Genome, transcriptome, and metabolome analyses provide new insights into the resource development in an edible fungus Dictyophora indusiata.

Dictyophora indusiata (Vent. Ex Pers.) Fisch. (DI) is an edible and medicinal fungus widely used in East Asian countries. However, during DI cultivation, the formation of fruiting bodies cannot be regulated, which leads to yield and quality losses. The present study performed a combined genome, transcriptome, and metabolome analysis of DI. Using Nanopore and Illumina sequencing approaches, we created the DI reference genome, which was 67.32 Mb long with 323 contigs. We identified 19,909 coding genes on this genome, of which 46 gene clusters were related to terpenoid synthesis. Subsequent transcriptome sequencing using five DI tissues (cap, indusia, mycelia, stipe, and volva) showed high expression levels of genes in the cap, indicating the tissue's importance in regulating the fruiting body formation. Meanwhile, the metabolome analysis identified 728 metabolites from the five tissues. Mycelium was rich in choline, while volva was rich in dendronobilin; stipe had monosaccharides as the primary component, and the cap was the main source of indole acetic acid (IAA) synthesis. We confirmed the importance of tryptophan metabolism for DI fruiting body differentiation based on KEGG pathway analysis. Finally, the combined multiomics analysis identified three new genes related to IAA synthesis of the tryptophan metabolic pathway in the cap, which may regulate DI fruiting body synthesis and improve DI quality. Thus, the study's findings expand our understanding of resource development and the molecular mechanisms underlying DI development and differentiation. However, the current genome is still a rough draft that needs to be strengthened.

Oct4A palmitoylation modulates tumorigenicity and stemness in human glioblastoma cells.

BACKGROUND: Glioblastoma multiforme and other solid malignancies are heterogeneous, containing subpopulations of tumor cells that exhibit stem characteristics. Oct4, also known as POU5F1, is a key transcription factor in the self-renewal, proliferation, and differentiation of stem cells. Although it has been detected in advanced gliomas, the biological function of Oct4, and transcriptional machinery maintained by the stemness of Oct4 protein-mediated glioma stem cells (GSC), has not been fully determined. METHODS: The expression of Oct4 variants was evaluated in brain cancer cell lines, and in brain tumor tissues, by quantitative real-time PCR, western blotting, and immunohistochemical analysis. The palmitoylation level of Oct4A was determined by the acyl-biotin exchange method, and the effects of palmitoylation Oct4A on GSCs were investigated by a series of in vitro (neuro-sphere formation assay, double immunofluorescence, pharmacological treatment, luciferase assay, and coimmunoprecipitation) and in vivo (xenograft model) experiments. RESULTS: Here, we report that all three variants of Oct4 are expressed in different types of cerebral cancer, while Oct4A is important for maintaining tumorigenicity in GSCs. Palmitoylation mediated by ZDHHC17 was indispensable for preserving Oct4A from lysosome degradation to maintain its protein stability. Oct4A palmitoylation also helped to integrate Sox4 and Oct4A in the SOX2 enhancement subregion to maintain the stem performance of GSCs. We also designed Oct4A palmitoylation competitive inhibitors, inhibiting the self-renewal ability and tumorigenicity of GSCs. CONCLUSIONS: These findings indicate that Oct4A acts on the tumorigenic activity of glioblastoma, and Oct4A palmitoylation is a candidate therapeutic target.

Systematic transcriptome profiling of pyroptosis related signature for predicting prognosis and immune landscape in lower grade glioma.

BACKGROUND: Pyroptosis is a programmed cell death mediated by the gasdermin superfamily, accompanied by inflammatory and immune responses. Exogenously activated pyroptosis is still not well characterized in the tumor microenvironment. Furthermore, whether pyroptosis-related genes (PRGs) in lower-grade glioma (LGG) may be used as a biomarker remains unknown. METHODS: The RNA-Sequencing and clinical data of LGG patients were downloaded from publicly available databases. Bioinformatics approaches were used to analyze the relationship between PRGs and LGG patients' prognosis, clinicopathological features, and immune status. The NMF algorithm was used to differentiate phenotypes, the LASSO regression model was used to construct prognostic signature, and GSEA was used to analyze biological functions and pathways. The expression of the signature genes was verified using qRT-PCR. In addition, the L1000FWD and CMap tools were utilized to screen potential therapeutic drugs or small molecule compounds and validate their effects in glioma cell lines using CCK-8 and colony formation assays. RESULTS: Based on PRGs, we defined two phenotypes with different prognoses. Stepwise regression analysis was carried out to identify the 3 signature genes to construct a pyroptosis-related signature. After that, samples from the training and test cohorts were incorporated into the signature and divided by the median RiskScore value (namely, Risk-H and Risk-L). The signature shows excellent predictive LGG prognostic power in the training and validation cohorts. The prognostic signature accurately stratifies patients according to prognostic differences and has predictive value for immune cell infiltration and immune checkpoint expression. Finally, the inhibitory effect of the small molecule inhibitor fedratinib on the viability and proliferation of various glioma cells was verified using cell biology-related experiments. CONCLUSION: This study developed and validated a novel pyroptosis-related signature, which may assist instruct clinicians to predict the prognosis and immunological status of LGG patients more precisely. Fedratinib was found to be a small molecule inhibitor that significantly inhibits glioma cell viability and proliferation, which provides a new therapeutic strategy for gliomas.

GSK3ß palmitoylation mediated by ZDHHC4 promotes tumorigenicity of glioblastoma stem cells in temozolomide-resistant glioblastoma through the EZH2-STAT3 axis.

Glioblastoma stem cells (GSCs) are a highly tumorigenic cell subgroup of glioblastoma (GBM). Glycogen synthase kinase 3ß (GSK3ß) is considered a key hub for promoting malignant phenotypes in GBM. However, the functional relationships between GSK3ß and GSCs in GBM are unclear. Here, we found that GSK3ß was noted as a substrate for ZDHHC4-mediated palmitoylation at the Cys14 residue, which enhanced GBM temozolomide (TMZ) resistance and GSC self-renewal. Clinically, the expression level of ZDHHC4 was upregulated in GBM, which significantly correlated with tumor grade and poor prognosis. The above phenotypes were based on decreasing p-Ser9 and increasing p-Tyr216 by GSK3ß palmitoylation, which further activated the enhancer of the zeste homolog 2 (EZH2)-STAT3 pathway. Notably, STAT3 silencing also inhibited ZDHHC4 expression. This study revealed that GSK3ß palmitoylation mediated by ZDHHC4 improved the stemness of TMZ-resistant GBM by activating the EZH2-STAT3 signaling axis, providing a new theoretical basis for further understanding the mechanism of TMZ resistance and recurrence after treatment.

SETD2 Palmitoylation Mediated by ZDHHC16 in Epidermal Growth Factor Receptor-Mutated Glioblastoma Promotes Ionizing Radiation-Induced DNA Damage.

PURPOSE: The prevalence of epidermal growth factor receptor (EGFR) mutations in glioblastoma multiforme (GBM) has elicited a significant focus on EGFR as a potential drug target. However, no significant clinical advancement in GBM treatment has occurred. METHODS AND MATERIALS: Bioinformatics analysis, western blotting, immunofluorescence, and immunohistochemistry were performed to detect the expression of ZDHHC16 and genetic EGFR alterations in GBM. The biological function of ZDHHC16/SETD2/H3K36me3 signaling axis after EGFR alterations was demonstrated by various in vitro (pharmacologic treatment, flow cytometry, transwell migration assay, and coimmunoprecipitation) and in vivo (xenograft model) experiments. RESULTS: We demonstrate that the ZDHHC16/SETD2/H3K36me3 signaling axis was inactivated in EGFR-altered GBM. ZDHHC16 was downregulated in GBM versus normal brain tissue; this was significantly related to EGFR alterations. These events contributed to p53 activation, halting cells at the G1/S checkpoint. Furthermore, DNA damage repair signaling in EGFR-amplified GBMs was affected after ionizing radiation-induced DNA damage via reduced SETD2 palmitoylation and methylation of its target, H3K36. Our findings suggest that a depalmitoylation inhibitor, PalmB, is useful as a potentially novel adjuvant treatment for patients with GBM undergoing radiation therapy. CONCLUSIONS: Our data present novel mechanistic evidence relating to signaling pathways with DNA damage responses in EGFR-mutated GBM.

Heterogeneity of subsets in glioblastoma mediated by Smad3 palmitoylation.

Glioblastoma (GBM) is the most common and deadly of the primary intracranial tumors and is comprised of subsets that show plasticity and marked heterogeneity, contributing to the lack of success in genomic profiling to guide development of precision medicine for these tumors. In this study, a mutation in isocitrate dehydrogenase 1 was found to suppress the transforming growth factor-beta signaling pathway and E2F4 interacted with Smad3 to inhibit expression of mesenchymal markers. However, palmitoylation of Smad3 mediated by palmitoyltransferase ZDHHC19 promoted activation of the transforming growth factor-beta signaling pathway, and its interaction with EP300 promoted expression of mesenchymal markers in the mesenchymal subtype of GBM. Smad3 and hypoxia-inducible factor 1-alpha may be important molecular targets for treatment of glioma because they appear to coordinate the basic aspects of cancer stem cell biology.

Constitutive BAK/MCL1 complexes predict paclitaxel and S63845 sensitivity of ovarian cancer.

We previously found that preformed complexes of BAK with antiapoptotic BCL2 proteins predict BH3 mimetic sensitivities in lymphohematopoietic cells. These complexes have not previously been examined in solid tumors or in the context of conventional anticancer drugs. Here we show the relative amount of BAK found in preformed complexes with MCL1 or BCLXL varies across ovarian cancer cell lines and patient-derived xenografts (PDXs). Cells bearing BAK/MCL1 complexes were more sensitive to paclitaxel and the MCL1 antagonist S63845. Likewise, PDX models with BAK/MCL1 complexes were more likely to respond to paclitaxel. Mechanistically, BIM induced by low paclitaxel concentrations interacted preferentially with MCL1 and displaced MCL1-bound BAK. Further studies indicated that cells with preformed BAK/MCL1 complexes were sensitive to the paclitaxel/S63845 combination, while cells without BAK/MCL1 complexes were not. Our study suggested that the assessment of BAK/MCL1 complexes might be useful for predicting response to paclitaxel alone or in combination with BH3 mimetics.

Local anesthetics impair the growth and self-renewal of glioblastoma stem cells by inhibiting ZDHHC15-mediated GP130 palmitoylation.

BACKGROUND: A large number of preclinical studies have shown that local anesthetics have a direct inhibitory effect on tumor biological activities, including cell survival, proliferation, migration, and invasion. There are few studies on the role of local anesthetics in cancer stem cells. This study aimed to determine the possible role of local anesthetics in glioblastoma stem cell (GSC) self-renewal and the underlying molecular mechanisms. METHODS: The effects of local anesthetics in GSCs were investigated through in vitro and in vivo assays (i.e., Cell Counting Kit 8, spheroidal formation assay, double immunofluorescence, western blot, and xenograft model). The acyl-biotin exchange method (ABE) assay was identified proteins that are S-acylated by zinc finger Asp-His-His-Cys-type palmitoyltransferase 15 (ZDHHC15). Western blot, co-immunoprecipitation, and liquid chromatograph mass spectrometer-mass spectrometry assays were used to explore the mechanisms of ZDHHC15 in effects of local anesthetics in GSCs. RESULTS: In this study, we identified a novel mechanism through which local anesthetics can damage the malignant phenotype of glioma. We found that local anesthetics prilocaine, lidocaine, procaine, and ropivacaine can impair the survival and self-renewal of GSCs, especially the classic glioblastoma subtype. These findings suggest that local anesthetics may weaken ZDHHC15 transcripts and decrease GP130 palmitoylation levels and membrane localization, thus inhibiting the activation of IL-6/STAT3 signaling. CONCLUSIONS: In conclusion, our work emphasizes that ZDHHC15 is a candidate therapeutic target, and local anesthetics are potential therapeutic options for glioblastoma.

A Novel Counterfeit Feature Extraction Technique for Exposing Face-Swap Images Based on Deep Learning and Error Level Analysis.

The quality and efficiency of generating face-swap images have been markedly strengthened by deep learning. For instance, the face-swap manipulations by DeepFake are so real that it is tricky to distinguish authenticity through automatic or manual detection. To augment the efficiency of distinguishing face-swap images generated by DeepFake from real facial ones, a novel counterfeit feature extraction technique was developed based on deep learning and error level analysis (ELA). It is related to entropy and information theory such as cross-entropy loss function in the final softmax layer. The DeepFake algorithm is only able to generate limited resolutions. Therefore, this algorithm results in two different image compression ratios between the fake face area as the foreground and the original area as the background, which would leave distinctive counterfeit traces. Through the ELA method, we can detect whether there are different image compression ratios. Convolution neural network (CNN), one of the representative technologies of deep learning, can extract the counterfeit feature and detect whether images are fake. Experiments show that the training efficiency of the CNN model can be significantly improved by the ELA method. In addition, the proposed technique can accurately extract the counterfeit feature, and therefore achieves outperformance in simplicity and efficiency compared with direct detection methods. Specifically, without loss of accuracy, the amount of computation can be significantly reduced (where the required floating-point computing power is reduced by more than 90%).

Protein Palmitoylation Regulates Cell Survival by Modulating XBP1 Activity in Glioblastoma Multiforme.

Glioblastoma multiforme (GBM) almost invariably acquires an invasive phenotype, resulting in limited therapeutic options. Protein palmitoylation markedly affects tumorigenesis and malignant progression in GBM. The role of protein palmitoylation in GBM, however, has not been systematically reported. This study aimed to investigate the effect of protein palmitoylation on GBM cell survival and the cell cycle. In this study, most palmitoyltransferases were upregulated in GBM and its cell lines, and protein palmitoylation participated in signaling pathways controlling cell survival and the GBM cell cycle. Inhibition of protein palmitoylation with substrate-analog inhibitors, that is, 2-bromopalmitate, cerulenin, and tunicamycin, induced G2 cell cycle arrest and cell death in GBM cells through enhanced endoplasmic reticulum (ER) stress. These effects are primarily attributed to the palmitoylation inhibitors activating pro-apoptotic pathways and ER stress signals. Further analysis revealed was the accumulation of SUMOylated XBP1 (X-box binding protein 1) and its transcriptional repression, along with a reduction in XBP1 palmitoylation. Taken together, the present results indicate that protein palmitoylation plays an important role in the survival of GBM cells, further providing a potential therapeutic strategy for GBM.

Molecular subtyping of glioblastoma based on immune-related genes for prognosis.

Glioblastoma (GBM) is associated with an increasing mortality and morbidity and is considered as an aggressive brain tumor. Recently, extensive studies have been carried out to examine the molecular biology of GBM, and the progression of GBM has been suggested to be correlated with the tumor immunophenotype in a variety of studies. Samples in the current study were extracted from the ImmPort and TCGA databases to identify immune-related genes affecting GBM prognosis. A total of 92 immune-related genes displaying a significant correlation with prognosis were mined, and a shrinkage estimate was conducted on them. Among them, the 14 most representative genes showed a marked correlation with patient prognosis, and LASSO and stepwise regression analysis was carried out to further identify the genes for the construction of a predictive GBM prognosis model. Then, samples in training and test cohorts were incorporated into the model and divided to evaluate the efficiency, stability, and accuracy of the model to predict and classify the prognosis of patients and to identify the relevant immune features according to the median value of RiskScore (namely, Risk-H and Risk-L). In addition, the constructed model was able to instruct clinicians in diagnosis and prognosis prediction for various immunophenotypes.

Supervillin promotes tumor angiogenesis in liver cancer.

Tumor angiogenesis is a hallmark of liver cancer and is necessary for tumor growth and progression. Supervillin (SVIL) is highly expressed and implicated in several malignant processes of liver cancer. However, the functional relationships between SVIL and tumor angiogenesis in liver cancer have not yet been fully elucidated. The present study was based on bioinformatics analysis, patient tissue sample detection, three­dimensional simulated blood vessel formation, a series of cytological experiments and mouse models. The results demonstrated the important role of SVIL in the progression of malignant liver cancer and tumor angiogenesis, both in terms of vasculogenic mimicry (VM) and endothelium­dependent vessel (EDV) development. SVIL knockdown inhibited VM formation and induced tumor cell apoptosis via the VEGF­p38 signaling axis and through various VM­associated transcriptional factors, including vascular endothelial­cadherin, matrix metalloproteinase 9/12 and migration­inducing protein 7. SVIL may therefore be considered a potential tumor vascular biomarker and a promising therapeutic target for patients with liver cancer.

Chemotherapy-induced pyroptosis is mediated by BAK/BAX-caspase-3-GSDME pathway and inhibited by 2-bromopalmitate.

Many chemotherapy treatments induce apoptosis or pyroptosis through BAK/BAX-dependent mitochondrial pathway. BAK/BAX activation causes the mitochondrial outer membrane permeabilization (MOMP), which induces the activation of pro-apoptotic caspase cascade. GSDME cleavage by the pro-apoptotic caspases determines whether chemotherapy drug treatments induce apoptosis or pyroptosis, however, its regulation mechanisms are not clear. In this study, we showed that TNFα+CHX and navitoclax-induced cancer cell pyroptosis through a BAK/BAX-caspase-3-GSDME signaling pathway. GSDME knockdown inhibited the pyroptosis, suggesting the essential role of GSDME in this process. Interestingly, GSDME was found to be palmitoylated on its C-terminal (GSDME-C) during chemotherapy-induced pyroptosis, while 2-bromopalmitate (2-BP) could inhibit the GSDME-C palmitoylation and chemotherapy-induced pyroptosis. Mutation of palmitoylation sites on GSDME also diminished the pyroptosis induced by chemotherapy drugs. Moreover, 2-BP treatment increased the interaction between GSDME-C and GSDME-N, providing a potential mechanism of this function. Further studies indicated several ZDHHC proteins including ZDHHC-2,7,11,15 could interact with and palmitoylate GSDME. Our findings offered new targets to achieve the transformation between chemotherapy-induced pyroptosis and apoptosis.

Activation of JNK and p38 MAPK Mediated by ZDHHC17 Drives Glioblastoma Multiforme Development and Malignant Progression.

Rationale: Glioblastoma multiforme (GBM) almost invariably gain invasive phenotype with limited therapeutic strategy and ill-defined mechanism. By studying the aberrant expression landscape of gliomas, we find significant up-regulation of p-MAPK level in GBM and a potent independent prognostic marker for overall survival. DHHC family was generally expressed in glioma and closely related to the activation of MAPK signaling pathway, but its role and clinical significance in GBM development and malignant progression are yet to be determined. Method: Bioinformatics analysis, western blotting and immunohistochemistry (IHC) were performed to detect the expression of ZDHHC17 in GBM. The biological function of ZDHHC17 was demonstrated by a series of in vitro and in vivo experiments. Pharmacological treatment, flow cytometry, Transwell migration assay, Co- Immunoprecipitation and GST pulldown were carried out to demonstrate the potential mechanisms of ZDHHC17. Results: ZDHHC17 is up-regulated and coordinated with MAPK activation in GBM. Mechanistically, ZDHHC17 interacts with MAP2K4 and p38/JNK to build a signaling module for MAPK activation and malignant progression. Notably, the ZDHHC17-MAP2K4-JNK/p38 signaling module contributes to GBM development and malignant progression by promoting GBM cell tumorigenicity and glioma stem cell (GSC) self-renewal. Moreover, we identify a small molecule, genistein, as a specific inhibitor to disrupt ZDHHC17-MAP2K4 complex formation for GBM cell proliferation and GSC self-renewal. Moreover, genistein, identified herein as a lead candidate for ZDHHC17-MAP2K4 inhibition, demonstrated potential therapeutic effect in patients with ZDHHC17-expressing GBM. Conclusions: Our study identified disruption of a previously unrecognized signaling module as a target strategy for GBM treatment, and provided direct evidence of the efficacy of its inhibition in glioma using a specific inhibitor.

Specific glioblastoma multiforme prognostic-subtype distinctions based on DNA methylation patterns.

DNA methylation is an important regulator of gene expression, and plays a significant role in carcinogenesis in the brain. Here, we explored specific prognosis-subtypes based on DNA methylation status using 138 Glioblastoma Multiforme (GBM) samples from The Cancer Genome Atlas (TCGA) database. The methylation profiles of 11,637 CpG sites that significantly correlated with survival in the training set were employed for consensus clustering. We identified three GBM molecular subtypes, and their survival curves were distinct from each other. Furthermore, ten feature CpG sites were obtained on conducting a weighted gene co-expression network analysis (WGCNA) of the CpG sites. We were able to classify the samples into high- and low-methylation groups, and classified the prognosis information of the samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained in the test set and clinical GBM specimens. Finally, we found that a positive relationship existed between methylation level and sensitivity to temozolomide (or radiotherapy) or anti-migration ability of GBM cells. Taken together, these results suggest that the model constructed in this study could help explain the heterogeneity of previous molecular subgroups in GBM and can provide guidance to clinicians regarding the prognosis of GBM.

Systematic Profiling of Alternative mRNA Splicing Signature for Predicting Glioblastoma Prognosis.

Emerging evidence suggests that alternative splicing (AS) is modified in cancer and is associated with cancer progression. Systematic analysis of AS signature in glioblastoma (GBM) is lacking and is greatly needed. We profiled genome-wide AS events in 498 GBM patients in TCGA using RNA-seq data, and splicing network and prognostic predictor were built by integrated bioinformatics analysis. Among 45,610 AS events in 10,434 genes, we detected 1,829 AS events in 1,311 genes, and 1,667 AS events in 1,146 genes that were significantly associated with overall survival and disease-free survival of GBM patients, respectively. Five potential feature genes, S100A4, ECE2, CAST, ASPH, and LY6K, were discovered after network mining as well as correlation analysis between AS and gene expression, most of which were related to carcinogenesis and development. Multivariate survival model analysis indicated that these five feature genes could classify the prognosis at AS event and gene expression level. This report opens up a new avenue for exploration of the pathogenesis of GBM through AS, thus more precisely guiding clinical treatment and prognosis judgment.

Specific Glioma Prognostic Subtype Distinctions Based on DNA Methylation Patterns.

DNA methylation is an important regulator of gene expression and may provide an important basis for effective glioma diagnosis and therapy. Here, we explored specific prognosis subtypes based on DNA methylation status using 653 gliomas from The Cancer Genome Atlas (TCGA) database. Five subgroups were distinguished by consensus clustering using 11,637 cytosines preceding a guanosine (CpGs) that significantly influenced survival. The specific DNA methylation patterns were correlated with age, tumor stage, and prognosis. Additionally, weighted gene co-expression network analysis (WGCNA) analysis of CpG sites revealed that 11 of them could distinguish the samples into high- and low-methylation groups and could classify the prognostic information of samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained from the test set and 12 glioma patients. Moreover, in vitro experiments revealed an inverse relationship between methylation level and migration ability or insensitivity to temozolomide (or radiotherapy) of glioma cells based on the final prognostic predictor. Thus, these results suggested that the model constructed in this study could provide guidance for clinicians regarding the prognosis of various epigenetic subtypes.

DHHC protein family targets different subsets of glioma stem cells in specific niches.

BACKGROUND: Glioblastomas (GBM) comprise different subsets that exhibit marked heterogeneity and plasticity, leading to a lack of success of genomic profiling in guiding the development of precision medicine approaches against these tumors. Accordingly, there is an urgent need to investigate the regulatory mechanisms for different GBM subsets and identify novel biomarkers and therapeutic targets relevant in the context of GBM-specific niches. The DHHC family of proteins is associated tightly with the malignant development and progression of gliomas. However, the role of these proteins in the plasticity of GBM subsets remains unclear. METHODS: This study utilized human glioma proneural or mesenchymal stem cells as indicated. The effects of DHHC proteins on different GBM subsets were investigated through in vitro and in vivo assays (i.e., colony formation assay, flow cytometry assay, double immunofluorescence, western blot, and xenograft model). Western blot, co-immunoprecipitation, and liquid chromatograph mass spectrometer-mass spectrometry assays were used to detect the protein complexes of ZDHHC18 and ZDHHC23 in various GBM subtypes, and explore the mechanism of DHHC proteins in targeting different subsets of GSCs in specific niches. RESULTS: ZDHHC18 and ZDHHC23 could target the glioma stem cells of different GBM subsets in the context of their specific niches and regulate the cellular plasticity of these subtypes. Moreover, mechanistic investigations revealed that ZDHHC18 and ZDHHC23 competitively interact with a BMI1 E3 ligase, RNF144A, to regulate the polyubiquitination and accumulation of BMI1. These events contributed to the transition of glioma stem cells in GBM and cell survival under the stressful tumor microenvironment. CONCLUSIONS: Our work highlights the role of DHHC proteins in the plasticity of GBM subsets and reveals that BMI1 represents a potential therapeutic target for human gliomas.