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Glioblastoma is an aggressive brain cancer with a poor prognosis. The O6-methylguanine-DNA methyltransferase (MGMT) gene methylation status is crucial for treatment stratification, yet economic constraints often limit access. This study aims to develop an artificial intelligence (AI) framework for predicting MGMT methylation. Diagnostic magnetic resonance (MR) images in public repositories were used for training. The algorithm created was validated in data from a single institution. All images were segmented according to widely used guidelines for radiotherapy planning and combined with clinical evaluations from neuroradiology experts. Radiomic features and clinical impressions were extracted, tabulated, and used for modeling. Feature selection methods were used to identify relevant phenotypes. A total of 100 patients were used for training and 46 for validation. A total of 343 features were extracted. Eight feature selection methods produced seven independent predictive frameworks. The top-performing ML model was a model post-Least Absolute Shrinkage and Selection Operator (LASSO) feature selection reaching accuracy (ACC) of 0.82, an area under the curve (AUC) of 0.81, a recall of 0.75, and a precision of 0.75. This study demonstrates that integrating clinical and radiotherapy-derived AI-driven phenotypes can predict MGMT methylation. The framework addresses constraints that limit molecular diagnosis access., Competing Interests: Declarations Competing interests The authors declare no competing interests. Institutional review board (IRB) approval number This study was conducted in accordance with the principles of the Declaration of Helsinki and was submitted and approved by the Brazilian National Health Council through the Brazil platform (identifier 63591922.6.0000.5461). As the study involved a retrospective analysis of hospital database records, a waiver for obtaining Informed Consent was requested and approved by the Research Ethics Committee of the Sírio-Libanês Hospital (ref. 5461), which also granted approval for both the research and the waiver of the informed consent form., (© 2024. The Author(s).)

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Adult glioblastoma (GBM) is a highly aggressive primary brain tumor, accounting for nearly half of all malignant brain tumors, with a median survival rate of only 8 months. Treatment for GBM is largely ineffective due to the highly invasive nature and complex tumor composition of this malignancy. MicroRNAs (miRNA) are short, non-coding RNAs that regulate gene expression by binding to messenger RNAs (mRNA). While specific miRNA have been associated with GBM, their precise roles in tumor development and progression remain unclear. In this study, the analysis of miRNA expression data from 743 adult GBM cases and 59 normal brain samples identified 94 downregulated miRNA and 115 upregulated miRNA. Many of these miRNA were previously linked to GBM pathology, confirming the robustness of our approach, while we also identified novel miRNA that may act as potential regulators in GBM. By integrating miRNA predictions with gene expression data, we were able to associate downregulated miRNA with tumor microenvironment factors, including extracellular matrix remodeling and signaling pathways involved in tumor initiation, while upregulated miRNA were found to be associated with essential neuronal processes. This analysis highlights the significance of miRNA in GBM and serves as a foundation for further investigation., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

HOX transcript antisense RNA (HOTAIR) is upregulated in glioblastoma (GBM) and associated with temozolomide (TMZ) resistance. However, the mechanisms underlying HOTAIR-mediated TMZ resistance remains poorly understood. HOTAIR expression in glioma-related public datasets and drug response estimation were analyzed using bioinformatics. These findings were verified by overexpressing HOTAIR in TMZ-sensitive U251 cells and/or silencing HOTAIR in resistant U251 cells (U251R). The cytotoxic effects were evaluated using cell viability assay and flow cytometry analysis of cell cycle and apoptosis. In this study, we found that HOTAIR was upregulated in TMZ-resistant GBM cell lines and patients with high HOTAIR expression responded poorly to TMZ therapy. HOTAIR knockdown restored TMZ sensitivity in U251R cells, while HOTAIR overexpression conferred TMZ resistance in U251 cells. Wnt/β-catenin signaling was enriched in patients with high HOTAIR expression; consistently, HOTAIR positively regulated β-catenin expression in U251 cells. Moreover, HOTAIR-mediated TMZ resistance was associated with increased MGMT protein level, which resulted from the HOTAIR/miR-214-3p/β-catenin network. Besides, GBM with high HOTAIR expression exhibited sensitivity to methotrexate. Methotrexate enhanced TMZ sensitivity in U251R cells, accompanied by reduced expression of HOTAIR and β-catenin. Thus, we conlcude that HOTAIR is a risk factor for TMZ resistance and methotrexate may represent a potential therapeutic drug for patients with high HOTAIR expression level., (© 2024. The Author(s).)

We presented a method to find potential cancer attractors using single-cell RNA sequencing (scRNA-seq) data. We tested our method in a Glioblastoma Multiforme (GBM) dataset, an aggressive brain tumor presenting high heterogeneity. Using the cancer attractor concept, we argued that the GBM's underlying dynamics could partially explain the observed heterogeneity, with the dataset covering a representative region around the attractor. Exploratory data analysis revealed promising GBM's cellular clusters within a 3-dimensional marker space. We approximated the clusters' centroid as stable states and each cluster covariance matrix as defining confidence regions. To investigate the presence of attractors inside the confidence regions, we constructed a GBM gene regulatory network, defined a model for the dynamics, and prepared a framework for parameter estimation. An exploration of hyperparameter space allowed us to sample time series intending to simulate myriad variations of the tumor microenvironment. We obtained different densities of stable states across gene expression space and parameters displaying multistability across different clusters. Although we used our methodological approach in studying GBM, we would like to highlight its generality to other types of cancer. Therefore, this report contributes to an advance in the simulation of cancer dynamics and opens avenues to investigate potential therapeutic targets., (© 2024. The Author(s).)

G protein subunit Gamma 5 (GNG5) has been found to be involved in regulating glioma progression. However, its function and mechanism in glioblastoma (GBM) progression need to be further elucidated. GBM cell proliferation, apoptosis, invasion and stemness were assessed by cell counting kit 8 assay, EdU assay, flow cytometry, transwell assay and sphere formation assay. The mRNA and protein levels of GNG5 and Yin Yang 1 (YY1) were determined by quantitative real-time PCR and western blot (WB). Detection of the glucose consumption, lactate production and ATP/ADP ratios were used to assess cell glycolysis. Besides, Wnt/β-catenin pathway-related protein levels were examined by WB. Mice xenograft model was also constructed to explore GNG5 roles in vivo. GNG5 was highly expressed in GBM, and its silencing inhibited GBM cell proliferation, invasion, stemness and glycolysis, while promoted apoptosis. Transcription factor YY1 could bind to the GNG5 promoter region and induce its expression. GNG5 overexpression reversed the inhibitory effects of YY1 silencing on GBM cell growth, invasion, stemness and glycolysis. YY1/GNG5 axis could activate the Wnt/β-catenin pathway, and Wnt/β-catenin pathway agonists SKL2001 could revert the effects of GNG5 silencing on GBM cell progression. Furthermore, GNG5 facilitated GBM tumor growth by mediating the Wnt/β-catenin pathway. YY1-mediated GNG5 promoted GBM progression through the Wnt/β-catenin pathway., (© 2024. The Author(s).)

Glioblastomas (GBMs) are the most aggressive types of central nervous system tumors. Although certain genomic alterations have been identified as prognostic biomarkers of GBMs, the histomorphological features that predict their prognosis remain elusive. In this study, following an integrative diagnosis of 227 GBMs based on the 2021 World Health Organization classification system, the cases were histologically fractionated by cellular variations and abundance to evaluate the relationship between cellular heterogeneity and prognosis in combination with O-6-methylguanine-DNA methyltransferase gene promoter methylation (mMGMTp) status. GBMs comprised four major cell types: astrocytic, pleomorphic, gemistocytic, and rhabdoid cells. t-distributed stochastic neighbor embedding analysis using the histological abundance of heterogeneous cell types identified two distinct groups with significantly different prognoses. In individual cell component analysis, the abundance of gemistocytes showed a significantly favorable prognosis but confounding to mMGMTp status. Conversely, the abundance of epithelioid cells was correlated with the unfavorable prognosis. Linear model analysis showed the favorable prognostic utility of quantifying gemistocytic and epithelioid cells, independent of mMGMTp. The evaluation of GBM cell histomorphological heterogeneity is more effective for prognosis prediction in combination with mMGMTp analysis, indicating that histomorphological analysis is a practical and useful prognostication tool in an integrative diagnosis of GBMs., (© 2024. The Author(s).)

Glioblastoma (GBM) is the most prevalent primary malignant tumor of the nervous system. In this study, we utilized pathomics analysis to explore the expression of CD40LG and its predictive value for the prognosis of GBM patients. We analyzed the expression differences of CD40LG in GBM tissue and normal brain tissue, along with performing survival prognosis analysis. Additionally, histopathological sections of GBM were used to screen for pathological features. Subsequently, SVM and LR pathomics models were constructed, and the models' performance was evaluated. The pathomics model was employed to predict CD40LG expression and patient prognosis. Furthermore, we investigated the potential molecular mechanisms through enrichment analysis, WGCNA analysis, immune correlation analysis, and immune checkpoint analysis. The expression level of CD40LG was significantly increased in GBM. Multivariate analysis demonstrated that high expression of CD40LG is a risk factor for overall survival (OS) in GBM patients. Five pathological features were identified, and SVM and LR pathomics models were constructed. Model evaluation showed promising predictive effects, with an AUC value of 0.779 for the SVM model, and the Hosmer-Lemeshow test confirmed the model's prediction probability consistency (P > 0.05). The LR model achieved an AUC value of 0.785, and the Hosmer-Lemeshow test indicated good agreement between the LR model's predicted probabilities and the true value (P > 0.05). Immune infiltration analysis revealed a significant correlation between the pathomics score (PS) and the degree of infiltration of activated DC cells, T cells CD4 naïve, Macrophages M2, Macrophages M1, and T cells CD4 memory resting. Our results demonstrate that the pathomics model exhibits predictability for CD40LG expression and GBM patient survival. These findings can be utilized to assist neurosurgeons in selecting optimal treatment strategies in clinical practice., (© 2024. The Author(s).)

Gliomas are the most common tumor in the central nervous system in adults, with glioblastoma (GBM) representing the most malignant form, while low-grade glioma (LGG) is a less severe. The prognosis for glioma remains poor even after various treatments, such as chemotherapy and immunotherapy. Cuproptosis is a newly defined form of programmed cell death, distinct from ferroptosis and apoptosis, primarily caused by the accumulation of the copper within cells. In this study, we compared the difference between the expression of cuproptosis-related genes in GBM and LGG, respectively, and conducted further analysis on the enrichment pathways of the exclusive expressed cuproptosis-related mRNAs in GBM and LGG. We established two prediction models for survival status using xgboost and random forest algorithms and applied the ROSE algorithm to balance the dataset to improve model performance., (© 2024. The Author(s).)

Glioblastoma multiforme (GBM) is the most aggressive type of primary brain tumor, and the presence of glioma stem cells (GSCs) has been linked to its resistance to treatments and recurrence. Additionally, aberrant glycosylation has been implicated in the aggressiveness of cancers. However, the influence and underlying mechanism of N-glycosylation on the GSC phenotype and GBM malignancy remain elusive. Here, we performed an in-silico analysis approach on publicly available datasets to examine the function of N-glycosylation-related genes in GSCs and gliomas, accompanied by a qRT-PCR validation experiment. We found that high α-1,2-mannosidase MAN1C1 is associated with immunological functions and worse survival of glioma patients. Differential gene expression analysis and qRT-PCR validation revealed that MAN1C1 is highly expressed in GSCs. Furthermore, higher MAN1C1 expression predicts worse outcomes in glioma patients. Also, MAN1C1 expression is increased in the perinecrotic region of GBM and is associated with immunological and inflammatory functions, a hallmark of the GBM mesenchymal subtype. Further analysis confirmed that MAN1C1 expression is closely associated with infiltrating immune cells and disrupted immune response in the GBM microenvironment. These suggest that MAN1C1 is a potential biomarker for gliomas and may be important as an immunotherapeutic target for GBM., (© 2024. The Author(s).)

Glioblastoma is a Grade 4 primary brain tumor defined by therapy resistance, diffuse infiltration, and near-uniform lethality. The underlying mechanisms are unknown, and no treatment has been curative. Using a recently developed creatine kinase inhibitor (CKi), we explored the role of this inhibitor on GBM biology in vitro. While CKi minimally impacted GBM cell proliferation and viability, it significantly affected migration. In established GBM cell lines and patient-derived xenografts, CKi ablated both the migration and invasion of GBM cells. CKi also hindered radiation-induced migration. RNA-seq revealed a decrease in invasion-related genes, with an unexpected increase in glutathione metabolism and ferroptosis protection genes post-CKi treatment. The effects of CKi could be reversed by the addition of cell-permeable glutathione. Carbon-13 metabolite tracing indicated heightened glutathione biosynthesis post-CKi treatment. Combinatorial CKi blockade and glutathione inhibition or ferroptosis activation abrogated cell survival. Our data demonstrated that CKi perturbs promigratory and anti-ferroptotic roles in GBM, identifying the creatine kinase axis as a druggable target for GBM treatment., (© 2024. The Author(s).)

Glioblastoma (GBM) is the most aggressive glial tumor of the adult brain, associated with invariably fatal outcome, and a deeper understanding of the underlying malignant mechanisms is necessary to address the current therapeutic failure. We previously demonstrated the role of the CXCL12/CXCR4 axis in GBM cell migration and resistance to ionizing radiation. The atypical chemokine receptor ACKR3, responsible for CXCL12 scavenging, was previously suggested as additional important player in the context of GBM. Following validation of the detection tools, we observed that ACKR3 is expressed within GBM patient tumor tissue, distributed in diverse cell types. In contrast to CXCR4, ACKR3 expression in patient-derived stem-like cells (GSCs) remains however low, while ACKR3 gene expression by tumor cells appears to be modulated by the in-vivo environment. Using overexpression models, we also showed that in vitro ACKR3 had no significant direct effect on cell proliferation or invasion. Altogether, these results suggest that in vitro ACKR3 plays a minor role in malignant GBM cell biology and that its expression is possibly regulated by in-vivo influences. The subtle and multifaceted functions ACKR3 could exert in GBM should therefore only be tackled within a comprehensive tumor microenvironment considering tumoral but also non-tumoral cells., (© 2024. The Author(s).)

Glioblastoma (GBM) represents an aggressive brain tumor, characterized by intra- and inter-tumoral heterogeneity and therapy resistance, leading to unfavourable prognosis. An increasing number of studies pays attention on the regulation of ferroptosis, an iron-dependent cell death, as a strategy to reverse drug resistance in cancer. However, the debate on whether this strategy may have important implications for the treatment of GBM is still ongoing. In the present study, we used ferric ammonium citrate and erastin to evaluate ferroptosis induction effects on two human GBM cell lines, U-251 MG, with proneural characteristics, and T98-G, with a mesenchymal profile. The response to ferroptosis induction was markedly different between cell lines, indeed T98-G cells showed an enhanced antioxidant defence, with increased glutathione levels, as compared to U-251 MG cells. Moreover, using bioinformatic approaches and analysing publicly available datasets from patients' biopsies, we found that GBM with a mesenchymal phenotype showed an up-regulation of several genes involved in antioxidant mechanisms as compared to proneural subtype. Thus, our results suggest that GBM subtypes differently respond to ferroptosis induction, emphasizing the significance of further molecular studies on GBM to better discriminate between various tumor subtypes and progressively move towards personalized therapy., (© 2024. The Author(s).)

Temozolomide (TMZ) resistance is a major challenge in the treatment of glioblastoma (GBM). Tumour reproductive cells (TRCs) have been implicated in the development of chemotherapy resistance. By culturing DBTRG cells in three-dimensional soft fibrin gels to enrich GBM TRCs and performing RNA-seq analysis, the expression of stanniocalcin-1 (STC), a gene encoding a secreted glycoprotein, was found to be upregulated in TRCs. Meanwhile, the viability of TMZ-treated TRC cells was significantly higher than that of TMZ-treated 2D cells. Analysis of clinical data from CGGA (Chinese Glioma Genome Atlas) database showed that high expression of STC1 was closely associated with poor prognosis, glioma grade and resistance to TMZ treatment, suggesting that STC1 may be involved in TMZ drug resistance. The expression of STC1 in tissues and cells was examined, as well as the effect of STC1 on GBM cell proliferation and TMZ-induced DNA damage. The results showed that overexpression of STC1 promoted and knockdown of STC1 inhibited TMZ-induced DNA damage. These results were validated in an intracranial tumour model. These data revealed that STC1 exerts regulatory functions on MGMT expression in GBM, and provides a rationale for targeting STC1 to overcome TMZ resistance., (© 2024. The Author(s).)

Glioblastoma (GBM) is a highly aggressive, infiltrative malignancy that cannot be completely cured by current treatment modalities, and therefore requires more precise molecular subtype signatures to predict treatment response for personalized precision therapy. Expression subtypes of GBM samples from the Cancer Genome Atlas (TCGA) were identified using BayesNM and compared with existing molecular subtypes of GBM. Biological features of the subtypes were determined by single-sample gene set enrichment analysis. Genomic and proteomic data from GBM samples were combined and Genomic Identification of Significant Targets in Cancer analysis was used to screen genes with recurrent somatic copy-number alterations phenomenon. The immune environment among subtypes was compared by assessing the expression of immune molecules and the infiltration of immune cells. Molecular subtypes adapted to immunotherapy were identified based on Tumor Immune Dysfunction and Exclusion (TIDE) score. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was performed on the expression profiles of S2, S3 and S4 in TCGA-GBM and RPPA to determine the respective corresponding best predictive model. Four novel molecular subtypes were classified. Specifically, S1 exhibited a low proliferative profile; S2 exhibited the profile of high proliferation, IDH1 mutation, TP53 mutation and deletion; S3 was characterized by high immune scores, innate immunity and adaptive immune infiltration scores, with the lowest TIDE score and was most likely to benefit from immunotherapy; S4 was characterized by high proliferation, EGFR amplification, and high protein abundance, and was the most suitable subtype for bevacizumab. LASSO analysis constructed the best prediction model composed of 13 genes in S2 with an accuracy of 96.7%, and the prediction model consisting of 17 genes in S3 with an accuracy of 86.7%, and screened 14 genes as components of the best prediction model in S4 with an accuracy of 93%. To conclude, our study classified reproducible and robust molecular subtypes of GBM, and these findings might contribute to the identification of patients responding to immunotherapy, thereby improving GBM prognosis., (© 2024. The Author(s).)

Glioblastoma is the most common primary brain tumor in adults, characterized by an inherent aggressivity and resistance to treatment leading to poor prognoses. While some resistance mechanisms have been elucidated, a deeper understanding of these mechanisms is needed to increase therapeutic efficacy. In this study we first discovered glial-cell derived neurotrophic factor (GDNF) to be upregulated in patient-derived glioblastoma spheroid cultures after chemotherapeutic temozolomide treatment, through RNA-Seq experiments. Therefore, we investigated the role of the GDNF/GDNF receptor alpha 1 (GFRA1) signaling pathway as a resistance mechanism to chemotherapy with temozolomide and lomustine, as well as irradiation using patient-derived glioblastoma spheroid cultures. With qPCR experiments we showed a consistent upregulation of GDNF and its primary receptor GFRA1 following all three lines of treatment. Moreover, CRISPR/Cas9 knock-outs of GDNF in two patient-derived models sensitized these cells to chemotherapy treatment, but not radiotherapy. The increased sensitivity was completely reversed by the addition of exogeneous GDNF, confirming the key role of this factor in chemoresistance. Finally, a CRISPR KO of GFRA1 demonstrated a similar increased sensitivity to temozolomide and lomustine treatment, as well as radiotherapy. Together, our findings support the role of the GDNF/GFRA1 signaling pathway in glioblastoma chemo and radioresistance., (© 2024. The Author(s).)

Antigen-specific cytotoxic CD8 T cells are extremely effective in controlling tumor growth and have been the focus of immunotherapy approaches. We leverage in silico tools to investigate whether the occurrence of mutations in proteins previously described as immunogenic and highly expressed by glioblastoma multiforme (GBM), such as Epidermal Growth Factor Receptor (EGFR), Isocitrate Dehydrogenase 1 (IDH1), Phosphatase and Tensin homolog (PTEN) and Tumor Protein 53 (TP53), may be contributing to the differential presentation of immunogenic epitopes. We recovered Class I MHC binding information from wild-type and mutated proteins using the Immune Epitope Database (IEDB). After that, we built peptide-MHC (pMHC-I) models in HLA-arena, followed by hierarchical clustering analysis based on electrostatic surface features from each complex. We identified point mutations that are determinants for the presentation of a set of peptides from TP53 protein. We point to structural features in the pMHC-I complexes of wild-type and mutated peptides, which may play a role in the recognition of CD8 T cells. To further explore these features, we performed 100 ns molecular dynamics simulations for the peptide pairs (wt/mut) selected. In pursuit of novel therapeutic targets for GBM treatment, we selected peptides where our predictive results indicated that mutations would not disrupt epitope presentation, thereby maintaining a specific CD8 T cell immune response. These peptides hold potential for future GBM interventions, including peptide-based or mRNA vaccine development applications., (© 2024. The Author(s).)

As the prevalence of Type 2 Diabetes Mellitus (T2DM) and Glioblastoma (GBM) rises globally, the relationship between T2DM and GBM remains controversial. This study aims to investigate whether genetically predicted T2DM is causally associated with GBM. We performed bidirectional Mendelian randomization (MR) analysis using data from genome-wide studies on T2DM (N = 62,892) and GBM (N = 218,792) in European populations. The results of the inverse-variance weighted (IVW) approach served as the primary outcomes. We applied Cochran's Q test and MR-Egger regression for heterogeneity assessment. Leave-one-out analysis was used to evaluate whether any single SNP significantly influenced the observed effect. Our findings reveal a significant causal association between T2DM and an increased risk of GBM (OR [95% CI] 1.70 [1.09, 2.65], P = 0.019). Conversely, the reverse association between T2DM and GBM was insignificant (OR [95% CI] 1.00 [0.99, 1.01], P = 0.408) (P > 0.40). Furthermore, the results from Cochran's Q-test and funnel plots in the MR-Egger method indicated no evidence of pleiotropy between the SNPs and GBM. Additionally, we mapped causal SNPs to genes and identified 10 genes, including MACF1, C1orf185, PTGFRN, NOTCH2, ABCB10, GCKR, THADA, RBMS1, SPHKAP, and PPARG, located on chromosomes 1, 2, and 3. These genes are involved in key biological processes such as the BMP signaling pathway and various metabolic pathways relevant to both conditions. This study provides robust evidence of a significant causal relationship between T2DM and an increased risk of GBM. The identified SNP-mapped genes highlight potential biological mechanisms underlying this association., (© 2024. The Author(s).)

O6-methylguanine-DNA methyltransferase (MGMT) has been demonstrated to be an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable radiomics model based on MRI data to predict the MGMT promoter methylation status of GBM. A total of 183 patients with glioblastoma were included in this retrospective study. The visually accessible Rembrandt images (VASARI) features were extracted for each patient, and a total of 14676 multi-region features were extracted from enhanced, necrotic, "non-enhanced, and edematous" areas on their multiparametric MRI. Twelve individual radiomics models were constructed based on the radiomics features from different subregions and different sequences. Four single-sequence models, three single-region models and the combined radiomics model combining all individual models were constructed. Finally, the predictive performance of adding clinical factors and VASARI characteristics was evaluated. The ComRad model combining all individual radiomics models exhibited the best performance in test set 1 and test set 2, with the area under the receiver operating characteristic curve (AUC) of 0.839 (0.709-0.963) and 0.739 (0.581-0.897), respectively. The results indicated that the radiomics model combining multi-region and multi-parametric MRI features has exhibited promising performance in predicting MGMT methylation status in GBM. The Modeling scheme that combining all individual radiomics models showed best performance among all constructed moels., (© 2024. The Author(s).)

Glioblastoma (GBM) is a highly aggressive and deadly brain cancer. Temozolomide (TMZ) is the standard chemotherapeutic agent for GBM, but the majority of patients experience recurrence and invasion of tumor cells. We investigated whether TMZ treatment of GBM cells regulates matrix metalloproteinases (MMPs), which have the main function to promote tumor cell invasion. TMZ effectively killed GL261, U343, and U87MG cells at a concentration of 500 µM, and surviving cells upregulated MMP9 expression and its activity but not those of MMP2. TMZ also elevated levels of MMP9 mRNA and MMP9 promoter activity. Subcutaneous graft tumors survived from TMZ treatment also exhibited increased expression of MMP9 and enhanced gelatinolytic activity. TMZ-mediated MMP9 upregulation was specifically mediated through the phosphorylation of p38 and JNK. This then stimulates AP-1 activity through the upregulation of c-Fos and c-Jun. Inhibition of the p38, JNK, or both pathways counteracted the TMZ-induced upregulation of MMP9 and AP-1. This study proposes a potential adverse effect of TMZ treatment for GBM: upregulation of MMP9 expression potentially associated with increased invasion and poor prognosis. This study also provides valuable insights into the molecular mechanisms by which TMZ treatment leads to increased MMP9 expression in GBM cells., (© 2024. The Author(s).)

Glioblastoma is a rare and deadly malignancy with a low survival rate. Emerging evidence has shown that aberrantly expressed circular RNAs (circRNAs) play a critical role in the initiation and progression of GBM tumorigenesis. The oncogenic function of circZNF609 and circNFIX is involved in several types of cancer, but the role and underlying mechanism of these circRNAs in glioblastoma remain unclear. In this study, we hypothesized that circZNF609 and circNFIX may regulate EGFR through sponging miR-145-5p. Herein, we assessed the expression levels of circZNF609, circNFIX, miR-145-5p, and EGFR using quantitative polymerase chain reaction in glioblastoma patients and normal brain samples. The results showed that circZNF609, circNFIX, and EGFR expression levels were upregulated and miR145-5p was downregulated (p = 0.001, 0.06, 0.002, and 0.0065, respectively), while there was no significant association between clinicopathological features of the patients and the level of these genes expression. We also found a significant inverse correlation between miR145-5p and the expression of cZNF609, cNFIX and EGFR (p = 0.0003, 0.0006, and 0.009, respectively). These findings may open a new window for researchers to better understand the potential pathways involved in GBM pathogenesis. In conclusion, it may provide a new potential pathway for the development of effective drugs for the treatment of GBM patients., (© 2024. The Author(s).)

Radiotherapy is the standard treatment for glioblastoma (GBM), but the overall survival rate for radiotherapy treated GBM patients is poor. The use of adjuvant and concomitant temozolomide (TMZ) improves the outcome; however, the effectiveness of this treatment varies according to MGMT levels. Herein, we evaluated whether MGMT expression affected the radioresponse of human GBM, GBM stem-like cells (GSCs), and melanoma. Our results indicated a correlation between MGMT promoter methylation status and MGMT expression. MGMT-producing cell lines ACPK1, GBMJ1, A375, and MM415 displayed enhanced radiosensitivity when MGMT was silenced using siRNA or when inhibited by lomeguatrib, whereas the OSU61, NSC11, WM852, and WM266-4 cell lines, which do not normally produce MGMT, displayed reduced radiosensitivity when MGMT was overexpressed. Mechanistically lomeguatrib prolonged radiation-induced γH2AX retention in MGMT-producing cells without specific cell cycle changes, suggesting that lomeguatrib-induced radiosensitization in these cells is due to radiation-induced DNA double-stranded break (DSB) repair inhibition. The DNA-DSB repair inhibition resulted in cell death via mitotic catastrophe in MGMT-producing cells. Overall, our results demonstrate that MGMT expression regulates radioresponse in GBM, GSC, and melanoma, implying a role for MGMT as a target for radiosensitization., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Micropeptides hidden in long non-coding RNAs (lncRNAs) have been uncovered to program various cell-biological changes associated with malignant transformation-glioblastoma (GBM) cascade. Here, we identified and characterized a novel hidden micropeptide implicated in GBM. We screened potential candidate lncRNAs by establishing a workflow involving ribosome-bound lncRNAs, publicly available MS/MS data, and prognosis-related lncRNAs. Micropeptide expression was detected by western blot (WB), immunofluorescence (IF), and immunohistochemistry (IHC). Cell proliferation rate was assessed by calcein/PI staining and EdU assay. Proteins interacted with the micropeptide were analyzed by proteomics after co-immunoprecipitation (Co-IP). We discovered that lncRNA AF127577.4 indeed encoded an endogenous micropeptide, named AF127577.4-ORF. AF127577.4-ORF was associated with GBM clinical grade. In vitro, AF127577.4-ORF could suppress GBM cell proliferation. Moreover, AF127577.4-ORF reduced m6A methylation level of GBM cells. Mechanistically, AF127577.4-ORF diminished ERK2 interaction with m6A reader methyltransferase like 3 (METTL3) and downregulated phosphorylated ERK (p-ERK) level. The ERK inhibitor reduced p-ERK level and downregulated METTL3 protein expression. AF127577.4-ORF weakened the stability of METTL3 protein by ERK. Also, AF127577.4-ORF suppressed GBM cell proliferation via METTL3. Our study identifies a novel micropeptide AF127577.4-ORF hidden in a lncRNA, with a potent anti-proliferating function in GBM by diminishing METTL3 protein stability by reducing the ERK2/METTL3 interaction. This micropeptide may be beneficial for development of therapeutic strategies against GBM., (© 2024. The Author(s).)

Numerous studies have highlighted the pivotal role of mitochondria-related genes (MRGs) in the initiation and progression of glioblastoma (GBM). However, the specific contributions of MRGs coding proteins to GBM pathology remain incompletely elucidated. The identification of prognostic MRGs in GBM holds promise for the development of personalized targeted therapies and the enhancement of patient prognosis. We combined differential expression with univariate Cox regression analysis to screen prognosis-associated MRGs in GBM. Based on the nine MRGs, the hazard ratio model was conducted using a multivariate Cox regression algorithm. SHC-related survival, pathway, and immune analyses in GBM cohorts were obtained from the Biomarker Exploration of the Solid Tumor database. The proliferation and migration of U87 cells were measured by CCK-8 and transwell assay. Apoptosis in U87 cells was evaluated using flow cytometry. Confocal microscopy was employed to measure mitochondrial reactive oxygen species (ROS) levels and morphology. The expression levels of SHC1 and other relevant proteins were examined via western blotting. We screened 15 prognosis-associated MRGs and constructed a 9 MRGs-based model. Validation of the model's risk score confirmed its efficacy in predicting the prognosis of patients with GBM. Furthermore, analysis revealed that SHC1, a constituent MRG of the prognostic model, was upregulated and implicated in the progression, migration, and immune infiltration of GBM. In vitro experiments elucidated that p66Shc, the longest isoform of SHC1, modulates mitochondrial ROS production and morphology, consequently promoting the proliferation and migration of U87 cells. The 9 MRGs-based prognostic model could predict the prognosis of GBM. SHC1 was upregulated and correlated with the prognosis of patients by involvement in immune infiltration. Furthermore, in vitro experiments demonstrated that p66Shc promotes U87 cell proliferation and migration by mediating mitochondrial ROS production. Thus, p66Shc may serve as a promising biomarker and therapeutic target for GBM., (© 2024. The Author(s).)

Glioblastoma (GB) is a devastating tumor of the central nervous system characterized by a poor prognosis. One of the best-established predictive biomarker in IDH-wildtype GB is O6-methylguanine-DNA methyltransferase (MGMT) methylation (mMGMT), which is associated with improved treatment response and survival. However, current efforts to monitor GB patients through mMGMT detection have proven unsuccessful. Small extracellular vesicles (sEVs) hold potential as a key element that could revolutionize clinical practice by offering new possibilities for liquid biopsy. This study aimed to determine the utility of sEV-based liquid biopsy as a predictive biomarker and disease monitoring tool in patients with IDH-wildtype GB. Our findings show consistent results with tissue-based analysis, achieving a remarkable sensitivity of 85.7% for detecting mMGMT in liquid biopsy, the highest reported to date. Moreover, we suggested that liquid biopsy assessment of sEV-DNA could be a powerful tool for monitoring disease progression in IDH-wildtype GB patients. This study highlights the critical significance of overcoming molecular underdetection, which can lead to missed treatment opportunities and misdiagnoses, possibly resulting in ineffective therapies. The outcomes of our research significantly contribute to the field of sEV-DNA-based liquid biopsy, providing valuable insights into tumor tissue heterogeneity and establishing it as a promising tool for detecting GB biomarkers. These results have substantial implications for advancing predictive and therapeutic approaches in the context of GB and warrant further exploration and validation in clinical settings., (© 2024. The Author(s).)

Glioblastoma multiforme (GBM), the most aggressive form of primary brain tumor, poses a considerable challenge in neuro-oncology. Despite advancements in therapeutic approaches, the prognosis for GBM patients remains bleak, primarily attributed to its inherent resistance to conventional treatments and a high recurrence rate. The primary goal of this study was to acquire molecular insights into GBM by constructing a gene co-expression network, aiming to identify and predict key genes and signaling pathways associated with this challenging condition. To investigate differentially expressed genes between various grades of Glioblastoma (GBM), we employed Weighted Gene Co-expression Network Analysis (WGCNA) methodology. Through this approach, we were able to identify modules with specific expression patterns in GBM. Next, genes from these modules were performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis using ClusterProfiler package. Our findings revealed a negative correlation between biological processes associated with neuronal development and functioning and GBM. Conversely, the processes related to the cell cycle, glomerular development, and ECM-receptor interaction exhibited a positive correlation with GBM. Subsequently, hub genes, including SYP, TYROBP, and ANXA5, were identified. This study offers a comprehensive overview of the existing research landscape on GBM, underscoring the challenges encountered by clinicians and researchers in devising effective therapeutic strategies., (© 2024. The Author(s).)

Bromodomain and extra-terminal domain (BET) proteins are therapeutic targets in several cancers including the most common malignant adult brain tumor glioblastoma (GBM). Multiple small molecule inhibitors of BET proteins have been utilized in preclinical and clinical studies. Unfortunately, BET inhibitors have not shown efficacy in clinical trials enrolling GBM patients. One possible reason for this may stem from resistance mechanisms that arise after prolonged treatment within a clinical setting. However, the mechanisms and timeframe of resistance to BET inhibitors in GBM is not known. To identify the temporal order of resistance mechanisms in GBM we performed quantitative proteomics using multiplex-inhibitor bead mass spectrometry and demonstrated that intrinsic resistance to BET inhibitors in GBM treatment occurs rapidly within hours and involves the fibroblast growth factor receptor 1 (FGFR1) protein. Additionally, small molecule inhibition of BET proteins and FGFR1 simultaneously induces synergy in reducing GBM tumor growth in vitro and in vivo. Further, FGFR1 knockdown synergizes with BET inhibitor mediated reduction of GBM cell proliferation. Collectively, our studies suggest that co-targeting BET and FGFR1 may dampen resistance mechanisms to yield a clinical response in GBM., (© 2024. The Author(s).)

Glioblastoma is one of the most common and aggressive brain tumors and has seen few improvements in patient outcomes. Inter-tumor heterogeneity between tumors of different patients as well as intra-tumor heterogeneity of cells within the same tumor challenge the development of effective drugs. MiRNAs play an essential role throughout the developing brain and regulate many key genes involved in oncogenesis, yet their role in driving many of the processes underlying tumor heterogeneity remains unclear. In this study, we highlight miRNAs from the Dlk1-Dio3 and miR-224/452 clusters which may be expressed cell autonomously and have expression that is associated with cell state genes in glioblastoma, most prominently in neural progenitor-like and mesenchymal-like states respectively. These findings implicate these miRNA clusters as potential regulators of glioblastoma intra-tumoral heterogeneity and may serve as valuable biomarkers for cell state identification., (© 2024. Crown.)

Glioblastoma multiforme (GBM) IDH-wildtype is the most prevalent brain malignancy in adults. However, molecular mechanisms, which leads to GBM have not been completely elucidated. Granulocyte colony-stimulating factor (GCSF), Granulocyte colony-stimulating factor receptor GCSFR, and Signal transducers and activators of transcription 3 (STAT3) have been involved in the occurrence and development of various cancers, but their role in GBM is little known. Herein, we have investigated the gene and protein expression of GCSF, GCSFR, and STAT3 in 21 tissue biopsy samples and also in tumor associated normal tissue (TANT) samples derived from glioblastoma patients, which revealed significantly differential expression of these genes. To validate our findings, we performed a comprehensive integrated analysis of transcriptomic and proteomic profiling of respective genes by retrieving GBM RNA-sequence data from Genome Atlas Databases. GO and KEGG analysis revealed enrichment in disease-related pathways, such as JAK/STAT pathway activation, which were associated with GBM progression. We further performed computational docking analysis of potential drug candidate Nisin against GCSF, and the results were validated in vitro through cytotoxic activity assay using a human glioblastoma cell line SF-767 in a dose-dependent manner. Our comprehensive analysis reveals that GCSF augments glioma progression, and its blockade with anticancer bacteriocin peptide Nisin can potentially inhibit the growth and metastasis of GBM., (© 2024. The Author(s).)

Glioblastoma is a highly heterogeneous disease, with variations observed at both phenotypical and molecular levels. Personalized therapies would be facilitated by non-invasive in vivo approaches for characterizing this heterogeneity. In this study, we developed unsupervised joint machine learning between radiomic and genomic data, thereby identifying distinct glioblastoma subtypes. A retrospective cohort of 571 IDH-wildtype glioblastoma patients were included in the study, and pre-operative multi-parametric MRI scans and targeted next-generation sequencing (NGS) data were collected. L21-norm minimization was used to select a subset of 12 radiomic features from the MRI scans, and 13 key driver genes from the five main signal pathways most affected in glioblastoma were selected from the genomic data. Subtypes were identified using a joint learning approach called Anchor-based Partial Multi-modal Clustering on both radiomic and genomic modalities. Kaplan-Meier analysis identified three distinct glioblastoma subtypes: high-risk, medium-risk, and low-risk, based on overall survival outcome (p < 0.05, log-rank test; Hazard Ratio = 1.64, 95% CI 1.17-2.31, Cox proportional hazard model on high-risk and low-risk subtypes). The three subtypes displayed different phenotypical and molecular characteristics in terms of imaging histogram, co-occurrence of genes, and correlation between the two modalities. Our findings demonstrate the synergistic value of integrated radiomic signatures and molecular characteristics for glioblastoma subtyping. Joint learning on both modalities can aid in better understanding the molecular basis of phenotypical signatures of glioblastoma, and provide insights into the biological underpinnings of tumor formation and progression., (© 2024. The Author(s).)

The choice of targeted therapies for treatment of glioblastoma patients is currently limited, and most glioblastoma patients die from the disease recurrence. Thus, systematic studies in simplified model systems are required to pinpoint the choice of targets for further exploration in clinical settings. Here, we report screening of 5 compounds targeting epigenetic writers or erasers and 6 compounds targeting cell cycle-regulating protein kinases against 3 glioblastoma cell lines following incubation under normoxic or hypoxic conditions. The viability/proliferation assay indicated that PRMT5 inhibitor onametostat was endowed with high potency under both normoxic and hypoxic conditions in cell lines that are strongly MGMT-positive (T98-G), weakly MGMT-positive (U-251 MG), or MGMT-negative (U-87 MG). In U-251 MG and U-87 MG cells, onametostat also affected the spheroid formation at concentrations lower than the currently used chemotherapeutic drug lomustine. In T98-G cell line, treatment with onametostat led to dramatic changes in the transcriptome profile by inducing the cell cycle arrest, suppressing RNA splicing, and down-regulating several major glioblastoma cell survival pathways. Further validation by immunostaining in three cell lines confirmed that onametostat affects cell cycle and causes reduction in nucleolar protein levels. In this way, inhibition of epigenetic targets might represent a viable strategy for glioblastoma treatment even in the case of decreased chemo- and radiation sensitivity, although further studies in clinically more relevant models are required., (© 2024. The Author(s).)

Glioblastoma is a highly aggressive and malignant type of brain cancer that originates from glial cells in the brain, with a median survival time of 15 months and a 5-year survival rate of less than 5%. Regulated cell death (RCD) is the autonomous and orderly cell death under genetic control, controlled by precise signaling pathways and molecularly defined effector mechanisms, modulated by pharmacological or genetic interventions, and plays a key role in maintaining homeostasis of the internal environment. The comprehensive and systemic landscape of the RCD in glioma is not fully investigated and explored. After collecting 18 RCD-related signatures from the opening literature, we comprehensively explored the RCD landscape, integrating the multi-omics data, including large-scale bulk data, single-cell level data, glioma cell lines, and proteome level data. We also provided a machine learning framework for screening the potentially therapeutic candidates. Here, based on bulk and single-cell sequencing samples, we explored RCD-related phenotypes, investigated the profile of the RCD, and developed an RCD gene pair scoring system, named RCD.GP signature, showing a reliable and robust performance in predicting the prognosis of glioblastoma. Using the machine learning framework consisting of Lasso, RSF, XgBoost, Enet, CoxBoost and Boruta, we identified seven RCD genes as potential therapeutic targets in glioma and verified that the SLC43A3 highly expressed in glioma grades and glioma cell lines through qRT-PCR. Our study provided comprehensive insights into the RCD roles in glioma, developed a robust RCD gene pair signature for predicting the prognosis of glioma patients, constructed a machine learning framework for screening the core candidates and identified the SLC43A3 as an oncogenic role and a prediction biomarker in glioblastoma., (© 2024. The Author(s).)

Disulfidptosis is a condition where dysregulated NAPDH levels and abnormal accumulation of cystine and other disulfides occur in cells with high SLC7A11 expression under glucose deficiency. This disrupts normal formation of disulfide bonds among cytoskeletal proteins, leading to histone skeleton collapse and triggering cellular apoptosis. However, the correlation between disulfidptosis and immune responses in relation to glioblastoma survival rates and immunotherapy sensitivity remains understudied. Therefore, we utilized The Cancer Genome Atlas and The Chinese Glioma Genome Atlas to identify disulfidptosis-related immune checkpoint genes and established an overall survival (OS) prediction model comprising six genes: CD276, TNFRSF 14, TNFSF14, TNFSF4, CD40, and TNFRSF18, which could also be used for predicting immunotherapy sensitivity. We identified a cohort of glioblastoma patients classified as high-risk, which exhibited an upregulation of angiogenesis, extracellular matrix remodeling, and epithelial-mesenchymal transition as well as an immunosuppressive tumor microenvironment (TME) enriched with tumor associated macrophages, tumor associated neutrophils, CD8  +  T-cell exhaustion. Immunohistochemical staining of CD276 in 144 cases further validated its negative correlation with OS in glioma. Disulfidptosis has the potential to induce chronic inflammation and an immunosuppressive TME in glioblastoma., (© 2024. The Author(s).)

Glioblastoma (GBM) is the most aggressive brain tumor and is characterized by a poor prognosis and high recurrence and mortality rates. Biochanin A (BCA) exhibits promising clinical anti-tumor effects. In this study, we aimed to explore the pharmacological mechanisms by which BCA acts against GBM. Network pharmacology was employed to identify overlapping target genes between BCA and GBM. Differentially expressed genes from the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database were visualized using VolcaNose. Interactions among these overlapping genes were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Protein-protein interaction networks were constructed using Cytoscape 3.8.1. The Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Survival analyses for these genes were performed using the GEPIA2 database. The Chinese Glioma Genome Atlas database was used to study the correlations between key prognostic genes. Molecular docking was confirmed using the DockThor database and visualized with PyMol software. Cell viability was assessed via the CCK-8 assay, apoptosis and the cell cycle stages were examined using flow cytometry, and protein expression was detected using western blotting. In all, 63 genes were initially identified as potential targets for BCA in treating GBM. Enrichment analysis suggested that the pharmacological mechanisms of BCA primarily involved cell cycle inhibition, induction of cell apoptosis, and immune regulation. Based on these findings, AKT1, EGFR, CASP3, and MMP9 were preliminarily predicted as key prognostic target genes for BCA in GBM treatment. Furthermore, molecular docking analysis suggested stable binding of BCA to the target protein. In vitro experiments revealed the efficacy of BCA in inhibiting GBM, with an IC50 value of 98.37 ± 2.21 μM. BCA inhibited cell proliferation, induced cell apoptosis, and arrested the cell cycle of GBM cells. Furthermore, the anti-tumor effects of BCA on U251 cells were linked to the regulation of the target protein. We utilized integrated bioinformatics analyses to predict targets and confirmed through experiments that BCA possesses remarkable anti-tumor activities. We present a novel approach for multi-target treatment of GBM using BCA., (© 2024. The Author(s).)

Quiescence, a reversible state of cell-cycle arrest, is an important state during both normal development and cancer progression. For example, in glioblastoma (GBM) quiescent glioblastoma stem cells (GSCs) play an important role in re-establishing the tumour, leading to relapse. While most studies have focused on identifying differentially expressed genes between proliferative and quiescent cells as potential drivers of this transition, recent studies have shown the importance of protein oscillations in controlling the exit from quiescence of neural stem cells. Here, we have undertaken a genome-wide bioinformatic inference approach to identify genes whose expression oscillates and which may be good candidates for controlling the transition to and from the quiescent cell state in GBM. Our analysis identified, among others, a list of important transcription regulators as potential oscillators, including the stemness gene SOX2, which we verified to oscillate in quiescent GSCs. These findings expand on the way we think about gene regulation and introduce new candidate genes as key regulators of quiescence., (© 2024. The Author(s).)

Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5-12.1; p < 0.001). We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status., (© 2023. The Author(s).)

In silico interrogation of glioblastoma (GBM) in The Cancer Genome Atlas (TCGA) revealed upregulation of GNA12 (Gα12), encoding the alpha subunit of the heterotrimeric G-protein G12, concomitant with overexpression of multiple G-protein coupled receptors (GPCRs) that signal through Gα12. Glioma stem cell lines from patient-derived xenografts also showed elevated levels of Gα12. Knockdown (KD) of Gα12 was carried out in two different human GBM stem cell (GSC) lines. Tumors generated in vivo by orthotopic injection of Gα12KD GSC cells showed reduced invasiveness, without apparent changes in tumor size or survival relative to control GSC tumor-bearing mice. Transcriptional profiling of GSC-23 cell tumors revealed significant differences between WT and Gα12KD tumors including reduced expression of genes associated with the extracellular matrix, as well as decreased expression of stem cell genes and increased expression of several proneural genes. Thrombospondin-1 (THBS1), one of the genes most repressed by Gα12 knockdown, was shown to be required for Gα12-mediated cell migration in vitro and for in vivo tumor invasion. Chemogenetic activation of GSC-23 cells harboring a Gα12-coupled DREADD also increased THBS1 expression and in vitro invasion. Collectively, our findings implicate Gα12 signaling in regulation of transcriptional reprogramming that promotes invasiveness, highlighting this as a potential signaling node for therapeutic intervention., (© 2023. The Author(s).)

Glioblastoma multiforme (GBM) is a complex disease to treat owing to its profound chemoresistance. Therefore, we evaluated the combined effect and therapeutic efficacy of temozolomide (TMZ), a potent alkylating agent and the current gold standard therapy for GBM, and cryptotanshinone (CTS), which inhibits glioma cell proliferation in GBM cells. Using LN229 and U87-MG human GBM cells in a short-term stimulation in vitro model, the cytotoxic and anti-proliferative effects of single and combined treatment with 4 μM CTS and 200 μM TMZ were investigated. Furthermore, cell viability, DNA damage, apoptosis rate, and signal transducer and activator of transcription 3 (STAT3) protein were measured using cytotoxic assay, comet assay, flow cytometry, and western blotting analysis, respectively. The two drugs' synergistic interaction was validated using the synergy score. We found that the anti-proliferative effects of combination therapy using the two drugs were greater than that of each agent used alone (CTS or TMZ). Western blot analysis indicated that treatment of GBM cells with CTS combined with TMZ more significantly decreased the expression of MGMT and STAT3, than that with TMZ alone. Combined treatment with CTS and TMZ might be an effective option to overcome the chemoresistance of GBM cells in a long-term treatment strategy., (© 2023. The Author(s).)

Tubulin polymerization promoting protein 3 (TPPP3), a member of the tubulin polymerization family, participates in cell progressions in several human cancers, its biological function and the underlying mechanisms in glioblastoma multiforme (GBM) remain unclear. Here, we investigated the role and application value of TPPP3 in gliomas and found that the expression of TPPP3 in glioma was higher than that in normal brain tissue (NBT), and increased with the grade of glioma. Up-regulation of TPPP3 expression in glioblastoma cells confer stronger ability of migration, invasion, proliferation and lower apoptosis in vitro. Inhibition of TPPP3 expression in GBM could reduce the migration, invasion, proliferation and induce the apoptosis of glioblastoma cells. TPPP3 affected the process of EMT by regulating the expression of Snail 1 protein. In clinical data analysis, we found a positive correlation between TPPP3 and Snail1 protein expression levels in glioblastomas. Low TPPP3 expression leads to better survival expectations in glioblastomas patients. The content of this study paves the way for further in-depth exploration of the role of TPPP3 in glioblastoma in the future, and provides new treatment and research directions., (© 2023. Springer Nature Limited.)

Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of cancer progression and are potential biomarkers for diagnosis and treatment. This study investigates the role of RARA Antisense RNA 1 (RARA-AS1) in cancer and its implications for diagnosis and treatment. Various bioinformatics tools were conducted to analyze the expression patterns, immune-related functions, methylation, and gene expression correlations of RARA-AS1, mainly including the comparisons of different subgroups and correlation analyses between RARA-AS1 expression and other factors. Furthermore, we used short hairpin RNA to perform knockdown experiments, investigating the effects of RARA-AS1 on cell proliferation, invasion, and migration in glioblastoma. Our results revealed that RARA-AS1 has distinct expression patterns in different cancers and exhibits notable correlation with prognosis. Additionally, RARA-AS1 is highly correlated with certain immune checkpoints and mismatch repair genes, indicating its potential role in immune infiltration and related immunotherapy. Further analysis identified potential effective drugs for RARA-AS1 and demonstrated its potential RNA binding protein (RBP) mechanism in glioblastoma. Besides, a series of functional experiments indicated inhibiting RARA-AS1 could decrease cell proliferation, invasion, and migration of glioblastoma cell lines. Finally, RARA-AS1 could act as an independent prognostic factor for glioblastoma patients and may serve as a promising therapeutic target. All in all, Our study provides a comprehensive understanding of the functions and implications of RARA-AS1 in pan-cancer, highlighting it as a promising biomarker for survival. It is also an independent risk factor affecting prognosis in glioblastoma and an important factor affecting proliferation and migration in glioblastoma, setting the stage for further mechanistic investigations., (© 2023. Springer Nature Limited.)

Glioblastoma multiforme (GBM) is probably the only tumor in which a unique epigenetic alteration, namely methylation of the MGMT gene, possesses direct clinical relevance. Now with the emergence of aberrant N6 methyladenosine (m6A) modifications (the most common epigenetic modification of mRNA, closely linked to the autophagy process) in cancer, the epi-transcriptomic landscape of GBM pathobiology has been expanded. Considering this, herein, we systematically analyzed m6A regulators, assessed their correlation with autophagy-related genes (ATG), and established a long non-coding RNAs (lncRNA)-dependent prognostic signature (m6A-autophagy-lncRNAs) for GBM. Our analysis identified a novel signature of five long non-coding RNAs (lncRNAs: ITGA6-AS1, AC124248.1, NFYC-AS1, AC025171.1, and AC005229.3) associated with survival of GBM patients, and four among them clearly showed cancer-associated potential. We further validated and confirmed the altered expression of two lncRNAs (AC124248.1, AC005229.3) in GBM associated clinical samples using RT-PCR. Concerning the prognostic ability, the obtained signature determined high-/low-risk groups in GBM patients and showed sensitivity to anticancer drugs. Collectively, the m6A-autophagy-lncRNAs signature presented in the study is clinically relevant and is the first attempt to systematically predict the potential interaction between the three key determinants (m6A, autophagy, lncRNA) in cancer, particularly in GBM., (© 2023. Springer Nature Limited.)

The purpose of this study was to explore the role of coixendide (Coix) combine with temozolomide (TMZ) in the treatment of Glioblastoma (GBM) and explore its possible mechanism. CCK-8 was used to determine the inhibitory rate of Coix group, TMZ group and drug combination group on GBM cells, and the combination index (CI) was calculated to determine whether they had synergistic effect. Then RNA was extracted from each group, transcriptome sequencing was performed, and differentially expressed genes (DEGs) were identified. The possible mechanism was analyzed by GO enrichment analysis and KEGG enrichment analysis. The CI of Coix and TMZ indicating a synergistic effect when TMZ concentration is 0.1 mg/ml and Coix concentration is 2 mg/ml. Transcriptome sequencing analysis showed that interferon (IFN) related genes were down-regulated by Coix and up-regulated by TMZ and combined drugs, however, the up-regulation induced by combined drugs was less than that of TMZ. Besides IFN related genes, cholesterol metabolism pathway were also been regulated. Coix and TMZ have synergistic effects in the treatment of GBM at certain doses. RNA-Seq results suggested that the abnormal on genetic materials caused by DNA damage induced by TMZ treatment can be sensed by IFN related genes and activates antiviral IFN signaling, causing the activation of repairing mechanism and drug resistance. Coix inhibits IFN related genes, thereby inhibits drug resistance of TMZ. In addition, the activation of ferroptosis and the regulation of DEGs in cholesterol metabolism pathway were also contributed to the synergistic effects of Coix and TMZ., (© 2023. Springer Nature Limited.)

Glioblastoma (GBM) is the most aggressive and lethal primary brain tumor. Conventional treatments have not achieved breakthroughs in improving survival. Therefore, novel molecular targets and biomarkers need to be identified. As signal transduction docks on the cell membrane, tetraspanins (TSPANs) are associated with various tumors; however, research on their role in GBM remains extremely scarce. Gene expression and clinicopathological characteristic data were obtained from GEPIA, CGGA, HPA, cBioPortal, and GSCA databases to analyze the mRNA and protein expression levels, prognostic value, clinical relevance, mutation status, and targeted drug sensitivity of TSPANs in GBM. Gene set enrichment analysis (GSEA), Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for biological process enrichment. Data from TCGA and TCIA were used to construct the tumor immune microenvironment landscape of TSPANs. Different R software algorithms were used to analyze the immune score, immune cell infiltration, and immune checkpoint correlation. Univariate and multivariate analyses were performed for TSPAN4, which had the most significant predictive prognostic value, and a nomogram model was constructed to predict individual outcomes. The expression and function of TSPAN4 were verified in vitro. TSPAN3/4/6/11/12/18/23/24/25/26/27/28/29/30/31expressions were significantly upregulated in GBM, and TSPAN3/4/6/11/18/24/25/26/29/30 were strongly correlated with prognosis. The expression of multiple TSPANs significantly correlated with 1p/19q co-deletion status, IDH mutation status, recurrence, age, and tumor grade. GSEA and GO analyses revealed the potential contribution of TSPANs in cell adhesion and migration. Immune correlation analysis revealed that TSPANs are related to the formation of the GBM tumor microenvironment (TME) and may influence immunotherapy outcomes. TSPAN4 is an independent prognostic factor and TSPAN4 knockdown has been demonstrated to strongly inhibit glioma cell proliferation, invasion, and migration in vitro. We comprehensively elaborated the prognostic value and potential role of differentially expressed TSPANs in GBM, including molecules that scientists have previously overlooked. This study provides a novel and comprehensive perspective on the pathological mechanisms of GBM and the future direction of individualized tumor immunotherapy, which may be a critical link between GBM malignant progression and TME remodeling., (© 2023. Springer Nature Limited.)

The prognosis of high-grade gliomas, such as glioblastoma multiforme (GBM), is extremely poor due to the highly invasive nature of these aggressive cancers. Previous work has demonstrated that TNF-weak like factor (TWEAK) induction of the noncanonical NF-κB pathway promotes the invasiveness of GBM cells in an NF-κB-inducing kinase (NIK)-dependent manner. While NIK activity is predominantly regulated at the posttranslational level, we show here that NIK (MAP3K14) is upregulated at the transcriptional level in invading cell populations, with the highest NIK expression observed in the most invasive cells. GBM cells with high induction of NIK gene expression demonstrate characteristics of collective invasion, facilitating invasion of neighboring cells. Furthermore, we demonstrate that the E2F transcription factors E2F4 and E2F5 directly regulate NIK transcription and are required to promote GBM cell invasion in response to TWEAK. Overall, our findings demonstrate that transcriptional induction of NIK facilitates collective cell migration and invasion, thereby promoting GBM pathogenesis., (© 2023. Springer Nature Limited.)

GBM (Glioblastoma) is the most lethal CNS (Central nervous system) tumor in adults, which inevitably develops resistance to standard treatments leading to recurrence and mortality. TRIB1 is a serine/threonine pseudokinase which functions as a scaffold platform that initiates degradation of its substrates like C/EBPα through the ubiquitin proteasome system and also activates MEK and Akt signaling. We found that increased TRIB1 gene expression associated with worse overall survival of GBM patients across multiple cohorts. Importantly, overexpression of TRIB1 decreased RT/TMZ (radiation therapy/temozolomide)-induced apoptosis in patient derived GBM cell lines in vitro. TRIB1 directly bound to MEK and Akt and increased ERK and Akt phosphorylation/activation. We also found that TRIB1 protein expression was maximal during G2/M transition of cell cycle in GBM cells. Furthermore, TRIB1 bound directly to HDAC1 and p53. Importantly, mice bearing TRIB1 overexpressing tumors had worse overall survival. Collectively, these data suggest that TRIB1 induces resistance of GBM cells to RT/TMZ treatments by activating the cell proliferation and survival pathways thus providing an opportunity for developing new targeted therapeutics., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The oncogenic role of long non-coding RNA SOX2 overlapping transcript (SOX2-OT) has been demonstrated as a miRNA decay system that sponges tumor suppressor miRNA, including miR-122-3p in glioblastoma and miR-194-5p in glioblastoma, gastric, and colorectal cancers. However, the molecular function of SOX2-OT remains unknown in most cancers, including lung cancer. In the current study, we aimed to evaluate the downstream regulatory function of SOX2-OT in A549 and Calu-3 lung cancer cell lines. We knocked down SOX2-OT expression using an RNA interference system, which significantly decreased expression in A549 and Calu-3 cells. The expression of down-regulating miRNAs (miR-122-3p and miR-194-5p) was evaluated, revealing increased expression of miR-122-3p and miR-194-5p. Additionally, the expression of miRNAs downstream mRNA, including FOXO1 (Forkhead Box O1) and FOXA1 (Forkhead Box O1), changed. Recently, critical roles of FOXO1 and FOXA1 proteins in pathways involved in proliferation, metastasis and apoptosis have been demonstrated. Downstream changes in cellular traits were assessed using MTT, flow cytometry, metastasis and apoptosis assays. These assessments confirmed that the biological behaviors of lung cancer cells were influenced after SOX2-OT knockdown. In summary, the present study highlights the oncogenic role of SOX2-OT through the regulation of miR-122-3p/FOXO1 and miR-194-5p/FOXA1 pathways., (© 2023. The Author(s).)

The average survival of patients with glioblastoma is 12-15 months. Therefore, finding a new treatment method is important, especially in cases that show resistance to treatment. Extremely low-frequency electromagnetic fields (ELF-EMF) have characteristics and capabilities that can be proposed as a new cancer treatment method with low side effects. This research examines the antitumor effect of ELF-EMF on U87 and U251 glioblastoma cell lines. Flowcytometry determined the viability/apoptosis and distribution of cells in different phases of the cell cycle. The size of cells was assessed by TEM. Important cell cycle regulation genes mRNA expression levels were investigated by real-time PCR. ELF-EMF induced apoptosis in U87cells much more than U251 (15% against 2.43%) and increased G2/M cell population in U87 (2.56%, p value < 0.05), and S phase in U251 (2.4%) (data are normalized to their sham exposure). The size of U87 cells increased significantly after ELF-EMF exposure (overexpressing P53 in U251 cells increased the apoptosis induction by ELF-EMF). The expression level of P53, P21, and MDM2 increased and CCNB1 decreased in U87. Among the studied genes, MCM6 expression decreased in U251. Increasing expression of P53, P21 and decreasing CCNB1, induction of cell G2/M cycle arrest, and consequently increase in the cell size can be suggested as one of the main mechanisms of apoptosis induction by ELF-EMF; furthermore, our results demonstrate the possible footprint of P53 in the apoptosis induction by ELF-EMF, as U87 carry the wild type of P53 and U251 has the mutated form of this gene., (© 2023. The Author(s).)

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy., (© 2023. The Author(s).)

TERT promoter mutations are a hallmark of glioblastoma (GBM). Accordingly, TERT and GABPB1, a subunit of the upstream mutant TERT promoter transcription factor GABP, are being considered as promising therapeutic targets in GBM. We recently reported that the expression of TERT or GABP1 modulates flux via the pentose phosphate pathway (PPP). Here, we investigated whether 13 C magnetic resonance spectroscopy (MRS) of hyperpolarized (HP) δ- [1- 13 C]gluconolactone can serve to image the reduction in PPP flux following TERT or GABPB1 silencing. We investigated two different human GBM cell lines stably expressing shRNAs targeting TERT or GABPB1, as well as doxycycline-inducible shTERT or shGABPB1cells. MRS studies were performed on live cells and in vivo tumors, and dynamic sets of 13 C MR spectra were acquired following injection of HP δ-[1- 13 C]gluconolactone. HP 6-phosphogluconolactone (6PG), the product of δ-[1- 13 C]gluconolactone via the PPP, was significantly reduced in TERT or GABPB1-silenced cells or tumors compared to controls in all our models. Furthermore, a positive correlation between TERT expression and 6PG levels was observed. Our data indicate that HP δ-[1- 13 C]gluconolactone, an imaging tool with translational potential, could serve to monitor TERT expression and its silencing with therapies that target either TERT or GABPB1 in mutant TERT promoter GBM patients., (© 2023. The Author(s).)

Accurate radiogenomic classification of brain tumors is important to improve the standard of diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused with radiomic features predicting the genetic subtype of glioblastoma. A novel fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, is proposed for latent feature extraction that fuses the quantitative knowledge to the spatial distribution and the size of tumorous structure through radiomic features: (GLCM, HOG, and LBP). The application of the novice rejection algorithm has been found significantly effective in selecting and isolating the negative training instances out of the original dataset. The fused feature vectors are then used for training and testing by k-NN and SVM classifiers. The 2021 RSNA Brain Tumor challenge dataset (BraTS-2021) consists of four structural mpMRIs, viz. fluid-attenuated inversion-recovery, T1-weighted, T1-weighted contrast enhancement, and T2-weighted. We evaluated the classification performance, for the very first time in published form, in terms of measures like accuracy, F 1 -score, and Matthews correlation coefficient. The Jackknife tenfold cross-validation was used for training and testing BraTS-2021 dataset validation. The highest classification performance is (96.84 ± 0.09)%, (96.08 ± 0.10)%, and (97.44 ± 0.14)% as accuracy, sensitivity, and specificity respectively to detect MGMT methylation status for patients suffering from glioblastoma. Deep learning feature extraction with radiogenomic features, fusing imaging phenotypes and molecular structure, using rejection algorithm has been found to perform outclass capable of detecting MGMT methylation status of glioblastoma patients. The approach relates the genomic variation with radiomic features forming a bridge between two areas of research that may prove useful for clinical treatment planning leading to better outcomes., (© 2023. The Author(s).)