Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities

Amino acid metabolism in glioma: in vivo MR-spectroscopic detection of alanine as a potential biomarker of poor survival in glioma patients

PURPOSE

Reprogramming of amino acid metabolism is relevant for initiating and fueling tumor formation and growth. Therefore, there has been growing interest in anticancer therapies targeting amino acid metabolism. While developing personalized therapeutic approaches to glioma, in vivo proton magnetic resonance spectroscopy (MRS) is a valuable tool for non-invasive monitoring of tumor metabolism. Here, we evaluated MRS-detected brain amino acids and myo-inositol as potential diagnostic and prognostic biomarkers in glioma.

METHOD

We measured alanine, glycine, glutamate, glutamine, and myo-inositol in 38 patients with MRI-suspected glioma using short and long echo-time single-voxel PRESS MRS sequences. The detectability of alanine, glycine, and myo-inositol and the (glutamate + glutamine)/total creatine ratio were evaluated against the patients' IDH mutation status, CNS WHO grade, and overall survival.

RESULTS

While the detection of alanine and non-detection of myo-inositol significantly correlated with IDH wildtype (p = 0.0008, p = 0.007, respectively) and WHO grade 4 (p = 0.01, p = 0.04, respectively), glycine detection was not significantly associated with either. The ratio of (glutamate + glutamine)/total creatine was significantly higher in WHO grade 4 than in 2 and 3. We found that the overall survival was significantly shorter in glioma patients with alanine detection (p = 0.00002).

CONCLUSION

Focusing on amino acids in MRS can improve its diagnostic and prognostic value in glioma. Alanine, which is visible at long TE even in the presence of lipids, could be a relevant indicator for overall survival.

Metabolic dysregulation of tricarboxylic acid cycle and oxidative phosphorylation in glioblastoma

Glioblastoma multiforme (GBM) exhibits genetic alterations that induce the deregulation of oncogenic pathways, thus promoting metabolic adaptation. The modulation of metabolic enzyme activities is necessary to generate nucleotides, amino acids, and fatty acids, which provide energy and metabolic intermediates essential for fulfilling the biosynthetic needs of glioma cells. Moreover, the TCA cycle produces intermediates that play important roles in the metabolism of glucose, fatty acids, or non-essential amino acids, and act as signaling molecules associated with the activation of oncogenic pathways, transcriptional changes, and epigenetic modifications. In this review, we aim to explore how dysregulated metabolic enzymes from the TCA cycle and oxidative phosphorylation, along with their metabolites, modulate both catabolic and anabolic metabolic pathways, as well as pro-oncogenic signaling pathways, transcriptional changes, and epigenetic modifications in GBM cells, contributing to the formation, survival, growth, and invasion of glioma cells. Additionally, we discuss promising therapeutic strategies targeting key players in metabolic regulation. Therefore, understanding metabolic reprogramming is necessary to fully comprehend the biology of malignant gliomas and significantly improve patient survival.

Modeling Glioma Intratumoral Heterogeneity with Primary Human Neural Stem and Progenitor Cells

Glioblastoma multiforme (GBM) is a deadly form of glioma notable for its significant intratumoral heterogeneity, which is believed to drive therapy resistance. GBM has been observed to mimic a neural stem cell hierarchy reminiscent of normal brain development. However, it is still unclear how cell-of-origin shapes intratumoral heterogeneity. Here, we develop a model of glioma initiation using neural stem and progenitor cells (NSPCs) purified from fetal human brain tissue. We previously described a method to prospectively isolate and culture tripotent neural stem cells (NSCs), bipotent glial progenitor cells (GPCs), and unipotent oligodendrocyte precursor cells (OPCs). We transduced these isogenic lines with dominant-negative TP53R175H and NF1 knockdown, a commonly-used genetic model of GBM in mice. These reprogrammed lines robustly engrafted when transplanted into the brains of immunodeficient mice, and showed significant expansion over time. Engrafted cells were reextracted from the mouse brain for single cell RNA sequencing (scRNA-seq), in order to quantify how the cell-of-origin modulates the cellular subtypes found in the resulting tumor. This result revealed the strong influence the cell-of-origin plays in glioma heterogeneity. Our platform is highly adaptable and allows for modular and systematic interrogation of how cell-of-origin shape the tumor landscape.

Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations

Targeting the distinct metabolic needs of tumor cells has recently emerged as a promising strategy for cancer therapy. The heterogeneous, context-dependent nature of cancer cell metabolism, however, poses challenges to identifying effective therapeutic interventions. Here, we utilize various unsupervised and supervised multivariate modeling approaches to systematically pinpoint recurrent metabolic states within hundreds of cancer cell lines, elucidate their association with tumor lineage and growth environments, and uncover vulnerabilities linked to their metabolic states across diverse genetic and tissue contexts. We validate key findings via analysis of data from patient-derived tumors and pharmacological screens and by performing genetic and pharmacological experiments. Our analysis uncovers synthetically lethal associations between the tumor metabolic state (e.g., oxidative phosphorylation), driver mutations (e.g., loss of tumor suppressor PTEN), and actionable biological targets (e.g., mitochondrial electron transport chain). Investigating the mechanisms underlying these relationships can inform the development of more precise and context-specific, metabolism-targeted cancer therapies.

SUMOylation modification of HNRNPK at the K422 site promotes invasion in glioblastoma

Glioblastoma multiforme (GBM) is a highly heterogeneous brain tumor with limited treatment options. Recent studies revealed cellular heterogeneity and the potential for interconversion between distinct cell types on the basis of RNA sequencing and single-cell analyses. The ability of different cell types to adapt to their surrounding environment and undergo transformation significantly complicates the study and treatment of GBM. In this study, we reveal that HNRNPK-SUMO1 expression is predominantly found in the GBM infiltration area. SUMOylation of the K422 residue of HNRNPK interferes with its DNA binding ability, thereby disrupting downstream transcription, and ultimately leading to transitions between different states of glioblastoma stem cells. Although the proneural subtype is considered to have a better prognosis, transitioning towards this state promotes tumor invasion. These findings serve as a reminder to exercise caution when considering treatments targeting specific cellular subtypes.

Matrix Protein of Vesicular Stomatitis Virus Targets the Mitochondria, Reprograms Glucose Metabolism, and Sensitizes to 2-Deoxyglucose in Glioblastoma

A potential therapeutic approach for cancer treatment is target oxidative phosphorylation and glycolysis simultaneously. The matrix protein of vesicular stomatitis virus (VSV MP) can target the surface of mitochondria, causing morphological changes that may be associated with mitochondrial dysfunction and oxidative phosphorylation inhibition. Previous research has shown that mitochondrial abnormalities can direct glucose metabolism toward glycolysis. Thus, after treatment with VSV MP, glycolysis inhibition is necessary to completely block glucose metabolism and eradicate cancer. Here, to inhibit glycolysis, the 2-deoxy-D-glucose (2-DG), a synthetic glucose analog was used to combine with VSV MP to treat cancer. This study aims to determine how VSV MP affects the glucose bioenergetic metabolism of cancer cells and to evaluate the synergistic effect of 2-DG when combined with VSV. Our results indicated that in U87 and C6 glioblastoma cell lines, VSV MP caused mitochondrial membrane potential loss, cytochrome c release, and glucose bioenergetics metabolism reprogramming. When combined with 2-DG, VSV MP synergistically aggravated cell viability, apoptosis, and G2/M phase arrest. Meanwhile, the combination therapy exacerbated ATP depletion, activated AMPK, and inhibited mammalian target of rapamycin signaling pathways. In addition, 2-DG treatment alone induced autophagy in glioblastoma cells; however, VSV MP inhibited the autophagy induced by 2-DG in combined treatment and finally contributed to the enhanced cytotoxic effect of the combination strategy in U87 and C6 cancer cells. In the orthotopic U87 glioblastoma model and subcutaneous C6 glioblastoma model, the combined treatment led to significant tumor regression and prolonged survival. A potent therapeutic approach for treating glioblastoma may be found in the combination of VSV MP and glycolytic inhibitors.

A cell state-specific metabolic vulnerability to GPX4-dependent ferroptosis in glioblastoma

Glioma cells hijack developmental programs to control cell state. Here, we uncover a glioma cell state-specific metabolic liability that can be therapeutically targeted. To model cell conditions at brain tumor inception, we generated genetically engineered murine gliomas, with deletion of p53 alone (p53) or with constitutively active Notch signaling (N1IC), a pathway critical in controlling astrocyte differentiation during brain development. N1IC tumors harbored quiescent astrocyte-like transformed cell populations while p53 tumors were predominantly comprised of proliferating progenitor-like cell states. Further, N1IC transformed cells exhibited increased mitochondrial lipid peroxidation, high ROS production and depletion of reduced glutathione. This altered mitochondrial phenotype rendered the astrocyte-like, quiescent populations more sensitive to pharmacologic or genetic inhibition of the lipid hydroperoxidase GPX4 and induction of ferroptosis. Treatment of patient-derived early-passage cell lines and glioma slice cultures generated from surgical samples with a GPX4 inhibitor induced selective depletion of quiescent astrocyte-like glioma cell populations with similar metabolic profiles. Collectively, these findings reveal a specific therapeutic vulnerability to ferroptosis linked to mitochondrial redox imbalance in a subpopulation of quiescent astrocyte-like glioma cells resistant to standard forms of treatment.

An ILK/STAT3 pathway controls glioblastoma stem cell plasticity

Glioblastoma (GBM) is driven by malignant neural stem-like cells that display extensive heterogeneity and phenotypic plasticity, which drive tumor progression and therapeutic resistance. Here, we show that the extracellular matrix-cell adhesion protein integrin-linked kinase (ILK) stimulates phenotypic plasticity and mesenchymal-like, invasive behavior in a murine GBM stem cell model. ILK is required for the interconversion of GBM stem cells between malignancy-associated glial-like states, and its loss produces cells that are unresponsive to multiple cell state transition cues. We further show that an ILK/STAT3 signaling pathway controls the plasticity that enables transition of GBM stem cells to an astrocyte-like state in vitro and in vivo. Finally, we find that ILK expression correlates with expression of STAT3-regulated proteins and protein signatures describing astrocyte-like and mesenchymal states in patient tumors. This work identifies ILK as a pivotal regulator of multiple malignancy-associated GBM phenotypes, including phenotypic plasticity and mesenchymal state.

High-throughput identification of repurposable neuroactive drugs with potent anti-glioblastoma activity

Glioblastoma, the most aggressive primary brain cancer, has a dismal prognosis, yet systemic treatment is limited to DNA-alkylating chemotherapies. New therapeutic strategies may emerge from exploring neurodevelopmental and neurophysiological vulnerabilities of glioblastoma. To this end, we systematically screened repurposable neuroactive drugs in glioblastoma patient surgery material using a clinically concordant and single-cell resolved platform. Profiling more than 2,500 ex vivo drug responses across 27 patients and 132 drugs identified class-diverse neuroactive drugs with potent anti-glioblastoma efficacy that were validated across model systems. Interpretable molecular machine learning of drug-target networks revealed neuroactive convergence on AP-1/BTG-driven glioblastoma suppression, enabling expanded in silico screening of more than 1 million compounds with high patient validation accuracy. Deep multimodal profiling confirmed Ca2+-driven AP-1/BTG-pathway induction as a neuro-oncological glioblastoma vulnerability, epitomized by the anti-depressant vortioxetine synergizing with current standard-of-care chemotherapies in vivo. These findings establish an actionable framework for glioblastoma treatment rooted in its neural etiology.

Macrophage-mediated myelin recycling fuels brain cancer malignancy

Tumors growing in metabolically challenged environments, such as glioblastoma in the brain, are particularly reliant on crosstalk with their tumor microenvironment (TME) to satisfy their high energetic needs. To study the intricacies of this metabolic interplay, we interrogated the heterogeneity of the glioblastoma TME using single-cell and multi-omics analyses and identified metabolically rewired tumor-associated macrophage (TAM) subpopulations with pro-tumorigenic properties. These TAM subsets, termed lipid-laden macrophages (LLMs) to reflect their cholesterol accumulation, are epigenetically rewired, display immunosuppressive features, and are enriched in the aggressive mesenchymal glioblastoma subtype. Engulfment of cholesterol-rich myelin debris endows subsets of TAMs to acquire an LLM phenotype. Subsequently, LLMs directly transfer myelin-derived lipids to cancer cells in an LXR/Abca1-dependent manner, thereby fueling the heightened metabolic demands of mesenchymal glioblastoma. Our work provides an in-depth understanding of the immune-metabolic interplay during glioblastoma progression, thereby laying a framework to unveil targetable metabolic vulnerabilities in glioblastoma.

Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis

Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.

Unveiling the role of TAGLN2 in glioblastoma: From proneural-mesenchymal transition to Temozolomide resistance

Glioblastoma (GBM) presents a daunting challenge due to its resistance to temozolomide (TMZ), a hurdle exacerbated by the proneural-to-mesenchymal transition (PMT) from a proneural (PN) to a mesenchymal (MES) phenotype. TAGLN2 is prominently expressed in GBM, particularly in the MES subtype compared to low-grade glioma (LGG) and the PN subtype. Our research reveals TAGLN2's involvement in PMT and TMZ resistance through a series of in vitro and in vivo experiments. TAGLN2 knockdown can restrain proliferation and invasion, trigger DNA damage and apoptosis, and heighten TMZ sensitivity in GBM cells. Conversely, elevating TAGLN2 levels amplifies resistance to TMZ in cellular and intracranial xenograft mouse models. We demonstrate the interaction relationship between TAGLN2 and ERK1/2 through co-immunoprecipitation (Co-IP) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrometry analysis. Knockdown of TAGLN2 results in a decrease in the expression of p-ERK1/2, whereas overexpression of TAGLN2 leads to an increase in p-ERK1/2 expression within the nucleus. Subsequently, the regulatory role of TAGLN2 in the expression and control of MGMT has been demonstrated. Finally, the regulation of TAGLN2 by NF-κB has been validated through chromatin immunoprecipitation and ChIP-PCR assays. In conclusion, our results confirm that TAGLN2 exerts its biological functions by interacting with the ERK/MGMT axis and being regulated by NF-κB, thereby facilitating the acquisition of promoting PMT and increased resistance to TMZ therapy in glioblastoma. These results provide valuable insights for the advancement of targeted therapeutic approaches to overcome TMZ resistance in clinical treatments.

Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations

Background

Glioma is a highly heterogeneous malignancy of the central nervous system. This heterogeneity is driven by various molecular processes, including neoplastic transformation, cell cycle dysregulation, and angiogenesis. Among these biomolecular events, inflammation and stress pathways in the development and driving factors of glioma heterogeneity have been reported. However, the mechanisms of glioma heterogeneity under stress response remain unclear, especially from a spatial aspect.

Methods

This study employed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore the impact of oxidative stress response genes in oligodendrocyte precursor cells (OPCs). Our analysis identified distinct pathways activated by oxidative stress in two different types of gliomas: high- and low- grade (HG and LG) gliomas.

Results

In HG gliomas, oxidative stress induced a metabolic shift from oxidative phosphorylation to glycolysis, promoting cell survival by preventing apoptosis. This metabolic reprogramming was accompanied by epithelial-to-mesenchymal transition (EMT) and an upregulation of stress response genes. Furthermore, SCENIC (Single-Cell rEgulatory Network Inference and Clustering) analysis revealed that oxidative stress activated the AP1 transcription factor in HG gliomas, thereby enhancing tumor cell survival and proliferation.

Conclusion

Our findings provide a novel perspective on the mechanisms of oxidative stress responses across various grades of gliomas. This insight enhances our comprehension of the evolutionary processes and heterogeneity within gliomas, potentially guiding future research and therapeutic strategies.

GABAergic neuronal lineage development determines clinically actionable targets in diffuse hemispheric glioma, H3G34-mutant

Diffuse hemispheric gliomas, H3G34R/V-mutant (DHG-H3G34), are lethal brain tumors lacking targeted therapies. They originate from interneuronal precursors; however, leveraging this origin for therapeutic insights remains unexplored. Here, we delineate a cellular hierarchy along the interneuron lineage development continuum, revealing that DHG-H3G34 mirror spatial patterns of progenitor streams surrounding interneuron nests, as seen during human brain development. Integrating these findings with genome-wide CRISPR-Cas9 screens identifies genes upregulated in interneuron lineage progenitors as major dependencies. Among these, CDK6 emerges as a targetable vulnerability: DHG-H3G34 tumor cells show enhanced sensitivity to CDK4/6 inhibitors and a CDK6-specific degrader, promoting a shift toward more mature interneuron-like states, reducing tumor growth, and prolonging xenograft survival. Notably, a patient with progressive DHG-H3G34 treated with a CDK4/6 inhibitor achieved 17 months of stable disease. This study underscores interneuronal progenitor-like states, organized in characteristic niches, as a distinct vulnerability in DHG-H3G34, highlighting CDK6 as a promising clinically actionable target.

Multi-omics and pharmacological characterization of patient-derived glioma cell lines

Glioblastoma (GBM) is the most common brain tumor and remains incurable. Primary GBM cultures are widely used tools for drug screening, but there is a lack of genomic and pharmacological characterization for these primary GBM cultures. Here, we collect 50 patient-derived glioma cell (PDGC) lines and characterize them by whole genome sequencing, RNA sequencing, and drug response screening. We identify three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Drug response profiling reveals that PN subtype PDGCs are sensitive to tyrosine kinase inhibitors, whereas OXPHOS subtype PDGCs are sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably form tumors in vivo upon intracranial transplantation into immunodeficient mice, whereas most MES subtype PDGCs fail to form tumors in vivo. In addition, PDGCs cultured by serum-free medium, especially long-passage PDGCs, carry MYC/MYCN amplification, which is rare in GBM patients. Our study provides a valuable resource for understanding primary glioma cell cultures and clinical translation and highlights the problems of serum-free PDGC culture systems that cannot be ignored.

Coordinated Targeting of S6K1/2 and AXL Disrupts Pyrimidine Biosynthesis in PTEN-Deficient Glioblastoma

Intrinsic resistance to targeted therapeutics in PTEN-deficient glioblastoma (GBM) is mediated by redundant signaling networks that sustain critical metabolic functions. Here, we demonstrate that coordinated inhibition of the ribosomal protein S6 kinase 1 (S6K1) and the receptor tyrosine kinase AXL using LY-2584702 and BMS-777607 can overcome network redundancy to reduce GBM tumor growth. This combination of S6K1 and AXL inhibition suppressed glucose flux to pyrimidine biosynthesis. Genetic inactivation studies to map the signaling network indicated that both S6K1 and S6K2 transmit growth signals in PTEN-deficient GBM. Kinome-wide ATP binding analysis in inhibitor-treated cells revealed that LY-2584702 directly inhibited S6K1, and substrate phosphorylation studies showed that BMS-777607 inactivation of upstream AXL collaborated to reduce S6K2-mediated signal transduction. Thus, combination targeting of S6K1 and AXL provides a kinase-directed therapeutic approach that circumvents signal transduction redundancy to interrupt metabolic function and reduce growth of PTEN-deficient GBM.

SIGNIFICANCE

Therapy for glioblastoma would be advanced by incorporating molecularly targeted kinase-directed agents, similar to standard of care strategies in other tumor types. Here, we identify a kinase targeting approach to inhibit the metabolism and growth of glioblastoma.

Accurate estimation of pathway activity in single cells for clustering and differential analysis

Inferring which and how biological pathways and gene sets change is a key question in many studies that utilize single-cell RNA sequencing. Typically, these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis. Here we offer SiPSiC, a new method to infer pathway activity in every single cell. This allows more sensitive differential analysis and utilization of pathway scores to cluster cells and compute UMAP or other similar projections. We apply our method to COVID-19, lung adenocarcinoma and glioma data sets, and demonstrate its utility. SiPSiC analysis results are consistent with findings reported in previous studies in many cases, but SiPSiC also reveals the differential activity of novel pathways, enabling us to suggest new mechanisms underlying the pathophysiology of these diseases and demonstrating SiPSiC's high accuracy and sensitivity in detecting biological function and traits. In addition, we demonstrate how it can be used to better classify cells based on activity of biological pathways instead of single genes and its ability to overcome patient-specific artifacts.

Genetic and epigenetic instability as an underlying driver of progression and aggressive behavior in IDH-mutant astrocytoma

In recent years, the classification of adult-type diffuse gliomas has undergone a revolution, wherein specific molecular features now represent defining diagnostic criteria of IDH-wild-type glioblastomas, IDH-mutant astrocytomas, and IDH-mutant 1p/19q-codeleted oligodendrogliomas. With the introduction of the 2021 WHO CNS classification, additional molecular alterations are now integrated into the grading of these tumors, given equal weight to traditional histologic features. However, there remains a great deal of heterogeneity in patient outcome even within these established tumor subclassifications that is unexplained by currently codified molecular alterations, particularly in the IDH-mutant astrocytoma category. There is also significant intercellular genetic and epigenetic heterogeneity and plasticity with resulting phenotypic heterogeneity, making these tumors remarkably adaptable and robust, and presenting a significant barrier to the design of effective therapeutics. Herein, we review the mechanisms and consequences of genetic and epigenetic instability, including chromosomal instability (CIN), microsatellite instability (MSI)/mismatch repair (MMR) deficits, and epigenetic instability, in the underlying biology, tumorigenesis, and progression of IDH-mutant astrocytomas. We also discuss the contribution of recent high-resolution transcriptomics studies toward defining tumor heterogeneity with single-cell resolution. While intratumoral heterogeneity is a well-known feature of diffuse gliomas, the contribution of these various processes has only recently been considered as a potential driver of tumor aggressiveness. CIN has an independent, adverse effect on patient survival, similar to the effect of histologic grade and homozygous CDKN2A deletion, while MMR mutation is only associated with poor overall survival in univariate analysis but is highly correlated with higher histologic/molecular grade and other aggressive features. These forms of genomic instability, which may significantly affect the natural progression of these tumors, response to therapy, and ultimately clinical outcome for patients, are potentially measurable features which could aid in diagnosis, grading, prognosis, and development of personalized therapeutics.

Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations

Targeting the distinct metabolic needs of tumor cells has recently emerged as a promising strategy for cancer therapy. The heterogeneous, context-dependent nature of cancer cell metabolism, however, poses challenges in identifying effective therapeutic interventions. Here, we utilize various unsupervised and supervised multivariate modeling approaches to systematically pinpoint recurrent metabolic states within hundreds of cancer cell lines, elucidate their association with tumor lineage and growth environments, and uncover vulnerabilities linked to their metabolic states across diverse genetic and tissue contexts. We validate key findings via analysis of data from patient-derived tumors and pharmacological screens, and by performing new genetic and pharmacological experiments. Our analysis uncovers new synthetically lethal associations between the tumor metabolic state (e.g., oxidative phosphorylation), driver mutations (e.g., loss of tumor suppressor PTEN), and actionable biological targets (e.g., mitochondrial electron transport chain). Investigating the mechanisms underlying these relationships can inform the development of more precise and context-specific, metabolism-targeted cancer therapies.

Suppressing PD-L1 Expression via AURKA Kinase Inhibition Enhances Natural Killer Cell-Mediated Cytotoxicity against Glioblastoma

Immunotherapies have shown significant promise as an impactful strategy in cancer treatment. However, in glioblastoma multiforme (GBM), the most prevalent primary brain tumor in adults, these therapies have demonstrated lower efficacy than initially anticipated. Consequently, there is an urgent need for strategies to enhance the effectiveness of immune treatments. AURKA has been identified as a potential drug target for GBM treatment. An analysis of the GBM cell transcriptome following AURKA inhibition revealed a potential influence on the immune system. Our research revealed that AURKA influenced PD-L1 levels in various GBM model systems in vitro and in vivo. Disrupting AURKA function genetically led to reduced PD-L1 levels and increased MHC-I expression in both established and patient-derived xenograft GBM cultures. This process involved both transcriptional and non-transcriptional pathways, partly implicating GSK3β. Interfering with AURKA also enhanced NK-cell-mediated elimination of GBM by reducing PD-L1 expression, as evidenced in rescue experiments. Furthermore, using a mouse model that mimics GBM with patient-derived cells demonstrated that Alisertib decreased PD-L1 expression in living organisms. Combination therapy involving anti-PD-1 treatment and Alisertib significantly prolonged overall survival compared to vehicle treatment. These findings suggest that targeting AURKA could have therapeutic implications for modulating the immune environment within GBM cells.

Liposomal Nanomaterials: A Rising Star in Glioma Treatment

Glioma is a primary malignant tumor in the central nervous system. In recent years, the treatment of glioma has developed rapidly, but the overall survival of glioma patients has not significantly improved. Due to the presence of the blood-brain barrier and intracranial tumor barrier, many drugs with good effects to cure glioma in vitro cannot be accurately transported to the corresponding lesions. In order to enable anti-tumor drugs to overcome the barriers and target glioma, nanodrug delivery systems have emerged recently. It is gratifying that liposomes, as a multifunctional nanodrug delivery carrier, which can be compatible with hydrophilic and hydrophobic drugs, easily functionalized by various targeted ligands, biodegradable, and hypoimmunogenic in vivo, has become a quality choice to solve the intractable problem of glioma medication. Therefore, we focused on the liposome nanodrug delivery system, and summarized its current research progress in glioma. Hopefully, this review may provide new ideas for the research and development of liposome-based nanomaterials for the clinical treatment of glioma.

Temporal and regional expression changes and co-staining patterns of metabolic and stemness-related markers during glioblastoma progression

Glioblastomas (GBMs) are characterized by high heterogeneity, involving diverse cell types, including those with stem-like features contributing to GBM's malignancy. Moreover, metabolic alterations promote growth and therapeutic resistance of GBM. Depending on the metabolic state, antimetabolic treatments could be an effective strategy. Against this background, we investigated temporal and regional expression changes and co-staining patterns of selected metabolic markers [pyruvate kinase muscle isozyme 1/2 (PKM1/2), glucose transporter 1 (GLUT1), monocarboxylate transporter 1/4 (MCT1/4)] in a rodent model and patient-derived samples of GBM. To understand the cellular sources of marker expression, we also examined the connection of metabolic markers to markers related to stemness [Nestin, Krüppel-like factor 4 (KLF4)] in a regional and temporal context. Rat tumour biopsies revealed a temporally increasing expression of GLUT1, higher expression of MCT1/4, Nestin and KLF4, and lower expression of PKM1 compared to the contralateral hemisphere. Patient-derived tumours showed a higher expression of PKM2 and Nestin in the tumour centre vs. edge. Whereas rare co-staining of GLUT1/Nestin was found in tumour biopsies, PKM1/2 and MCT1/4 showed a more distinct co-staining with Nestin in rats and humans. KLF4 was mainly co-stained with GLUT1, MCT1 and PKM1/2 in rat and human tumours. All metabolic markers yielded individual co-staining patterns among themselves. Co-staining mainly occurred later in tumour progression and was more pronounced in tumour centres. Also, positive correlations were found amongst markers that showed co-staining. Our results highlight a link between metabolic alterations and stemness in GBM progression, with complex distinctions depending on studied markers, time points and regions.

Deuterium Metabolic Imaging Differentiates Glioblastoma Metabolic Subtypes and Detects Early Response to Chemoradiotherapy

Metabolic subtypes of glioblastoma (GBM) have different prognoses and responses to treatment. Deuterium metabolic imaging with 2H-labeled substrates is a potential approach to stratify patients into metabolic subtypes for targeted treatment. In this study, we used 2H magnetic resonance spectroscopy and magnetic resonance spectroscopic imaging (MRSI) measurements of [6,6'-2H2]glucose metabolism to identify metabolic subtypes and their responses to chemoradiotherapy in patient-derived GBM xenografts in vivo. The metabolism of patient-derived cells was first characterized in vitro by measuring the oxygen consumption rate, a marker of mitochondrial tricarboxylic acid cycle activity, as well as the extracellular acidification rate and 2H-labeled lactate production from [6,6'-2H2]glucose, which are markers of glycolytic activity. Two cell lines representative of a glycolytic subtype and two representative of a mitochondrial subtype were identified. 2H magnetic resonance spectroscopy and MRSI measurements showed similar concentrations of 2H-labeled glucose from [6,6'-2H2]glucose in all four tumor models when implanted orthotopically in mice. The glycolytic subtypes showed higher concentrations of 2H-labeled lactate than the mitochondrial subtypes and normal-appearing brain tissue, whereas the mitochondrial subtypes showed more glutamate/glutamine labeling, a surrogate for tricarboxylic acid cycle activity, than the glycolytic subtypes and normal-appearing brain tissue. The response of the tumors to chemoradiation could be detected within 24 hours of treatment completion, with the mitochondrial subtypes showing a decrease in both 2H-labeled glutamate/glutamine and lactate concentrations and glycolytic tumors showing a decrease in 2H-labeled lactate concentration. This technique has the potential to be used clinically for treatment selection and early detection of treatment response.

SIGNIFICANCE

Deuterium magnetic resonance spectroscopic imaging of glucose metabolism has the potential to differentiate between glycolytic and mitochondrial metabolic subtypes in glioblastoma and to evaluate early treatment responses, which could guide patient treatment.

Resistance to Spindle Inhibitors in Glioblastoma Depends on STAT3 and Therapy Induced Senescence

While mitotic spindle inhibitors specifically kill proliferating tumor cells without the toxicities of microtubule poisons, resistance has limited their clinical utility. Treating glioblastomas with the spindle inhibitors ispinesib, alisertib, or volasertib creates a subpopulation of therapy induced senescent cells that resist these drugs by relying upon the anti-apoptotic and metabolic effects of activated STAT3. Furthermore, these senescent cells expand the repertoire of cells resistant to these drugs by secreting an array of factors, including TGFβ, which induce proliferating cells to exit mitosis and become quiescent-a state that also resists spindle inhibitors. Targeting STAT3 restores sensitivity to each of these drugs by depleting the senescent subpopulation and inducing quiescent cells to enter the mitotic cycle. These results support a therapeutic strategy of targeting STAT3-dependent therapy-induced senescence to enhance the efficacy of spindle inhibitors for the treatment of glioblastoma.

Highlights

• Resistance to non-microtubule spindle inhibitors limits their efficacy in glioblastoma and depends on STAT3.• Resistance goes hand in hand with development of therapy induced senescence (TIS).• Spindle inhibitor resistant glioblastomas consist of three cell subpopulations-proliferative, quiescent, and TIS-with proliferative cells sensitive and quiescent and TIS cells resistant.• TIS cells secrete TGFβ, which induces proliferative cells to become quiescent, thereby expanding the population of resistant cells in a spindle inhibitor resistant glioblastoma• Treatment with a STAT3 inhibitor kills TIS cells and restores sensitivity to spindle inhibitors.

The effects of glycemic index on prostate cancer progression in a xenograft mouse model

BACKGROUND

Previously, we found low-carbohydrate diets slowed prostate cancer (PC) growth and increased survival vs. a Western diet in mice, by inhibiting the insulin/IGF-1 axis. Thus, we tested whether modifying carbohydrate quality to lower glycemic index (GI) without changing quantity results in similar benefits as with reduced quantity.

METHODS

Male SCID mice injected with LAPC-4 cells were single-housed and randomized when their tumors reached 200 mm3 on average to a LoGI (48% carbohydrate kcal, from Hylon-VII) or HiGI Western diet (48% carbohydrate kcal, from sucrose). Body weight and tumor volume were measured weekly. Body composition was assessed 35 days after randomization. Blood glucose and serum insulin, IGF-1 and IGFBP3 were measured at study end when tumor volumes reached 800 mm3. We analyzed gene expression of mice tumors by RNA-sequencing and human tumors using the Prostate Cancer Transcriptome Atlas.

RESULTS

There were no significant differences in tumor volume (P > 0.05), tumor proliferation (P = 0.29), and overall survival (P = 0.15) between groups. At 35 days after randomization, the LoGI group had 30% lower body fat (P = 0.007) despite similar body weight (P = 0.58). At sacrifice, LoGI mice had smaller livers (P < 0.001) and lower glucose (P = 0.15), insulin (P = 0.11), IGF-1 (P = 0.07) and IGF-1:IGFBP3 ratio (P = 0.05), and higher IGFBP3 (P = 0.09) vs. HiGI, although none of these metabolic differences reached statistical significance. We observed differential gene expression and pathway enrichment in mice tumors by diet. The most upregulated and downregulated gene in the LoGI group showed expression patterns more closely resembling expression in human benign prostate tissue vs. PC.

CONCLUSIONS

In this single mouse xenograft model, consuming a low GI diet did not delay PC growth or survival vs. a high GI diet despite suggestions of decreased activation of the insulin/IGF-1 pathway. These data suggest that improving carbohydrate quality alone while consuming a high carbohydrate diet may not effectively slow PC growth.

Genome-wide CRISPR screens identify novel regulators of wild-type and mutant p53 stability

Tumor suppressor p53 (TP53) is frequently mutated in cancer, often resulting not only in loss of its tumor-suppressive function but also acquisition of dominant-negative and even oncogenic gain-of-function traits. While wild-type p53 levels are tightly regulated, mutants are typically stabilized in tumors, which is crucial for their oncogenic properties. Here, we systematically profiled the factors that regulate protein stability of wild-type and mutant p53 using marker-based genome-wide CRISPR screens. Most regulators of wild-type p53 also regulate p53 mutants, except for p53 R337H regulators, which are largely private to this mutant. Mechanistically, FBXO42 emerged as a positive regulator for a subset of p53 mutants, working with CCDC6 to control USP28-mediated mutant p53 stabilization. Additionally, C16orf72/HAPSTR1 negatively regulates both wild-type p53 and all tested mutants. C16orf72/HAPSTR1 is commonly amplified in breast cancer, and its overexpression reduces p53 levels in mouse mammary epithelium leading to accelerated breast cancer. This study offers a network perspective on p53 stability regulation, potentially guiding strategies to reinforce wild-type p53 or target mutant p53 in cancer.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte- like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

METTL8 links mt-tRNA m3C modification to the HIF1α/RTK/Akt axis to sustain GBM stemness and tumorigenicity

Epitranscriptomic RNA modifications are crucial for the maintenance of glioma stem cells (GSCs), the most malignant cells in glioblastoma (GBM). 3-methylcytosine (m3C) is a new epitranscriptomic mark on RNAs and METTL8 represents an m3C writer that is dysregulated in cancer. Although METTL8 has an established function in mitochondrial tRNA (mt-tRNA) m3C modification, alternative splicing of METTL8 can also generate isoforms that localize to the nucleolus where they may regulate R-loop formation. The molecular basis for METTL8 dysregulation in GBM, and which METTL8 isoform(s) may influence GBM cell fate and malignancy remain elusive. Here, we investigated the role of METTL8 in regulating GBM stemness and tumorigenicity. In GSC, METTL8 is exclusively localized to the mitochondrial matrix where it installs m3C on mt-tRNAThr/Ser(UCN) for mitochondrial translation and respiration. High expression of METTL8 in GBM is attributed to histone variant H2AZ-mediated chromatin accessibility of HIF1α and portends inferior glioma patient outcome. METTL8 depletion impairs the ability of GSC to self-renew and differentiate, thus retarding tumor growth in an intracranial GBM xenograft model. Interestingly, METTL8 depletion decreases protein levels of HIF1α, which serves as a transcription factor for several receptor tyrosine kinase (RTK) genes, in GSC. Accordingly, METTL8 loss inactivates the RTK/Akt axis leading to heightened sensitivity to Akt inhibitor treatment. These mechanistic findings, along with the intimate link between METTL8 levels and the HIF1α/RTK/Akt axis in glioma patients, guided us to propose a HIF1α/Akt inhibitor combination which potently compromises GSC proliferation/self-renewal in vitro. Thus, METTL8 represents a new GBM dependency that is therapeutically targetable.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Cellular diversity through space and time: adding new dimensions to GBM therapeutic development

The current median survival for glioblastoma (GBM) patients is only about 16 months, with many patients succumbing to the disease in just a matter of months, making it the most common and aggressive primary brain cancer in adults. This poor outcome is, in part, due to the lack of new treatment options with only one FDA-approved treatment in the last decade. Advances in sequencing techniques and transcriptomic analyses have revealed a vast degree of heterogeneity in GBM, from inter-patient diversity to intra-tumoral cellular variability. These cutting-edge approaches are providing new molecular insights highlighting a critical role for the tumor microenvironment (TME) as a driver of cellular plasticity and phenotypic heterogeneity. With this expanded molecular toolbox, the influence of TME factors, including endogenous (e.g., oxygen and nutrient availability and interactions with non-malignant cells) and iatrogenically induced (e.g., post-therapeutic intervention) stimuli, on tumor cell states can be explored to a greater depth. There exists a critical need for interrogating the temporal and spatial aspects of patient tumors at a high, cell-level resolution to identify therapeutically targetable states, interactions and mechanisms. In this review, we discuss advancements in our understanding of spatiotemporal diversity in GBM with an emphasis on the influence of hypoxia and immune cell interactions on tumor cell heterogeneity. Additionally, we describe specific high-resolution spatially resolved methodologies and their potential to expand the impact of pre-clinical GBM studies. Finally, we highlight clinical attempts at targeting hypoxia- and immune-related mechanisms of malignancy and the potential therapeutic opportunities afforded by single-cell and spatial exploration of GBM patient specimens.

Triggering receptor expressed on myeloid cells 2 (TREM2) regulates phagocytosis in glioblastoma

BACKGROUND

Glioblastomas (GBMs) are central nervous system tumors that resist standard-of-care interventions and even immune checkpoint blockade. Myeloid cells in the tumor microenvironment can contribute to GBM progression; therefore, emerging immunotherapeutic approaches include reprogramming these cells to achieve desirable antitumor activity. Triggering receptor expressed on myeloid cells 2 (TREM2) is a myeloid signaling regulator that has been implicated in a variety of cancers and neurological diseases with contrasting functions, but its role in GBM immunopathology and progression is still under investigation.

METHODS

Our reverse translational investigations leveraged single-cell RNA sequencing and cytometry of human gliomas to characterize TREM2 expression across myeloid subpopulations. Using 2 distinct murine glioma models, we examined the role of Trem2 on tumor progression and immune modulation of myeloid cells. Furthermore, we designed a method of tracking phagocytosis of glioma cells in vivo and employed in vitro assays to mechanistically understand the influence of TREM2 signaling on tumor uptake.

RESULTS

We discovered that TREM2 expression does not correlate with immunosuppressive pathways, but rather showed strong a positive association with the canonical phagocytosis markers lysozyme (LYZ) and macrophage scavenger receptor (CD163) in gliomas. While Trem2 deficiency was found to be dispensable for gliomagenesis, Trem2+ myeloid cells display enhanced tumor uptake compared to Trem2- cells. Mechanistically, we demonstrate that TREM2 mediates phagocytosis via Syk signaling.

CONCLUSIONS

These results indicate that TREM2 is not associated with immunosuppression in gliomas. Instead, TREM2 is an important regulator of phagocytosis that may be exploited as a potential therapeutic strategy for brain tumors.

Cancer stem cell hypothesis 2.0 in glioblastoma: Where are we now and where are we going?

Over the past 2 decades, the cancer stem cell (CSC) hypothesis has provided insight into many malignant tumors, including glioblastoma (GBM). Cancer stem cells have been identified in patient-derived tumors and in some mouse models, allowing for a deeper understanding of cellular and molecular mechanisms underlying GBM growth and therapeutic resistance. The CSC hypothesis has been the cornerstone of cellular heterogeneity, providing a conceptual and technical framework to explain this longstanding phenotype in GBM. This hypothesis has evolved to fit recent insights into how cellular plasticity drives tumor growth to suggest that CSCs do not represent a distinct population but rather a cellular state with substantial plasticity that can be achieved by non-CSCs under specific conditions. This has further been reinforced by advances in genomics, including single-cell approaches, that have used the CSC hypothesis to identify multiple putative CSC states with unique properties, including specific developmental and metabolic programs. In this review, we provide a historical perspective on the CSC hypothesis and its recent evolution, with a focus on key functional phenotypes, and provide an update on the definition for its use in future genomic studies.

Integrated Proteogenomics Uncover Mechanisms of Glioblastoma Evolution, Pointing to Novel Therapeutic Targets

Nearly all glioblastoma (GBM) patients relapse following standard treatment and eventually succumb to disease. While large-scale, integrated multiomic studies have tremendously advanced the understanding of primary GBM at the cellular and molecular level, the posttherapeutic trajectory and biological properties of recurrent GBM remain poorly understood. This knowledge gap was addressed in a recent Cancer Cell article in which Kim and colleagues report on a highly integrative proteogenomic analysis performed on 123 matched primary and recurrent GBMs that uncovered a dramatic evolutionary shift from a proliferative state at initial diagnosis to the activation of neuronal and synaptogenic pathways at recurrence following therapy. Neuronal transition was characterized by posttranslational activation of WNT/PCP signaling and BRAF kinase, while many canonical oncogenic pathways, and EGFR in particular, were downregulated. Parallel multiomics analyses of patient-derived xenograft (PDX) models corroborated this evolutionary trajectory, allowing in vivo experiments for translational significance. Notably, targeting BRAF kinase disrupted both the neuronal transition and migration capabilities of recurrent gliomas, which were key characteristics of posttreatment progression. Furthermore, combining BRAF inhibitor vemurafenib with temozolomide prolonged survival in PDX models. Overall, the results reveal novel biological mechanisms of GBM evolution and therapy resistance, and suggest promising therapeutic intervention.

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes

Introduction

Aberrant reactive oxygen species (ROS) production is one of the hallmarks of cancer. During their growth and dissemination, cancer cells control redox signaling to support protumorigenic pathways. As a consequence, cancer cells become reliant on major antioxidant systems to maintain a balanced redox tone, while avoiding excessive oxidative stress and cell death. This concept appears especially relevant in the context of glioblastoma multiforme (GBM), the most aggressive form of brain tumor characterized by significant heterogeneity, which contributes to treatment resistance and tumor recurrence. From this viewpoint, this study aims to investigate whether gene regulatory networks can effectively capture the diverse redox states associated with the primary phenotypes of GBM.

Methods

In this study, we utilized publicly available GBM datasets along with proprietary bulk sequencing data. Employing computational analysis and bioinformatics tools, we stratified GBM based on their antioxidant capacities and evaluated the distinctive functionalities and prognostic values of distinct transcriptional networks in silico.

Results

We established three distinct transcriptional co-expression networks and signatures (termed clusters C1, C2, and C3) with distinct antioxidant potential in GBM cancer cells. Functional analysis of each cluster revealed that C1 exhibits strong antioxidant properties, C2 is marked with a discrepant inflammatory trait and C3 was identified as the cluster with the weakest antioxidant capacity. Intriguingly, C2 exhibited a strong correlation with the highly aggressive mesenchymal subtype of GBM. Furthermore, this cluster holds substantial prognostic importance: patients with higher gene set variation analysis (GSVA) scores of the C2 signature exhibited adverse outcomes in overall and progression-free survival.

Conclusion

In summary, we provide a set of transcriptional signatures that unveil the antioxidant potential of GBM, offering a promising prognostic application and a guide for therapeutic strategies in GBM therapy.

An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma

Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.

Nonepithelial cancer dissemination: specificities and challenges

Epithelial cancers have served as a paradigm to study tumor dissemination but recent data have highlighted significant differences with nonepithelial cancers. Here, we review the current knowledge on nonepithelial tumor dissemination, drawing examples from the latest developments in melanoma, glioma, and sarcoma research. We underscore the importance of the reactivation of developmental processes during cancer progression and describe the nongenetic mechanisms driving nonepithelial tumor spread. We also outline therapeutic opportunities and ongoing clinical approaches to fight disseminating cancers. Finally, we discuss remaining challenges and emerging questions in the field. Defining the core principles underlying nonepithelial cancer dissemination may uncover actionable vulnerabilities of metastatic tumors and help improve the prognosis of patients with cancer.

Integrative multi-omics characterization reveals sex differences in glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults, with limited treatment modalities and poor prognosis. Recent studies have highlighted the importance of considering sex differences in cancer incidence, prognosis, molecular disparities, and treatment outcomes across various tumor types, including colorectal adenocarcinoma, lung adenocarcinoma, and GBM.

METHODS

We performed comprehensive analyses of large-scale multi-omics data (genomic, transcriptomic, and proteomic data) from TCGA, GLASS, and CPTAC to investigate the genetic and molecular determinants that contribute to the unique clinical properties of male and female GBM patients.

RESULTS

Our results revealed several key differences, including enrichments of MGMT promoter methylation, which correlated with increased overall and post-recurrence survival and improved response to chemotherapy in female patients. Moreover, female GBM exhibited a higher degree of genomic instability, including aneuploidy and tumor mutational burden. Integrative proteomic and phosphor-proteomic characterization uncovered sex-specific protein abundance and phosphorylation activities, including EGFR activation in males and SPP1 hyperphosphorylation in female patients. Lastly, the identified sex-specific biomarkers demonstrated prognostic significance, suggesting their potential as therapeutic targets.

CONCLUSIONS

Collectively, our study provides unprecedented insights into the fundamental modulators of tumor progression and clinical outcomes between male and female GBM patients and facilitates sex-specific treatment interventions. Highlights Female GBM patients were characterized by increased MGMT promoter methylation and favorable clinical outcomes compared to male patients. Female GBMs exhibited higher levels of genomic instability, including aneuploidy and TMB. Each sex-specific GBM is characterized by unique pathway dysregulations and molecular subtypes. EGFR activation is prevalent in male patients, while female patients are marked by SPP1 hyperphosphorylation.

Proneural-mesenchymal antagonism dominates the patterns of phenotypic heterogeneity in glioblastoma

The aggressive nature of glioblastoma (GBM) - one of the deadliest forms of brain tumors - is majorly attributed to underlying phenotypic heterogeneity. Early attempts to classify this heterogeneity at a transcriptomic level in TCGA GBM cohort proposed the existence of four distinct molecular subtypes: Proneural, Neural, Classical, and Mesenchymal. Further, a single-cell RNA sequencing (scRNA-seq) analysis of primary tumors also reported similar four subtypes mimicking neurodevelopmental lineages. However, it remains unclear whether these four subtypes identified via bulk and single-cell transcriptomics are mutually exclusive or not. Here, we perform pairwise correlations among individual genes and gene signatures corresponding to these proposed subtypes and show that the subtypes are not distinctly mutually antagonistic in either TCGA or scRNA-seq data. We observed that the proneural (or neural progenitor-like)-mesenchymal axis is the most prominent antagonistic pair, with the other two subtypes lying on this spectrum. These results are reinforced through a meta-analysis of over 100 single-cell and bulk transcriptomic datasets as well as in terms of functional association with metabolic switching, cell cycle, and immune evasion pathways. Finally, this proneural-mesenchymal antagonistic trend percolates to the association of relevant transcription factors with patient survival. These results suggest rethinking GBM phenotypic characterization for more effective therapeutic targeting efforts.

OGDH and Bcl-xL loss causes synthetic lethality in glioblastoma

Glioblastoma (GBM) remains an incurable disease, requiring more effective therapies. Through interrogation of publicly available CRISPR and RNAi library screens, we identified the α-ketoglutarate dehydrogenase (OGDH) gene, which encodes an enzyme that is part of the tricarboxylic acid (TCA) cycle, as essential for GBM growth. Moreover, by combining transcriptome and metabolite screening analyses, we discovered that loss of function of OGDH by the clinically validated drug compound CPI-613 was synthetically lethal with Bcl-xL inhibition (genetically and through the clinically validated BH3 mimetic, ABT263) in patient-derived xenografts as well neurosphere GBM cultures. CPI-613-mediated energy deprivation drove an integrated stress response with an upregulation of the BH3-only domain protein, Noxa, in an ATF4-dependent manner, as demonstrated by genetic loss-of-function experiments. Consistently, silencing of Noxa attenuated cell death induced by CPI-613 in model systems of GBM. In patient-derived xenograft models of GBM in mice, the combination treatment of ABT263 and CPI-613 suppressed tumor growth and extended animal survival more potently than each compound on its own. Therefore, combined inhibition of Bcl-xL along with disruption of the TCA cycle might be a treatment strategy for GBM.

Integrated proteogenomic characterization of glioblastoma evolution

The evolutionary trajectory of glioblastoma (GBM) is a multifaceted biological process that extends beyond genetic alterations alone. Here, we perform an integrative proteogenomic analysis of 123 longitudinal glioblastoma pairs and identify a highly proliferative cellular state at diagnosis and replacement by activation of neuronal transition and synaptogenic pathways in recurrent tumors. Proteomic and phosphoproteomic analyses reveal that the molecular transition to neuronal state at recurrence is marked by post-translational activation of the wingless-related integration site (WNT)/ planar cell polarity (PCP) signaling pathway and BRAF protein kinase. Consistently, multi-omic analysis of patient-derived xenograft (PDX) models mirror similar patterns of evolutionary trajectory. Inhibition of B-raf proto-oncogene (BRAF) kinase impairs both neuronal transition and migration capability of recurrent tumor cells, phenotypic hallmarks of post-therapy progression. Combinatorial treatment of temozolomide (TMZ) with BRAF inhibitor, vemurafenib, significantly extends the survival of PDX models. This study provides comprehensive insights into the biological mechanisms of glioblastoma evolution and treatment resistance, highlighting promising therapeutic strategies for clinical intervention.

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

Unraveling the intricacies of glioblastoma progression and recurrence: insights into the role of NFYB and oxidative phosphorylation at the single-cell level

Background

Glioblastoma (GBM), with its high recurrence and mortality rates, makes it the deadliest neurological malignancy. Oxidative phosphorylation is a highly active cellular pathway in GBM, and NFYB is a tumor-associated transcription factor. Both are related to mitochondrial function, but studies on their relationship with GBM at the single-cell level are still scarce.

Methods

We re-analyzed the single-cell profiles of GBM from patients with different subtypes by single-cell transcriptomic analysis and further subdivided the large population of Glioma cells into different subpopulations, explored the interrelationships and active pathways among cell stages and clinical subtypes of the populations, and investigated the relationship between the transcription factor NFYB of the key subpopulations and GBM, searching for the prognostic genes of GBM related to NFYB, and verified by experiments.

Results

Glioma cells and their C5 subpopulation had the highest percentage of G2M staging and rGBM, which we hypothesized might be related to the higher dividing and proliferating ability of both Glioma and C5 subpopulations. Oxidative phosphorylation pathway activity is elevated in both the Glioma and C5 subgroup, and NFYB is a key transcription factor for the C5 subgroup, suggesting its possible involvement in GBM proliferation and recurrence, and its close association with mitochondrial function. We also identified 13 prognostic genes associated with NFYB, of which MEM60 may cause GBM patients to have a poor prognosis by promoting GBM proliferation and drug resistance. Knockdown of the NFYB was found to contribute to the inhibition of proliferation, invasion, and migration of GBM cells.

Conclusion

These findings help to elucidate the key mechanisms of mitochondrial function in GBM progression and recurrence, and to establish a new prognostic model and therapeutic target based on NFYB.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.

SIGNIFICANCE

Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.

Mitochondrial Mechanisms in Temozolomide Resistance: Unraveling the Complex Interplay and Therapeutic Strategies in Glioblastoma

Glioblastoma (GBM) is a highly aggressive and lethal brain tumor, with temozolomide (TMZ) being the standard chemotherapeutic agent for its treatment. However, TMZ resistance often develops, limiting its therapeutic efficacy and contributing to poor patient outcomes. Recent evidence highlights the crucial role of mitochondria in the development of TMZ resistance through various mechanisms, including alterations in reactive oxygen species (ROS) production, metabolic reprogramming, apoptosis regulation, biogenesis, dynamics, stress response, and mtDNA mutations. This review article aims to provide a comprehensive overview of the mitochondrial mechanisms involved in TMZ resistance and discuss potential therapeutic strategies targeting these mechanisms to overcome resistance in GBM. We explore the current state of clinical trials targeting mitochondria or related pathways in primary GBM or recurrent GBM, as well as the challenges and future perspectives in this field. Understanding the complex interplay between mitochondria and TMZ resistance will facilitate the development of more effective therapeutic strategies and ultimately improve the prognosis for GBM patients.

IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy

BACKGROUND

Glioblastoma (GBM) brain tumors lacking IDH1 mutations (IDHwt) have the worst prognosis of all brain neoplasms. Patients receive surgery and chemoradiotherapy but tumors almost always fatally recur.

RESULTS

Using RNA sequencing data from 107 pairs of pre- and post-standard treatment locally recurrent IDHwt GBM tumors, we identify two responder subtypes based on longitudinal changes in gene expression. In two thirds of patients, a specific subset of genes is upregulated from primary to recurrence (Up responders), and in one third, the same genes are downregulated (Down responders), specifically in neoplastic cells. Characterization of the responder subtypes indicates subtype-specific adaptive treatment resistance mechanisms that are associated with distinct changes in the tumor microenvironment. In Up responders, recurrent tumors are enriched in quiescent proneural GBM stem cells and differentiated neoplastic cells, with increased interaction with the surrounding normal brain and neurotransmitter signaling, whereas Down responders commonly undergo mesenchymal transition. ChIP-sequencing data from longitudinal GBM tumors suggests that the observed transcriptional reprogramming could be driven by Polycomb-based chromatin remodeling rather than DNA methylation.

CONCLUSIONS

We show that the responder subtype is cancer-cell intrinsic, recapitulated in in vitro GBM cell models, and influenced by the presence of the tumor microenvironment. Stratifying GBM tumors by responder subtype may lead to more effective treatment.

Branched-chain amino acid transaminase 1 regulates glioblastoma cell plasticity and contributes to immunosuppression

BACKGROUND

Glioblastoma is the most common malignant brain tumor in adults. Cellular plasticity and the poorly differentiated features result in a fast relapse of the tumors following treatment. Moreover, the immunosuppressive microenvironment proved to be a major obstacle to immunotherapeutic approaches. Branched-chain amino acid transaminase 1 (BCAT1) was shown to drive the growth of glioblastoma and other cancers;however, its oncogenic mechanism remains poorly understood.

METHODS

Using human tumor data, cell line models and orthotopic immuno-competent and -deficient mouse models, we investigated the phenotypic and mechanistic effects of BCAT1 on glioblastoma cell state and immunomodulation.

RESULTS

Here, we show that BCAT1 is crucial for maintaining the poorly differentiated state of glioblastoma cells and that its low expression correlates with a more differentiated glioblastoma phenotype. Furthermore, orthotopic tumor injection into immunocompetent mice demonstrated that the brain microenvironment is sufficient to induce differentiation of Bcat1-KO tumors in vivo. We link the transition to a differentiated cell state to the increased activity of ten-eleven translocation demethylases and the hypomethylation and activation of neuronal differentiation genes. In addition, the knockout of Bcat1 attenuated immunosuppression, allowing for an extensive infiltration of CD8+ cytotoxic T-cells and complete abrogation of tumor growth. Further analysis in immunodeficient mice revealed that both tumor cell differentiation and immunomodulation following BCAT1-KO contribute to the long-term suppression of tumor growth.

CONCLUSIONS

Our study unveils BCAT1's pivotal role in promoting glioblastoma growth by inhibiting tumor cell differentiation and sustaining an immunosuppressive milieu. These findings offer a novel therapeutic avenue for targeting glioblastoma through the inhibition of BCAT1.

Regulation of cancer stem cells and immunotherapy of glioblastoma (Review)

Glioblastoma (GB) is one of the most adverse diagnoses in oncology. Complex current treatment results in a median survival of 15 months. Resistance to treatment is associated with the presence of cancer stem cells (CSCs). The present review aimed to analyze the mechanisms of CSC plasticity, showing the particular role of β-catenin in regulating vital functions of CSCs, and to describe the molecular mechanisms of Wnt-independent increase of β-catenin levels, which is influenced by the local microenvironment of CSCs. The present review also analyzed the reasons for the low effectiveness of using medication in the regulation of CSCs, and proposed the development of immunotherapy scenarios with tumor cell vaccines, containing heterogenous cancer cells able of producing a multidirectional antineoplastic immune response. Additionally, the possibility of managing lymphopenia by transplanting hematopoietic stem cells from a healthy sibling and using clofazimine or other repurposed drugs that reduce β-catenin concentration in CSCs was discussed in the present study.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.