Most human cancers develop from stem and progenitor cell populations through the sequential accumulation of various genetic and epigenetic alterations. Cancer stem cells have been identified from medulloblastoma (MB), but a comprehensive understanding of MB stemness, including the interactions between the tumor immune microenvironment and MB stemness, is lacking. Here, we employed a trained stemness index model based on an existent one‐class logistic regression (OCLR) machine‐learning method to score MB samples; we then obtained two stemness indices, a gene expression‐based stemness index (mRNAsi) and a DNA methylation‐based stemness index (mDNAsi), to perform an integrated analysis of MB stemness in a cohort of primary cancer samples (n = 763). We observed an inverse trend between mRNAsi and mDNAsi for MB subgroup and metastatic status. By applying the univariable Cox regression analysis, we found that mRNAsi significantly correlated with overall survival (OS) for all MB patients, whereas mDNAsi had no significant association with OS for all MB patients. In addition, by combining the Lasso‐penalized Cox regression machine‐learning approach with univariate and multivariate Cox regression analyses, we identified a stemness‐related gene expression signature that accurately predicted survival in patients with Sonic hedgehog (SHH) MB. Furthermore, positive correlations between mRNAsi and prognostic copy number aberrations in SHH MB, including MYCN amplifications and GLI2 amplifications, were detected. Analyses of the immune microenvironment revealed unanticipated correlations of MB stemness with infiltrating immune cells. Lastly, using the Connectivity Map, we identified potential drugs targeting the MB stemness signature. Our findings based on stemness indices might advance the development of objective diagnostic tools for quantitating MB stemness and lead to novel biomarkers that predict the survival of patients with MB or the efficacy of strategies targeting MB stem cells.

This overview seeked to bring together the microRNA (miRNA) researches on biogenesis and bio-function in these areas of clinical diagnosis and therapy for malignant glioma. Using the keyword terms "glioma" and "miRNA," we performed the literature search in PubMed, Ovid, and web.metstr.com databases from their inception to October 2014. In screening out the quality of the articles, factors such as clinical setting of the study, the size of clinical samples were taken into consideration. Animal studied for verification and reviews article were also included in our data collection. Despite many advance in miRNA for malignant glioma, further studies were still required to focus on the following aspects: (i) Improving the understanding about biogenesis of miRNA and up-down regulation; (ii) utilizing high-throughput miRNA expression analysis to screen out the core miRNA for glioma; (iii) Focusing related miRNAs on the signal transduction pathways that regulate the proliferation and growth of glioma. We discussed the most promising miRNA, correlative signaling pathway and their relation with gliomas in the way of prompting miRNA target into being a clinical therapeutic strategy.

Background: Glioblastoma multiforme (GBM) remains to be one of the top lethal cancer types for adult to date. Current GBM therapies suffer greatly from the highly heterogeneous and adaptable nature of GBM cells, indicating an urgent need of alternative therapeutic options. In this study, we focused on identifying novel epigenetic targeted strategy against GBM. Methods: A collection of epigenetic modulating small molecules were subjected to anti-GBM screening and the inhibitory effect of identified agent was validated both in vitro and in vivo. Genetic targeting approaches were also used to verify the on-target inhibitory effect of identified agent. Furthermore, the inhibitory mechanism of identified agent was investigated by integrative analyses of drug-treated GBM cells and GBM tumor databases. Results: The covalent CDK7 inhibitor THZ1 was one of the top hits in our screening and its anti-GBM activity was confirmed both in vitro and in vivo. CDK7 inhibition through CRISPR-Cas9 or RNA interference also markedly disrupted GBM cell growth. Furthermore, analyses of multiple GBM tumor databases consistently revealed that CDK7 expression was significantly elevated in GBM compared with normal brain tissues and lower grade gliomas. Higher CDK7 expression was correlated with worse prognosis for both glioma and GBM. Mechanistically, THZ1 treatment led to considerable disruption of global gene transcription in GBM cells, preferentially targeting those associated with super-enhancers (SEs). We also showed that THZ1 sensitive and SE-related genes had important roles for GBM growth.
Conclusion: Our study shows that targeting SE-associated transcription addiction by CDK7 inhibition could be an effective therapeutic strategy against GBM.

Glioblastoma (GBM) is the most common and most malignant primary brain cancer in adults. Despite multimodality treatment, the prognosis is still poor. Therefore, further work is urgently required to discover novel therapeutic strategies for GBM treatment. The synergistic effects of cotreatment with the histone deacetylase (HDAC) inhibitor panobinostat and bromodomain inhibitor JQ1 or OTX015 were validated using cell viability assays in GBM cell lines. Furthermore, the inhibitory mechanisms were investigated via an EdU proliferation assay, an apoptosis assay, qPCR, Western blot and RNAseq analyses. We found that the cotreatment with panobinostat and JQ1 or OTX015 synergistically inhibited cell viability in GBM cells. The cotreatment with panobinostat and JQ1 or OTX015 markedly inhibited cell proliferation and induced apoptosis in GBM cells. Compared with treatment with each drug alone, the cotreatment with panobinostat and JQ1 induced more profound caspase 3/7 activation and cytotoxicity. Mechanistic investigation showed that combination of panobinostat with JQ1 or OTX015 results in stronger repression of GBM-associated oncogenic genes or pathways as well as higher induction of GBM-associated tumor-suppressive genes. Our study demonstrated that HDAC inhibitor and bromodomain inhibitor had synergistical efficacy against GBM cells. The cotreatment with HDAC inhibitor and bromodomain inhibitor warrants further attention in GBM therapy.