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Medulloblastoma - BioProject

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Last Updated: 24 July 2022

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Integrative Genomic Analysis of Medulloblastoma Identifies a Molecular Subgroup That Drives Poor Clinical Outcome [DNA copy number]

Medulloblastomas are heterogeneous tumors that collectively account for children's most common malignant brain tumor. Six molecular subgroups of medulloblastoma have been identified, each with a unique combination of numerical and chromosomal aberrations that globally influence mRNA and miRNA expression. A previously unidentified molecular subgroup is significantly lower in event-free and overall survivals, with rises in c-MYC copy number increases and transcriptionally by enrichment of photoreceptor pathways and increased miR-183-96-182 expression, as a whole. On 115 and 98 of these, respectively, we reviewed the mRNA transcriptome of 194 medulloblastomas and performed high-density single nucleotide polymorphism array and miRNA analysis. Signal intensities and genotype calls were obtained by using Affymetrix 250K Sty arrays or Affymetrix 6. 0 arrays to obtain signal intensities and genotype numbers.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/857031


Primary cilia control translation and the cell cycle in medulloblastoma

For most tumors, the presence or absence of primary cilia is a distinguishing feature of a given tumor type; however, whether and how the primary cilium contributes to tumor formation is uncertain. Medulloblastoma is a common pediatric brain tumor that affects four groups: SHH, WNT, group 3, and group 4. Primary cilia are abundant in SHH and WNT MBs, but not so prevalent in G3 and G4 MBs, according to 111 cases of MB. In addition, we extend the function of primary cilia to translation control and describe a molecular mechanism by which cilia regulate cell cycle progression in both normal and pathologic conditions, providing new frameworks for investigating cilia function in normal and pathological conditions. Overall design: 3 WNT MB mouse models used for experiments were used for experiments, and 3 shIft88 knocked down WNT MB mouse models used for comparison and data analysis.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/853310


Spatial transcriptomic analysis of Sonic Hedgehog Medulloblastoma identified that loss of heterogeneity and promotion of differentiation underlies the response to CDK4/6 inhibition

Our analysis indicates that SHH tumours in the mouse brain possess multiple malignant transcriptional states, emphasizing the extent of intratumoural cellular diversity found in primary human SHH MB. This research is, to the best of our knowledge, the first spatially confirmed gene expression atlas of SHH PDOX MB and serves as a proof-of-principle for the use of ST-seq in determining spatially-organised tumour heterogeneity of MB.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/850254


PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [mouse]

Medulloblastoma is divided into four categories, including SHH medulloblastoma, which is characterised by elevated SHH signaling and a cerebellum granule neuron precursor cell-of-origin. Complex 2 of histone H3K27 methyltransferase polycomb repressor complex 2 is often heterogeneous within particular SHH medulloblastoma tumors, according to here. Complete deletion of the PRC2 core subunit EED in mouse models reduced tumor formation, while a mosaic deletion of EED greatly boosted tumor formation. Medulloblastoma progression in SHH were shown to be both relevant and sufficient for SHH medulloblastoma progression. Surprisingly, medulloblastomas with mosaic EED increased faster than control wildtype tumors and revealed higher amounts of oncogenes such as Igf2, which are specifically suppressed by PRC2 and are therefore both essential and sufficient for SHH medulloblastoma progression. IGF2 modulated tumor growth-inhibition by PRC2 heterogeneity. EEDlow cells can promote EEDhigh cell growth in a human medulloblastoma cell line with different EED levels, according to EEDlow clones, which stimulate EEDhigh cell proliferation by crine IGF2 signaling.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/848790


PRC2 Heterogeneity Drives Tumor Growth in Medulloblastoma [Human]

Medulloblastoma is divided into four subtypes, including SHH medulloblastoma, which is characterized by elevated SHH signaling and a cerebellum granule neuron precursor cell-of-origin. The histone H3K27 methyltransferase polycomb repressor complex 2 in particular SHH medulloblastoma tumors is often heterogeneous within individual SHH medulloblastoma tumors, as shown here. Complete deletion of the PRC2 core subunit EED in mouse models reduced tumor formation, while a mosaic deletion of EED significantly increased tumor growth. Mesulloblastoma progression in SHH Medulloblastoma was discovered to be both appropriate and sufficient for SHH medulloblastoma progression. Surprisingly, medulloblastomas with mosaic EED growth grew faster than control wildtype tumors, as well as increased amounts of oncogenes such as Igf2, which is specifically repressed by PRC2 and has been shown to be both essential and sufficient for SHH medulloblasto medoma progression. PRC2 heterogeneity in tumor formation was oncogenic factors of IGF2 proliferation, according to IGF2. EEDlow cells can promote EEDhigh cell proliferation through crine IGF2 signaling, according to estimating clones of a human medulloblastoma cell line with different EED levels.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/848779


Integrative Genomic Analysis of Medulloblastoma Identifies a Molecular Subgroup That Drives Poor Clinical Outcome

Medulloblastomas are heterogeneous tumors that collectively characterize children's most common malignant brain tumor. Six molecular subgroups of medulloblastoma have been identified, each with a unique combination of numerical and structural chromosomal aberrations that can influence mRNA and miRNA expression globally. The c-MYC copy number increases and transcriptionally by enrichment of photoreceptor pathways and increased miR-183-96-182 expression, as a whole, is associated with significantly lower rates of event-free and overall survivals. We reviewed the transcriptome of 194 medulloblastomas and performed high-density single nucleotide polymorphism array and miRNA analysis on 115 and 98 of these, respectively, as part of the overall scheme. For each, non-negative matrix factorization-based clustering of mRNA expression results was used to identify molecular subgroups of medulloblastoma; DNA copy number, miRNA profiles, and clinical findings were evaluated; for each.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/834075


Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Feature

Under institutional review board approval, matched blood samples were obtained from the COG Tumor Bank and Children's Hospital Boston. Pomeroy et al. 's data set contained another series of 47 samples was collected from the Pomeroy et al. database. Kool et al. The remaining 16 samples were all with DNA copy number information, and all of them had DNA copy number information, and all had DNA copy number information. Finished design: From a research cohort of 96 children treated for medulloblastoma, a Bayesian cumulative log-odds model of outcome was created, starting with the evidence derived from disease subtype-independence and disease subtype-dependent pathways, and then finally adding genetic information about disease subtype-dependent and disease subtype-dependent pathways, with increasing frequency of genetic mutations spanning high-level genomic abnormalities. Samples were used for Affymetrix gene expression profiling in total 62 medulloblastoma samples. Patients of Medulloblastoma were treated with craniospinal radiation therapy in 2,400 percentiGray in Medulloblastoma, with a tumour dose of 5,300 u20137,200 cGy. Patients with medulloblastoma were treated with chemotherapy containing cisplatin and vincristine, as well as multiple combinations of carboplatin, etoposide, cyclophosphamide, or lumustine. The data were split into three groups: data set A; data set B; and data set C. Supplementary Information II includes the clinical characteristics of each of the patients in the study. Microarray intensity was corrected using a linear scaling algorithm as detailed in Supplementary Information I. Scans were rejected if the scaling factor exceeded 3, but fewer than 1,000 genes were retrieved u2018 present>u2019 calls were received, or microarray artefacts were apparent.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/832260


RNAseq of 6 medulloblastoma cell lines

Six medulloblastoma cell lines, DAOY, ONS-76, D458, CHLA-01-MED, CHLA-01R-MED, CHLA-01-MED, CHLA-01R-MED, DAOY, D458, DWAY, CHLA-01-MED, CHLA-01-CHLA-01-P, CHLA-76, DROY, CHLA-01-CHLA-01-CHLA-01R-MED, CHLA-01-MED, CHLA-01R-MED, CHLA-01-MED, CHLA-01R-MED, CHLA-01H, CHLA-01R-MED, CHLA-01-MED, CHLA-01R Methods: When 70% confluency was achieved, tens of different subgroups were cultured and cell lines representing the various subgroups were cultured and cell lines, as well as RNA isolation. DAOY and D458 were grown in DMEM with 10% FBS, ONS-76, and CHLA-01-01-MED were grown in RPMI 1640, supplemented with B27, 20 ng/ml EGF, and 20 ng/ml bFGF. During the course of this research, all cell lines were consistently found to be mycoplasma negative. Cell pellets of at least 100,000 cells were washed with HBSS and frozen in liquid nitrogen. According to the manufacturer's instructions, total RNA was isolated from 2D pellets using the NucleoSpin RNA Plus Kit. RNA amounts were determined using the Qubit RNA BR kit with the Qubit 4 for the Qubit 4. Following sequencing, quality control of the sequencing results was performed, which showed that all samples had high quality scores, indicating good technical results of the sequencing. Using the Cutadapt package [reference], we used FastQC to perform quality checks of raw RNA samples followed by adapter and low quality read filtering using the Cutadapt package. Unique reads from genome alignment were processed, and transcript abundance quantification was performed using the featureCount software. As input into edgeR, STAR read counts were used. Genes with read counts greater than ten in three or more samples were retained for subsequent testing.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/812473


Disease-associated KBTBD4 mutations in medulloblastoma elicit neomorphic ubiquitylation activity to promote CoREST degradation

The Cullin RING Ligases' ligases assemble into multiprotein complexes to diversify substrate adaptors and guarantee selectivity in substrate engagement for degradation. Here we discuss a novel process by which mutations in substrate adaptors can lead to cancer neo-substrate degradation. In a subset of non-WNT/non-SHH medulloblastomas, KBTBD4 is a CRL3 substrate adaptor harboring recurrent indel mutations in a subset of non-WNT/non-SHH medulloblastomas. These findings show mutation-driven neomorphic E3 ligase activity as a previously unknown process in tumor formation, with implications for medulloblastoma pathogenesis and therapy. Overall construction: D283MED cell lines conditionally expressing KBTBD4 WT, R313PRR, or P311PR.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/809413


Beta-blockers disrupt mitochondrial bioenergetics and increase radiotherapy efficacy independently of beta-adrenergic receptors in medulloblastoma.

Propranolol, carvedilol, and nebivolol reduced medulloblastoma cell formation and invasion by altering energy metabolism pathways and inducing a metabolic disease that deprived tumor cells of their adaptive bioenergetics capacities. The resulting cell lines, i. e. , ONS-76 RP, ONS-76 RC, and ONS-76 RN, all displayed a higher mitochondrial OCR and ATP production than the sensitive parental ONS-76 WT cells. Cell death could not be explained by the down-regulation of essential proteins of the u03b2-AR downstream signaling, such as the adenylate cyclase or their transcriptional targets, according to the adenylate cyclase or their transcriptional targets.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/789912

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions