Single-Cell RNA-Seq Analysis of Infiltrating Neoplastic Cells at the Migrating Front of Human Glioblastoma. Cell Rep. 2017;21:1399-1410. [PMID: 29091775 DOI: 10.1016/j.celrep.2017.10.030]

A dynamic and multimodal framework to define microglial states

The widespread use of single-cell RNA sequencing has generated numerous purportedly distinct and novel subsets of microglia. Here, we challenge this fragmented paradigm by proposing that microglia exist along a continuum rather than as discrete entities. We identify a methodological over-reliance on computational clustering algorithms as the fundamental issue, with arbitrary cluster numbers being interpreted as biological reality. Evidence suggests that the observed transcriptional diversity stems from a combination of microglial plasticity and technical noise, resulting in terminology describing largely overlapping cellular states. We introduce a continuous model of microglial states, where cell positioning along the continuum is determined by biological aging and cell-specific molecular contexts. The model accommodates the dynamic nature of microglia. We advocate for a parsimonious approach toward classification and terminology that acknowledges the continuous spectrum of microglial states, toward a robust framework for understanding these essential immune cells of the CNS.

Therapeutic and prognostic values of ferroptosis signature in glioblastoma

Ferroptosis is a regulated cell death process that results in decreased tumor growth and aggressiveness when targeted in various cancer cells. Studying the impact of ferroptosis in glioblastoma (GBM) will provide important knowledge about tumor biology and potential treatment strategies. The high metabolic activity resulting in ROS production, iron content and active lipid metabolism of glioblastoma cells make them particularly susceptible to ferroptosis. Single-cell RNA sequencing reveals the molecular signature of GBM and its tumor microenvironment, introducing ferroptosis-related biomarkers pathways and drug resistance mechanisms to enhance treatment outcomes for GBM patients. The relationship between ferroptosis and the immune landscape in GBM is complex and can have either positive or negative effects. These effects can be identified through single-cell RNA sequencing to develop targeted chemo-, radio- and immuno- therapies against glioma stem cells and tumor-supportive immune cells. Additionally, the implication of oncolytic virotherapy in combination with ferroptosis induction can lead to improved treatment of GBM in a clinical setting.

Targeting the glioblastoma resection margin with locoregional nanotechnologies

Surgical resection is the first stage of treatment for patients diagnosed with resectable glioblastoma and is followed by a combination of adjuvant radiotherapy and systemic single-agent chemotherapy, which is typically commenced 4-6 weeks after surgery. This delay creates an interval during which residual tumour cells residing in the resection margin can undergo uninhibited proliferation and further invasion, even immediately after surgery, thus limiting the effectiveness of adjuvant therapies. Recognition of the postsurgical resection margin and peri-marginal zones as important anatomical clinical targets and the need to rethink current strategies can galvanize opportunities for local, intraoperative approaches, while also generating a new landscape of innovative treatment modalities. In this Perspective, we discuss opportunities and challenges for developing locoregional therapeutic strategies to target the glioblastoma resection margin as well as emerging opportunities offered by nanotechnology in this clinically transformative setting. We also discuss how persistent barriers to clinical translation can be overcome to offer a potential path forward towards broader acceptability of such advanced technologies.

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.

Cooperative Role of Carbonic Anhydrase IX/XII in Driving Tumor Invasion and Metastasis: A Novel Targeted Therapeutic Strategy

Cancer invasion and metastasis are critical factors that influence patient prognosis. Carbonic anhydrase IX (CA IX) and carbonic anhydrase XII (CA XII) are key regulators of hypoxia and pH homeostasis in the tumor microenvironment (TME). It has been verified that both CA IX and CA XII play significant roles in promoting tumor metastasis in recent years, but most of the literature tends to treat them as separate entities rather than exploring their synergistic effects. This review provides a comprehensive overview of the roles of CA IX and CA XII in tumor invasion and metastasis, along with their clinical applications, including their spatial distribution characteristics, molecular mechanisms that facilitate tumor metastasis, and their potential for clinical translation. Moreover, this review incorporates the classical tumor core-invasive front model to propose a metabolic coupling model of CA IX and CA XII, offering a fresh perspective on precision therapies that target tumor metabolism. By emphasizing the metabolic coupling between these two molecules, this review offers new insights distinct from previous studies and highlights the clinical therapeutic potential of simultaneously targeting both during treatment. It sheds new light on future research and clinical applications, aiming to enhance the prognosis of cancer patients through innovative therapeutic strategies.

Targeting Glioma Stem Cells: Therapeutic Opportunities and Challenges

Glioblastoma (GBM), or grade 4 glioma, is the most common and aggressive primary brain tumor in adults with a median survival of 15 months. Increasing evidence suggests that GBM's aggressiveness, invasiveness, and therapy resistance are driven by glioma stem cells (GSCs), a subpopulation of tumor cells that share molecular and functional characteristics with neural stem cells (NSCs). GSCs are heterogeneous and highly plastic. They evade conventional treatments by shifting their state and entering in quiescence, where they become metabolically inactive and resistant to radiotherapy and chemotherapy. GSCs can exit quiescence and be reactivated to divide into highly proliferative tumor cells which contributes to recurrence. Understanding the molecular mechanisms regulating the biology of GSCs, their plasticity, and the switch between quiescence and mitotic activity is essential to shape new therapeutic strategies. This review examines the latest evidence on GSC biology, their role in glioblastoma progression and recurrence, emerging therapeutic approaches aimed at disrupting their proliferation and survival, and the mechanisms underlying their resistance to therapy.

Brain-wide neuronal circuit connectome of human glioblastoma

Glioblastoma (GBM) infiltrates the brain and can be synaptically innervated by neurons, which drives tumour progression1,2. Synaptic inputs onto GBM cells identified so far are largely short range and glutamatergic3,4. The extent of GBM integration into the brain-wide neuronal circuitry remains unclear. Here we applied rabies virus-mediated and herpes simplex virus-mediated trans-monosynaptic tracing5,6 to systematically investigate circuit integration of human GBM organoids transplanted into adult mice. We found that GBM cells from multiple patients rapidly integrate into diverse local and long-range neural circuits across the brain. Beyond glutamatergic inputs, we identified various neuromodulatory inputs, including synapses between basal forebrain cholinergic neurons and GBM cells. Acute acetylcholine stimulation induces long-lasting elevation of calcium oscillations and transcriptional reprogramming of GBM cells into a more motile state via the metabotropic CHRM3 receptor. CHRM3 activation promotes GBM cell motility, whereas its downregulation suppresses GBM cell motility and prolongs mouse survival. Together, these results reveal the striking capacity for human GBM cells to rapidly and robustly integrate into anatomically diverse neuronal networks of different neurotransmitter systems. Our findings further support a model in which rapid connectivity and transient activation of upstream neurons may lead to a long-lasting increase in tumour fitness.

Cell-intrinsic metabolic phenotypes identified in patients with glioblastoma, using mass spectrometry imaging of 13C-labelled glucose metabolism

Transcriptomic studies have attempted to classify glioblastoma (GB) into subtypes that predict survival and have different therapeutic vulnerabilities1-3. Here we identified three metabolic subtypes: glycolytic, oxidative and a mix of glycolytic and oxidative, using mass spectrometry imaging of rapidly excised tumour sections from two patients with GB who were infused with [U-13C]glucose and from spatial transcriptomic analysis of contiguous sections. The phenotypes are not correlated with microenvironmental features, including proliferation rate, immune cell infiltration and vascularization, are retained when patient-derived cells are grown in vitro or as orthotopically implanted xenografts and are robust to changes in oxygen concentration, demonstrating their cell-intrinsic nature. The spatial extent of the regions occupied by cells displaying these distinct metabolic phenotypes is large enough to be detected using clinically applicable metabolic imaging techniques. A limitation of the study is that it is based on only two patient tumours, albeit on multiple sections, and therefore represents a proof-of-concept study.

Single-cell RNA sequencing for characterizing the immune communication and iron metabolism roles in CD31+ glioma cells

Background

Gliomas are aggressive brain tumors marked by complex cellular interactions and significant immune cell infiltration. This study investigated the role of CD31+ immune cells, specifically macrophages and T cells, in the glioma microenvironment through single-cell RNA sequencing (scRNA-seq).

Methods

We employed the CellChat framework to map cell-cell communication pathways and used Monocle3 for pseudotime trajectory analysis to characterize the signaling and developmental progressions within CD31+ cells. Pathways such as osteopontin (SPP1) and major histocompatibility complex class II (MHC-II) were analyzed in terms of their role in immune regulation, and we examined the expression of ferritin, an iron-binding protein, to assess its potential function in modulating CD31+ cell activity.

Results

Our findings highlight the expression of key pathways, including SPP1 and MHC-II, influencing immune regulation. Ferritin was found to be highly expressed in CD31+ cells, suggesting a dual role in iron metabolism and immune modulation within the glioma microenvironment.

Conclusions

This study clarified the distinct roles of CD31+ immune cells in glioma progression and identified ferritin as a potential therapeutic target for modulating immune responses in gliomas. These findings may offer new directions in glioma research and the development of immunotherapy, which can aid in improving treatment outcomes.

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.

Multi-transcriptomics reveals niche-specific expression programs and endothelial cells in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a highly lethal malignant intracranial tumor, distinguished from low-grade glioma by histopathological hallmarks such as pseudopalisading cells around necrosis (PAN) and microvascular proliferation (MVP). To date the spatial organization of the molecular and cellular components of these specific histopathological features has not been fully elucidated.

METHODS

Here, using bulk RNA sequencing, spatial transcriptomic and single cell RNA sequencing (scRNA-seq) data of GBM patients, we identified niche-specific transcriptional programs and characterized the differences in molecular expression and cellular organization between PAN and MVP.

RESULTS

Notably, we discovered spatially distinct domains within the tumor core and identified niche-specific signatures: NDRG1 and EPAS1, specifically expressed in the PAN and MVP regions. The clustering results showed two distinct phenotypes of endothelial cells (ECs) were enriched in the MVP and PAN regions, respectively. PAN-associated endothelial cells exhibit copy number variations similar to those in GBM cells. Single cell trajectory analysis reveals a pseudotime trajectory, indicating the differentiation of glioblastoma stem cells (GSCs) toward ECs.

CONCLUSIONS

Necrosis cores which are surrounded by hypoxic and perivascular niches and microvascular proliferation area within the glioblastoma tumor microenvironment, have been considered as standardized morphological indicators of aggressive GBM. Our findings provide a cellular and molecular insights into GBM progression.

Extracellular vesicle-derived miRNA-mediated cell-cell communication inference for single-cell transcriptomic data with miRTalk

MicroRNAs are released from cells in extracellular vesicles (EVs), representing an essential mode of cell-cell communication (CCC) via a regulatory effect on gene expression. Single-cell RNA-sequencing technologies have ushered in an era of elucidating CCC at single-cell resolution. Herein, we present miRTalk, a pioneering approach for inferring CCC mediated by EV-derived miRNA-target interactions (MiTIs). The benchmarking against simulated and real-world datasets demonstrates the superior performance of miRTalk, and the application to four disease scenarios reveals the in-depth MiTI-mediated CCC mechanisms. Collectively, miRTalk can infer EV-derived MiTI-mediated CCC with scRNA-seq data, providing new insights into the intercellular dynamics of biological processes.

Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research

INTRODUCTION

Glioblastoma (GBM) progression and therapeutic resistance are significantly influenced by complex interactions between tumor cells and the brain microenvironment, particularly neurons. However, studying these interactions in physiologically relevant conditions has remained challenging due to limitations in existing model systems.

OBJECTIVES

Here, we present hGliCS (human glioma-cortical spheroid), a novel fully human brain tumor model that overcomes key limitations of current approaches by combining patient-derived GBM cells with mature human cortical neurons derived from induced pluripotent stem cells.

RESULTS

We demonstrate that GBM cells in hGliCS develop three critical hallmark features observed in patients: (i) formation of tumor microtubes enabling intercellular communication, (ii) establishment of neuron-glioma synapses, and (iii) development of an interconnected network with coordinated calcium signaling. Single-cell RNA sequencing reveals that tumor cells in hGliCS exhibit cellular heterogeneity and transcriptional profiles remarkably similar to those observed in mouse xenografts, including activation of key oncogenic pathways and neuronal-like features. Notably, while GBM cells showed substantial transcriptional adaptation to the neural environment, neurons maintained their core identity with only subtle alterations in glutamate signaling and structural gene expression. We validate hGliCS as a drug screening platform by demonstrating resistance patterns to standard chemotherapy and radiation similar to clinical observations. Furthermore, we show the model's utility in testing standard and novel therapeutic compounds targeting cell proliferation and tumor-specific neurobiological features, respectively.

CONCLUSION

This physiologically relevant human model system provides new opportunities for studying GBM biology and tumor-neuron interactions in a controlled environment. By bridging the gap between simplified in vitro systems and complex in vivo models, hGliCS represents a promising platform for therapeutic development and personalized medicine approaches in GBM treatment.

Targeting therapeutic nanoparticles to the glioblastoma resection margin by harnessing post-operative spatiotemporal blood-brain barrier disruption

Resection surgery is the first-line therapy for glioblastoma (GBM) that is performed in >70% of patients, typically within days of suspected diagnosis. Current protocols for follow-on chemoradiotherapy have shown only modest efficacy in eliminating residual disease, leading to inevitable tumour recurrence. There remains a need for new approaches to swiftly and effectively treat post-operative residual disease to prevent the rapid early progression of recurrent GBM. Using syngeneic preclinical models of glioblastoma resection, we identified a spatially and temporally restricted window of blood brain barrier (BBB) disruption localised to the resection margin, during the immediate (15 min) and early (48-72h) postoperative periods. Intravenous administration of fluorescently labelled, clinically-used liposome nanoparticles during these periods demonstrated that selective accumulation at the postoperative resection margin, while largely being excluded from areas of the brain with an intact BBB, could be achieved. Confocal analysis confirmed the presence of extravasated nanoparticles within the margin parenchyma which largely interacted with microglial populations closely associated with residual tumour cells. Exploiting this, we performed intravenous administration of doxorubicin-loaded liposomes (DOX-Lipo) coinciding with the peak of postoperative BBB disruption and demonstrated both enhanced chemotherapy delivery and consequently complete inhibition of tumour recurrence from a single administration. Overall, this work underscores the importance of timing concomitant chemotherapy to the post-operative timeframe and demonstrates that clinically-used liposomal nanomedicines could be readily repurposed for early post-operative therapy in aggressive brain tumours.

Transcript-targeted antigen mapping reveals the potential of POSTN splicing junction epitopes in glioblastoma immunotherapy

Tumor antigens are crucial for T-cell mediated immunotherapy, but identified antigens for gliomas remain limited. Aberrant splicing variants are commonly expressed in tumors, resulting in unique tumor isoforms with potential antigenic properties. Herein, we analyzed multi-omics data from 587 glioma patients and assembled a library of putative tumor-enriched isoform antigens (TIA) and corresponding peptides presented on each HLA-I allele. We constructed an individual-specific TIA peptide candidate repertoire for each patient based on their TIA expression and HLA-I haplotypes. TIAs were highly expressed, enriched with glioma malignancy, and demonstrated strong HLA-binding affinity. We focused on periostin isoform-203 (POSTN-203), which was associated with poor survival of patients and contained multiple predicted HLA-restricted peptide epitopes. A selected HLA-A11-restricted peptide from POSTN-203 (POSTN-203A11) induced antigen-specific T-cell responses against both peptide-pulsed and POSTN-203-expressing glioma cells in an HLA-specific manner. Our findings highlight TIAs as a promising source of immunogenic antigens and POSTN-203 as a potential promising target for glioma immunotherapy.

Exploring Multi-Target Therapeutic Strategies for Glioblastoma via Endogenous Network Modeling

Medical treatment of glioblastoma presents a significant challenge. A conventional medication has limited effectiveness, and a single-target therapy is usually effective only in the early stage of the treatment. Recently, there has been increasing focus on multi-target therapies, but the vast range of possible combinations makes clinical experimentation and implementation difficult. From the perspective of systems biology, this study conducted simulations for multi-target glioblastoma therapy based on dynamic analysis of previously established endogenous networks, validated with glioblastoma single-cell RNA sequencing data. Several potentially effective target combinations were identified. The findings also highlight the necessity of multi-target rather than single-target intervention strategies in cancer treatment, as well as the promise in clinical applications and personalized therapies.

A Single-Cell Atlas of RNA Alternative Splicing in the Glioma-Immune Ecosystem

Single-cell analysis has refined our understanding of cellular heterogeneity in glioma, yet RNA alternative splicing (AS)-a critical layer of transcriptome regulation-remains underexplored at single-cell resolution. Here, we present a pan-glioma single-cell AS analysis in both tumor and immune cells through integrating seven SMART-seq2 datasets of human gliomas. Our analysis reveals lineage-specific AS across glioma cellular states, with the most divergent AS landscapes between mesenchymal- and neuronal-like glioma cells, exemplified by AS in TCF12 and PTBP2. Comparison between core and peripheral glioma cells highlights AS-redox co-regulation of cytoskeleton organization. Further analysis of glioma-infiltrating immune cells reveals potential isoform-level regulation of protein glycosylation in regulatory T cells and a link between MS4A7 AS in macrophages and clinical response to anti-PD-1 therapy. This study emphasizes the role of AS in glioma cellular heterogeneity, highlighting the importance of an isoform-centric approach to better understand the complex biological processes driving tumorigenesis.

Unraveling anoikis in glioblastoma: insights from single-cell sequencing and prognostic modeling

BACKGROUND

Despite advances, Glioblastoma (GBM) treatment remains challenging due to its rapid progression and resistance to therapies.

OBJECTIVES

This study aimed to investigate the role of anoikis-a mechanism by which cells evade programmed cell death upon detachment from the extracellular matrix-in GBM progression and prognosis.

METHODS

Utilizing single-cell sequencing and bulk-transcriptome sequencing data from TCGA, GEO, and CGGA databases, we performed comprehensive bioinformatics analyses. We identified anoikis-related genes, constructed a prognostic model using 101 machine learning algorithms, and validated its clinical utility across multiple cohorts.Finally, we also verified the expression of model genes and the function of key gene in clinical samples and cell lines.

RESULTS

Single-cell sequencing revealed heterogeneous expression of anoikis-related genes across distinct cell populations within GBM. MES-like Malignant cells and Myeloids exhibited higher enrichment of these genes, implicating their role in anoikis resistance and tumor aggressiveness. The prognostic model, based on identified genes, effectively stratified patients into high-risk and low-risk groups, demonstrating significant differences in survival outcomes. Mutation and tumor microenvironment analyses highlighted distinct genetic landscapes and immune cell infiltration patterns associated with different risk groups. SLC43A3 emerged as a key gene, showing significant upregulation in tumor tissues and correlating with poor prognosis in GBM.

CONCLUSION

This study provides insights into the molecular mechanisms of anoikis resistance in GBM, underscoring its critical role in tumor progression and patient prognosis. The developed prognostic model offers a promising tool for personalized treatment strategies and warrants further exploration of targeted therapies to improve outcomes for GBM patients.

Integrative multi-omic profiling of the neoantigen landscape of glioblastoma for the development of therapeutic vaccines reveals vast heterogeneity in immunogenic signatures

Introduction

Glioblastoma (GBM) is the most common primary brain malignancy. Few neoantigens have been tested in trials as the cancer vaccine against GBM.

Methods

To better understand the neoantigen landscape and its associated tumor microenvironment (TME) for the optimized vaccine design of our initiated GBM trial, we apply the integrative multi-omics approach to comprehensively profile the mutation, HLA typing, TCR/BCR repertoire, immune cell components on the tumor tissue and peripheral blood mononuclear cell (PMBC) specimen of 24 GBM patients.

Results

On average, 148 mutated genes and 200 mutated sites per patient were identified, with no predominant mutated sites and genes in this cohort. Diversified HLA genotypes and expression rate across A, B, and C alleles, with A30:01&A11:01, B13:02, and C06:02, as the most frequent genotypes at respective alleles. Clustered CDR3 of TCR/BCR existed in tumor tissue with decreased richness compared with PMBC. NK and Th1 cells were revealed as the predominant immune cells within the tumor microenvironment (TME). Neoantigens were feasible predicted and designed for each patient, with an average number of 107. Very few neoantigens were shared by more than two patients and no dominant neoantigen could be identified. A minimum of 11-peptide bulk was required to cover this 24-patient cohort, guaranteeing each patient could have at least one neoantigen.

Discussion

In summary, our data reveals a heterogeneous landscape of the neoantigen and its associated immune TME of GBM, based on which a peptide bulk is feasibly developed to cover these patients as a cohort.

Current Applications of Single-Cell RNA Sequencing in Glioblastoma: A Scoping Review

Background and Objective: The discovery of novel molecular biomarkers via next-generation sequencing technologies has revolutionized how glioblastomas (GBMs) are classified nowadays. This has resulted in more precise diagnostic, prognostic, and therapeutic approaches to address this malignancy. The present work examines the applications of single-cell RNA sequencing (scRNA-seq) in GBM, focusing on its potential to address tumor complexity and therapeutic resistance and improve patient outcomes. Methods: A scoping review of original studies published between 2009 and 2024 was conducted using the PUBMED and EMBASE databases. Studies in English or Spanish related to single-cell analysis and GBM were included. Key Findings: The database search yielded 453 publications. Themes related to scRNA-seq applied for the diagnosis, prognosis, treatment, and understanding of the cancer biology of GBM were used as criteria for article selection. Of the 24 studies that were included in the review, 11 focused on the tumor microenvironment and cell subpopulations in GBM samples, 5 investigated the use of sequencing to elucidate the GBM cancer biology, 3 examined disease prognosis using sequencing models, 3 applied translational research through scRNA-seq, and 2 addressed treatment-related problems in GBM elucidated by scRNA-seq. Conclusions: This scoping review explored the various clinical applications of scRNA-seq technologies in approaching GBM. The findings highlight the utility of this technology in unraveling the complex cellular and immune landscapes of GBM, paving the way for improved diagnosis and personalized treatments. This cutting-edge approach might strengthen treatment strategies against tumor progression and recurrence, setting the stage for multi-targeted interventions that could significantly improve outcomes for patients with aggressive, treatment-resistant GBMs.

Glioma-astrocyte connexin43 confers temozolomide resistance through activation of the E2F1/ERCC1 axis

BACKGROUND

Glioma is the most prevalent and lethal tumor of the central nervous system. Routine treatment with temozolomide (TMZ) would unfortunately result in inevitable recurrence and therapy resistance, severely limiting therapeutic efficacy. Tumor-associated astrocytes (TAAs) are key components of the tumor microenvironment and increasing evidence has demonstrated that aberrant expression of connexin43 (Cx43) was closely associated with glioma progression and TMZ resistance. However, the specific role of Cx43 in mediating TMZ resistance through glioma and astrocyte interactions has not been fully explored.

METHODS

The expression and prognostic value of Cx43 were evaluated in tumor samples and clinical databases. ShRNA-medicated knockdown and Gfap-Cre Cx43flox/flox gene mouse were used to assess the role and functional significance of Cx43 in vitro and in vivo. Moreover, we performed mass spectrometry analysis, chromatin immunoprecipitation, and other biochemical assays to define the molecular mechanisms by which Cx43 promotes TMZ resistance.

RESULTS

We confirmed that the upregulation of Cx43 expression between TAAs and glioma cells contributed to TMZ resistance and tumor recurrence. Genetic knockdown or pharmacological inhibition of Cx43 enhanced TMZ-induced cytotoxicity. Mechanistically, elevated Cx43 expression induced β-catenin accumulation at the cell surface of glioma cells, suppressing T-cell factor/lymphoid enhancer-binding factor transcription. This led to impaired miR-205-5p expression and subsequent activation of the E2F1/ERCC1 axis, which eventually led to chemoresistance.

CONCLUSIONS

Our study reveals a novel regulatory mechanism in which the Cx43/miR-205-5p/E2F1/ERCC1 axis contributes to TMZ resistance in glioma. These findings further highlight the potential of targeting Cx43 as a therapeutic strategy in glioma.

A 5-Year Update on the Clinical Development of Cancer Cell-Based Vaccines for Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is considered one of the most aggressive forms of brain cancer with a 15-month median survival, despite advancements in surgery, radiotherapy, and chemotherapy. The immune-suppressed tumor microenvironment and the blood-brain barrier are major contributors to its poor prognosis and treatment resistance. In the last decade, significant progress has been made in developing cell-based vaccines to boost immune responses against GBM. This review provides an extensive update on recent clinical trials involving various cancer cell vaccines, including ICT-107, the α-type-1 DC vaccine, and others. Although these trials have demonstrated potential improvements in progression-free survival (PFS) and overall survival (OS), the diverse and immune-suppressed nature of GBM poses challenges for consistent therapeutic success. We discuss the details of these trials along with the potential mechanism of vaccine efficacy and immune activations. The findings of these trials highlight the significance of a personalized immunotherapy approach and suggest that patient stratification could significantly advance the clinical management of GBM.

Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics

Glioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizing these features would improve the clinical management of glioblastoma. Glucose flux rates through glycolysis and mitochondrial oxidation have been recently shown to quantitatively depict glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the spatial features of tumor microenvironment phenotypes remain hitherto unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI) approach for profiling tumor microenvironments through glucose conversion kinetics. Using a multimodal combination of tumor mouse models, novel strategies for spectroscopic imaging and noise attenuation, and histopathological correlations, we show that tumor lactate turnover mirrors phenotype differences between GL261 and CT2A mouse glioblastoma, whereas recycling of the peritumoral glutamate-glutamine pool is a potential marker of invasion capacity in pooled cohorts, linked to secondary brain lesions. These findings were validated by histopathological characterization of each tumor, including cell density and proliferation, peritumoral invasion and distant migration, and immune cell infiltration. Our study bodes well for precision neuro-oncology, highlighting the importance of mapping glucose flux rates to better understand the metabolic heterogeneity of glioblastoma and its links to disease phenotypes.

SCANER: robust and sensitive identification of malignant cells from the scRNA-seq profiled tumor ecosystem

Single-cell RNA sequencing (scRNA-seq) has enabled the dissection of complex tumor ecosystems. Recognition of malignant cells as an essential step has a profound impact on downstream interpretation. However, most existing computational strategies are based on prior knowledge of canonical cell-type markers. We have developed a marker-free approach, the Seed-Cluster based Approach for NEoplastic cells Recognition (SCANER), to identify malignant cells based on significant gene expression variations caused by genomic instability. Upon analyzing different cancer types, SCANER achieved superior accuracy and robustness in identifying malignant cells, effectively addressing dropout events and tumor purity variations. Besides, SCANER can significantly detect copy number variations (CNVs) in malignant cells compared to nonmalignant cells, which is further confirmed through the paired whole exome sequencing data. In conclusion, SCANER has the potential to facilitate the biological exploration of the tumor ecosystem by accurately identifying malignant cells and it is applicable across various solid cancer types regardless of prior knowledge. SCANER is available at https://github.com/woolingxiang/SCANER.

A creatine efflux transporter in oligodendrocytes

Creatine is essential for ATP regeneration in energy-demanding cells. Creatine deficiency results in severe neurodevelopmental impairments. In the brain, creatine is synthesized locally by oligodendrocytes to supply neighboring neurons. Neuronal uptake is mediated by SLC6A8. However, it is still unknown how creatine is released from the producing cells. Here, we investigated the function of the transporter SLC22A15, which exhibits strikingly high amino acid sequence conservation. The release of substrates from 293 cells via heterologously expressed human and rat SLC22A15 was analyzed by mass spectrometry. A number of zwitterions were identified as substrates, with similar efflux transport efficiencies. However, in absolute numbers, the efflux of creatine far outweighed all other substrates. In contrast to the permanent creatine efflux mediated by SLC16A12 and SLC16A9, SLC22A15 was, by default, completely inactive, thereby preventing continuous creatine loss from producing cells. External substrates such as guanidinoacetic acid, GABA, or MPP+ trigger creatine release through a one-to-one exchange. Human and mouse mRNA profiles indicate that SLC22A15 expression is highest in oligodendrocytes and bone marrow. Single-cell RNA sequencing data substantiate the hypothesis that SLC22A15 depends on high intracellular creatine concentrations: high SLC22A15 counts, as in oligodendrocytes and macrophages, correlate with high counts of the creatine synthesis enzymes AGAT and GAMT in both humans and mice, whereas in proximal tubular cells and hepatocytes, AGAT counts are high, but SLC22A15 is absent. Our findings establish SLC22A15 as the pivotal transporter for controlled creatine release from oligodendrocytes, filling a critical gap in understanding creatine metabolism in the brain.

Scalable co-sequencing of RNA and DNA from individual nuclei

The ideal technology for directly investigating the relationship between genotype and phenotype would analyze both RNA and DNA genome-wide and with single-cell resolution; however, existing tools lack the throughput required for comprehensive analysis of complex tumors and tissues. We introduce a highly scalable method for jointly profiling DNA and expression following nucleosome depletion (DEFND-seq). In DEFND-seq, nuclei are nucleosome-depleted, tagmented and separated into individual droplets for messenger RNA and genomic DNA barcoding. Once nuclei have been depleted of nucleosomes, subsequent steps can be performed using the widely available 10x Genomics droplet microfluidic technology and commercial kits. We demonstrate the production of high-complexity mRNA and gDNA sequencing libraries from thousands of individual nuclei from cell lines, fresh and archived surgical specimens for associating gene expression with both copy number and single-nucleotide variants.

Malignant Cells Beyond the Tumor Core: The Non-Negligible Factor to Overcome the Refractory of Glioblastoma

BACKGROUND

Glioblastoma (GBM) is one of the most aggressive primary brain tumors in adults. Over 95% of GBM patients experience recurrence in the peritumoral brain tissue or distant regions, indicating the presence of critical factors in these areas that drive tumor recurrence. Current clinical treatments primarily focus on tumor cells from the tumor core (TC), while the role of neoplastic cells beyond the TC has been largely neglected.

METHODS

We conducted a comprehensive review of existing literature and studies on GBM, focusing on the identification and characterization of questionable cells (Q cells). Advanced imaging techniques, such as diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET), were utilized to identify Q cells beyond the tumor core. We also analyzed the functional properties, cellular microenvironment, and physical characteristics of Q cells, as well as their implications for surgical resection.

RESULTS

Our review revealed that Q cells exhibit unique functional attributes, including enhanced invasiveness, metabolic adaptations, and resistance mechanisms. These cells reside in a distinct cellular microenvironment and are influenced by physical properties such as solid stress and stiffness. Advanced imaging techniques have improved the identification of Q cells, enabling more precise surgical resection. Targeting Q cells in therapeutic strategies could significantly reduce the risk of GBM recurrence.

CONCLUSION

The presence of Q cells in the peritumoral brain zone (PBZ) and beyond is a critical factor in GBM recurrence. Current treatments, which primarily target tumor cells in the TC, are insufficient to prevent recurrence due to the neglect of Q cells. Future research should focus on understanding the mechanisms influencing Q cells and developing targeted therapies to improve patient outcomes.

InfoScan: A New Transcript Identification Tool Based on scRNA-Seq and Its Application in Glioblastoma

InfoScan is a novel bioinformatics tool designed for the comprehensive analysis of full-length single-cell RNA sequencing (scRNA-seq) data. It enables the identification of unannotated transcripts and rare cell populations, providing a powerful platform for transcriptome characterization. In this study, InfoScan was applied to glioblastoma multiforme (GBM), identifying a rare "neoplastic-stemness" subpopulation exhibiting cancer stem cell-like features. Functional analyses suggested that tumor-associated macrophages (TAMs) secrete SPP1, which binds to CD44 on neoplastic-stemness cells, activating the PI3K/AKT pathway and driving lncRNA transcription to promote metastasis. Integration of TCGA and CGGA datasets further supported these findings, highlighting key mutations associated with the neoplastic-stemness subpopulation. Drug sensitivity assays indicated that neoplastic-stemness cells might be sensitive to omipalisib, a PI3K inhibitor, pointing to a potential therapeutic target. InfoScan offers a robust framework for exploring complex transcriptomic landscapes and characterizing rare cell populations, providing valuable insights into GBM biology and advancing precision cancer therapy.

Harnessing Macrophages in Cancer Therapy: from Immune Modulators to Therapeutic Targets

Macrophages, as the predominant phagocytes, play an essential role in pathogens defense and tissue homeostasis maintenance. In the context of cancer, tumor-associated macrophages (TAMs) have evolved into cunning actors involved in angiogenesis, cancer cell proliferation and metastasis, as well as the construction of immunosuppressive microenvironment. Once properly activated, macrophages can kill tumor cells directly through phagocytosis or attack tumor cells indirectly by stimulating innate and adaptive immunity. Thus, the prospect of targeting TAMs has sparked significant interest and emerged as a promising strategy in immunotherapy. In this review, we summarize the diverse roles and underlying mechanisms of TAMs in cancer development and immunity and highlight the TAM-based therapeutic strategies such as inhibiting macrophage recruitment, inhibiting the differentiation reprogramming of TAMs, blocking phagocytotic checkpoints, inducing trained macrophages, as well as the potential of engineered CAR-armed macrophages in cancer therapy.

Single-cell transcriptomes reveal cell-type-specific and sample-specific gene function in human cancer

Accurate annotation of gene function in individual samples and even in each cell type is essential for understanding the pathogenesis of cancers. Single-cell RNA-sequencing (scRNA-seq) provides unprecedented resolution to decipher gene function. In order to explore how scRNA-seq contributes to the understanding of gene function in cancers, we constructed an assessment framework based on co-expression network and neighbor-voting method using 116,814 cells. Compared with bulk transcriptome, scRNA-seq recalled more experimentally verified gene functions. Surprisingly, scRNA-seq revealed cell-type-specific functions, especially in immune cells, whose expression profile recalled immune-related functions that were not discovered in cancer cells. Furthermore, scRNA-seq discovered sample-specific functions, highlighting that it provided sample-specific information. We also explored factors affecting the performance of gene function prediction. We found that 500 or more cells should be considered in the prediction with scRNA-seq, and that scRNA-seq datasets generated from 10x Genomics platform had a better performance than those from Smart-seq2. Collectively, we compared the prediction performance of bulk data and scRNA-seq data from multiple perspectives, revealing the irreplaceable role of single-cell sequencing in decoding the biological progresses in which the gene involved.

An integrated perspective on single-cell and spatial transcriptomic signatures in high-grade gliomas

High-grade gliomas (HGG) are incurable brain malignancies in children and adults. Breakthrough advances in transcriptomic technologies unveiled the intricate diversity of cellular states and their spatial organization within HGGs. We qualitatively integrated 55 neoplastic transcriptomic signatures described in 17 single-cell and spatial RNA sequencing-based studies. Our review delineates a spectrum of cellular states, represented by the expression of specific genes, which can be conceptualized along a "reactive-developmental programs" axis. Additionally, we discussed the potential cues influencing these cellular states, including how spatial organization may impact transcriptomic dynamics. Leveraging these insightful discoveries, we discussed a novel, evolutive way to integrate the different transcriptomic signatures in two or three dimensions, incorporating developmental states, their proliferative capacity, and their possible transition towards reactive states. This integrated analysis illuminates the diverse cellular landscape of HGGs and provides a valuable resource for further elucidation of malignant mechanisms, and for the design of therapeutic endeavors.

ELLIPSIS: robust quantification of splicing in scRNA-seq

MOTIVATION

Alternative splicing is a tightly regulated biological process, that due to its cell type specific behavior, calls for analysis at the single cell level. However, quantifying differential splicing in scRNA-seq is challenging due to low and uneven coverage. Hereto, we developed ELLIPSIS, a tool for robust quantification of splicing in scRNA-seq that leverages locally observed read coverage with conservation of flow and intra-cell type similarity properties. Additionally, it is also able to quantify splicing in novel splicing events, which is extremely important in cancer cells where lots of novel splicing events occur.

RESULTS

Application of ELLIPSIS to simulated data proves that our method is able to robustly estimate Percent Spliced In values in simulated data, and allows to reliably detect differential splicing between cell types. Using ELLIPSIS on glioblastoma scRNA-seq data, we identified genes that are differentially spliced between cancer cells in the tumor core and infiltrating cancer cells found in peripheral tissue. These genes showed to play a role in a.o. cell migration and motility, cell projection organization, and neuron projection guidance.

AVAILABILITY AND IMPLEMENTATION

ELLIPSIS quantification tool: https://github.com/MarchalLab/ELLIPSIS.git.

Mapping the developmental trajectory of human astrocytes reveals divergence in glioblastoma

Glioblastoma (GBM) is defined by heterogeneous and resilient cell populations that closely reflect neurodevelopmental cell types. Although it is clear that GBM echoes early and immature cell states, identifying the specific developmental programmes disrupted in these tumours has been hindered by a lack of high-resolution trajectories of glial and neuronal lineages. Here we delineate the course of human astrocyte maturation to uncover discrete developmental stages and attributes mirrored by GBM. We generated a transcriptomic and epigenomic map of human astrocyte maturation using cortical organoids maintained in culture for nearly 2 years. Through this approach, we chronicled a multiphase developmental process. Our time course of human astrocyte maturation includes a molecularly distinct intermediate period that serves as a lineage commitment checkpoint upstream of mature quiescence. This intermediate stage acts as a site of developmental deviation separating IDH-wild-type neoplastic astrocyte-lineage cells from quiescent astrocyte populations. Interestingly, IDH1-mutant tumour astrocyte-lineage cells are the exception to this developmental perturbation, where immature properties are suppressed as a result of D-2-hydroxyglutarate oncometabolite exposure. We propose that this defiance is a consequence of IDH1-mutant-associated epigenetic dysregulation, and we identified biased DNA hydroxymethylation (5hmC) in maturation genes as a possible mechanism. Together, this study illustrates a distinct cellular state aberration in GBM astrocyte-lineage cells and presents developmental targets for experimental and therapeutic exploration.

Morphoregulatory ADD3 underlies glioblastoma growth and formation of tumor-tumor connections

Glioblastoma is a major unmet clinical need characterized by striking inter- and intra-tumoral heterogeneity and a population of glioblastoma stem cells (GSCs), conferring aggressiveness and therapy resistance. GSCs communicate through a network of tumor-tumor connections (TTCs), including nanotubes and microtubes, promoting tumor progression. However, very little is known about the mechanisms underlying TTC formation and overall GSC morphology. As GSCs closely resemble neural progenitor cells during neurodevelopment, we hypothesized that GSCs' morphological features affect tumor progression. We identified GSC morphology as a new layer of tumoral heterogeneity with important consequences on GSC proliferation. Strikingly, we showed that the neurodevelopmental morphoregulator ADD3 is sufficient and necessary for maintaining proper GSC morphology, TTC abundance, cell cycle progression, and chemoresistance, as well as required for cell survival. Remarkably, both the effects on cell morphology and proliferation depend on the stability of actin cytoskeleton. Hence, cell morphology and its regulators play a key role in tumor progression by mediating cell-cell communication. We thus propose that GSC morphological heterogeneity holds the potential to identify new therapeutic targets and diagnostic markers.

Network analyses of brain tumor multiomic data reveal 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.

Single-nucleus and spatial landscape of the sub-ventricular zone in human glioblastoma

The sub-ventricular zone (SVZ) is the most well-characterized neurogenic area in the mammalian brain. We previously showed that in 65% of patients with glioblastoma (GBM), the SVZ is a reservoir of cancer stem-like cells that contribute to treatment resistance and the emergence of recurrence. Here, we build a single-nucleus RNA-sequencing-based microenvironment landscape of the tumor mass and the SVZ of 15 patients and two histologically normal SVZ samples as controls. We identify a ZEB1-centered mesenchymal signature in the tumor cells of the SVZ. Moreover, the SVZ microenvironment is characterized by tumor-supportive microglia, which spatially coexist and establish crosstalks with tumor cells. Last, differential gene expression analyses, predictions of ligand-receptor and incoming/outgoing interactions, and functional assays reveal that the interleukin (IL)-1β/IL-1RAcP and Wnt-5a/Frizzled-3 pathways represent potential therapeutic targets in the SVZ. Our data provide insights into the biology of the SVZ in patients with GBM and identify potential targets of this microenvironment.

In Silico Born Designed Anti-EGFR Aptamer Gol1 Has Anti-Proliferative Potential for Patient Glioblastoma Cells

The epidermal growth factor receptor (EGFR) is one of the key oncomarkers in glioblastoma (GB) biomedical research. High levels of EGFR expression and mutations have been found in many GB patients, making the EGFR an attractive target for therapeutic treatment. The EGFRvIII mutant is the most studied, it is not found in normal cells and is positively associated with tumor cell aggressiveness and poor patient prognosis, not to mention there is a possibility of it being a tumor stem cell marker. Some anti-EGFR DNA aptamers have already been selected, including the aptamer U2. The goal of this study was to construct a more stable derivative of the aptamer U2, while not ruining its functional potential toward cell cultures from GB patients. A multiloop motif in a putative secondary structure of the aptamer U2 was taken as a key feature to design a novel minimal aptamer, Gol1, using molecular dynamics simulations for predicted 3D models. It turned out that the aptamer Gol1 has a similar putative secondary structure, with G-C base pairs providing its stability. The anti-proliferative activities of the aptamer Gol1 were assessed using patient-derived GB continuous cell cultures, G01 and BU881, with different abundances of EGFR and EGFRvIII. The transcriptome data for the cell culture G01, after aptamer Gol1 treatment, revealed significant changes in gene expression; it induced the transcription of genes associated with neurogenesis and cell differentiation, and it decreased the transcription of genes mediating key nuclear processes. There were significant changes in the gene transcription of key pro-oncogenic signaling pathways mediated by the EGFR. Therefore, the aptamer Gol1 could potentially be an efficient molecule for translation into biomedicine, in order to develop targeted therapy for GB patients.

Bulk and single-cell transcriptome revealed the metabolic heterogeneity in human glioma

Background

Emerging perspectives on tumor metabolism reveal its heterogeneity, a characteristic yet to be fully explored in gliomas. To advance therapies targeting metabolic processes, it is crucial to uncover metabolic differences and identify distinct metabolic subtypes. Therefore, we aimed to develop a classification system for gliomas based on the enrichment levels of four key metabolic pathways: glutaminolysis, glycolysis, the pentose phosphate pathway, and fatty acid oxidation.

Methods

Energy-related features of glioma were characterized through integrative analyses of multiple datasets, including bulk, single-cell, and spatial transcriptome profiling. The glioma energy metabolic subtypes were constructed using the R package ConsensusClusterPlus. Kaplan-Meier analysis was conducted to compare clinical outcomes between different metabolic groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological functions of genes of interest. Cell-cell communication analysis was performed at single-cell resolution using the R package CellChat and at spatial resolution using the standard stLearn pipeline.

Results

Glioma samples were stratified into two prognostic subtypes. Group 1, enriched in the glutaminolysis pathway, had better clinical outcomes. In contrast, Group 2 exhibited high activities in glycolysis, the pentose phosphate pathway, and fatty acid oxidation, correlating with decreased survival time. Group 1 samples were predominantly located in the peripheral region and had a high composition of neuron cells. Group 2, however, had increased infiltration of tumor-promoting immune cells, such as M2 macrophages, and was characterized by traits of invasion, hypoxia, and immunity. Lastly, cell-cell communications were compared across different tumor regions, and the CX3CL1/CX3CR1 ligand-receptor pair was validated using spatial transcriptomic data.

Conclusions

Our work revealed the metabolic heterogeneity in glioma by developing a new classification system with significant prognostic and therapeutic value. Single-cell transcriptional profiles offer novel insights into tumor metabolic reprogramming, which could enhance therapies tailored to cell- or patient-specific metabolic patterns.

Metabolomic characterisation of the glioblastoma invasive margin reveals a region-specific signature

Isocitrate dehydrogenase wild-type glioblastoma (GBM) is characterised by a heterogeneous genetic landscape resulting from dynamic competition between tumour subclones to survive selective pressures. Improvements in metabolite identification and metabolome coverage have led to increased interest in clinically relevant applications of metabolomics. Here, we use liquid chromatography-mass spectrometry and gene expression microarray to profile integrated intratumour metabolic heterogeneity, as a direct functional readout of adaptive responses of subclones to the tumour microenvironment. Multi-region surgical sampling was performed on five adult GBM patients based on pre-operative brain imaging and fluorescence-guided surgery. Polar and hydrophobic metabolites extracted from tumour fragments were assessed, followed by putative assignment of metabolite identifications based on retention times and molecular mass. Class discrimination between tumour regions through showed clear separation of tumour regions based on polar metabolite profiles. Metabolic pathway assignments revealed several significantly altered metabolites between the tumour core and invasive region to be associated with purine and pyrimidine metabolism. This proof-of-principle study assesses intratumour heterogeneity through mass spectrometry-based metabolite profiling of multi-region biopsies. Bioinformatic interpretation of the GBM metabolome has highlighted the invasive region to be biologically distinct compared to tumour core and revealed putative drug-targetable metabolic pathways associated with purine and pyrimidine metabolism.

Endothelial-secreted Endocan activates PDGFRA and regulates vascularity and spatial phenotype in glioblastoma

Extensive neovascularization is a hallmark of glioblastoma (GBM). In addition to supplying oxygen and nutrients, vascular endothelial cells provide trophic support to GBM cells via paracrine signaling. Here we report that Endocan (ESM1), an endothelial-secreted proteoglycan, confers enhanced proliferative, migratory, and angiogenic properties to GBM cells and regulates their spatial identity. Mechanistically, Endocan exerts at least part of its functions via direct binding and activation of the PDGFRA receptor. Subsequent downstream signaling enhances chromatin accessibility of the Myc promoter and upregulates Myc expression inducing stable phenotypic changes in GBM cells. Furthermore, Endocan confers radioprotection on GBM cells in vitro and in vivo. Inhibition of Endocan-PDGFRA signaling with ponatinib increases survival in the Esm1 wild-type but not in the Esm1 knock-out mouse GBM model. Our findings identify Endocan and its downstream signaling axis as a potential target to subdue GBM recurrence and highlight the importance of vascular-tumor interactions for GBM development.

Bridging the gap between tumor and disease: Innovating cancer and glioma models

Recent advances in cancer biology and therapeutics have underscored the importance of preclinical models in understanding and treating cancer. Nevertheless, current models often fail to capture the complexity and patient-specific nature of human tumors, particularly gliomas. This review examines the strengths and weaknesses of such models, highlighting the need for a new generation of models. Emphasizing the critical role of the tumor microenvironment, tumor, and patient heterogeneity, we propose integrating our advanced understanding of glioma biology with innovative bioengineering and AI technologies to create more clinically relevant, patient-specific models. These innovations are essential for improving therapeutic development and patient outcomes.

Microtubule-associated NAV3 regulates invasive phenotypes in glioblastoma cells

Glioblastomas are aggressive brain tumors for which effective therapy is still lacking, resulting in dismal survival rates. These tumors display significant phenotypic plasticity, harboring diverse cell populations ranging from tumor core cells to dispersed, highly invasive cells. Neuron navigator 3 (NAV3), a microtubule-associated protein affecting microtubule growth and dynamics, is downregulated in various cancers, including glioblastoma, and has thus been considered a tumor suppressor. In this study, we challenge this designation and unveil distinct expression patterns of NAV3 across different invasion phenotypes. Using glioblastoma cell lines and patient-derived glioma stem-like cell cultures, we disclose an upregulation of NAV3 in invading glioblastoma cells, contrasting with its lower expression in cells residing in tumor spheroid cores. Furthermore, we establish an association between low and high NAV3 expression and the amoeboid and mesenchymal invasive phenotype, respectively, and demonstrate that overexpression of NAV3 directly stimulates glioblastoma invasive behavior in both 2D and 3D environments. Consistently, we observed increased NAV3 expression in cells migrating along blood vessels in mouse xenografts. Overall, our results shed light on the role of NAV3 in glioblastoma invasion, providing insights into this lethal aspect of glioblastoma behavior.

Multidimensional analysis of matched primary and recurrent glioblastoma identifies contributors to tumor recurrence influencing time to relapse

Glioblastoma (GBM) is a lethal brain tumor without effective treatment options. This study aimed to characterize longitudinal tumor changes in order to find potentially actionable targets to prevent GBM relapse. We extracted RNA and proteins from fresh frozen tumor samples from patient-matched IDHwt WHO grade 4 primary (pGBM) and recurrent (rGBM) tumors for transcriptomics and proteomics analysis. A tissue microarray containing paired tumor samples was processed for spatial transcriptomics analysis. Differentially expressed genes and proteins between pGBM and rGBM were involved in synapse development and myelination. By categorizing patients into short (STTR) and long (LTTR) time-to-lapse, we identified genes/proteins whose expression levels positively or negatively correlated with TTR. In rGBM, expressions of Fcγ receptors (FCGRs) and complement system genes were negatively correlated with TTR, whereas expression of genes involved in DNA methylation was positively correlated with TTR. Spatial transcriptomics of the tumor cells showed enrichment of oligodendrocytes in rGBM. Besides, we observed changes in the myeloid compartment such as a switch from quiescent to activated microglia and an enrichment in B and T cells in rGBM with STTR. Our results uncover a role for activated microglia/macrophages in GBM recurrence and suggest that interfering with these cells may hinder GBM relapse.

Supramarginal Resection of Glioblastoma: A Review

This article discusses the evidence supporting the resection of glioblastoma beyond the borders of contrast-enhancing tumor. While several techniques for this have been described, including a so-called FLAIRectomy, lobectomy, or via the use of adjuncts such as fluorescence or intraoperative MRI, the optimal extent of additional resection has yet to be established. Many authors have noted a survival benefit with supramarginal resection without significant additional morbidity.

The Slovenian translational platform GlioBank for brain tumor research: Identification of molecular signatures of glioblastoma progression

Background

Glioblastoma (GB) is one of the most lethal solid tumors in humans, with an average patient life expectancy of 15 months and a 5-year survival rate of 5%-10%. GB is still uncurable due to tumor heterogeneity and invasive nature as well as therapy-resistant cancer cells. Centralized biobanks with clinical data and corresponding biological material of GB patients facilitate the development of new treatment approaches and the search for clinically relevant biomarkers, with the goal of improving outcomes for GB patients. The aim of this study was firstly to establish a Slovenian translation platform, GlioBank, and secondly to demonstrate its utility through the identification of molecular signatures associated with GB progression and patient survival.

Methods

GlioBank contains tissue samples and corresponding tumor models as well as clinical data from patients diagnosed with glioma, with a focus on GB. Primary GB cells, glioblastoma stem cells (GSCs), and organoids have been established from fresh tumor biopsies. We performed expression analyses of genes associated with GB progression and bioinformatics analyses of available clinical and research data obtained from a subset of 91 GB patients. qPCR was performed to determine the expression of genes associated with therapy resistance and cancer cell invasion, including markers of different GB subtypes, GSCs, epithelial-to-mesenchymal transition, and immunomodulation/chemokine signaling in tumor tissues and corresponding cellular models.

Results

GlioBank contains biological material and research, and clinical data collected in the SciNote electronic laboratory notebook. To date, more than 240 glioma tissue samples have been collected and stored in GlioBank, most of which are GB tissues (205) and were further processed to establish primary GB cells (n = 64), GSCs (n = 14), and GB organoids (n = 17). Corresponding blood plasma (n = 103) and peripheral blood mononuclear cells (n = 101) are also stored. GB tumors were classified into 4 different subtypes that differed regarding patient survival; the mixed subtype exhibited the longest patient survival. High DAB2, S100A4, and STAT3 expression were associated with poor overall patient survival, and DAB2 was found to be an independent prognostic marker for GB survival. We analyzed the molecular signatures between different tumor regions (core vs. rim). STMN4, ERBB3, and ACSBG1 were upregulated in the tumor rim, suggesting that these genes are associated with the invasive nature of GB.

Conclusions

GlioBank is a centralized biobank that has been built by a multidisciplinary network with the aim of facilitating disease-oriented basic and clinical research. The advantages of GlioBank include the molecular characterization of GB based on targeted gene expression, the availability of diverse cellular models (eg, GB cells and organoids), and a large number of patient-matched tumor core and rim samples, all with accompanying molecular and clinical data. We report here for the first time an association between DAB2 expression and low overall survival in GB patients, indicative of a prognostic value of DAB2.

Turning attention to tumor-host interface and focus on the peritumoral heterogeneity of glioblastoma

Approximately 90% of glioblastoma recurrences occur in the peritumoral brain zone (PBZ), while the spatial heterogeneity of the PBZ is not well studied. In this study, two PBZ tissues and one tumor tissue sample are obtained from each patient via preoperative imaging. We assess the microenvironment and the characteristics of infiltrating immune/tumor cells using various techniques. Our data indicate there are one or more regions with higher cerebral blood flow in PBZ, which we collectively name the "higher cerebral blood flow interface" (HBI). The HBI exhibited more neovascularization than the "lower cerebral blood flow interfaces" (LBI). The HBI tend to have increased infiltration of macrophages and T lymphocytes infiltration compared with that in LBI. There are more tumor cells in the HBI than in LBI, with substantial differences in the gene expression profiles of these tumor cells. HBI may be the key area of PBZ-targeting therapy after surgical resection.

An integrated transcriptomic analysis of brain aging and strategies for healthy aging

Background

It is been noted that the expression levels of numerous genes undergo changes as individuals age, and aging stands as a primary factor contributing to age-related diseases. Nevertheless, it remains uncertain whether there are common aging genes across organs or tissues, and whether these aging genes play a pivotal role in the development of age-related diseases.

Methods

In this study, we screened for aging genes using RNAseq data of 32 human tissues from GTEx. RNAseq datasets from GEO were used to study whether aging genes drives age-related diseases, or whether anti-aging solutions could reverse aging gene expression.

Results

Aging transcriptome alterations showed that brain aging differ significantly from the rest of the body, furthermore, brain tissues were divided into four group according to their aging transcriptome alterations. Numerous genes were downregulated during brain aging, with functions enriched in synaptic function, ubiquitination, mitochondrial translation and autophagy. Transcriptome analysis of age-related diseases and retarding aging solutions showed that downregulated aging genes in the hippocampus further downregulation in Alzheimer's disease but were effectively reversed by high physical activity. Furthermore, the neuron loss observed during aging was reversed by high physical activity.

Conclusion

The downregulation of many genes is a major contributor to brain aging and neurodegeneration. High levels of physical activity have been shown to effectively reactivate these genes, making it a promising strategy to slow brain aging.

Gene choice in cancer cells is exclusive in ion transport but concurrent in DNA replication

Cancers share common cellular and physiological features. Little is known about whether distinctive gene expression patterns can be displayed at the single-cell level by gene families in cancer cells. The expression of gene homologs within a family can exhibit concurrence and exclusivity. Concurrence can promote all-or-none expression patterns of related genes and underlie alternative physiological states. Conversely, exclusive gene families express the same or similar number of homologs in each cell, allowing a broad repertoire of cell identities to be generated. We show that gene families involved in the cell-cycle and antigen presentation are expressed concurrently. Concurrence in the DNA replication complex MCM reflects the replicative status of cells, including cell lines and cancer-derived organoids. Exclusive expression requires precise regulatory mechanism, but cancer cells retain this form of control for ion homeostasis and extend it to gene families involved in cell migration. Thus, the cell adhesion-based identity of healthy cells is transformed to an identity based on migration in the population of cancer cells, reminiscent of epithelial-mesenchymal transition.

Artificial intelligence and omics in malignant gliomas

Glioblastoma multiforme (GBM) is one of the most common and aggressive type of malignant glioma with an average survival time of 12-18 mo. Despite the utilization of extensive surgical resections using cutting-edge neuroimaging, and advanced chemotherapy and radiotherapy, the prognosis remains unfavorable. The heterogeneity of GBM and the presence of the blood-brain barrier further complicate the therapeutic process. It is crucial to adopt a multifaceted approach in GBM research to understand its biology and advance toward effective treatments. In particular, omics research, which primarily includes genomics, transcriptomics, proteomics, and epigenomics, helps us understand how GBM develops, finds biomarkers, and discovers new therapeutic targets. The availability of large-scale multiomics data requires the development of computational models to infer valuable biological insights for the implementation of precision medicine. Artificial intelligence (AI) refers to a host of computational algorithms that is becoming a major tool capable of integrating large omics databases. Although the application of AI tools in GBM-omics is currently in its early stages, a thorough exploration of AI utilization to uncover different aspects of GBM (subtype classification, prognosis, and survival) would have a significant impact on both researchers and clinicians. Here, we aim to review and provide database resources of different AI-based techniques that have been used to study GBM pathogenesis using multiomics data over the past decade. We summarize different types of GBM-related omics resources that can be used to develop AI models. Furthermore, we explore various AI tools that have been developed using either individual or integrated multiomics data, highlighting their applications and limitations in the context of advancing GBM research and treatment.

Low expression of GRM4 is associated with poor prognosis and tumor immune infiltration in glioma

INTRODUCTION

The metabotropic glutamate receptor 4 (mGlu4, GRM4) exhibits significant expression within the central nervous system (CNS) and has been implicated to be correlated with a poor prognosis.

OBJECTIVE

This study was aimed to elucidate the relationship between the expression profile of GRM4 and the prognosis of glioma patients.

METHODS

RNA-sequencing datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and China Glioma Genome Atlas (CGGA) repositories were used to evaluate the potential relationship. The value of clinical prognostic about GRM4 was assessed using clinical survival data from CGGA and TCGA. The GEPIA database was used to select genes like GRM4. PPI network was constructed by the database of (STRING), GO and KEGG analyses were performed. TargetScan, TarBase, miRDB, and starBase were used to explore miRNAs that could regulate GRM4 expression. EWAS Data Hub, MethSurv, and MEXPRESS were used for the analysis and relationship between DNA methylation and GRM4 expression and prognosis in glioma. TIMER2.0 and CAMOIP databases were used to assess the association between immune cell infiltration and GRM4. Human GBM cell lines were used to validate the function of GRM4.

RESULTS

Our study shows that GRM4 is under expressed among gliomas and accompanied by poorer OS. Multivariate analysis showed that low mRNA expression of GRM4 was an independent factor of prognostic for shorter OS in all glioma patients. MiR-1262 affects the malignant phenotype of gliomas through GRM4. Methylation of DNA plays an important role in the instruction of GRM4 expression, the methylation level of GRM4 in glioma tissue is higher in comparison to normal tissue, and the higher methylation level was accompanied with the worse prognosis. Further analysis showed that GRM4 mRNA expression in GBM linked negatively with common lymphoid progenitor, Macrophage M1, Macrophage, and T cell CD4+ Th2, but not with the tumor purity. Overexpression of GRM4 prevents the migration of human GBM cell lines in vitro.

CONCLUSION

GRM4 may have a substantial impact on the infiltration of immune cells and serve as a valuable prognostic biomarker in gliomas.