Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients

Ensemble learning prediction framework for EGFR amplification status of glioma based on terahertz spectral features

Epidermal growth factor receptor (EGFR) plays a pivotal role in the initiation and progression of gliomas. In particular, in glioblastoma, EGFR amplification emerges as a catalyst for invasion, proliferation, and resistance to radiotherapy and chemotherapy. Current approaches are not capable of providing rapid diagnostic results of molecular pathology. In this study, we propose a terahertz spectroscopic approach for predicting the EGFR amplification status of gliomas for the first time. A machine learning model was constructed using the terahertz response of the measured glioma tissues, including the absorption coefficient, refractive index, and dielectric loss tangent. The novelty of our model is the integration of three classical base classifiers, i.e., support vector machine, random forest, and extreme gradient boosting. The ensemble learning method combines the advantages of various base classifiers, this model has more generalization ability. The effectiveness of the proposed method was validated by applying an individual test set. The optimal performance of the integrated algorithm was verified with an area under the curve (AUC) maximum of 85.8 %. This signifies a significant stride toward more effective and rapid diagnostic tools for guiding postoperative therapy in gliomas.

Resection of supratentorial high-grade gliomas availing of neuronavigation matched intraoperative ultrasound and Fluorescein: How far is it safe to push the resection?

Background

High-Grade Gliomas are the most common primary brain malignancies and despite the multimodal treatment, and the increasing amount of adjuvant treatment options the overall prognosis remains dismal. The present investigation aims to analyze the safety profile of the use of intraoperative ultrasounds (Io-US) in a homogeneous and matched cohort of patients suffering from High-grade gliomas (HGG) operated on with or without the aid of Io-US and Fluorescein in specific relation to the incidence of neurological and functional status sequelae.

Methods and materials

A retrospective analysis was performed on 74 patients affected by HGG. 22 patients were treated with Io-US matched with neuronavigational system (Group A); 15 patients were treated both with the use of Io-US and Fluorescein matched with neuronavigational system (Group B); 37 patients were treated with the use of the neuronavigational system only (Group C). Primary endpoints were the extent of resection and functional outcome (measured with Karnofski Performance Status).

Results

Significative differences were observed in terms of a higher extent of resection in Group B. In a multivariate analysis, this data appears to be independent of the location (eloquent/non-eloquent) of the lesion and from its histology. Regarding functional outcomes, no differences were detected between the two groups.

Conclusions

The present study is the first that analyzes the simultaneous use of Io-US and Fluorescein, and the results demonstrate that these two instruments together could improve the extent of resection in HGG while ensuring good outcomes in terms of functional status.

Expression of overall survival-EMT-immune cell infiltration genes predict the prognosis of glioma

This study investigates the crucial role of immune- and epithelial-mesenchymal transition (EMT)-associated genes and non-coding RNAs in glioma development and diagnosis, given the challenging 5-year survival rates associated with this prevalent CNS malignant tumor. Clinical and RNA data from glioma patients were meticulously gathered from CGGA databases, and EMT-related genes were sourced from dbEMT2.0, while immune-related genes were obtained from MSigDB. Employing consensus clustering, novel molecular subgroups were identified. Subsequent analyses, including ESTIMATE, TIMER, and MCP counter, provided insights into the tumor microenvironment (TIME) and immune status. Functional studies, embracing GO, KEGG, GSVA, and GSEA analyses, unraveled the underlying mechanisms governing these molecular subgroups. Utilizing the LASSO algorithm and multivariate Cox regression, a prognostic risk model was crafted. The study unveiled two distinct molecular subgroups with significantly disparate survival outcomes. A more favorable prognosis was linked to low immune scores, high tumor purity, and an abundance of immune infiltrating cells with differential expression of non-coding RNAs, including miRNAs. Functional analyses illuminated enrichment of immune- and EMT-associated pathways in differentially expressed genes and non-coding RNAs between these subgroups. GSVA and GSEA analyses hinted at abnormal EMT status potentially contributing to glioma-associated immune disorders. The risk model, centered on OS-EMT-ICI genes, exhibited promise in accurately predicting survival in glioma. Additionally, a nomogram integrating the risk model with clinical characteristics demonstrated notable accuracy in prognostic predictions for glioma patients. In conclusion, OS-EMT-ICI gene and non-coding RNA expression emerges as a valuable indicator intricately linked to immune microenvironment dysregulation, offering a robust tool for precise prognosis prediction in glioma patients within the OBMRC framework.

Hypoxia coordinates the spatial landscape of myeloid cells within glioblastoma to affect survival

Myeloid cells are highly prevalent in glioblastoma (GBM), existing in a spectrum of phenotypic and activation states. We now have limited knowledge of the tumor microenvironment (TME) determinants that influence the localization and the functions of the diverse myeloid cell populations in GBM. Here, we have utilized orthogonal imaging mass cytometry with single-cell and spatial transcriptomic approaches to identify and map the various myeloid populations in the human GBM tumor microenvironment (TME). Our results show that different myeloid populations have distinct and reproducible compartmentalization patterns in the GBM TME that is driven by tissue hypoxia, regional chemokine signaling, and varied homotypic and heterotypic cellular interactions. We subsequently identified specific tumor subregions in GBM, based on composition of identified myeloid cell populations, that were linked to patient survival. Our results provide insight into the spatial organization of myeloid cell subpopulations in GBM, and how this is predictive of clinical outcome.

mTORC1 regulates cell survival under glucose starvation through 4EBP1/2-mediated translational reprogramming of fatty acid metabolism

Energetic stress compels cells to evolve adaptive mechanisms to adjust their metabolism. Inhibition of mTOR kinase complex 1 (mTORC1) is essential for cell survival during glucose starvation. How mTORC1 controls cell viability during glucose starvation is not well understood. Here we show that the mTORC1 effectors eukaryotic initiation factor 4E binding proteins 1/2 (4EBP1/2) confer protection to mammalian cells and budding yeast under glucose starvation. Mechanistically, 4EBP1/2 promote NADPH homeostasis by preventing NADPH-consuming fatty acid synthesis via translational repression of Acetyl-CoA Carboxylase 1 (ACC1), thereby mitigating oxidative stress. This has important relevance for cancer, as oncogene-transformed cells and glioma cells exploit the 4EBP1/2 regulation of ACC1 expression and redox balance to combat energetic stress, thereby supporting transformation and tumorigenicity in vitro and in vivo. Clinically, high EIF4EBP1 expression is associated with poor outcomes in several cancer types. Our data reveal that the mTORC1-4EBP1/2 axis provokes a metabolic switch essential for survival during glucose starvation which is exploited by transformed and tumor cells.

Cysteine and glycine-rich protein 2 is crucial for maintaining the malignant phenotypes of gliomas through its action on Notch signalling cascade

Cysteine and glycine-rich protein 2 (CSRP2) is expressed differently in numerous cancers and plays a key role in carcinogenesis. However, the role of CSRP2 in glioma is unknown. This study sought to determine the expression profile and clinical significance of CSRP2 in glioma and explore its biological functions and mechanisms via lentivirus-mediated CSRP2 silencing experiments. Increased CSRP2 was frequently observed in gliomas, which was associated with clinicopathological characteristics and an unfavourable prognosis. Decreasing CSRP2 led to the suppression of malignant proliferation, metastasis and stemness in glioma cells while causing hypersensitivity to chemotherapeutic drugs. Mechanistic investigations revealed that CSRP2 plays a role in mediating the Notch signalling cascade. Silencing CSRP2 decreased the levels of Notch1, cleaved Notch1, HES1 and HEY1, suppressing the Notch signalling cascade. Reactivation of Notch markedly diminished the tumour-inhibiting effects of CSRP2 silencing on the malignant phenotypes of glioma cells. Notably, CSRP2-silencing glioma cells exhibited reduced potential in the formation of xenografts in nude mice in vivo, which was associated with an impaired Notch signalling cascade. These results showed that CSRP2 is overexpressed in glioma and has a crucial role in sustaining the malignant phenotypes of glioma, suggesting that targeting CSRP2 could be a promising strategy for glioma treatment.

Understanding the immunosuppressive microenvironment of glioma: mechanistic insights and clinical perspectives

Glioblastoma (GBM), the predominant and primary malignant intracranial tumor, poses a formidable challenge due to its immunosuppressive microenvironment, thereby confounding conventional therapeutic interventions. Despite the established treatment regimen comprising surgical intervention, radiotherapy, temozolomide administration, and the exploration of emerging modalities such as immunotherapy and integration of medicine and engineering technology therapy, the efficacy of these approaches remains constrained, resulting in suboptimal prognostic outcomes. In recent years, intensive scrutiny of the inhibitory and immunosuppressive milieu within GBM has underscored the significance of cellular constituents of the GBM microenvironment and their interactions with malignant cells and neurons. Novel immune and targeted therapy strategies have emerged, offering promising avenues for advancing GBM treatment. One pivotal mechanism orchestrating immunosuppression in GBM involves the aggregation of myeloid-derived suppressor cells (MDSCs), glioma-associated macrophage/microglia (GAM), and regulatory T cells (Tregs). Among these, MDSCs, though constituting a minority (4-8%) of CD45+ cells in GBM, play a central component in fostering immune evasion and propelling tumor progression, angiogenesis, invasion, and metastasis. MDSCs deploy intricate immunosuppressive mechanisms that adapt to the dynamic tumor microenvironment (TME). Understanding the interplay between GBM and MDSCs provides a compelling basis for therapeutic interventions. This review seeks to elucidate the immune regulatory mechanisms inherent in the GBM microenvironment, explore existing therapeutic targets, and consolidate recent insights into MDSC induction and their contribution to GBM immunosuppression. Additionally, the review comprehensively surveys ongoing clinical trials and potential treatment strategies, envisioning a future where targeting MDSCs could reshape the immune landscape of GBM. Through the synergistic integration of immunotherapy with other therapeutic modalities, this approach can establish a multidisciplinary, multi-target paradigm, ultimately improving the prognosis and quality of life in patients with GBM.

Glioblastoma stem cells deliver ABCB4 transcribed by ATF3 via exosomes conferring glioblastoma resistance to temozolomide

Glioblastoma stem cells (GSCs) play a key role in glioblastoma (GBM) resistance to temozolomide (TMZ) chemotherapy. With the increase in research on the tumour microenvironment, exosomes secreted by GSCs have become a new focus in GBM research. However, the molecular mechanism by which GSCs affect drug resistance in GBM cells via exosomes remains unclear. Using bioinformatics analysis, we identified the specific expression of ABCB4 in GSCs. Subsequently, we established GSC cell lines and used ultracentrifugation to extract secreted exosomes. We conducted in vitro and in vivo investigations to validate the promoting effect of ABCB4 and ABCB4-containing exosomes on TMZ resistance. Finally, to identify the transcription factors regulating the transcription of ABCB4, we performed luciferase assays and chromatin immunoprecipitation-quantitative PCR. Our results indicated that ABCB4 is highly expressed in GSCs. Moreover, high expression of ABCB4 promoted the resistance of GSCs to TMZ. Our study found that GSCs can also transmit their highly expressed ABCB4 to differentiated glioma cells (DGCs) through exosomes, leading to high expression of ABCB4 in these cells and promoting their resistance to TMZ. Mechanistic studies have shown that the overexpression of ABCB4 in GSCs is mediated by the transcription factor ATF3. In conclusion, our results indicate that GSCs can confer resistance to TMZ in GBM by transmitting ABCB4, which is transcribed by ATF3, through exosomes. This mechanism may lead to drug resistance and recurrence of GBM. These findings contribute to a deeper understanding of the mechanisms underlying drug resistance in GBM and provide novel insights into its treatment.

MET fusions and splicing variants is a strong adverse prognostic factor in astrocytoma, isocitrate dehydrogenase mutant

Liu et al. describe the adverse prognostic role of MET fusions and splicing variants in astrocytoma, isocitrate dehydrogenase mutant. On this basis, MET fusions and splicing variants was suggested to be a biomarker for the diagnosis of high-grade astrocytoma, isocitrate dehydrogenase mutant.

CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle

Glioblastoma (GBM) is characterized by significant heterogeneity, leading to poor survival outcomes for patients, despite the implementation of comprehensive treatment strategies. The roles of cyclin A2 (CCNA2) and NIMA related kinase 2 (NEK2) have been extensively studied in numerous cancers, but their specific functions in GBM remain to be elucidated. The present study aimed to investigate the potential molecular mechanisms of CCNA2 and NEK2 in GBM. CCNA2 and NEK2 expression and prognosis in glioma were evaluated by bioinformatics methods. In addition, the distribution of CCNA2 and NEK2 expression in GBM subsets was determined using pseudo-time analysis and tricycle position of single-cell sequencing. Gene Expression Omnibus and Kyoto Encyclopedia of Genes and Genome databases were employed and enrichment analyses were conducted to investigate potential signaling pathways in GBM subsets and a nomogram was established to predict 1-, 2- and 3-year overall survival probability in GBM. CCNA2 and NEK2 expression levels were further validated by western blot analysis and immunohistochemical staining in GBM samples. High expression of CCNA2 and NEK2 in glioma indicates poor clinical outcomes. Single-cell sequencing of GBM revealed that these genes were upregulated in a subset of positive neural progenitor cells (P-NPCs), which showed significant proliferation and progression properties and may activate G2M checkpoint pathways. A comprehensive nomogram predicts 1-, 2- and 3-year overall survival probability in GBM by considering P-NPCs, age, chemotherapy and radiotherapy scores. CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle, thus indicating the potential of novel therapy directed to CCNA2 and NEK2 in GBM.

HNF1A induces glioblastoma by upregulating EPS8 and activating PI3K/AKT signaling pathway

Despite the exact biological role of HNF1 homolog A (HNF1A) in the regulatory mechanism of glioblastoma (GBM), the molecular mechanism, especially the downstream regulation as a transcription factor, remains to be further elucidated. Immunohistochemistry was used to detect the expression and clinical relevance of HNF1A in GBM patients. CCK8, TUNEL, and subcutaneous tumor formation in nude mice were used to evaluate the effect of HNF1A on GBM in vitro and in vivo. The correction between HNF1A and epidermal growth factor receptor pathway substrate 8 (EPS8) was illustrated by bioinformatics analysis and luciferase assay. Further mechanism was explored that the transcription factor HNF1A regulated the expression of EPS8 and downstream signaling pathways by directly binding to the promoter region of EPS8. Our comprehensive analysis of clinical samples in this study showed that upregulated expression of HNF1A was associated with poor survival in GBM patients. Further, we found that knockdown of HNF1A markedly suppressed the malignant phenotype of GBM cells in vivo and in vitro as well as promoted apoptosis of tumor cells, which was reversed by upregulation of HNF1A. Mechanistically, HNF1A could significantly activate PI3K/AKT signaling pathway by specifically binding to the promoter regions of EPS8. Moreover, overexpression of EPS8 was able to reverse the apoptosis of tumor cells caused by HNF1A knockdown, thereby exacerbating the GBM progression. Correctively, our study has clarified the explicit mechanism by which HNF1A promotes GBM malignancy and provides a new therapeutic target for further clinical application.

Expression of molecular markers and synergistic anticancer effects of chemotherapy with antimicrobial peptides on glioblastoma cells

OBJECTIVE

Glioblastoma multiforme (GBM) is the most aggressive and fatal malignant primary brain tumor. The enhancement of the survival rate for glioma patients remains limited, even with the utilization of a combined treatment approach involving surgery, radiotherapy, and chemotherapy. This study was designed to assess the expression of IDH1, TP53, EGFR, Ki-67, GFAP, H3K27M, MGMT, VEGF, NOS, CD99, and ATRX in glioblastoma tissue from 11 patients. We investigated the anticancer impact and combined effects of cathelicidin (LL-37), protegrin-1 (PG-1), with chemotherapy-temozolomide (TMZ), doxorubicin (DOX), carboplatin (CB), cisplatin (CPL), and etoposide (ETO) in primary GBM cells. In addition, we examined the effect of LL-37, PG-1 on normal human fibroblasts and in the C6/Wistar rat intracerebral glioma model.

METHODS

For this study, 11 cases of glioblastoma were evaluated immunohistochemically for IDH1, TP53, EGFR, Ki-67, GFAP, H3K27M, MGMT, VEGF, NOS, CD99, and ATRX. The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was used to study cells viability and to determine cytotoxic effects of LL-37, PG-1 and their combination with chemotherapy in primary GBM cells. Synergism or antagonism was determined using combination index (CI) method. Finally, we established C6 glioblastoma model in Wistar rats to investigate the antitumor activity.

RESULTS

Peptides showed a strong cytotoxic effect on primary GBM cells in the MTT test (IC50 2-16 and 1-32 μM) compared to chemotherapy. The dual-drug combinations of LL-37 + DOX, LL-37 + CB (CI 0.46-0.75) and PG-1 + DOX, PG-1 + CB, PG-1 + TMZ (CI 0.11-0.77), demonstrated a synergism in primary GBM cells. In rat C6 intracerebral GBM model, survival of rats in experimental group (66.75 ± 12.6 days) was prolonged compared with that in control cohort (26.2 ± 2.66 days, p = 0.0008). After LL-37 treatment, experimental group rats showed significantly lower tumor volumes (31.00 ± 8.8 mm3) and weight (49.4 ± 13.3 mg) compared with control group rats (153.8 ± 43.53 mg, p = 0.038; 82.50 ± 7.60 mm3, respectively).

CONCLUSIONS

The combination of antimicrobial peptides and chemical drugs enhances the cytotoxicity of chemotherapy and exerts synergistic antitumor effects in primary GBM cells. Moreover, in vivo study provided the first evidence that LL-37 could effectively inhibit brain tumor growth in rat C6 intracerebral GBM model. These results suggested a significant strategy for proposing a promising therapy for the treatment of GBM.

Disruption of metazoan gene regulatory networks in cancer alters the balance of co-expression between genes of unicellular and multicellular origins

BACKGROUND

Metazoans inherited genes from unicellular ancestors that perform essential biological processes such as cell division, metabolism, and protein translation. Multicellularity requires careful control and coordination of these unicellular genes to maintain tissue integrity and homeostasis. Gene regulatory networks (GRNs) that arose during metazoan evolution are frequently altered in cancer, resulting in over-expression of unicellular genes. We propose that an imbalance in co-expression of unicellular (UC) and multicellular (MC) genes is a driving force in cancer.

RESULTS

We combine gene co-expression analysis to infer changes to GRNs in cancer with protein sequence conservation data to distinguish genes with UC and MC origins. Co-expression networks created using RNA sequencing data from 31 tumor types and normal tissue samples are divided into modules enriched for UC genes, MC genes, or mixed UC-MC modules. The greatest differences between tumor and normal tissue co-expression networks occur within mixed UC-MC modules. MC and UC genes not commonly co-expressed in normal tissues form distinct co-expression modules seen only in tumors. The degree of rewiring of genes within mixed UC-MC modules increases with tumor grade and stage. Mixed UC-MC modules are enriched for somatic mutations in cancer genes, particularly amplifications, suggesting an important driver of the rewiring observed in tumors is copy number changes.

CONCLUSIONS

Our study shows the greatest changes to gene co-expression patterns during tumor progression occur between genes of MC and UC origins, implicating the breakdown and rewiring of metazoan gene regulatory networks in cancer development and progression.

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma

Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

HIF-1α-mediated LAMC1 overexpression is an unfavorable predictor of prognosis for glioma patients: evidence from pan-cancer analysis and validation experiments

BACKGROUND

Laminin subunit gamma-1 (LAMC1) is a major extracellular matrix molecule involved in the tumor microenvironment. Knowledge of the biological features and clinical relevance of LAMC1 in cancers remains limited.

METHODS

We conducted comprehensive bioinformatics analysis of LAMC1 gene expression and clinical relevance in pan-cancer datasets of public databases and validated LAMC1 expression in glioma tissues and cell lines. The association and regulatory mechanism between hypoxia inducible factor-1α (HIF-1α) and LAMC1 expression were explored.

RESULTS

LAMC1 expression in most cancers in The Cancer Genome Atlas (TCGA) including glioma was significantly higher than that in normal tissues, which had a poor prognosis and were related to various clinicopathological features. Data from the Chinese Glioma Genome Atlas also showed high expression of LAMC1 in glioma associated with poor prognoses. In clinical glioma tissues, LAMC1 protein was highly expressed and correlated to poor overall survival. LAMC1 knockdown in Hs683 glioma cells attenuated cell proliferation, migration, and invasion, while overexpression of LAMC1 in U251 cells leads to the opposite trend. Most TCGA solid cancers including glioma showed enhancement of HIF-1α expression. High HIF-1α expression leads to adverse prognosis in gliomas, besides, HIF-1α expression was positively related to LAMC1. Mechanistically, HIF-1α directly upregulated LAMC1 promotor activity. Hypoxia (2% O2)-treated Hs683 and U251 cells exhibited upregulated HIF-1α and LAMC1 expression, which was significantly attenuated by HIF-1α inhibitor YC-1 and accompanied by attenuated cell proliferation and invasion.

CONCLUSIONS

High expression of LAMC1 in some solid tumors including gliomas suggests a poor prognosis. The hypoxic microenvironment in gliomas activates the HIF-1α/LAMC1 signaling, thereby promoting tumor progression. Targeted intervention on the HIF-1α/LAMC1 signaling attenuates cell growth and invasion, suggesting a new strategy for glioma treatment.

Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid (DNA) methylation, and naris-occlusion controlled genes (NOCGs) was performed. Immunohistochemistry was used to evaluate GNAL level in glioma. Further analysis was conducted to evaluate the drug sensitivity, immunotherapy response, and functional enrichment of GNAL. GNAL was an independent prognostic factor, and patients with low GNAL expression have a poor prognosis. Expression of GNAL was closely associated with clinicopathological characteristics, DNA methylation, and several immune-related pathways. Immune infiltration analysis indicated that GNAL levels were negatively correlated with immune scores. GNAL low-expression group showed efficacy with anti-PD-1 therapy. Ten compounds with significantly different half-maximal inhibitory concentration (IC50) values between the GNAL high and low-expression groups were identified. Furthermore, its expression was associated with several immune cells, immune-related genes, and NOCGs. The expression of GNAL is closely associated with clinicopathological characteristics, TIME, and the response to therapeutic interventions, highlighting its potential as a prognostic biomarker for glioma.

A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

Haploinsufficiency of phosphodiesterase 10A activates PI3K/AKT signaling independent of PTEN to induce an aggressive glioma phenotype

Glioblastoma is universally fatal and characterized by frequent chromosomal copy number alterations harboring oncogenes and tumor suppressors. In this study, we analyzed exome-wide human glioblastoma copy number data and found that cytoband 6q27 is an independent poor prognostic marker in multiple data sets. We then combined CRISPR-Cas9 data, human spatial transcriptomic data, and human and mouse RNA sequencing data to nominate PDE10A as a potential haploinsufficient tumor suppressor in the 6q27 region. Mouse glioblastoma modeling using the RCAS/tv-a system confirmed that Pde10a suppression induced an aggressive glioma phenotype in vivo and resistance to temozolomide and radiation therapy in vitro. Cell culture analysis showed that decreased Pde10a expression led to increased PI3K/AKT signaling in a Pten-independent manner, a response blocked by selective PI3K inhibitors. Single-nucleus RNA sequencing from our mouse gliomas in vivo, in combination with cell culture validation, further showed that Pde10a suppression was associated with a proneural-to-mesenchymal transition that exhibited increased cell adhesion and decreased cell migration. Our results indicate that glioblastoma patients harboring PDE10A loss have worse outcomes and potentially increased sensitivity to PI3K inhibition.

Proteomic Analysis of Spatial Heterogeneity Identifies HMGB2 as Putative Biomarker of Tumor Progression in Adult-Type Diffuse Astrocytomas

Although grading is defined by the highest histological grade observed in a glioma, most high-grade gliomas retain areas with histology reminiscent of their low-grade counterparts. We sought to achieve the following: (i) identify proteins and molecular pathways involved in glioma evolution; and (ii) validate the high mobility group protein B2 (HMGB2) as a key player in tumor progression and as a prognostic/predictive biomarker for diffuse astrocytomas. We performed liquid chromatography tandem mass spectrometry (LC-MS/MS) in multiple areas of adult-type astrocytomas and validated our finding in multiplatform-omics studies and high-throughput IHC analysis. LC-MS/MSdetected proteomic signatures characterizing glioma evolution towards higher grades associated with, but not completely dependent, on IDH status. Spatial heterogeneity of diffuse astrocytomas was associated with dysregulation of specific molecular pathways, and HMGB2 was identified as a putative driver of tumor progression, and an early marker of worse overall survival in grades 2 and 3 diffuse gliomas, at least in part regulated by DNA methylation. In grade 4 astrocytomas, HMGB2 expression was strongly associated with proliferative activity and microvascular proliferation. Grounded in proteomic findings, our results showed that HMGB2 expression assessed by IHC detected early signs of tumor progression in grades 2 and 3 astrocytomas, as well as identified GBMs that had a better response to the standard chemoradiation with temozolomide.

A Lactate-Depleting metal organic framework-based nanocatalyst reinforces intratumoral T cell response to boost anti-PD1 immunotherapy

Infiltration and activation of intratumoral T lymphocytes are critical for immune checkpoint blockade (ICB) therapy. Unfortunately, the low tumor immunogenicity and immunosuppressive tumor microenvironment (TME) induced by tumor metabolic reprogramming cooperatively hinder the ICB efficacy. Herein, we engineered a lactate-depleting MOF-based catalytic nanoplatform (LOX@ZIF-8@MPN), encapsulating lactate oxidase (LOX) within zeolitic imidazolate framework-8 (ZIF-8) coupled with a coating of metal polyphenol network (MPN) to reinforce T cell response based on a "two birds with one stone" strategy. LOX could catalyze the degradation of the immunosuppressive lactate to promote vascular normalization, facilitating T cell infiltration. On the other hand, hydrogen peroxide (H2O2) produced during lactate depletion can be transformed into anti-tumor hydroxyl radical (•OH) by the autocatalytic MPN-based Fenton nanosystem to trigger immunogenic cell death (ICD), which largely improved the tumor immunogenicity. The combination of ICD and vascular normalization presents a better synergistic immunopotentiation with anti-PD1, inducing robust anti-tumor immunity in primary tumors and recurrent malignancies. Collectively, our results demonstrate that the concurrent depletion of lactate to reverse the immunosuppressive TME and utilization of the by-product from lactate degradation via cascade catalysis promotes T cell response and thus improves the effectiveness of ICB therapy.

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas

Gliomas are the most prevalent primary malignant tumors affecting the brain, with high recurrence and mortality rates. Accurate diagnoses and effective treatment challenges persist, emphasizing the need for identifying new biomarkers to guide clinical decisions. Long noncoding RNAs (lncRNAs) hold potential as diagnostic and therapeutic biomarkers in cancer. However, only a limited subset of lncRNAs in gliomas have been explored. Therefore, this study aims to identify lncRNA signatures applicable to patients with gliomas across all grades and explore their clinical significance and potential biological mechanisms. Data used in this study were obtained from TCGA, CGGA, and GEO datasets to identify key lncRNA signatures in gliomas through differential and survival analyses and machine learning algorithms. We examined their associations with the clinical characteristics, gene mutations, diagnosis, and prognosis of gliomas. Functional enrichment analysis was employed to elucidate the potential biological mechanisms associated with these significant lncRNA signatures. We explored competing endogenous RNA (ceRNA) regulatory networks. We found that NDUFA6-DT emerged as a significant lncRNA signature in gliomas, with reduced NDUFA6-DT expression associated with a worse prognosis in gliomas. Nomogram analysis incorporating NDUFA6-DT expression levels exhibited excellent prognostic and predictive capabilities. Functional annotation suggested that NDUFA6-DT might influence immunological responses and synaptic transmission, potentially modifying glioma initiation and progression. The associated ceRNA network revealed the possible presence of the NDUFA6-DT-miR-455-3p-YWHAH/YWHAG axis in low-grade glioma (LGG) and glioblastoma multiforme (GBM), regulating the PI3K-AKT signaling pathway and influencing glioma cell survival and apoptosis. We believe that NDUFA6-DT is a novel lncRNA linked to glioma diagnosis and prognosis, potentially becoming a pivotal biomarker for glioma.

ecGBMsub: an integrative stacking ensemble model framework based on eccDNA molecular profiling for improving IDH wild-type glioblastoma molecular subtype classification

IDH wild-type glioblastoma (GBM) intrinsic subtypes have been linked to different molecular landscapes and outcomes. Accurate prediction of molecular subtypes of GBM is very important to guide clinical diagnosis and treatment. Leveraging machine learning technology to improve the subtype classification was considered a robust strategy. Several single machine learning models have been developed to predict survival or stratify patients. An ensemble learning strategy combines several basic learners to boost model performance. However, it still lacked a robust stacking ensemble learning model with high accuracy in clinical practice. Here, we developed a novel integrative stacking ensemble model framework (ecGBMsub) for improving IDH wild-type GBM molecular subtype classification. In the framework, nine single models with the best hyperparameters were fitted based on extrachromosomal circular DNA (eccDNA) molecular profiling. Then, the top five optimal single models were selected as base models. By randomly combining the five optimal base models, 26 different combinations were finally generated. Nine different meta-models with the best hyperparameters were fitted based on the prediction results of 26 different combinations, resulting in 234 different stacked ensemble models. All models in ecGBMsub were comprehensively evaluated and compared. Finally, the stacking ensemble model named "XGBoost.Enet-stacking-Enet" was chosen as the optimal model in the ecGBMsub framework. A user-friendly web tool was developed to facilitate accessibility to the XGBoost.Enet-stacking-Enet models (https://lizesheng20190820.shinyapps.io/ecGBMsub/).

CCR2 and CCR5 co-inhibition modulates immunosuppressive myeloid milieu in glioma and synergizes with anti-PD-1 therapy

Immunotherapy has revolutionized the treatment of cancers. Reinvigorating lymphocytes with checkpoint blockade has become a cornerstone of immunotherapy for multiple tumor types, but the treatment of glioblastoma has not yet shown clinical efficacy. A major hurdle to treat GBM with checkpoint blockade is the high degree of myeloid-mediated immunosuppression in brain tumors that limits CD8 T-cell activity. A potential strategy to improve anti-tumor efficacy against glioma is to use myeloid-modulating agents to target immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment. We found that the co-inhibition of the chemokine receptors CCR2 and CCR5 in murine model of glioma improves the survival and synergizes robustly with anti-PD-1 therapy. Moreover, the treatment specifically reduced the infiltration of monocytic-MDSCs (M-MDSCs) into brain tumors and increased lymphocyte abundance and cytokine secretion by tumor-infiltrating CD8 T cells. The depletion of T-cell subsets and myeloid cells abrogated the effects of CCR2 and CCR5 blockade, indicating that while broad depletion of myeloid cells does not improve survival, specific reduction in the infiltration of immunosuppressive myeloid cells, such as M-MDSCs, can boost the anti-tumor immune response of lymphocytes. Our study highlights the potential of CCR2/CCR5 co-inhibition in reducing myeloid-mediated immunosuppression in GBM patients.

Explorative Discovery of Gene Signatures and Clinotypes in Glioblastoma Cancer Through GeneTerrain Knowledge Map Representation

This study introduces the GeneTerrain Knowledge Map Representation (GTKM), a novel method for visualizing gene expression data in cancer research. GTKM leverages protein-protein interactions to graphically display differentially expressed genes (DEGs) on a 2-dimensional contour plot, offering a more nuanced understanding of gene interactions and expression patterns compared to traditional heatmap methods. The research demonstrates GTKM's utility through four case studies on glioblastoma (GBM) datasets, focusing on survival analysis, subtype identification, IDH1 mutation analysis, and drug sensitivities of different tumor cell lines. Additionally, a prototype website has been developed to showcase these findings, indicating the method's adaptability for various cancer types. The study reveals that GTKM effectively identifies gene patterns associated with different clinical outcomes in GBM, and its profiles enable the identification of sub-gene signature patterns crucial for predicting survival. The methodology promises significant advancements in precision medicine, providing a powerful tool for understanding complex gene interactions and identifying potential therapeutic targets in cancer treatment.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

BACKGROUND

A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials.

METHODS

Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors.

RESULTS

We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components.

CONCLUSIONS

Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.

EZH2 Promotes Glioma Cell Proliferation, Invasion, and Migration via Mir-142-3p/KCNQ1OT1/HMGB3 Axis : Running Title: EZH2 Promotes Glioma cell Malignant Behaviors

This study investigates the role and molecular mechanism of EZH2 in glioma cell proliferation, invasion, and migration. EZH2, miR-142-3p, lncRNA KCNQ1OT1, LIN28B, and HMGB3 expressions in glioma tissues and cells were determined using qRT-PCR or Western blot, followed by CCK-8 assay detection of cell viability, Transwell detection of invasion and migration, ChIP analysis of the enrichment of EZH2 and H3K27me3 on miR-142-3p promoter, dual-luciferase reporter assay and RIP validation of the binding of miR-142-3p-KCNQ1OT1 and KCNQ1OT1-LIN28B, and actinomycin D detection of KCNQ1OT1 and HMGB3 mRNA stability. A nude mouse xenograft model and a lung metastasis model were established. EZH2, KCNQ1OT1, LIN28B, and HMGB3 were highly expressed while miR-142-3p was poorly expressed in gliomas. EZH2 silencing restrained glioma cell proliferation, invasion, and migration. EZH2 repressed miR-142-3p expression by elevating the H3K27me3 level. miR-142-3p targeted KCNQ1OT1 expression, and KCNQ1OT1 bound to LIN28B to stabilize HMGB3 mRNA, thereby promoting its protein expression. EZH2 silencing depressed tumor growth and metastasis in nude mice via the miR-142-3p/KCNQ1OT1/HMGB3 axis. In conclusion, EZH2 curbed miR-142-3p expression, thereby relieving the inhibition of KCNQ1OT1 expression by miR-142-3p, enhancing the binding of KCNQ1OT1 to LIN28B, elevating HMGB3 expression, and ultimately accelerating glioma cell proliferation, invasion, and migration.

Identification of genetic modifiers enhancing B7-H3-targeting CAR T cell therapy against glioblastoma through large-scale CRISPRi screening

BACKGROUND

Glioblastoma multiforme (GBM) is a highly aggressive brain tumor with a poor prognosis. Current treatment options are limited and often ineffective. CAR T cell therapy has shown success in treating hematologic malignancies, and there is growing interest in its potential application in solid tumors, including GBM. However, current CAR T therapy lacks clinical efficacy against GBM due to tumor-related resistance mechanisms and CAR T cell deficiencies. Therefore, there is a need to improve CAR T cell therapy efficacy in GBM.

METHODS

We conducted large-scale CRISPR interference (CRISPRi) screens in GBM cell line U87 MG cells co-cultured with B7-H3 targeting CAR T cells to identify genetic modifiers that can enhance CAR T cell-mediated tumor killing. Flow cytometry-based tumor killing assay and CAR T cell activation assay were performed to validate screening hits. Bioinformatic analyses on bulk and single-cell RNA sequencing data and the TCGA database were employed to elucidate the mechanism underlying enhanced CAR T efficacy upon knocking down the selected screening hits in U87 MG cells.

RESULTS

We established B7-H3 as a targetable antigen for CAR T therapy in GBM. Through large-scale CRISPRi screening, we discovered genetic modifiers in GBM cells, including ARPC4, PI4KA, ATP6V1A, UBA1, and NDUFV1, that regulated the efficacy of CAR T cell-mediated tumor killing. Furthermore, we discovered that TNFSF15 was upregulated in both ARPC4 and NDUFV1 knockdown GBM cells and revealed an immunostimulatory role of TNFSF15 in modulating tumor-CAR T interaction to enhance CAR T cell efficacy.

CONCLUSIONS

Our study highlights the power of CRISPR-based genetic screening in investigating tumor-CAR T interaction and identifies potential druggable targets in tumor cells that confer resistance to CAR T cell killing. Furthermore, we devised targeted strategies that synergize with CAR T therapy against GBM. These findings shed light on the development of novel combinatorial strategies for effective immunotherapy of GBM and other solid tumors.

Deep-targeted gene sequencing reveals ARID1A mutation as an important driver of glioblastoma

AIMS

To investigate the key factors influencing glioma progression and the emergence of treatment resistance by examining the intrinsic connection between mutations in DNA damage and repair-related genes and the development of chemoresistance in gliomas.

METHODS

We conducted a comprehensive analysis of deep-targeted gene sequencing data from 228 glioma samples. This involved identifying differentially mutated genes across various glioma grades, assessing their functions, and employing I-TASSER for homology modeling. We elucidated the functional changes induced by high-frequency site mutations in these genes and investigated their impact on glioma progression.

RESULTS

The analysis of sequencing mutation results of deep targeted genes in integration revealed that ARID1A gene mutation occurs frequently in glioblastoma and alteration of ARID1A could affect the tolerance of glioma cells to temozolomide treatment. The deletion of proline at position 16 in the ARID1A protein affected the stability of binding of the SWI/SNF core subunit BRG1, which in turn affected the stability of the SWI/SNF complex and led to altered histone modifications in the CDKN1A promoter region, thereby affecting the biological activity of glioma cells, as inferred from modeling and protein interaction analysis.

CONCLUSION

The ARID1A gene is a critical predictive biomarker for glioma. Mutations at the ARID1A locus alter the stability of the SWI/SNF complex, leading to changes in transcriptional regulation in glioma cells. This contributes to an increased malignant phenotype of GBM and plays a pivotal role in mediating chemoresistance.

A TGF-β signaling-related lncRNA signature for prediction of glioma prognosis, immune microenvironment, and immunotherapy response

AIMS

The dysregulation of TGF-β signaling is a crucial pathophysiological process in tumorigenesis and progression. LncRNAs have diverse biological functions and are significant participants in the regulation of tumor signaling pathways. However, the clinical value of lncRNAs related to TGF-β signaling in glioma is currently unclear.

METHODS

Data on glioma's RNA-seq transcriptome, somatic mutation, DNA methylation data, and clinicopathological information were derived from the CGGA and TCGA databases. A prognostic lncRNA signature was constructed by Cox and LASSO regression analyses. TIMER2.0 database was utilized to deduce immune infiltration characteristics. "ELMER v.2" was used to reconstruct TF-methylation-gene regulatory network. Immunotherapy and chemotherapy response predictions were implemented by the TIDE algorithm and GDSC database, respectively. In vitro and in vivo experiments were conducted to verify the results and clarify the regulatory mechanism of lncRNA.

RESULTS

In glioma, a TGF-β signaling-related 15-lncRNA signature was constructed, including AC010173.1, HOXA-AS2, AC074286.1, AL592424.1, DRAIC, HOXC13-AS, AC007938.1, AC010729.1, AC013472.3, AC093895.1, AC131097.4, AL606970.4, HOXC-AS1, AGAP2-AS1, and AC002456.1. This signature proved to be a reliable prognostic tool, with high risk indicating an unfavorable prognosis and being linked to malignant clinicopathological and genomic mutation traits. Risk levels were associated with different immune infiltration landscapes, where high risk was indicative of high levels of macrophage infiltration. In addition, high risk also suggested better immunotherapy and chemotherapy response. cg05987823 was an important methylation site in glioma progression, and AP-1 transcription factor family participated in the regulation of signature lncRNA expression. AGAP2-AS1 knockdown in in vitro and in vivo experiments inhibited the proliferation, migration, and invasion of glioma cells, as well as the growth of glioma, by downregulating the expression levels of NF-κB and ERK 1/2 in the TGF-β signaling pathway.

CONCLUSIONS

A prognostic lncRNA signature of TGF-β signaling was established in glioma, which can be used for prognostic judgment, immune infiltration status inference, and immunotherapy response prediction. AGAP2-AS1 plays an important role in glioma progression.

PSMA2 promotes glioma proliferation and migration via EMT

BACKGROUND

Gliomas advance rapidly and are associated with a poor prognosis. Epithelial-mesenchymal transition (EMT) accelerates the progression of gliomas, exerting a pivotal role in glioma development. Proteasome subunit alpha type-2 (PSMA2) exhibits high expression levels in gliomas. however, its specific involvement in glioma progression and its correlation with EMT remain elusive. This study aims to elucidate the role of PSMA2 in glioma progression and its potential association with EMT.

METHODS

Online tools were employed to analyze the expression patterns and survival curves of PSMA2 in gliomas. The relationship between PSMA2 and various characteristics of glioma patients was investigated using data from the TCGA and CGGA databases. In vitro, cell proliferation and migration were assessed through CCK-8, colony formation, and transwell assays. Furthermore, a tumor xenograft model in nude mice was established to evaluate in vivo tumorigenesis. Protein binding to PSMA2 was scrutinized using co-immunoprecipitation MS (co-IP MS). The potential biological functions and molecular pathways associated with PSMA2 were explored through GO analysis and KEGG analysis, and the correlation between PSMA2 and EMT was validated through correlation analysis and Western blot experiments.

RESULTS

Bioinformatics analysis revealed a significant upregulation of PSMA2 across various cancers, with particularly heightened expression in gliomas. Moreover, elevated PSMA2 levels were correlated with advanced tumor stages and diminished survival rates among glioma patients. Inhibition of PSMA2 demonstrated a pronounced suppressive effect on glioma cell proliferation, both in vitro and in vivo. Knockdown of PSMA2 also impeded the migratory capacity of glioma cells. GO and KEGG enrichment analyses indicated that PSMA2-binding proteins (identified through Co-IP-MS) were associated with cell adhesion molecule binding and cadherin binding. Western blot results further confirmed the role of PSMA2 in promoting epithelial-mesenchymal transition (EMT) in glioma cells.

CONCLUSION

Our study provides evidence supporting the role of PSMA2 as a regulatory factor in EMT and suggests its potential as a prognostic biomarker for glioma progression.

Potential value of expression of receptor accessory protein 4 for evaluating the prognosis of lower-grade glioma patients

BACKGROUND

REEP4 is involved in the regulation of the biological process of mitosis. Lower grade glioma (LGG), as a malignant tumor, is accompanied by abnormalities in mitosis, but there have been no reports of REEP4 so far.

METHODS

We collected transcriptome data, DNA methylation data and the clinical characteristics of thousands of patients with LGG. Various big data analysis methods and molecular biology experiments were employed to reveal the impact of REEP4 on the pathological process of LGG.

RESULTS

It was found that the expression of REEP4 was significantly elevated and negatively regulated by its methylation site. Therefore, both the high expression of REEP4 and low methylation state of cg16311504 showed that the patients are correlated with lower patient survival rate. In addition, high REEP4 expression participates in the regulation of various cancer-related cellular signaling pathways, such as the cell cycle, MAPK signaling pathway, NOD-like receptor signaling pathway, etc. More importantly, the level of immune cell infiltration significantly increased in the high expression group of REEP4 in the LGG tumor microenvironment and REEP4 has a high positive correlation with PD-L1 and other immune checkpoints.

CONCLUSIONS

In brief, this study is the first to introduce REEP4 in malignant tumors, which can be used as an independent risk factor that participates in the malignant process of LGG. More importantly, REEP4 has the potential to become a new star in the field of anti-tumor treatment.

Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential

Glioblastoma, a notably aggressive brain tumor, is characterized by a brief survival period and resistance to conventional therapeutic approaches. With the recent identification of "Cuproptosis," a copper-dependent apoptosis mechanism, this study aimed to explore its role in glioblastoma prognosis and potential therapeutic implications. A comprehensive methodology was employed, starting with the identification and analysis of 65 cuproptosis-related genes. These genes were subjected to differential expression analyses between glioblastoma tissues and normal counterparts. A novel metric, the "CP-score," was devised to quantify the cuproptosis response in glioblastoma patients. Building on this, a prognostic model, the CP-model, was developed using Cox regression techniques, designed to operate on both bulk and single-cell data. The differential expression analysis revealed 31 genes with distinct expression patterns in glioblastoma. The CP-score was markedly elevated in glioblastoma patients, suggesting an intensified cuproptosis response. The CP-model adeptly stratified patients into distinct risk categories, unveiling intricate associations between glioblastoma prognosis, immune response pathways, and the tumor's immunological environment. Further analyses indicated that high-risk patients, as per the CP-model, exhibited heightened expression of certain immune checkpoints, suggesting potential therapeutic targets. Additionally, the model hinted at the possibility of personalized therapeutic strategies, with certain drugs showing increased efficacy in high-risk patients. The CP-model offers a promising tool for glioblastoma prognosis and therapeutic strategy development, emphasizing the potential of Cuproptosis in cancer treatment.

Revealing the role of SPP1+ macrophages in glioma prognosis and therapeutic targeting by investigating tumor-associated macrophage landscape in grade 2 and 3 gliomas

BACKGROUND

Glioma is a highly heterogeneous brain tumor categorized into World Health Organization (WHO) grades 1-4 based on its malignancy. The suppressive immune microenvironment of glioma contributes significantly to unfavourable patient outcomes. However, the cellular composition and their complex interplays within the glioma environment remain poorly understood, and reliable prognostic markers remain elusive. Therefore, in-depth exploration of the tumor microenvironment (TME) and identification of predictive markers are crucial for improving the clinical management of glioma patients.

RESULTS

Our analysis of single-cell RNA-sequencing data from glioma samples unveiled the immunosuppressive role of tumor-associated macrophages (TAMs), mediated through intricate interactions with tumor cells and lymphocytes. We also discovered the heterogeneity within TAMs, among which a group of suppressive TAMs named TAM-SPP1 demonstrated a significant association with Epidermal Growth Factor Receptor (EGFR) amplification, impaired T cell response and unfavourable patient survival outcomes. Furthermore, by leveraging genomic and transcriptomic data from The Cancer Genome Atlas (TCGA) dataset, two distinct molecular subtypes with a different constitution of TAMs, EGFR status and clinical outcomes were identified. Exploiting the molecular differences between these two subtypes, we developed a four-gene-based prognostic model. This model displayed strong associations with an elevated level of suppressive TAMs and could be used to predict anti-tumor immune response and prognosis in glioma patients.

CONCLUSION

Our findings illuminated the molecular and cellular mechanisms that shape the immunosuppressive microenvironment in gliomas, providing novel insights into potential therapeutic targets. Furthermore, the developed prognostic model holds promise for predicting immunotherapy response and assisting in more precise risk stratification for glioma patients.

Gene expression analysis suggests immunosuppressive roles of endolysosomes in glioblastoma

Targeting endolysosomes is a strategy extensively pursued for treating cancers, including glioblastomas (GBMs), on the basis that the intact function of these subcellular organelles is key to tumor cell autophagy and survival. Through gene expression analyses and cell type abundance estimation in GBMs, we showed that genes associated with the endolysosomal machinery are more prominently featured in non-tumor cells in GBMs than in tumor cells, and that tumor-associated macrophages represent the primary immune cell type that contributes to this trend. Further analyses found an enrichment of endolysosomal pathway genes in immunosuppressive (pro-tumorigenic) macrophages, such as M2-like macrophages or those associated with worse prognosis in glioma patients, but not in those linked to inflammation (anti-tumorigenic). Specifically, genes critical to the hydrolysis function of endolysosomes, including progranulin and cathepsins, were among the most positively correlated with immunosuppressive macrophages, and elevated expression of these genes is associated with worse patient survival in GBMs. Together, these results implicate the hydrolysis function of endolysosomes in shaping the immunosuppressive microenvironment of GBM. We propose that targeting endolysosomes, in addition to its detrimental effects on tumor cells, can be leveraged for modulating immunosuppression to render GBMs more amenable to immunotherapies.

STING is significantly increased in high-grade glioma with high risk of recurrence

In this study, we aimed to comprehensively characterize the potential relationships among the frequently mutated genes, well-known homologous recombination repair (HRR) proteins, and immune proteins in glioma from a clinical perspective. A total of 126 surgical tissues from patients initially diagnosed with glioma were included. The genetic alterations were tested using the targeted next-generation sequencing technique. The expression of HRR proteins, immune proteins, and genetic alteration-related proteins were detected using immunostaining. Integrated analysis showed that ATRX is positively correlated with STING in high-grade glioma (HGG) with wild-type ATRX and IDH1. Then, a relapse predictive risk-scoring model was established using the least absolute shrinkage and selection operator regression algorithms. The scores based on the expression of ATRX and STING significantly predict the recurrence for glioma patients, which further predict the survival for specific subgroups, characterized with high expression of RAD51 and wild-type TERT. Moreover, STING is significantly higher in patients with high relapse risk. Interestingly, STING inhibitors and agonists both suppress the growth of HGG cells, regardless of their STING levels and STING pathway activity, whereas RAD51 inhibitor B02 is found to exclusively sensitize HGG cells with high expression of STING to temozolomide in vitro and in vivo. Overall, findings in the study not only reveal that ATRX is closely correlated with STING to drive the relapse of HGG, but also provide a STING-guided combined strategy to treat patients with aggressive gliomas. Translation of these findings will ultimately improve the outcomes for ATRX and IDH1 genomically stratified subgroups in HGG.

hsa-miR-34a-5p enhances temozolomide anti-tumoral effects on glioblastoma: in-silico and in-vitro study

Glioblastoma multiform (GBM) is a commonly diagnosed brain neoplasm with a poor prognosis. Accumulating evidence has highlighted the significance of microRNA (miR) dysregulation in tumor development and progression. This study investigated the effect of hsa-miR-34a-5p and its combination with temozolomide on GBM, the related molecular mechanisms, and the signaling pathway using in-silico and in-vitro approaches. The in-silico tumor bulk and single-cell RNA sequencing analyses were done on TCGA-GTEx, CGGA, GSE13276, GSE90603, and GSE182109 datasets. After selecting the A172 cell line, hsa-miR-34a-5p mimics were transfected, and the cell viability, migration, cell cycle, clonogenicity, and apoptosis of studied groups were studied using MTT, scratch, flow cytometry, colony formation, and Annexin V/PI assays. The mRNA expression of CASP9, CASP3, CASP8, MMP2, CD44, CDK6, CDK4, CCND1, RAF1, MAP2K1, MET, SRC, and CD274 was studied using qRT-PCR method. hsa-miR-34a-5p downregulated RAF1 expression, as the signaling factor of the MAPK pathway. The combined treatment significantly downregulated the expression of MET, SRC, and MAP2K1, leading to the inhibition of the MET/MAPK pathway compared to temozolomide. Besides exerting anti-tumoral effects on the cell viability, migration, cell cycle, apoptosis, and clonogenicity of A172 cells, its combination with temozolomide enhanced temozolomide anti-tumoral effect. Compared to temozolomide, the combined treatment significantly decreased CDK4, CDK6, CCND1, and MMP2 expression. hsa-miR-34a-5p targets RAF1, as the signaling factor of the MAPK pathway, and potentiates the temozolomide anti-tumoral effect on A172 cells.

Advances in the field of developing biomarkers for re-irradiation: a how-to guide to small, powerful data sets and artificial intelligence

Introduction

Patient selection remains challenging as the clinical use of re-irradiation (re-RT) increases. Re-RT data is limited to retrospective studies and small prospective single-institution reports, resulting in small, heterogenous data sets. Validated prognostic and predictive biomarkers are derived from large-volume studies with long-term follow-up. This review aims to examine existing re-RT publications and available data sets and discuss strategies using artificial intelligence (AI) to approach small data sets to optimize the use of re-RT data.

Methods

Re-RT publications were identified where associated public data was present. The existing literature on small data sets to identify biomarkers was also explored.

Results

Publications with associated public data were identified, with glioma and nasopharyngeal cancers emerging as the most common tumor sites where the use of re-RT was the primary management approach. Existing and emerging AI strategies have been used to approach small data sets including data generation, augmentation, discovery, and transfer learning.

Conclusions

Further data is needed to generate adaptive frameworks, improve the collection of specimens for molecular analysis, and improve the interpretability of results in re-RT data.

Identification of PANoptosis-related predictors for prognosis and tumor microenvironment by multiomics analysis in glioma

PANoptosis is a newly described inflammatory programmed cell death, that highlights coordination between pyroptosis, apoptosis and necroptosis. However, the functions of PANoptosis-related genes in glioma progression still remain to be explored. This study aims to identify PANoptosis-related predictors that may be utilized for prognosis prediction and development of new therapeutic targets. Firstly, bulk and single-cell RNA-seq (scRNA-seq) data of glioma patients were extracted from TCGA, CGGA and GEO database. Genetic analysis indicates a considerably high mutation frequency of PANoptosis-related genes (PANRGs) in glioma. Consensus clustering was applied to reveal different subtypes of glioma based on PANRGs. Two PANoptosis subtypes with distinct prognostic and TME characteristics were identified. Then, with LASSO-Cox regression analysis, four PANoptosis-related predictors (MYBL2, TUBA1C, C21orf62 and KCNIP2) were determined from bulk and scRNA-seq analysis. Predictive PANRG score model was established with these predictors and its correlation with tumor microenvironment (TME) was investigated. The results showed that patients with low PANRG score, had higher infiltration of anti-tumor immune cells, higher MSI score and lower TIDE score, which are more likely to benefit from immunotherapy. Further analysis identified 16 potential drugs associated with PANoptosis-related predictors. Moreover, the expression levels of four PANoptosis-related predictors were examined in clinical samples and the results were consistent with those analyzed in the database. Besides, we also confirmed the biological functions of two oncogenic predictors (MYBL2 and TUBA1C) by cell experiments, which revealed that knockdown of MYBL2 or TUBA1C could significantly inhibit the proliferation and migration of glioma cells. These findings highlight the prognostic value and biological functions of PANRGs in glioma, which may provide valuable insights for individualized treatment.

Glioma-targeted oxaliplatin/ferritin clathrate reversing the immunosuppressive microenvironment through hijacking Fe2+ and boosting Fenton reaction

Glioma is easy to develop resistance to temozolomide (TMZ). TMZ-resistant glioma secretes interleukin-10 (IL-10) and transforming growth factor-β (TGF-β), recruiting regulatory T cell (Treg) and inhibiting the activity of T cells and natural killer cell (NK cell), subsequently forming an immunosuppressive microenvironment. Oxaliplatin (OXA) greatly inhibits the proliferation of TMZ-resistant glioma cells, but the ability of OXA to cross blood-brain barrier (BBB) is weak. Thus, the therapeutic effect of OXA on glioma is not satisfactory. Transferrin receptor 1 (TfR1) is highly expressed in brain capillary endothelial cells and TMZ-resistant glioma cells. In this study, OXA was loaded into ferritin (Fn) to prepare glioma-targeted oxaliplatin/ferritin clathrate OXA@Fn. OXA@Fn efficiently crossed BBB and was actively taken up by TMZ-resistant glioma cells via TfR1. Then, OXA increased the intracellular H2O2 level and induced the apoptosis of TMZ-resistant glioma cells. Meanwhile, Fn increased Fe2+ level in TMZ-resistant glioma cells. In addition, the expression of ferroportin 1 was significantly reduced, resulting in Fe2+ to be locked up inside the TMZ-resistant glioma cells. This subsequently enhanced the Fenton reaction and boosted the ferroptosis of TMZ-resistant glioma cells. Consequently, T cell mediated anti-tumor immune response was strongly induced, and the immunosuppressive microenvironment was significantly reversed in TMZ-resistant glioma tissue. Ultimately, the growth and invasion of TMZ-resistant glioma was inhibited by OXA@Fn. OXA@Fn shows great potential in the treatment of TMZ-resistant glioma and prospect in clinical transformation.

Suppression of ITPKB degradation by Trim25 confers TMZ resistance in glioblastoma through ROS homeostasis

Temozolomide (TMZ) represents a standard-of-care chemotherapeutic agent in glioblastoma (GBM). However, the development of drug resistance constitutes a significant hurdle in the treatment of malignant glioma. Although specific innovative approaches, such as immunotherapy, have shown favorable clinical outcomes, the inherent invasiveness of most gliomas continues to make them challenging to treat. Consequently, there is an urgent need to identify effective therapeutic targets for gliomas to overcome chemoresistance and facilitate drug development. This investigation used mass spectrometry to examine the proteomic profiles of six pairs of GBM patients who underwent standard-of-care treatment and surgery for both primary and recurrent tumors. A total of 648 proteins exhibiting significant differential expression were identified. Gene Set Enrichment Analysis (GSEA) unveiled notable alterations in pathways related to METABOLISM_OF_LIPIDS and BIOLOGICAL_OXIDATIONS between the primary and recurrent groups. Validation through glioma tissue arrays and the Xiangya cohort confirmed substantial upregulation of inositol 1,4,5-triphosphate (IP3) kinase B (ITPKB) in the recurrence group, correlating with poor survival in glioma patients. In TMZ-resistant cells, the depletion of ITPKB led to an increase in reactive oxygen species (ROS) related to NADPH oxidase (NOX) activity and restored cell sensitivity to TMZ. Mechanistically, the decreased phosphorylation of the E3 ligase Trim25 at the S100 position in recurrent GBM samples accounted for the weakened ITPKB ubiquitination. This, in turn, elevated ITPKB stability and impaired ROS production. Furthermore, ITPKB depletion or the ITPKB inhibitor GNF362 effectively overcome TMZ chemoresistance in a glioma xenograft mouse model. These findings reveal a novel mechanism underlying TMZ resistance and propose ITPKB as a promising therapeutic target for TMZ-resistant GBM.

Exosome-transmitted podoplanin promotes tumor-associated macrophage-mediated immune tolerance in glioblastoma

AIMS

Glioblastoma is the most frequent and aggressive primary brain tumor, characterized by rapid disease course and poor treatment responsiveness. The abundance of immunosuppressive macrophages in glioblastoma challenges the efficacy of novel immunotherapy.

METHODS

Bulk RNA-seq and single-cell RNA-seq of glioma patients from public databases were comprehensively analyzed to illustrate macrophage infiltration patterns and molecular characteristics of podoplanin (PDPN). Multiplexed fluorescence immunohistochemistry staining of PDPN, GFAP, CD68, and CD163 were performed in glioma tissue microarray. The impact of PDPN on macrophage immunosuppressive polarization was investigated using a co-culture system. Bone marrow-derived macrophages (BMDMs) and OT-II T cells isolated from BALB/c and OT-II mice respectively were co-cultured to determine T-cell adherence. Pathway alterations were probed through RNA sequencing and western blot analyses.

RESULTS

Our findings demonstrated that PDPN is notably correlated with the expression of CD68 and CD163 in glioma tissues. Additionally, macrophages phagocytosing PDPN-containing EVs (EVsPDPN ) from GBM cells presented increased CD163 expression and augmented secretion of immunoregulatory cytokine (IL-6, IL-10, TNF-α, and TGF-β1). PDPN within EVs was also associated with enhanced phagocytic activity and reduced MHC II expression in macrophages, compromising CD4+ T-cell activation.

CONCLUSIONS

This investigation underscores that EVsPDPN derived from glioblastoma cells contributes to M2 macrophage-mediated immunosuppression and is a potential prognostic marker and therapeutic target in glioblastoma.

Epigenetic Mechanisms Histone Deacetylase-Dependent Regulate the Glioblastoma Angiogenic Matrisome and Disrupt Endothelial Cell Behavior In Vitro

Glioblastoma (GBM) is the most aggressive brain tumor and different efforts have been employed in the search for new drugs and therapeutic protocols for GBM. Epitranscriptomics has shed light on new druggable Epigenetic therapies specifically designed to modulate GBM biology and behavior such as Histone Deacetylase inhibitors (iHDAC). Although the effects of iHDAC on GBM have been largely explored, there is a lack of information on the underlaying mechanisms HDAC-dependent that modulate the repertoire of GBM secreted molecules focusing on the set of Extracellular Matrix (ECM) associated proteins, the Matrisome, that may impact the surrounding tumor microenvironment. To acquire a better comprehension of the impacts of HDAC activity on the GBM Matrisome, we studied the alterations on the Matrisome-associated ECM regulators, Core Matrisome ECM glycoproteins, ECM-affiliated proteins and Proteoglycans upon HDAC inhibition in vitro as well as their relationship with glioma pathophysiological/clinical features and angiogenesis. For this, U87MG GBM cells were treated for with iHDAC or vehicle (control) and the whole secretome was processed by Mass Spectrometry NANOLC-MS/MS. In silico analyses revealed that proteins associated to the Angiogenic Matrisome (AngioMatrix), including Decorin, ADAM10, ADAM12 and ADAM15 were differentially regulated in iHDAC versus control secretome. Interestingly, genes coding for the Matrisome proteins differentially regulated were found mutated in patients and were correlated to glioma pathophysiological/clinical features. In vitro functional assays, using HBMEC endothelial cells exposed to the secretome of control or iHDAC treated GBM cells, coupled to 2D and 3D GBM cell culture system, showed impaired migratory capacity of endothelial cells and disrupted tubulogenesis in a Fibronectin and VEGF independent fashion. Collectively, our study provides understanding of epigenetic mechanisms HDAC-dependent to key Matrisomal proteins that may contribute to identify new druggable Epigenetic therapies or gliomagenesis biomarkers with relevant implications to improve therapeutic protocols for this malignancy.

SMG9 is a novel prognostic-related biomarker in glioma correlating with ferroptosis and immune infiltrates

Background

Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery.

Methods

The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities.

Results

We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers.

Conclusion

In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.

BTK Expression Level Prediction and the High-Grade Glioma Prognosis Using Radiomic Machine Learning Models

We aimed to study whether the Bruton's tyrosine kinase (BTK) expression is correlated with the prognosis of patients with high-grade gliomas (HGGs) and predict its expression level prior to surgery, by constructing radiomic models. Clinical and gene expression data of 310 patients from The Cancer Genome Atlas (TCGA) were included for gene-based prognostic analysis. Among them, contrast-enhanced T1-weighted imaging (T1WI + C) from The Cancer Imaging Archive (TCIA) with genomic data was selected from 82 patients for radiomic models, including support vector machine (SVM) and logistic regression (LR) models. Furthermore, the nomogram incorporating radiomic signatures was constructed to evaluate its clinical efficacy. BTK was identified as an independent risk factor for HGGs through univariate and multivariate Cox regression analyses. Three radiomic features were selected to construct the SVM and LR models, and the validation set showed area under curve (AUCs) values of 0.711 (95% CI, 0.598-0.824) and 0.736 (95% CI, 0.627-0.844), respectively. The median survival times of the high Rad_score and low-Rad_score groups based on LR model were 15.53 and 23.03 months, respectively. In addition, the total risk score of each patient was used to construct a predictive nomogram, and the AUCs calculated from the corresponding time-dependent ROC curves were 0.533, 0.659, and 0.767 for 1, 3, and 5 years, respectively. BTK is an independent risk factor associated with poor prognosis in patients, and the radiomic model constructed in this study can effectively and non-invasively predict preoperative BTK expression levels and patient prognosis based on T1WI + C.

Machine learning-based investigation of regulated cell death for predicting prognosis and immunotherapy response in glioma patients

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.

Chronic stress as an emerging risk factor for the development and progression of glioma

ABSTRACT

Gliomas tend to have a poor prognosis and are the most common primary malignant tumors of the central nervous system. Compared with patients with other cancers, glioma patients often suffer from increased levels of psychological stress, such as anxiety and fear. Chronic stress (CS) is thought to impact glioma profoundly. However, because of the complex mechanisms underlying CS and variability in individual tolerance, the role of CS in glioma remains unclear. This review suggests a new proposal to redivide the stress system into two parts. Neuronal activity is dominant upstream. Stress-signaling molecules produced by the neuroendocrine system are dominant downstream. We discuss the underlying molecular mechanisms by which CS impacts glioma. Potential pharmacological treatments are also summarized from the therapeutic perspective of CS.

Let-7b-5p promotes triptolide-induced growth-inhibiting effects in glioma by targeting IGF1R

Glioma is one of the most common malignancies of the central nervous system. The therapeutic effect has not been satisfactory despite advances in comprehensive treatment techniques. Our previous studies have found that triptolide inhibits glioma proliferation through the ROS/JNK pathway, but in-depth mechanisms need to be explored. Recent studies have confirmed that miRNAs may function as tumor suppressor genes or oncogenes and be involved in cancer development and progression. In this study, we found that let-7b-5p expression levels closely correlated with WHO grades and overall survival in patients in tumor glioma-CGGA-mRNAseq-325, and the upregulation of let-7b-5p can inhibit the proliferation and induce apoptosis of glioma cells. Functionally, upregulation of let-7b-5p increased the inhibitory effect on cell viability and colony formation caused by triptolide and promoted the apoptosis rate of triptolide-treated U251 cells. Conversely, downregulation of let-7b-5p had the opposite effect, indicating that let-7b-5p is a tumor suppressor miRNA in glioma cells. Moreover, target prediction, luciferase reporter assays and functional experiments revealed that IGF1R was a direct target of let-7b-5p. In addition, upregulation of IGF1R reversed the triptolide-regulated inhibition of cell viability but promoted glioma cell apoptosis and activated the ROS/JNK signaling pathway induced by triptolide. The results obtained in vivo experiments substantiated those from the in vitro experiments. In summary, the current study provides evidence that triptolide inhibits the growth of glioma cells by regulating the let-7b-5p-IGF1R-ROS/JNK axis in vitro and in vivo. These findings may provide new ideas and potential targets for molecularly targeted therapies for comprehensive glioma treatment.

Functional Contribution and Clinical Implication of Cancer-Associated Fibroblasts in Glioblastoma

PURPOSE

The abundance and biological contribution of cancer-associated fibroblasts (CAF) in glioblastoma (GBM) are poorly understood. Here, we aim to uncover its molecular signature, cellular roles, and potential tumorigenesis implications.

EXPERIMENTAL DESIGN

We first applied single-cell RNA sequencing (RNA-seq) and bioinformatics analysis to identify and characterize stromal cells with CAF transcriptomic features in human GBM tumors. Then, we performed functional enrichment analysis and in vitro assays to investigate their interactions with malignant GBM cells.

RESULTS

We found that CAF abundance was low but significantly correlated with tumor grade, poor clinical outcome, and activation of extracellular matrix remodeling using three large cohorts containing bulk RNA-seq data and clinical information. Proteomic analysis of a GBM-derived CAF line and its secretome revealed fibronectin (FN1) as a critical candidate factor mediating CAF functions. This was validated using in vitro cellular models, which demonstrated that CAF-conditioned media and recombinant FN1 could facilitate the migration and invasion of GBM cells. In addition, we showed that CAFs were more abundant in the mesenchymal-like state (or subtype) than in other states of GBMs. Interestingly, cell lines resembling the proneural state responded to the CAF signaling better for the migratory and invasive phenotypes.

CONCLUSIONS

Overall, this study characterized the molecular features and functional impacts of CAFs in GBM, alluding to novel cell interactions mediated by CAFs in the GBM microenvironment.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

Comprehensive analysis of PSMD family members and validation of PSMD9 as a potential therapeutic target in human glioblastoma

AIMS

PSMD family members, as important components of the 26S proteasome, are well known to be involved in protein degradation. However, their role in glioblastoma (GBM) has not been rigorously investigated. We aimed to perform systematic analysis of the expression signature, prognostic significance and functions of PSMD family genes in GBM to reveal potential prognostic markers and new therapeutic targets among PSMD family members.

METHODS

In this study, we systemically analyzed PSMD family members in terms of their expression profiles, prognostic implications, DNA methylation levels, and genetic alterations; the relationships between their expression levels and immune infiltration and drug sensitivity; and their potential functional enrichment in GBM through bioinformatics assessment. Moreover, in vitro and in vivo experiments were used to validate the biological functions of PSMD9 and its targeted therapeutic effect in GBM.

RESULTS

The mRNA levels of PSMD5/8/9/10/11/13/14 were higher in GBM than in normal brain tissues, and the mRNA levels of PSMD1/4/5/8/9/11/12 were higher in high-grade glioma (WHO grade III & IV) than in low-grade glioma (WHO grade II). High mRNA expression of PSMD2/6/8/9/12/13/14 and low mRNA expression of PSMD7 were associated with poor overall survival (OS). Multivariate Cox regression analysis identified PSMD2/5/6/8/9/10/11/12 as independent prognostic factors for OS prediction. In addition, the protein-protein interaction network and gene set enrichment analysis results suggested that PSMD family members and their interacting molecules were involved in the regulation of the cell cycle, cell invasion and migration, and other biological processes in GBM. In addition, knockdown of PSMD9 inhibited cell proliferation, invasion and migration and induced G2/M cell cycle arrest in LN229 and A172 GBM cells. Moreover, PSMD9 promoted the malignant progression of GBM in vivo. GBM cell lines with high PSMD9 expression were more resistant to panobinostat, a potent deacetylase inhibitor, than those with low PSMD9 expression. In vitro and in vivo experiments further validated that PSMD9 overexpression rescued the GBM inhibitory effect of panobinostat.

CONCLUSION

This study provides new insights into the value of the PSMD family in human GBM diagnosis and prognosis evaluation, and we further identified PSMD9 as a potential therapeutic target. These findings may lead to the development of effective therapeutic strategies for GBM.