble MYC-activated MBs. Clinical samples provide a wealth of information about the genetic divergence between primary tumors and metastatic clones, but recurrent MBs are rarely resected. Molecularly stratified treatment options are limited, and targeted therapies are still in preclinical development. Attacking these aggressive tumors at multiple frontiers will be needed to improve stagnant survival rates.

Origins and clinical relevance of proteoforms in pediatric malignancies

INTRODUCTION

Cancer changes the proteome in complex ways that reach well beyond simple changes in protein abundance. Genomic and transcriptional variations and post-translational protein modification create functional variants of a protein, known as proteoforms. Childhood cancers have fewer genomic alterations but show equally dramatic phenotypic changes as malignant cells in adults. Therefore, unraveling the complexities of the proteome is even more important in pediatric malignancies. Areas covered: In this review, the biological origins of proteoforms and technological advancements in the study of proteoforms are discussed. Particular emphasis is given to their implication in childhood malignancies and the critical role of cancer-specific proteoforms for the next generation of cancer therapies and diagnostics. Expert opinion: Recent advancements in technology have led to a better understanding of the underlying mechanisms of tumorigenesis. This has been critical for the development of more effective and less harmful treatments that are based on direct targeting of altered proteins and deregulated pathways. As proteome coverage and the ability to detect complex proteoforms increase, the most need for change is in data compilation and database availability to mediate high-level data analysis and allow for better functional annotation of proteoforms.

Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.