Spatially resolved multi-omics deciphers bidirectional tumor-host interdependence in glioblastoma

Advances in Sampling and Analytical Techniques for Single-Cell Metabolomics: Exploring Cellular Heterogeneity

Single-cell metabolomics is an emerging and powerful technology that uncovers intercellular heterogeneity and reveals microenvironmental dynamics in both physiological and pathological conditions. This technology enables detailed observations of cellular interactions, providing valuable insights into processes such as aging, immune responses, and disease development. Despite significant advances, the need for detailed discussions on sampling and analytical methods in single-cell metabolomics continues to grow, with increasing focus on selecting the most suitable techniques for diverse research objectives. This review addresses these challenges by exploring key sampling and analytical strategies used in single-cell metabolomics. We focus on three main approaches: the capture and isolation of specific cell types, the precise aspiration of individual cells, and in situ mass spectrometry imaging. These methods are critically assessed to highlight strategies for achieving accurate metabolite detection at the single-cell level across diverse research applications.

Decoding glioblastoma's diversity: Are neurons part of the game?

Glioblastoma multiforme (GBM, WHO Grade 4) is a highly aggressive primary brain tumor with limited treatment options and a poor prognosis. A key challenge in GBM therapy lies in its pronounced heterogeneity, both within individual tumors (intratumoral) and between patients (intertumoral). Historically, neurons have been underexplored in GBM research; however, recent studies reveal that GBM development is closely linked to neural and glial progenitors, often mimicking neurodevelopmental processes in a dysregulated manner. Beyond damaging neuronal tissue, GBM actively engages with neurons to promote pro-tumorigenic signaling, including neuronal hyperexcitability and seizures. Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of the tumor microenvironment (TME), uncovering the critical roles of immune cells, endothelial cells, and astrocytes in tumor progression. However, technical limitations of scRNA-seq hinder its ability to capture the transcriptomes of neurons, necessitating the use of single-nucleus RNA sequencing (snRNA-seq) to study these interactions at single-cell resolution. This work collects the emerging insights of glioblastoma-neuron interactions, focusing on how GBM exploits neurodevelopmental pathways and reshapes neuronal networks. Moreover, we perform bioinformatic analysis of publicly available snRNA-seq datasets to propose putative cell-cell interactions driving glioma-neuronal dynamics. This study delineates key signaling pathways and underscores the need for further investigation to evaluate their potential as therapeutic targets.

Glioma-neuronal circuit remodeling induces regional immunosuppression

Neuronal activity-driven mechanisms influence glioblastoma cell proliferation and invasion, while glioblastoma remodels neuronal circuits. Although a subpopulation of malignant cells enhances neuronal connectivity, their impact on the immune system remains unclear. Here, we show that glioblastoma regions with enhanced neuronal connectivity exhibit regional immunosuppression, characterized by distinct immune cell compositions and the enrichment of anti-inflammatory tumor-associated macrophages (TAMs). In preclinical models, knockout of Thrombospondin-1 (TSP1/Thbs1) in glioblastoma cells suppresses synaptogenesis and glutamatergic neuronal hyperexcitability. Furthermore, TSP1 knockout restores antigen presentation-related genes, promotes the infiltration of pro-inflammatory TAMs and CD8 + T-cells in the tumor, and alleviates TAM-mediated T-cell suppression. Pharmacological inhibition of glutamatergic signaling also shifts TAMs toward a less immunosuppressive state, prolongs survival in mice, and shows the potential to enhance the efficacy of immune cell-based therapy. These findings confirm that glioma-neuronal circuit remodeling is strongly linked with regional immunosuppression and suggest that targeting glioma-neuron-immune crosstalk could provide avenues for immunotherapy.

Glioblastoma-instructed astrocytes suppress tumour-specific T cell immunity

Glioblastoma is the most common and aggressive primary brain cancer and shows minimal response to therapies. The immunosuppressive tumour microenvironment in glioblastoma contributes to the limited therapeutic response. Astrocytes are abundant in the central nervous system and have important immunoregulatory roles. However, little is known about their role in the immune response to glioblastoma1. Here we used single-cell and bulk RNA sequencing of clinical glioblastoma samples and samples from preclinical models, multiplexed immunofluorescence, in vivo CRISPR-based cell-specific genetic perturbations and in vitro mouse and human experimental systems to address this gap in knowledge. We identified an astrocyte subset that limits tumour immunity by inducing T cell apoptosis through the death receptor ligand TRAIL. Moreover, we identified that IL-11 produced by tumour cells is a driver of STAT3-dependent TRAIL expression in astrocytes. Astrocyte signalling through STAT3 and TRAIL expression were associated with a shorter time to recurrence and overall decreased survival in patients with glioblastoma. Genetic inactivation of the IL-11 receptor or TRAIL in astrocytes extended survival in mouse models of glioblastoma and enhanced T cell and macrophage responses. Finally, treatment with an oncolytic HSV-1 virus engineered to express a TRAIL-blocking single-chain antibody in the tumour microenvironment extended survival and enhanced tumour-specific immunity in preclinical models of glioblastoma. In summary, we establish that IL-11-STAT3-driven astrocytes suppress glioblastoma-specific protective immunity by inducing TRAIL-dependent T cell apoptosis, and engineered therapeutic viruses can be used to target this mechanism of astrocyte-driven tumour immunoevasion.

Dissecting the immune landscape in pediatric high-grade glioma reveals cell state changes under therapeutic pressure

Pediatric high-grade gliomas (pHGGs) are among the most lethal childhood tumors. While therapeutic approaches were largely adapted from adult treatment regime, significant biological differences between pediatric and adult gliomas exist, which influence the immune microenvironment and may contribute to the limited response to current pHGG treatment strategies. We provide a comprehensive transcriptomic analysis of the pHGG immune landscape using single-cell RNA sequencing and spatial transcriptomics. We analyze matched malignant, myeloid, and T cells from patients with pediatric diffuse high-grade glioma (HGG) or high-grade ependymoma, examining immune microenvironment distinctions after chemo-/radiotherapy, immune checkpoint inhibition treatment, and by age. Our analysis reveals differences in the proportions of pediatric myeloid subpopulations compared to adult counterparts. Additionally, we observe significant shifts toward immune-suppressive environments following cancer therapy. Our findings offer valuable insights into potential immunotherapy targets and serve as a robust resource for understanding immune microenvironmental variations across HGG age groups and treatment regimens.

O-GlcNAcylation stabilized WTAP promotes GBM malignant progression in an N6-methyladenosine-dependent manner

BACKGROUND

Interactions between mesenchymal glioblastoma stem cells (MES GSCs) and myeloid-derived macrophages (MDMs) shape the tumor-immunosuppressive microenvironment (TIME), promoting the progression of glioblastoma (GBM). N6-methyladenosine (m6A) plays important roles in the tumor progression. However, the mechanism of m6A in shaping the TIME of GBM remains elusive.

METHODS

Single-cell RNA sequencing and bulk RNA-seq datasets were employed to identify the critical role of WTAP in interactions between MES GBM and MDMs. The biological function of WTAP was confirmed both in vitro and in vivo. Mechanistically, mass spectrum, RNA immunoprecipitation (RIP), and co-immunoprecipitation assays were conducted.

RESULTS

Here, we identified that m6A methyltransferase Wilms' tumor 1-associated protein (WTAP), whose protein stability could be synergistically enhanced via OGT-mediated O-GlcNAcylation and USP7-mediated de-ubiquitination, promoted LOXL2 m6A modification to enhance its mRNA stabilization in an IGF2BP2-dependent manner, upregulating secretion of LOXL2 protein (sLOXL2). sLOXL2 then interacted with integrin α5β1 on GSCs to activate FAK-ERK signaling, inducing mesenchymal transition of GSCs in an autocrine manner. Meanwhile, sLOXL2 also activated the integrin α5β1-FAK-ERK axis in MDMs, which promoted M2-like MDM phenotypes in a paracrine pathway, thereby contributing to T-cell exhaustion to induce GBM immune escape. In translational medicine, combinations of the OGT inhibitor by targeting WTAP expression and the LOXL2 antagonist by disrupting MES GSC and MDM interactions showed favorable outcomes to the anti-PD1 immunotherapy.

CONCLUSIONS

WTAP plays critical roles in mesenchymal transition of GSCs and formation of TIME, highlighting the therapeutic potential of targeting WTAP and its downstream effectors to enhance the efficacy of immunotherapy.

Stress-induced pro-inflammatory glioblastoma stem cells secrete TNFAIP6 to enhance tumor growth and induce suppressive macrophages

Glioblastoma (GBM) is the most aggressive primary intracranial tumor, with glioblastoma stem cells (GSCs) enforcing the intratumoral hierarchy. The inflammatory microenvironment influences tumor development at varying stages, while the underlying mechanism of GSCs facing pro-inflammatory stress remains unclear. Here, we show that, in human GBM, pro-inflammatory stress from pro-inflammatory macrophages (pTAMs) maintains GSC proliferation and self-renewal. Tumor necrosis factor alpha-induced protein 6 (TNFAIP6), as a responder in patient-derived GSCs to pro-inflammatory stress tumor necrosis factor alpha (TNF-α) from human pTAMs, promotes tumor growth through binding epidermal growth factor (EGF) and prolonging EGF receptor (EGFR)-phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) signaling activation. Meanwhile, pro-inflammatory stress-induced patient-derived GSCs secrete TNFAIP6 to transform macrophage phenotype from pTAMs to inflammatory-suppressive macrophages (sTAMs). Collectively, pharmacological or genetic disruption of TNFAIP6 autocrine and paracrine communication between patient-derived GSCs and TAMs inhibited GSC proliferation and self-renewal in vitro and in patient-derived xenograft tumor-bearing mice, suggesting that TNFAIP6 is an effective target for GBM therapy.

Neurodevelopmental hijacking of oligodendrocyte lineage programs drives glioblastoma infiltration

Glioblastoma (GBM) is an aggressive brain tumor with a highly invasive nature. Despite the clinical relevance of this behavior, the molecular underpinnings of infiltrating GBM cells in the peritumoral zone remain underexplored in patients. Here, we show that peritumoral progenitor-like GBM cells activate transcriptional programs associated with increased invasivity, synaptic activity, and NOTCH signaling. These cells spatially colocalize with neurons and exhibit an increased propensity for neuronal crosstalk. The epigenetic encoding of these infiltrative cells mirrors that of uncommitted oligodendrocyte progenitor cells (OPCs) in the developing human brain, a neurodevelopmental state marked by increased synaptic and migratory potential. Functional perturbation of a nominated regulatory factor, ZEB1, confirmed its role in maintaining the invasive and uncommitted developmental potential of infiltrative GBM cells. Our findings provide insights into the neurodevelopmental hijacking that drives GBM infiltration in patients, rationalizing further investigation into targeting differentiation potential as a therapeutic strategy.

Targeting mesenchymal monocyte-derived macrophages to enhance the sensitivity of glioblastoma to temozolomide by inhibiting TNF/CELSR2/p65/Kla-HDAC1/EPAS1 axis

INTRODUCTION

Temozolomide (TMZ) resistance poses a significant challenge to the treatment of aggressive and highly lethal glioblastomas (GBM). Monocyte-derived Macrophages (MDM) within the tumor microenvironment are key factors contributing to TMZ resistance in GBM. Lactate-mediated histone lysine lactylation (Kla) plays a crucial role in the regulation of tumor progression. However, the mechanism through which MDM-induced Kla expression promotes TMZ resistance in GBM remains unclear.

OBJECTIVES

The objective of this study s to identify a subtype of MDM with therapeutic potential target and to elucidate the mechanisms through which this subtype of MDM contributes to tumor malignant progression and TMZ resistance.

METHODS

We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to evaluate whether mesenchymal (MES) MDM is associated with poor prognosis. By establishing a subtype model of GBM cells for the first time, we validated the mechanism by which MES-MDM promotes subtype conversion of tumor cells. Using patient-derived GBM organoids and an intracranial orthotopic GBM model, we demonstrated that targeting MES-MDM increased GBM sensitivity to TMZ treatment.

RESULTS

We identified a novel MDM subtype, MES-MDM, in the hypoxic niches of the perinecrotic region characterized by high TREM1 expression, which fueled GBM progression. Hypoxia drived MES-MDM signatures by activating ATF3 transcription. MES-MDM facilitated the transition from the NPC to the MES subtype in GBM cells, in which Histone Deacetylase 1 (HDAC1) Kla, induced by the TNF-CELSR2/p65 signaling pathway, promoted this conversion, thereby promoting TMZ resistance. Targeting MES-MDM with TREM1 inhibitory peptides amplified TMZ sensitivity, offering a potential strategy for overcoming resistance to therapy in GBM. Targeting TREM1 enhanced the effectiveness of anti-PD-1 immunotherapy.

CONCLUSION

This study provides a potential therapeutic strategy for patients with MES-subtype GBM by targeting MES-MDM in combination with TMZ or PD-1 antibody treatment.

Spatial multi-omics reveals the potential involvement of SPP1+ fibroblasts in determining metabolic heterogeneity and promoting metastatic growth of colorectal cancer liver metastasis

This study investigates key microscopic regions involved in colorectal cancer liver metastasis (CRLM), focusing on the crucial role of cancer-associated fibroblasts (CAFs) in promoting tumor progression and providing molecular- and metabolism-level insights for its diagnosis and treatment using multi-omics. We followed 12 fresh surgical samples from 2 untreated CRLM patients. Among these, 4 samples were used for spatial transcriptomics (ST), 4 for spatial metabolomics, and 4 for single-cell RNA sequencing (scRNA-seq). Additionally, 92 frozen tissue samples from 40 patients were collected. Seven patients were used for immunofluorescence and RT-qPCR, while 33 patients were used for untargeted metabolomics. ST revealed that the spatial regions of CRLM consists of 7 major components, with fibroblast-dominated regions being the most prominent. These regions are characterized by diverse cell-cell interactions, and immunosuppressive and tumor growth-promoting environments. scRNA-seq identified that SPP1+ fibroblasts interact with CD44+ tumor cells, as confirmed through immunofluorescence. Spatial metabolomics revealed suberic acid and tetraethylene glycol as specific metabolic components of this structure, which was further validated by untargeted metabolomics. In conclusion, an SPP1+ fibroblast-rich spatial region with metabolic reprogramming capabilities and immunosuppressive properties was identified in CRLM, which potentially facilitates metastatic outgrowth through interactions with tumor cells.

Deciphering the Dialogue between Brain Tumors, Neurons, and Astrocytes

Glioblastoma (GB) and brain metastases (BM) from peripheral tumors account for most cases of tumors in the central nervous system (CNS) while also being the deadliest. From a structural point of view, malignant brain tumors are classically characterized by hypercellularity of glioma and vascular endothelial cells. Given these atypical histologic features, GB and BM have long been considered as "foreign" entities with few to no connections to the brain parenchyma. The identification of intricate connections established between GB cells and the brain parenchyma paired with the ability of peripheral metastatic cells to form functional synapses with neurons challenged the concept of brain tumors disconnected from the CNS. Tumor cell integration to the CNS alters brain functionality in patients and accelerates cancer progression. Next-generation precision medicine should therefore attempt to disconnect brain cancer cells from the brain. This review encompasses recent discoveries on the mechanisms underlying these relationships and discusses the impact of these connections on tumor progression. It also summarizes the therapeutic opportunities of interrupting the dialogue between healthy and neoplastic brains.

Single-cell and spatial analyses reveal the effect of VSIG4+S100A10+TAMs on the immunosuppression of glioblastoma and anti-PD-1 immunotherapy

Therapeutic strategies aiming at the tumor immune microenvironment (TIME) hold promise for glioblastoma (GBM) treatment. However, adjuvant immunotherapies targeting checkpoint inhibitors just prove effective for a selected group of GBM patients. The extensive involvement of GBM-associated macrophages highlights their potential role in tumor behavior. In-depth exploration of the impact of macrophages on the efficacy of immunotherapy is crucial for enhancing treatment outcomes. In this study, we conducted a comprehensive analysis using bulk RNA-seq, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to explore the heterogeneity of tumor-associated macrophages (TAMs) in GBM. Flow cytometry was employed to investigate the effects of VSIG4 on TAM phenotypes, and co-culture cellular assays were performed to evaluate its contribution to GBM malignancy. Integrating 16 patient samples, we examined the immunological significance of VSIG4+S100A10+TAMs. VSIG4 expression on macrophages is significantly upregulated and correlated with the TIME, promoting the polarization of macrophages towards M2 and facilitating GBM progression. Spatial transcriptomics and human samples multiplex immunofluorescence (mIF) confirmed the co-localization of VSIG4+S100A10+TAMs with various T cells, resulting in the inhibition of T cell immune responses and a reduction in anti-tumor immunity. Our findings demonstrate for the first time that VSIG4+S100A10+TAM is an independent prognostic indicator of poor outcome for GBM and markedly accumulates in patients exhibiting non-responsiveness to anti-PD-1 immunotherapy. Targeting this specific bifunctional subgroup can potentially open up new avenues for the immunotherapy of GBM.

The multilayered transcriptional architecture of glioblastoma ecosystems

In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al.

Integrating Multiplex Immunohistochemistry and Machine Learning for Glioma Subtyping and Prognosis Prediction

Glioma subtyping is crucial for treatment decisions, but traditional approaches often fail to capture tumor heterogeneity. This study proposes a novel framework integrating multiplex immunohistochemistry (mIHC) and machine learning for glioma subtyping and prognosis prediction. 185 patient samples from the Huashan hospital cohort were stained using a multi-label mIHC panel and analyzed with an AI-based auto-scanning system to calculate cell ratios and determine the proportion of positive tumor cells for various markers. Patients were divided into two cohorts (training: N = 111, testing: N = 74), and a machine learning model was then developed and validated for subtype classification and prognosis prediction. The framework identified two distinct glioma subtypes with significant differences in prognosis, clinical characteristics, and molecular profiles. The high-risk subtype, associated with older age, poorer outcomes, astrocytoma/glioblastoma, higher tumor grades, elevated mesenchymal scores, and an inhibitory immune microenvironment, exhibited IDH wild-type, 1p19q non-codeletion, and MGMT promoter unmethylation, suggesting chemotherapy resistance. Conversely, the low-risk subtype, characterized by younger age, better prognosis, astrocytoma/oligodendroglioma, lower tumor grades, and favorable molecular profiles (IDH mutation, 1p19q codeletion, MGMT promoter methylation), indicated chemotherapy sensitivity. The mIHC-based framework enables rapid glioma classification, facilitating tailored treatment strategies and accurate prognosis prediction, potentially improving patient management and outcomes.

Fn14-targeting, NIR-II responsive nanomaterials for enhanced radiotherapy against glioblastomas

Radiotherapy is a common treatment option for patients with glioblastoma multiforme. However, tumor heterogeneity causes varying responses to radiation among different tumor subpopulations. Cancer cells that endure radiotherapy exhibit radioresistance, resulting in the ineffectiveness of radiation therapy and eventual tumor relapse. In this study, we discovered that the fibroblast growth factor-inducible 14 (Fn14)-positive tumor cells were enriched in tumor residual foci after radiation, ultimately leading to treatment failure. Fn14-expressing glioma cells survived ionizing radiation through preferential activation of DNA damage checkpoint response. We have thus engineered an Fn14-targeting and NIR-II responsive plasmonic gold nanosystem named Fn14-AuNPs, which can precisely internalize into Fn14-overexpressed glioma cells and have an excellent BBB-crossing capability. As gold nanoparticles, by inhibition of DNA repair processes and induction of G2/M cells cycle arrest, Fn14-AuNPs nanoparticles improved the radiosensitivity of tumor cells. Meanwhile, Fn14-AuNPs induced localized heat under NIR-II photoirradiation, thus impeding RT-induced DNA damage checkpoint response. This versatile nanosensitizer, combined with NIR-II laser photoirradiation, can eradicate radioresistant subpopulations of glioblastoma and improve the therapeutic effect of radiotherapy. This finding presents an effective radiosensitization strategy by targeting radioresistant subpopulations, which can efficiently overcome the constraints imposed in clinical radiotherapy and offer a hopeful avenue to enhance the treatment effectivity of radiotherapy in glioblastoma.

Single-nucleus RNA sequencing reveals a preclinical model for the most common subtype of glioblastoma

Different glioblastoma (GBM) subtypes have been identified based on the tumor microenvironment (TME). The discovery of new therapies for these hard-to-treat tumors requires a thorough characterization of preclinical models, including their TME, to apply preclinical results to the most similar GBM subtype. Using single-nucleus RNA sequencing (snRNA-seq), we characterized the tumor and TME in an immunocompetent mouse model with intracranially implanted GBM stem cells at different stages and treatments. Visium spatial transcriptomics confirmed the location of annotated cells. This model exhibits GBM targets related to integration into neural circuits - Grik2, Nlgn3, Gap43 or Kcnn4-, immunoevasion - Nt5e, Cd274 or Irf8- and immunosuppression - Csf1r, Arg1, Mrc1 and Tgfb1. The landscape of cytokines, checkpoint ligands and receptors uncovered Mrc1, PD-L1, TIM-3 or B7-H3, among the immunotherapy targets that can be addressed in this model. The comparison with human GBMs unveiled crucial similarities with TMEMed GBM, the most frequent subtype.

Discovery and therapeutic exploitation of Master Regulatory miRNAs in Glioblastoma

Glioblastoma is a fatal primary malignant brain tumor. Despite therapies involving surgical resection, chemotherapy, and radiation therapy, the average survival for glioblastoma patients remains at approximately 15 months. MicroRNAs (miRNAs) are short noncoding RNA molecules that regulate the expression of the majority of human genes. Numerous genes are concurrently deregulated in glioblastoma. Consequently, molecular monotherapies have failed to achieve improvements in clinical outcomes. Several lines of evidence suggest that simultaneous targeting of several deregulated molecules is required to achieve better therapies. However, the simultaneous targeting of several deregulated oncogenic drivers is severely limited by the fact that the drugs needed to target many deregulated molecules do not currently exist, and because combining several drugs in a clinical setting leads to an exponential increase in toxicity. We hypothesized that we can develop and use miRNA to simultaneously inhibit multiple deregulated genes for more efficacious glioblastoma therapies. The goal of this study was therefore to identify master regulatory microRNAs (miRNAs) and use them to simultaneously target multiple deregulated molecules for GBM therapy. We defined master regulatory miRNAs as those that target several deregulated genes in glioblastoma. To find master regulatory miRNAs, we first used PAR-CLIP screenings to identify all targets of all miRNAs in glioblastoma cells. We then analyzed TCGA tumor data to determine which of these targets are deregulated in human tumors. We developed and used an algorithm to rank these targets for significance in glioblastoma malignancy based on their magnitude of deregulation, frequency of deregulation, and correlation with patient survival. We then ranked the miRNAs for their capacity of targeting multiple glioblastoma-deregulated genes and therefore the potential to exhibit strong anti-tumor effects when delivered as therapy. Using this strategy, we selected two tumor suppressor master regulatory miRNAs, miR-340, miR-382 and an oncogenic master regulatory miRNA, miR-17. We validated the target genes of the miRNAs and showed that they form part of important glioblastoma regulatory pathways. We then showed that the miRNAs (miR-340 and miR-582) or the miR-17 inhibitor have strong inhibitory effects on glioblastoma cell growth, survival, invasion, stemness and in vivo tumor growth. Ultimately, we developed and successfully tested a new therapeutic approach to delivery miR-340 using MRI guided focused ultrasound and microbubbles (FUS-MB) and special brain penetrating nanoparticles (BPN). This approach resulted in a substantial reduction in tumor volume and prolongation of the survival of glioblastoma-bearing mice and can be translated into clinical trials. We therefore developed and successfully tested a novel strategy to discover and deliver miRNAs for glioblastoma and cancer therapy.

Mapping the spatial architecture of glioblastoma from core to edge delineates niche-specific tumor cell states and intercellular interactions

Treatment resistance in glioblastoma (GBM) is largely driven by the extensive multi-level heterogeneity that typifies this disease. Despite significant progress toward elucidating GBM's genomic and transcriptional heterogeneity, a critical knowledge gap remains in defining this heterogeneity at the spatial level. To address this, we employed spatial transcriptomics to map the architecture of the GBM ecosystem. This revealed tumor cell states that are jointly defined by gene expression and spatial localization, and multicellular niches whose composition varies along the tumor core-edge axis. Ligand-receptor interaction analysis uncovered a complex network of intercellular communication, including niche- and region-specific interactions. Finally, we found that CD8 positive GZMK positive T cells colocalize with LYVE1 positive CD163 positive myeloid cells in vascular regions, suggesting a potential mechanism for immune evasion. These findings provide novel insights into the GBM tumor microenvironment, highlighting previously unrecognized patterns of spatial organization and intercellular interactions, and novel therapeutic avenues to disrupt tumor-promoting interactions and overcome immune resistance.

Unified molecular approach for spatial epigenome, transcriptome, and cell lineages

Spatial epigenomics and multiomics can provide fine-grained insights into cellular states but their widespread adoption is limited by the requirement for bespoke slides and capture chemistries for each data modality. Here, we present SPatial assay for Accessible chromatin, Cell lineages, and gene Expression with sequencing (SPACE-seq), a method that utilizes polyadenine-tailed epigenomic libraries to enable facile spatial multiomics using standard whole transcriptome reagents. Applying SPACE-seq to a human glioblastoma specimen, we reveal the state of the tumor microenvironment, extrachromosomal DNA copy numbers, and identify putative mitochondrial DNA variants.

Regulatory T Cell Mimicry by a Subset of Mesenchymal GBM Stem Cells Suppresses CD4 and CD8 Cells

Attempts to activate an anti-tumor immune response in glioblastoma (GBM) have been met with many challenges due to its inherently immunosuppressive tumor microenvironment. The degree and mechanisms by which molecularly and phenotypically diverse tumor-propagating glioma stem cells (GSCs) contribute to this state are poorly defined. In this study, our multifaceted approach combining bioinformatics analyses of clinical and experimental datasets, single-cell sequencing, and the molecular and pharmacologic manipulation of patient-derived cells identified GSCs expressing immunosuppressive effectors mimicking regulatory T cells (Tregs). We showed that this immunosuppressive Treg-like (ITL) GSC state is specific to the mesenchymal GSC subset and is associated with and driven specifically by TGFβ type II receptor (TGFBR2) in contrast to TGFBR1. Transgenic TGFBR2 expression in patient-derived GBM neurospheres promoted a mesenchymal transition and induced a six-gene ITL signature consisting of CD274 (PD-L1), NT5E (CD73), ENTPD1 (CD39), LGALS1 (galectin-1), PDCD1LG2 (PD-L2), and TGFB1. This TGFBR2-driven ITL signature was identified in clinical GBM specimens, patient-derived GSCs, and systemic mesenchymal malignancies. TGFBR2high GSCs inhibited CD4+ and CD8+ T cell viability and their capacity to kill GBM cells, effects reversed by pharmacologic and shRNA-based TGFBR2 inhibition. Collectively, our data identify an immunosuppressive GSC state that is TGFBR2-dependent and susceptible to TGFBR2-targeted therapeutics.

Emerging therapeutic strategies in glioblastsoma: drug repurposing, mechanisms of resistance, precision medicine, and technological innovations

Glioblastoma (GBM) is an aggressive Grade IV brain tumor with a poor prognosis. It results from genetic mutations, epigenetic changes, and factors within the tumor microenvironment (TME). Traditional treatments like surgery, radiotherapy, and chemotherapy provide limited survival benefits due to the tumor's heterogeneity and resistance mechanisms. This review examines novel approaches for treating GBM, focusing on repurposing existing medications such as antipsychotics, antidepressants, and statins for their potential anti-GBM effects. Advances in molecular profiling, including next-generation sequencing, artificial intelligence (AI), and nanotechnology-based drug delivery, are transforming GBM diagnosis and treatment. The TME, particularly GBM stem cells and immune evasion, plays a key role in therapeutic resistance. Integrating multi-omics data and applying precision medicine show promise, especially in combination therapies and immunotherapies, to enhance clinical outcomes. Addressing challenges such as drug resistance, targeting GBM stem cells, and crossing the blood-brain barrier is essential for improving treatment efficacy. While current treatments offer limited benefits, emerging strategies such as immunotherapies, precision medicine, and drug repurposing show significant potential. Technologies like liquid biopsies, AI-powered diagnostics, and nanotechnology could help overcome obstacles like the blood-brain barrier and GBM stem cells. Ongoing research into combination therapies, targeted drug delivery, and personalized treatments is crucial. Collaborative efforts and robust clinical trials are necessary to translate these innovations into effective therapies, offering hope for improved survival and quality of life for GBM patients.

A Spatial Multi-Omic Framework Identifies Gliomas Permissive to TIL Expansion

Tumor-infiltrating lymphocyte (TIL) therapy, recently approved by the FDA for melanoma, is an emerging modality for cell-based immunotherapy. However, its application in immunologically 'cold' tumors such as glioblastoma remains limited due to sparse T cell infiltration, antigenic heterogeneity, and a suppressive tumor microenvironment. To identify genomic and spatial determinants of TIL expandability, we performed integrated, multimodal profiling of high-grade gliomas using spectral flow cytometry, TCR sequencing, single-cell RNA-seq, Xenium in situ transcriptomics, and CODEX spatial proteomics. Comparative analysis of TIL-generating (TIL+) versus non-generating (TIL-) tumors revealed that IL7R expression, structured perivascular immune clustering, and tumor-intrinsic metabolic programs such as ACSS3 were associated with successful TIL expansion. In contrast, TIL-; tumors were enriched for neuronal lineage signatures, immunosuppressive transcripts including TOX and FERMT1, and tumor-connected macrophages. This study defines spatial and molecular correlates of TIL manufacturing success and establishes a genomics-enabled selection platform for adoptive T cell therapy. The profiling approach is now being prospectively implemented in the GIANT clinical trial ( NCT06816927 ), supporting its translational relevance and scalability across glioblastoma and other immune-excluded cancers.

From surfing to diving into the tumor microenvironment through multiparametric imaging mass cytometry

The tumor microenvironment (TME) is a complex ecosystem where malignant and non-malignant cells cooperate and interact determining cancer progression. Cell abundance, phenotype and localization within the TME vary over tumor development and in response to therapeutic interventions. Therefore, increasing our knowledge of the spatiotemporal changes in the tumor ecosystem architecture is of importance to better understand the etiologic development of the neoplastic diseases. Imaging Mass Cytometry (IMC) represents the elective multiplexed imaging technology enabling the in-situ analysis of up to 43 different protein markers for in-depth phenotypic and spatial investigation of cells in their preserved microenvironment. IMC is currently applied in cancer research to define the composition of the cellular landscape and to identify biomarkers of predictive and prognostic significance with relevance in mechanisms of drug resistance. Herein, we describe the general principles and experimental workflow of IMC raising the informative potential in preclinical and clinical cancer research.

Multimodal sequencing of neoadjuvant nivolumab treatment in hepatocellular carcinoma reveals cellular and molecular immune landscape for drug response

A striking characteristic of liver cancer is its extensive heterogeneity, particularly with regard to its varied response to immunotherapy. In this study, we employed multimodal sequencing approaches to explore the various aspects of neoadjuvant nivolumab treatment in liver cancer patients. We used spatially-resolved transcriptomics, single- and bulk-cell transcriptomics, and TCR clonotype analyses to examine the spatiotemporal dynamics of the effects of nivolumab. We observed a significantly higher clonal expansion of T cells in the tumors of patients who responded to the treatment, while lipid accumulation was detected in those of non-responders, likely due to inherent differences in lipid metabolic processes. Furthermore, we found a preferential enrichment of T cells, which was associated with a better drug response. Our results also indicate a functional antagonism between tumor-associated macrophages (TAMs) and CD8 cells and their spatial separation. Notably, we identified a UBASH3B/NR1I2/CEACAM1/HAVCR2 signaling axis, highlighting the intense communication among TAMs, tumor cells, and T-cells that leads to pro-tumorigenic outcomes resulting in poorer nivolumab response. In summary, using integrative multimodal sequencing investigations, combined with the multi-faceted exploration of pre- and post-treatment samples of neoadjuvant nivolumab-treated HCC patients, we identified useful mechanistic determinants of therapeutic response. We also reconstructed the spatiotemporal model that recapitulates the physiological restoration of T cell cytotoxicity by anti-PD1 blockade. Our findings could provide important biomarkers and explain the mechanistic basis differentiating the responders and non-responders.

Multi-omic landscape of human gliomas from diagnosis to treatment and recurrence

Gliomas are among the most lethal cancers, with limited treatment options. To uncover hallmarks of therapeutic escape and tumor microenvironment (TME) evolution, we applied spatial proteomics, transcriptomics, and glycomics to 670 lesions from 310 adult and pediatric patients. Single-cell analysis shows high B7H3+ tumor cell prevalence in glioblastoma (GBM) and pleomorphic xanthoastrocytoma (PXA), while most gliomas, including pediatric cases, express targetable tumor antigens in less than 50% of tumor cells, potentially explaining trial failures. Longitudinal samples of isocitrate dehydrogenase (IDH)-mutant gliomas reveal recurrence driven by tumor-immune spatial reorganization, shifting from T-cell and vasculature-associated myeloid cell-enriched niches to microglia and CD206+ macrophage-dominated tumors. Multi-omic integration identified N-glycosylation as the best classifier of grade, while the immune transcriptome best predicted GBM survival. Provided as a community resource, this study opens new avenues for glioma targeting, classification, outcome prediction, and a baseline of TME composition across all stages.

Radiomic Profiling of Orthotopic Mouse Models of Glioblastoma Reveals Histopathological Correlations Associated with Tumour Response to Ionising Radiation

BACKGROUND

Glioblastoma (GB) is a particularly malignant brain tumour which carries a poor prognosis and presents limited treatment options. MRI is standard practice for differential diagnosis at initial presentation of GB and can assist in both treatment planning and response assessment. MRI radiomics allows for discerning GB features of clinical importance that are not evident by visual analysis, augmenting the morphological and functional tumour characterisation beyond traditional imaging techniques. Given that radiotherapy is part of the standard of care for GB patients, establishing a platform for phenotyping radiation treatment responses using non-invasive methods is of high relevance.

METHODS

In this study, we modelled the responses to ionising radiation across four orthotopic mouse models of GB using diffusion and perfusion radiomics. We have identified the optimal set of radiomic features that reflect tumour cellularity, microvascularity, and blood flow changes brought about by radiation treatment in these murine orthotopic models of GB, and directly compared them with endpoint histopathological analysis.

RESULTS

We showed that the selected radiomic features can quantify textural information and pixel interrelationships of tumour response to radiation therapy, revealing subtle image patterns that may reflect intra-tumoural spatial heterogeneity. When compared to GB patients, similarities in selected radiomic features were noted between orthotopic murine tumours and non-enhancing central tumour areas in patients, along with several discrepancies in tumour cellularity and vascularization, denoted by distinct grey level intensities and nonuniformity metrics.

CONCLUSION

As the field evolves, radiomic profiling of GB may enhance the evaluation of targeted therapeutic strategies, accelerate the development of new therapies, and act as a potential virtual biopsy tool.

Single-cell and spatial transcriptomic insights into glioma cellular heterogeneity and metabolic adaptations

Glioblastoma, one of the most aggressive and heterogeneous malignant tumors, presents significant challenges for clinical management due to its cellular and metabolic complexity. This review integrates recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to elucidate glioblastoma's cellular heterogeneity and metabolic reprogramming. Diverse cellular subpopulations, including malignant proliferative cells, stem-like cells, mesenchymal-like cells, and immune-related cells, contribute to tumor progression, treatment resistance, and microenvironmental interactions. Spatial transcriptomics has further revealed distinct spatial distributions of these subpopulations, highlighting differences in metabolic activities between the tumor core and periphery. Key metabolic adaptations, such as enhanced glycolysis, fatty acid oxidation, and glutamine metabolism, play critical roles in supporting tumor growth, immune evasion, and therapeutic resistance. Targeting these metabolic pathways, especially in combination with immunotherapy, represents a promising avenue for glioblastoma treatment. This review emphasizes the importance of integrating single-cell and spatial multi-omics technologies to decode glioblastoma's metabolic landscape and explore novel therapeutic strategies. By addressing current challenges, such as metabolic redundancy and spatiotemporal dynamics, this work provides insights into advancing precision medicine for glioblastoma.

Spatial transcriptomics of the aging mouse brain reveals origins of inflammation in the white matter

To systematically understand age-induced molecular changes, we performed spatial transcriptomics of young, middle-aged, and old mouse brains and identified seven transcriptionally distinct regions. All regions exhibited age-associated upregulation of inflammatory mRNAs and downregulation of mRNAs related to synaptic function. Notably, aging white matter fiber tracts showed the most prominent changes with pronounced effects in females. The inflammatory signatures indicated major ongoing events: microglia activation, astrogliosis, complement activation, and myeloid cell infiltration. Immunofluorescence and quantitative MRI analyses confirmed physical interaction of activated microglia with fiber tracts and concomitant reduction of myelin in old mice. In silico analyses identified potential transcription factors influencing these changes. Our study provides a resourceful dataset of spatially resolved transcriptomic features in the naturally aging murine brain encompassing three age groups and both sexes. The results link previous disjointed findings and provide a comprehensive overview of brain aging identifying fiber tracts as a focal point of inflammation.

Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy

Tumor organoids are important tools for cancer research, but current models have drawbacks that limit their applications for predicting response to therapy. Here, we developed a fast, efficient, and complex culture system (IPTO, individualized patient tumor organoid) that accurately recapitulates the cellular and molecular pathology of human brain tumors. Patient-derived tumor explants were cultured in induced pluripotent stem cell (iPSC)-derived cerebral organoids, thus enabling culture of a wide range of human tumors in the central nervous system (CNS), including adult, pediatric, and metastatic brain cancers. Histopathological, genomic, epigenomic, and single-cell RNA sequencing (scRNA-seq) analyses demonstrated that the IPTO model recapitulates cellular heterogeneity and molecular features of original tumors. Crucially, we showed that the IPTO model predicts patient-specific drug responses, including resistance mechanisms, in a prospective patient cohort. Collectively, the IPTO model represents a major breakthrough in preclinical modeling of human cancers, which provides a path toward personalized cancer therapy.

Single-Cell Profiling and Proteomics-Based Insights Into mTORC1-Mediated Angio+TAMs Polarization in Recurrent IDH-Mutant Gliomas

BACKGROUND

IDH mutant gliomas often exhibit recurrence and progression, with the mTORC1 pathway and tumor-associated macrophages potentially contributing to these processes. However, the precise mechanisms are not fully understood. This study seeks to investigate these relationships using proteomic, phosphoproteomic, and multi-dimensional transcriptomic approaches.

METHODS

This study established a matched transcriptomic, proteomic, and phosphoproteomic cohort of IDH-mutant gliomas with recurrence and progression, incorporating multiple glioma-related datasets. We first identified the genomic landscape of recurrent IDH-mutant gliomas through multi-dimensional differential enrichment, GSVA, and deconvolution analyses. Next, we explored tumor-associated macrophage subpopulations using single-cell sequencing in mouse models of IDH-mutant and wild-type gliomas, analyzing transcriptional changes via AddmodelScore and pseudotime analysis. We then identified these subpopulations in matched primary and recurrent IDH-mutant datasets, investigating their interactions with the tumor microenvironment and performing deconvolution to explore their contribution to glioma progression. Finally, spatial transcriptomics was used to map these subpopulations to glioma tissue sections, revealing spatial co-localization with mTORC1 and angiogenesis-related pathways.

RESULTS

Multi-dimensional differential enrichment, GSVA, and deconvolution analyses indicated that the mTORC1 pathway and the proportion of M2 macrophages are upregulated during the recurrence and progression of IDH-mutant gliomas. CGGA database analysis showed that mTORC1 activity is significantly higher in recurrent IDH-mutant gliomas compared to IDH-wildtype, with a correlation to M2 macrophage infiltration. KSEA revealed that AURKA is enriched during progression, and its inhibition reduces mTORC1 pathway activity. Single-cell sequencing in mouse models identified a distinct glioma subpopulation with upregulated mTORC1, exhibiting both M2 macrophage and angiogenesis transcriptional features, which increased after implantation of IDH-mutant tumor cells. Similarly, human glioma single-cell data revealed the same subpopulation, with cell-cell communication analysis showing active VEGF signaling. Finally, spatial transcriptomics deconvolution confirmed the co-localization of this subpopulation with mTORC1 and VEGFA in high-grade IDH-mutant gliomas.

CONCLUSIONS

Our findings suggest mTORC1 activation and Angio-TAMs play key roles in the recurrence and progression of IDH-mutant gliomas.

Spatially resolved transcriptomic analysis of the adult human prostate

The prostate is an organ characterized by significant spatial heterogeneity. To better understand its intricate structure and cellular composition, we constructed a comprehensive single-cell atlas of the adult human prostate. Our high-resolution mapping effort identified 253,381 single cells and 34,876 nuclei sampled from 11 patients who underwent radical resection of bladder cancer, which were categorized into 126 unique subpopulations. This work revealed various new cell types in the human prostate and their specific spatial localization. Notably, we discovered four distinct acini, two of which were tightly associated with E-twenty-six transcription factor family (ETS)-fusion-negative prostate cancer. Through the integration of spatial, single-cell and bulk-seq analyses, we propose that two specific luminal cell types could serve as the common origins of prostate cancer. Additionally, our findings suggest that zone-specific fibroblasts may contribute to the observed heterogeneity among luminal cells. This atlas will serve as a valuable reference for studying prostate biology and diseases such as prostate cancer.

Resilience in adversity: Exploring adaptive changes in cancer cells under stress

OBJECTIVE

Cancer cells undergo adaptive processes that favor their survival and proliferation when subjected to different types of cellular stress. These changes are linked to oncogenic processes such as genetic instability, tumor proliferation, therapy resistance, and invasion. Therefore, this study aimed to review studies that discuss possible morphological and genetic changes acquired by neoplastic cells under stressful conditions.

METHODS

The articles used in this integrative review were searched on PubMed, Web of Science, CAPES, BVS and Scopus. Studies that discussed how cells undergo morphogenetic changes as an adaptive response to stress in cancer were included.

RESULTS

This article reviewed 82 studies that highlighted multiple types of stress to which cancer can be subjected, such as oxidative, thermal and mechanical stress; glucose and other nutrients deficiency; hypoxia and chemotherapy. Neoplastic cells under stress can undergo adaptive changes that make it possible to overcome this obstacle. In this adaptive process, the acquisition of certain mutations implies cellular morphological changes such as Epithelial-Mesenchymal Transition, polyploidy, mitochondrial and cytoskeletal changes. These adaptive changes occur concomitantly with processes related to oncogenesis such as gene instability, tumor proliferation, resistance to therapy and invasion.

CONCLUSIONS

This study reveals that adaptations to cellular stress promote morphological and functional changes that accompany or accelerate oncogenesis. It has been revised how epithelial-mesenchymal transition, polyploidy and mitochondrial dysfunctions not only reinforce the survival of tumor cells in adverse environments, but also increase therapeutic resistance and invasive capacity. Also noteworthy are the contributions on genomic instability associated with stress and the potential of senescent cells in tumor heterogeneity, both as factors of tumor resistance and progression. These insights suggest new therapeutic targets and prognostic biomarkers, expanding the possibilities for more effective strategies to combat cancer.

Programs, origins and immunomodulatory functions of myeloid cells in glioma

Gliomas are incurable malignancies notable for having an immunosuppressive microenvironment with abundant myeloid cells, the immunomodulatory phenotypes of which remain poorly defined1. Here we systematically investigate these phenotypes by integrating single-cell RNA sequencing, chromatin accessibility, spatial transcriptomics and glioma organoid explant systems. We discovered four immunomodulatory expression programs: microglial inflammatory and scavenger immunosuppressive programs, which are both unique to primary brain tumours, and systemic inflammatory and complement immunosuppressive programs, which are also expressed by non-brain tumours. The programs are not contingent on myeloid cell type, developmental origin or tumour mutational state, but instead are driven by microenvironmental cues, including tumour hypoxia, interleukin-1β, TGFβ and standard-of-care dexamethasone treatment. Their relative expression can predict immunotherapy response and overall survival. By associating the respective programs with mediating genomic elements, transcription factors and signalling pathways, we uncover strategies for manipulating myeloid-cell phenotypes. Our study provides a framework to understand immunomodulation by myeloid cells in glioma and a foundation for the development of more-effective immunotherapies.

Overcoming immunotherapy resistance in glioblastoma: challenges and emerging strategies

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults, characterized by rapid proliferation, extensive infiltration, and significant intratumoral heterogeneity. Despite advancements in conventional treatments, including surgery, radiotherapy, and chemotherapy, the prognosis for GBM patients remains poor, with a median survival of approximately 15 months. Immunotherapy has emerged as a promising alternative; however, the unique biological and immunological features, including its immunosuppressive tumor microenvironment (TME) and low mutational burden, render it resistant to many immunotherapeutic strategies. This review explores the key challenges in GBM immunotherapy, focusing on immune evasion mechanisms, the blood-brain barrier (BBB), and the TME. Immune checkpoint inhibitors and CAR-T cells have shown promise in preclinical models but have limited clinical success due to antigen heterogeneity, immune cell exhaustion, and impaired trafficking across the BBB. Emerging strategies, including dual-targeting CAR-T cells, engineered immune cells secreting therapeutic molecules, and advanced delivery systems to overcome the BBB, show potential for enhancing treatment efficacy. Addressing these challenges is crucial for improving GBM immunotherapy outcomes.

Combined targeting of glioblastoma stem cells of different cellular states disrupts malignant progression

Glioblastoma (GBM) is the most lethal primary brain tumor with intra-tumoral hierarchy of glioblastoma stem cells (GSCs). The heterogeneity of GSCs within GBM inevitably leads to treatment resistance and tumor recurrence. Molecular mechanisms of different cellular state GSCs remain unclear. Here, we find that classical (CL) and mesenchymal (MES) GSCs are enriched in reactive immune region and high CL-MES signature informs poor prognosis in GBM. Through integrated analyses of GSCs RNA sequencing and single-cell RNA sequencing datasets, we identify specific GSCs targets, including MEOX2 for the CL GSCs and SRGN for the MES GSCs. MEOX2-NOTCH and SRGN-NFκB axes play important roles in promoting proliferation and maintaining stemness and subtype signatures of CL and MES GSCs, respectively. In the tumor microenvironment, MEOX2 and SRGN mediate the resistance of CL and MES GSCs to macrophage phagocytosis. Using genetic and pharmacologic approaches, we identify FDA-approved drugs targeting MEOX2 and SRGN. Combined CL and MES GSCs targeting demonstrates enhanced efficacy, both in vitro and in vivo. Our results highlighted a therapeutic strategy for the elimination of heterogeneous GSCs populations through combinatorial targeting of MEOX2 and SRGN in GSCs.

Interfacing with the Brain: How Nanotechnology Can Contribute

Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain-machine interfaces have changed over time, along with the available technology. Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another. Nanotechnology, which encompasses engineered solid-state objects and integrated circuits, excels at small length scales of single to a few hundred nanometers and, thus, matches the sizes of biomolecules, biomolecular assemblies, and parts of cells. Consequently, we envision nanomaterials and nanotools as opportunities to interface with the brain in alternative ways. Here, we review the existing literature on the use of nanotechnology in brain-machine interfaces and look forward in discussing perspectives and limitations based on the authors' expertise across a range of complementary disciplines─from neuroscience, engineering, physics, and chemistry to biology and medicine, computer science and mathematics, and social science and jurisprudence. We focus on nanotechnology but also include information from related fields when useful and complementary.

AMP-activated protein kinase mediates adaptation of glioblastoma cells to conditions of the tumor microenvironment

AMP-activated protein kinase (AMPK) is an energy sensor that regulates cellular metabolic activity. We hypothesized that in glioblastoma (GB), AMPK plays a pivotal role in balancing metabolism under conditions of the tumor microenvironment with fluctuating and often low nutrient and oxygen availability. Impairment of this network could thus interfere with tumor progression. AMPK activity was modulated genetically by CRISPR/Cas9-based double knockout (DKO) of the catalytic α1 and α2 subunits in human GB cells and effects were confirmed by pharmacological AMPK inhibition using BAY3827 and an inactive control compound in primary GB cell cultures. We found that metabolic adaptation of GB cells under energy stress conditions (hypoxia, glucose deprivation) was dependent on AMPK and accordingly that AMPK DKO cells were more vulnerable to glucose deprivation or inhibition of glycolysis and sensitized to hypoxia-induced cell death. This effect was rescued by reexpression of the AMPK α2 subunit. Similar results were observed using the selective pharmacological AMPK inhibitor BAY3827. Mitochondrial biogenesis was regulated AMPK-dependently with a reduced mitochondrial mass and mitochondrial membrane potential in AMPK DKO GB cells. In vivo, AMPK DKO GB cells showed impaired tumor growth and tumor formation in CAM assays as well as in an orthotopic glioma mouse model. Our study highlights the importance of AMPK for GB cell adaptation towards energy depletion and emphasizes the role of AMPK for tumor formation in vivo. Moreover, we identified mitochondria as central downstream effectors of AMPK signaling. The development of AMPK inhibitors could open opportunities for the treatment of hypoxic tumors.

Advances in Spatial Omics Technologies

Rapidly developing spatial omics technologies provide us with new approaches to deeply understanding the diversity and functions of cell types within organisms. Unlike traditional approaches, spatial omics technologies enable researchers to dissect the complex relationships between tissue structure and function at the cellular or even subcellular level. The application of spatial omics technologies provides new perspectives on key biological processes such as nervous system development, organ development, and tumor microenvironment. This review focuses on the advancements and strategies of spatial omics technologies, summarizes their applications in biomedical research, and highlights the power of spatial omics technologies in advancing the understanding of life sciences related to development and disease.

Extracellular Vesicles Carrying Tenascin-C are Clinical Biomarkers and Improve Tumor-Derived DNA Analysis in Glioblastoma Patients

Extracellular vesicles (EVs) act as carriers of biological information from tumors to the bloodstream, enabling the detection of circulating tumor material and tracking of disease progression. This is particularly crucial in glioblastoma, a highly aggressive and heterogeneous tumor that is challenging to monitor. Using imaging flow cytometry (IFCM), we conducted an immunophenotyping analysis of eight glioma-associated antigens and tetraspanins in plasma EVs from 37 newly diagnosed glioblastoma patients (pre- and post-surgery), 11 matched individuals with recurrent glioblastoma, and 22 healthy donors (HD). Tenascin-C (TNC) positive EVs displayed the strongest differences in newly diagnosed and recurrent glioblastoma patients, when compared to non-tumor subjects. Among dual-positive subpopulations, TNC+/CD9+ EVs were the most elevated in newly diagnosed (FC = 7.6, p <0.0001, AUC = 81%) and recurrent patients (FC = 16.5, p <0.0001; AUC = 90%) than HD. In comparison with other CNS tumors (n = 25), this subpopulation was also 34.5-fold higher in glioblastoma than in meningioma cases (p <0.01). Additionally, TNC+/CD9+ EV levels were 3.3-fold elevated in cerebrospinal fluid from glioblastoma patients (n = 6) than controls (p <0.05). Aberrant TNC levels were further observed in glioblastoma EVs from different sources and purified via different methods. Immunohistochemical analysis revealed high levels of TNC in tumor tissues. Spatial transcriptomic analysis indicated a TNC overexpression in malignant cell populations of glioblastoma resections, particularly in cells with mesenchymal-like signatures and chromosomal aberrations. Lastly, we purified TNC+ EVs from plasma of 21 glioblastoma patients by magnetic sorting and detected the oncogenic mutation TERT*C228T by droplet digital PCR. The mutant allele frequency was higher in TNC+ EVs vs TNC-negative EVs (FC = 32, p <0.001), total EVs (FC = 5.3, p <0.001) or cell-free DNA (FC = 5.3, p <0.01). In conclusion, circulating TNC+ EVs may have potential as clinical biomarkers in glioblastoma, and their purification could improve the identification of tumor-specific mutations in liquid biopsies.

Response to anti-angiogenic therapy is affected by AIMP protein family activity in glioblastoma and lower-grade gliomas

Background

Glioblastoma (GBM) is a highly vascularized, heterogeneous tumor, yet anti-angiogenic therapies have yielded limited survival benefits. The lack of validated predictive biomarkers for treatment response stratification remains a major challenge. Aminoacyl tRNA synthetase complex-interacting multicomplex proteins (AIMPs) 1/2/3 have been implicated in CNS diseases, but their roles in gliomas remain unexplored. We investigated their association with angiogenesis and their significance as predictive biomarkers for anti-angiogenic treatment response.

Methods

In this multi-cohort retrospective study we analyzed glioma samples from TCGA, CGGA, Rembrandt, Gravendeel, BELOB and REGOMA trials, and four single-cell transcriptomic datasets. Multi-omic analyses incorporated transcriptomic, epigenetic, and proteomic data. Kaplan-Meier and Cox proportional hazards models were used to assess the prognostic value of AIMPs in heterogeneous and homogeneous treatment-groups. Using single-cell transcriptomics, we explored spatial and cell-type-specific AIMP2 expression in GBM.

Results

AIMP1/2/3 expressions correlated significantly with angiogenesis across TCGA cancers. In gliomas, AIMPs were upregulated in tumor vs. normal tissues, higher- vs. lower-grade gliomas, and recurrent vs. primary tumors (p<0.05). Upon retrospective analysis of two clinical trials assessing different anti-angiogenic drugs, we found that high-AIMP2 subgroups had improved response to therapies in GBM (REGOMA: HR 4.75 [1.96-11.5], p<0.001; BELOB: HR 2.3 [1.17-4.49], p=0.015). AIMP2-cg04317940 methylation emerged as a clinically applicable stratification marker. Single-cell analysis revealed homogeneous AIMP2 expression in tumor tissues, particularly in AC-like cells, suggesting a mechanistic link to tumor angiogenesis.

Conclusions

These findings provide novel insights into the role of AIMPs in angiogenesis, offering improved patient stratification and therapeutic outcomes in recurrent GBM.

Blocking ITGA5 potentiates the efficacy of anti-PD-1 therapy on glioblastoma by remodeling tumor-associated macrophages

BACKGROUND

Glioblastoma (GBM) is largely refractory to antibodies against programmed cell death 1 (anti-PD-1) therapy. Fully understanding the cellular heterogeneity and immune adaptations in response to anti-PD-1 therapy is necessary to design more effective immunotherapies for GBM. This study aimed to dissect the molecular mechanisms of specific immunosuppressive subpopulations to drive anti-PD-1 resistance in GBM.

METHODS

We systematically analysed single-cell RNA sequencing and spatial transcriptomics data from GBM tissues receiving anti-PD-1 therapy to characterize the microenvironment alterations. The biological functions of a novel circular RNA (circRNA) were validated both in vitro and in vivo. Mechanically, co-immunoprecipitation, RNA immunoprecipitation and pull-down assays were conducted.

RESULTS

Mesenchymal GBM (MES-GBM) cells, which were associated with a poor prognosis, and secreted phosphoprotein 1 (SPP1)+ myeloid-derived macrophages (SPP1+ MDMs), a unique subpopulation of MDMs with complex functions, preferentially accumulated in non-responders to anti-PD-1 therapy, indicating that MES-GBM cells and SPP1+ MDMs were the main anti-PD-1-resistant cell subpopulations. Functionally, we determined that circular RNA succinate dehydrogenase complex assembly factor 2 (circSDHAF2), which was positively associated with the abundance of these two anti-PD-1-resistant cell subpopulations, facilitated the formation of a regional MES-GBM and SPP1+ MDM cell interaction loop, resulting in a spatially specific adaptive immunosuppressive microenvironment. Mechanically, we found that circSDHAF2 promoted MES-GBM cell formation by stabilizing the integrin alpha 5 (ITGA5) protein through N-glycosylation. Meanwhile, the N-glycosylation of the ITGA5 protein facilitated its translocation into exosomes and subsequent delivery to MDMs to induce the formation of SPP1+ MDMs, which in turn maintained the MES-GBM cell status and induced T-cell dysfunction via the SPP1-ITGA5 pathway, ultimately promoting GBM immune escape. Importantly, our findings demonstrated that antibody-mediated ITGA5 blockade enhanced anti-PD-1-mediated antitumor immunity.

CONCLUSIONS

This work elucidated the potential tissue adaptation mechanism of intratumoral dynamic interactions between MES-GBM cells, MDMs and T cells in anti-PD-1 non-responders and identified the therapeutic potential of targeting ITGA5 to reduce anti-PD-1 resistance in GBM.

Targeting CHEK2-YBX1&YBX3 regulatory hub to potentiate immune checkpoint blockade response in gliomas

Although GBM's immunosuppressive environment is well known, the tumor's resistance to CD8+ T cell killing is not fully understood. Our previous study identified Checkpoint Kinase 2 (Chek2) as the key driver of CD8+ T cell resistance in mouse glioma through an in vivo CRISPR screen and demonstrated that Chk2 inhibition, combined with PD-1/PD-L1 blockade, significantly enhanced CD8+ T cell-mediated tumor killing and improved survival in preclinical model. Here, we aimed to elucidate the immunosuppressive function of Chek2. Immunoprecipitation (IP) followed by mass spectrometry (MS) and phosphoproteomics identified an association between Chek2 with the DNA/RNA-binding proteins YBX1 and YBX3 that are implicated in transcriptional repression of pro-inflammatory genes. Single-gene knock-out and overexpression studies of CHEK2, YBX1, and YBX3 in multiple glioma cell lines revealed that these proteins positively regulate each other's expression. RNA sequencing coupled with chromatin immunoprecipitation-sequencing (ChIP-seq) analysis demonstrated common inflammatory genes repressed by CHK2-YBX1&YBX3 hub. Targeting one of the hub proteins, YBX1, with the YBX1 inhibitor SU056 led to degradation of CHK2-YBX1&YBX3 hub. Targeting of this hub by SU056 led to enhanced antigen presentation and antigen specific CD8+ T cell proliferation. Further, combination of SU056 with ICB significantly improved survival in multiple glioma models. Collectively, these findings reveal an immunosuppressive mechanism mediated by the CHK2-YBX1&YBX3 hub proteins. Therefore, CHK2-YBX1&YBX3 hub targeting in combination with immune checkpoint blockade therapies in gliomas is warranted.

Tumor cell villages define the co-dependency of tumor and microenvironment in liver cancer

Spatial cellular context is crucial in shaping intratumor heterogeneity. However, understanding how each tumor establishes its unique spatial landscape and what factors drive the landscape for tumor fitness remains significantly challenging. Here, we analyzed over 2 million cells from 50 tumor biospecimens using spatial single-cell imaging and single-cell RNA sequencing. We developed a deep learning-based strategy to spatially map tumor cell states and the architecture surrounding them, which we referred to as Spatial Dynamics Network (SDN). We found that different tumor cell states may be organized into distinct clusters, or 'villages', each supported by unique SDNs. Notably, tumor cell villages exhibited village-specific molecular co-dependencies between tumor cells and their microenvironment and were associated with patient outcomes. Perturbation of molecular co-dependencies via random spatial shuffling of the microenvironment resulted in destabilization of the corresponding villages. This study provides new insights into understanding tumor spatial landscape and its impact on tumor aggressiveness.

Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments

The tumor microenvironment (TME) plays a crucial role in orchestrating tumor cell behavior and cancer progression. Recent advances in spatial profiling technologies have uncovered novel spatial signatures, including univariate distribution patterns, bivariate spatial relationships, and higher-order structures. These signatures have the potential to revolutionize tumor mechanism and treatment. In this review, we summarize the current state of spatial signature research, highlighting computational methods to uncover spatially relevant biological significance. We discuss the impact of these advances on fundamental cancer biology and translational research, address current challenges and future research directions.

TMED9: a potential therapeutic target and prognostic marker in glioma and its implications across pan-cancer contexts

Background

The escalating global cancer burden, projected to reach 35 million new cases by 2050, underscores the urgent need for innovative cancer biomarkers to improve treatment efficacy and patient outcomes. The TMED family, particularly TMED9, has garnered attention for its involvement in cancer progression; however, its comprehensive role across various cancer types remains poorly understood.

Methods

Utilizing multi-omics data, we analyzed the expression pattern, prognostic significance, genomic alterations, and immunological features of TMED9 in various cancer types. Through in vitro experiments, we paid special attention to its role in glioma, especially its correlation with glioma cell migration and invasion behavior.

Results

Our findings reveal that TMED9 is significantly overexpressed in various tumor tissues and is associated with poor prognosis in cancers such as glioblastoma and lower-grade gliomas. Genetic analysis shows TMED9 mutations predominantly in kidney renal clear cell carcinoma, with its expression linked to chromosomal instability. Immunological analysis indicates that TMED9 correlates positively with immune cell infiltration, particularly macrophages, suggesting its role in promoting tumor immunity. Furthermore, TMED9 expression was negatively correlated with tumor stemness, indicating its potential influence on chemotherapy resistance. Knockdown of TMED9 led to reduced migration and invasion in glioma cell lines.

Conclusions

Our comprehensive analysis positions TMED9 as a critical player in cancer progression and immune modulation, especially in gliomas. Elevated TMED9 expression correlates with poorer outcomes and may serve as a prognostic marker and therapeutic target. Future research should focus on elucidating TMED9's mechanistic pathways and validating its role in clinical settings to enhance glioma treatment strategies.

Harnessing transcriptional regulation of alternative end-joining to predict cancer treatment

Alternative end-joining (alt-EJ) is an error-prone DNA repair pathway that cancer cells deficient in homologous recombination rely on, making them vulnerable to synthetic lethality via inhibition of poly(ADP-ribose) polymerase (PARP). Targeting alt-EJ effector DNA polymerase theta (POLθ), which synergizes with PARP inhibitors and can overcome resistance, is of significant preclinical and clinical interest. However, the transcriptional regulation of alt-EJ and its interactions with processes driving cancer progression remain poorly understood. Here, we show that alt-EJ is suppressed by hypoxia while positively associated with MYC (myelocytomatosis oncogene) transcriptional activity. Hypoxia reduces PARP1 and POLQ expression, decreases MYC binding at their promoters, and lowers PARylation and alt-EJ-mediated DNA repair in cancer cells. Tumors with HIF1A mutations overexpress the alt-EJ gene signature. Inhibition of hypoxia-inducible factor 1α or HIF1A expression depletion, combined with PARP or POLθ inhibition, synergistically reduces the colony-forming capacity of cancer cells. Deep learning reveals the anticorrelation between alt-EJ and hypoxia across regions in tumor images, and the predictions for these and MYC activity achieve area under the curve values between 0.70 and 0.86. These findings further highlight the critical role of hypoxia in modulating DNA repair and present a strategy for predicting and improving outcomes centered on targeting alt-EJ.

Brain tumour histopathology through the lens of deep learning: A systematic review

PROBLEM

Machine learning (ML)/Deep learning (DL) techniques have been evolving to solve more complex diseases, but it has been used relatively little in Glioblastoma (GBM) histopathological studies, which could benefit greatly due to the disease's complex pathogenesis.

AIM

Conduct a systematic review to investigate how ML/DL techniques have influenced the progression of brain tumour histopathological research, particularly in GBM.

METHODS

54 eligible studies were collected from the PubMed and ScienceDirect databases, and their information about the types of brain tumour/s used, types of -omics data used with histopathological data, origins of the data, types of ML/DL and its training and evaluation methodologies, and the ML/DL task it was set to perform in the study were extracted to inform us of trends in GBM-related ML/DL-based research.

RESULTS

Only 8 GBM-related studies in the eligible utilised ML/DL methodologies to gain deeper insights into GBM pathogenesis by contextualising histological data with -omics data. However, we report that these studies have been published more recently. The most popular ML/DL models used in GBM-related research are the SVM classifier and ResNet-based CNN architecture. Still, a considerable number of studies failed to state training and evaluative methodologies clearly.

CONCLUSION

There is a growing trend towards using ML/DL approaches to uncover relationships between biological and histopathological data to bring new insights into GBM, thus pushing GBM research forward. Much work still needs to be done to properly report the ML/DL methodologies to showcase the models' robustness and generalizability and ensure the models are reproducible.

Spatial omics shed light on the tumour organisation of glioblastoma

The glioblastoma tumour microenvironment is characterised by immense heterogeneity, with malignant and non-malignant cells that interact in a complex ecosystem. Emerging evidence suggests that the tumour microenvironment is key in facilitating rapid proliferation, invasion, migration and cancer cell survival, crucial for treatment resistance. Spatial omics technologies have enabled the molecular characterisation of regions or individual cells within their spatial context, providing previously unattainable insights into the complex organisation of the glioblastoma tumour microenvironment. Understanding this organisation is crucial for the development of new therapeutics and novel diagnostic tools that guide patient care. This review explores spatial omics technologies and how they have contributed to the development of a model outlining the architecture of the glioblastoma tumour microenvironment.

Modulation of blood-tumor barrier transcriptional programs improves intratumoral drug delivery and potentiates chemotherapy in GBM

Efficient drug delivery to glioblastoma (GBM) is a major obstacle as the blood-brain barrier (BBB) and the blood-tumor barrier (BTB) prevent passage of the majority of chemotherapies into the brain. Here, we identified a transcriptional 12-gene signature associated with the BTB in GBM. We identified CDH5 as a core molecule in this set and confirmed its expression in GBM vasculature using transcriptomics and immunostaining of patient specimens. The indirubin-derivative, 6-bromoindirubin acetoxime (BIA), down-regulates CDH5 and other BTB signature genes, causing endothelial barrier disruption in vitro and in murine GBM xenograft models. Treatment with BIA increased intratumoral cisplatin accumulation and potentiated DNA damage by targeting DNA repair pathways. Last, using an injectable BIA nanoparticle formulation, PPRX-1701, we significantly improved cisplatin efficacy in murine GBM. Our work reveals potential targets of the BTB and the bifunctional properties of BIA as a BTB modulator and a potentiator of chemotherapy, supporting its further development.

The spatial landscape of cancer hallmarks reveals patterns of tumor ecological dynamics and drug sensitivity

Tumors are complex ecosystems of interacting cell types. The concept of cancer hallmarks distills this complexity into underlying principles that govern tumor growth. Here, we explore the spatial distribution of cancer hallmarks across 63 primary untreated tumors from 10 cancer types using spatial transcriptomics. We show that hallmark activity is spatially organized, with the cancer compartment contributing to the activity of seven out of 13 hallmarks, while the tumor microenvironment (TME) contributes to the activity of the rest. Additionally, we discover that genomic distance between tumor subclones correlates with differences in hallmark activity, even leading to clone-hallmark specialization. Finally, we demonstrate interdependent relationships between hallmarks at the junctions of TME and cancer compartments and how they relate to sensitivity to different neoadjuvant treatments in 33 bladder cancer patients from the DUTRENEO trial. In conclusion, our findings may improve our understanding of tumor ecology and help identify new drug biomarkers.