MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

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.

Investigative needle core biopsies support multimodal deep-data generation in glioblastoma

Glioblastoma (GBM) is an aggressive primary brain cancer with few effective therapies. Stereotactic needle biopsies are routinely used for diagnosis; however, the feasibility and utility of investigative biopsies to monitor treatment response remains ill-defined. Here, we demonstrate the depth of data generation possible from routine stereotactic needle core biopsies and perform highly resolved multi-omics analyses, including single-cell RNA sequencing, spatial transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics on standard biopsy tissue obtained intra-operatively. We also examine biopsies taken from different locations and provide a framework for measuring spatial and genomic heterogeneity. Finally, we investigate the utility of stereotactic biopsies as a method for generating patient-derived xenograft (PDX) models. Multimodal dataset integration highlights spatially mapped immune cell-associated metabolic pathways and validates inferred cell-cell ligand-receptor interactions. In conclusion, investigative biopsies provide data-rich insight into disease processes and may be useful in evaluating treatment responses.

The epigenetic mechanisms involved in the treatment resistance of glioblastoma

Glioblastoma (GBM) is an aggressive malignant brain tumor with almost inevitable recurrence despite multimodal management with surgical resection and radio-chemotherapy. While several genetic, proteomic, cellular, and anatomic factors interplay to drive recurrence and promote treatment resistance, the epigenetic component remains among the most versatile and heterogeneous of these factors. Herein, the epigenetic landscape of GBM refers to a myriad of modifications and processes that can alter gene expression without altering the genetic code of cancer cells. These processes encompass DNA methylation, histone modification, chromatin remodeling, and non-coding RNA molecules, all of which have been found to be implicated in augmenting the tumor's aggressive behavior and driving its resistance to therapeutics. This review aims to delve into the underlying interactions that mediate this role for each of these epigenetic components. Further, it discusses the two-way relationship between epigenetic modifications and tumor heterogeneity and plasticity, which are crucial to effectively treat GBM. Finally, we build on the previous characterization of epigenetic modifications and interactions to explore specific targets that have been investigated for the development of promising therapeutic agents.

Splicing dysregulation in glioblastoma alters the function of cell migration-related genes

Glioblastoma (GBM) has a poor prognosis with a high recurrence and low survival rate. Previous RNA-seq analyses have revealed that alternative splicing (AS) plays a role in GBM progression. Here, we present a novel AS analysis method (Semi-Q) and describe its use to identify GBM-specific AS events. We analyzed RNA-seq data from normal brain (NB), normal human astrocytes (NHAs) and GBM samples, and found that comparison between NHA and GBM was especially informative. Importantly, this analysis revealed that genes encoding cell migration-related proteins, including filamins (FLNs) and actinins (ACTNs), were among those most affected by differential AS. Functional assays revealed that dysregulated AS of FLNA, B and C transcripts produced protein isoforms that not only altered transcription of cell proliferation-related genes but also led to enhanced cell migration, resistance to cell death and/or mitochondrial respiratory function, while a dysregulated AS isoform of ACTN4 enhanced cell migration. Together, our results indicate that cell migration and actin cytoskeleton-related genes are differentially regulated by AS in GBM, supporting a role for AS in facilitating tumor growth and invasiveness.

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.

Markers of tumor-associated macrophages and microglia exhibit high intratumoral heterogeneity in human glioblastoma tissue

BACKGROUND

Human glioblastoma multiforme (GBM) is a highly aggressive tumor with insufficient therapies available. Especially, novel concepts of immune therapies fail due to a complex immunosuppressive microenvironment, high mutational rates, and inter-patient variations. The intratumoral heterogeneity is currently not sufficiently investigated.

METHODS

Biopsies from six different locations were taken in a cohort of 16 GBM patients who underwent surgery. The tissue slides were analyzed utilizing high-content imaging microscopy and algorithm-based image quantification. Several immune markers for macrophage and microglia subpopulations were investigated. Flow cytometry was used to validate key results. Besides the surface marker, cytokines were measured and categorized based on their heterogenicity and overall expression.

RESULTS

M2-like antigens, including CD204, CD163, Arg1, and CSF1R, showed comparatively higher expression, with GFAP displaying the least intratumoral heterogeneity. In contrast, anti-tumor-macrophage-like antigens, such as PSGL-1, CD16, CD68, and MHC-II, exhibited low overall expression and concurrent high intratumoral heterogeneity. CD16 and PSGL-1 were the most heterogeneous antigens. High expression levels were observed for cytokines IL-6, VEGF, and CCL-2. VILIP-a was revealed to differentiate most in principle component analysis. Cytokines with the lowest overall expression, such as TGF-β1, β-NGF, TNF-α, and TREM1, showed low intratumoral heterogeneity, in contrast to βNGF, TNF-α, and IL-18, which displayed high heterogeneity despite low expression.

CONCLUSION

The study showed high intratumoral heterogeneity in GBM, emphasizing the need for a more detailed understanding of the tumor microenvironment. The described findings could be essential for future personalized treatment strategies and the implementation of reliable diagnostics in GBM.

Inferring gene regulatory networks of ALS from blood transcriptome profiles

One of the most robust approaches to the prediction of causal driver genes of complex diseases is to apply reverse engineering methods to infer a gene regulatory network (GRN) from gene expression profiles (GEPs). In this work, we analysed 794 GEPs of 1117 human whole-blood samples from Amyotrophic Lateral Sclerosis (ALS) patients and healthy subjects reported in the GSE112681 dataset. GRNs for ALS and healthy individuals were reconstructed by ARACNe-AP (Algorithm for the Reconstruction of Accurate Cellular Networks - Adaptive Partitioning). In order to examine phenotypic differences in the ALS population surveyed, several datasets were built by arranging GEPs according to sex, spinal or bulbar onset, and survival time. The designed reverse engineering methodology identified a significant number of potential ALS-promoting mechanisms and putative transcriptional biomarkers that were previously unknown. In particular, the characterization of ALS phenotypic networks by pathway enrichment analysis has identified a gender-specific disease signature, namely network activation related to the radiation damage response, reported in the networks of bulbar and female ALS patients. Also, focusing on a smaller interaction network, we selected some hub genes to investigate their inferred pathological and healthy subnetworks. The inferred GRNs revealed the interconnection of the four selected hub genes (TP53, SOD1, ALS2, VDAC3) with p53-mediated pathways, suggesting the potential neurovascular response to ALS neuroinflammation. In addition to being well consistent with literature data, our results provide a novel integrated view of ALS transcriptional regulators, expanding information on the possible mechanisms underlying ALS and also offering important insights for diagnostic purposes and for developing possible therapies for a disease yet incurable.

Oligodendrocyte-specific expression of PSG8-AS1 suggests a role in myelination with prognostic value in oligodendroglioma

The segmentally duplicated Pregnancy-specific glycoprotein (PSG) locus on chromosome 19q13 may be one of the most rapidly evolving in the human genome. It comprises ten coding genes (PSG1-9, 11) and one predominantly non-coding gene (PSG10) that are expressed in the placenta and gut, in addition to several poorly characterized long non-coding RNAs. We report that long non-coding RNA PSG8-AS1 has an oligodendrocyte-specific expression pattern and is co-expressed with genes encoding key myelin constituents. PSG8-AS1 exhibits two peaks of expression during human brain development coinciding with the most active periods of oligodendrogenesis and myelination. PSG8-AS1 orthologs were found in the genomes of several primates but significant expression was found only in the human, suggesting a recent evolutionary origin of its proposed role in myelination. Additionally, because co-deletion of chromosomes 1p/19q is a genomic marker of oligodendroglioma, expression of PSG8-AS1 was examined in these tumors. PSG8-AS1 may be a promising diagnostic biomarker for glioma, with prognostic value in oligodendroglioma.

REST-dependent glioma progression occurs independently of the repression of the long non-coding RNA HAR1A

The long non-coding RNA (lncRNA), HAR1A is emerging as a putative tumour suppressor. In non-neoplastic brain cells, REST suppresses HAR1A expression. In gliomas REST acts as an oncogene and is a potential therapeutic target. It is therefore conceivable that REST promotes glioma progression by down-regulating HAR1A. To test this hypothesis, glioma clinical databases were analysed to study: (I) HAR1A/REST correlation; (II) HAR1A and REST prognostic role; (III) molecular pathways associated with these genes. HAR1A expression and subcellular localization were studied in glioblastoma and paediatric glioma cells. REST function was also studied in these cells, by observing the effects of gene silencing on: (I) HAR1A expression; (II) cancer cell proliferation, apoptosis, migration; (III) expression of neural differentiation genes. The same phenotypes (and cell morphology) were studied in HAR1A overexpressing cells. Our results show that REST and HAR1A are negatively correlated in gliomas. Higher REST expression predicts worse prognosis in low-grade gliomas (the opposite is true for HAR1A). REST-silencing induces HAR1A upregulation. HAR1A is primarily detected in the nucleus. REST-silencing dramatically reduces cell proliferation and induces apoptosis, but HAR1A overexpression has no major effect on investigated cell phenotypes. We also show that REST regulates the expression of neural differentiation genes and that its oncogenic function is primarily HAR1A-independent.

Single-cell multi-omics sequencing uncovers region-specific plasticity of glioblastoma for complementary therapeutic targeting

Glioblastoma (GBM) cells are highly heterogeneous and invasive, leading to treatment resistance and relapse. However, the molecular regulation in and distal to tumors remains elusive. Here, we collected paired tissues from the tumor core (TC) and peritumoral brain (PTB) for integrated snRNA-seq and snATAC-seq analyses. Tumor cells infiltrating PTB from TC behave more like oligodendrocyte progenitor cells than astrocytes at the transcriptome level. Dual-omics analyses further suggest that the distal regulatory regions in the tumor genome and specific transcription factors are potential determinants of regional heterogeneity. Notably, while activator protein 1 (AP-1) is active in all GBM states, its activity declines from TC to PTB, with another transcription factor, BACH1, showing the opposite trend. Combined inhibition of AP-1 and BACH1 more efficiently attenuates the tumor progression in mice and prolongs survival than either single-target treatment. Together, our work reveals marked molecular alterations of infiltrated GBM cells and a synergy of combination therapy targeting intratumor heterogeneity in and distal to GBM.

CLIC4 Is a New Biomarker for Glioma Prognosis

BACKGROUND

Chloride Intracellular Channel 4 (CLIC4) plays a versatile role in cellular functions beyond its role in primary chloride ion transport. Notably, many studies found an association between CLIC4 expression and cancers. However, the correlation between CLIC4 and glioma remains to be uncovered.

METHODS

A total of 3162 samples from nine public datasets were analyzed to reveal the relationship between CLIC4 expression and glioma malignancy or prognosis. Immunohistochemistry (IHC) staining was performed to examine the results in an in-house cohort. A nomogram model was constructed to predict the prognosis. Functional enrichment analysis was employed to find CLIC4-associated differentially expressed genes in glioma. Immune infiltration analysis, correlation analysis, and IHC staining were employed, aiming to examine the correlation between CLIC4 expression, immune cell infiltration, and ECM (extracellular matrix)-related genes.

RESULTS

The expression level of CLIC4 was correlated with the malignancy of glioma and the prognosis of patients. More aggressive gliomas and mesenchymal GBM are associated with a high expression of CLIC4. Gliomas with IDH mutation or 1p19q codeletion express a low level of CLIC4, and a high expression of CLIC4 correlates with poor prognosis. The nomogram model shows a good predictive performance. The DEGs (differentially expressed genes) in gliomas with high and low CLIC4 expression are enriched in extracellular matrix and immune functions. On the one hand, gliomas with high CLIC4 expression have a greater presence of macrophages, neutrophils, and eosinophils; on the other hand, a high CLIC4 expression in gliomas is positively associated with ECM-related genes.

CONCLUSIONS

Compared to glioma cells with low CLIC4 expression, gliomas with high CLIC4 expression exhibit greater malignancy and poorer prognosis. Our findings indicate that a high level of CLIC4 correlates with high expression of ECM-related genes and the infiltration of macrophages, neutrophils, and eosinophils within glioma tissues.

Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network

OBJECTIVES

Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the value of diffusion-weighted imaging (DWI) for predicting pTERT mutation status in WHO grade IV glioma.

METHODS

MRI data and molecular information were obtained for 266 patients with WHO grade IV glioma at the hospital and divided into training and validation sets. The ratio of training to validation set was approximately 10:3. We trained the same residual convolutional neural network (ResNet) for each MR modality, including structural MRIs (T1-weighted, T2-weighted, and contrast-enhanced T1-weighted) and DWI*, to compare the predictive capacities between DWI and conventional structural MRI. We also explored the effects of different regions of interest on pTERT mutation status prediction outcomes.

RESULTS

Structural MRI modalities poorly predicted the pTERT mutation status (accuracy = 51%-54%; area under the curve [AUC]=0.545-0.571), whereas DWI combined with its apparent diffusive coefficient maps yielded the best predictive performance (accuracy = 85.2%, AUC = 0.934). Including the radiological and clinical characteristics did not further improve the performance for predicting pTERT mutation status. The entire tumour volume yielded the best prediction performance.

CONCLUSIONS

DWI technology shows promising potential for predicting pTERT mutations in WHO grade IV glioma and should be included in the MRI protocol for WHO grade IV glioma in clinical practice.

ADVANCES IN KNOWLEDGE

This is the first large-scale model study to validate the predictive value of DWI for pTERT in WHO grade IV glioma.

IDH Mutations in Glioma: Molecular, Cellular, Diagnostic, and Clinical Implications

In 2021, the World Health Organization classified isocitrate dehydrogenase (IDH) mutant gliomas as a distinct subgroup of tumors with genetic changes sufficient to enable a complete diagnosis. Patients with an IDH mutant glioma have improved survival which has been further enhanced by the advent of targeted therapies. IDH enzymes contribute to cellular metabolism, and mutations to specific catalytic residues result in the neomorphic production of D-2-hydroxyglutarate (D-2-HG). The accumulation of D-2-HG results in epigenetic alterations, oncogenesis and impacts the tumor microenvironment via immunological modulations. Here, we summarize the molecular, cellular, and clinical implications of IDH mutations in gliomas as well as current diagnostic techniques.

Regulation of HTT mRNA Biogenesis: The Norm and Pathology

Huntington's disease (HD) is a neurodegenerative disorder caused by the expansion of the CAG repeat in exon 1 of the HTT gene, leading to the formation of a toxic variant of the huntingtin protein. It is a rare but severe hereditary disease for which no effective treatment method has been found yet. The primary therapeutic targets include the mutant protein and the mutant mRNA of HTT. Current clinical trial approaches in gene therapy involve the application of splice modulation, siRNA, or antisense oligonucleotides for RNA-targeted knockdown of HTT. However, these approaches do not take into account the diversity of HTT transcript isoforms in the normal conditions and in HD. In this review, we discuss the features of transcriptional regulation and processing that lead to the formation of various HTT mRNA variants, each of which may uniquely contribute to the progression of the disease. Furthermore, understanding the role of known transcription factors of HTT in pathology may aid in the development of potentially new therapeutic tools based on endogenous regulators.

Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of recurrent glioblastoma. This study addresses the need for non-invasive approaches to map heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We developed BioNet, a biologically-informed neural network, to predict regional distributions of two primary tissue-specific gene modules: proliferating tumor (Pro) and reactive/inflammatory cells (Inf). BioNet significantly outperforms existing methods (p < 2e-26). In cross-validation, BioNet achieved AUCs of 0.80 (Pro) and 0.81 (Inf), with accuracies of 80% and 75%, respectively. In blind tests, BioNet achieved AUCs of 0.80 (Pro) and 0.76 (Inf), with accuracies of 81% and 74%. Competing methods had AUCs lower or around 0.6 and accuracies lower or around 70%. BioNet's voxel-level prediction maps reveal intratumoral heterogeneity, potentially improving biopsy targeting and treatment evaluation. This non-invasive approach facilitates regular monitoring and timely therapeutic adjustments, highlighting the role of ML in precision medicine.

The peritumoral brain zone in glioblastoma: a review of the pretreatment approach

Glioblastomas are the most common and aggressive form of malignant primary brain tumors in adults. The standard treatment is surgical resection followed by radiotherapy and chemotherapy. Despite optimal treatment methods, the prognosis for patients remains poor. Preoperative determination of glioblastoma margins remains beneficial for the complete removal of the tumor mass. Radiotherapy is essential for post-surgery treatment, but radioresistance is a significant challenge contributing to high mortality rates. Advanced imaging technologies are used to analyze the changes in the peritumoral brain zone (PTZ). Consequently, they may lead to the development of novel therapeutic options, especially targeting the marginal parts of a tumor, which could improve the prognosis of glioblastoma patients. The clinical presentation of glioblastoma is heterogeneous and mostly depends on the location and size of a tumor. Glioblastomas are characterized by both intratumoral cellular heterogeneity and an extensive, diffuse infiltration into the normal tissue bordering a tumor called the PTZ. Neuroimaging techniques, such as diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), proton magnetic resonance spectroscopy (1H MRS), and chemical exchange saturation transfer (CEST) are useful methods in the evaluation of the tumor infiltration and thus the resection margin.

Integrated bioinformatics analysis and experimental validation on malignant progression and immune cell infiltration of LTBP2 in gliomas

BACKGROUND

Gliomas are the highly aggressive brain tumor and also the most devastating human tumors. The latent TGF binding proteins (LTBP) had been found to be involved in malignant biological process and could be used as potent biomarkers in several solid tumors. While the role of LTBP family in human glioma remain to be elucidated.

METHODS

Normalized gene expression and corresponding clinical data of 2407 gliomas samples in public datasets were downloaded from Gliovis. Kaplan-Meier methods and Cox regression analysis was used for survival analyses.Western blot (WB) and Immunohistochemical (IHC) testing were employed to test LTBPs protein level in 154 gliomas samples. Correlation between LTBP2 expression and immune infiltration was evaluated by immunofluorescence (IF) and IHC in glioma tissues. CCK8 and flow cytometric analysis were used to detect the effect of LTBP2 on glioma cells. Orthotopic glioma- mouse models were utilized to evaluate effects in vivo.

RESULTS

LTBP2 mRNA level was dramatically higher in glioma samples compared with non-tumor brain tissues in XENA-TCGA_GTEx, Gill and Gravendeel datasets (all P < 0.01), and its expression positively correlated with glioma WHO grade, IDH1/2 wildtype and mesenchymal subtypes. These results were confirmed by In-house cohort which was detected by WB and IHC. We found that gliomas patients with high LTBP2 level had shorter OS than those with low LTBP2 level. LTBP2 expression significantly associated with glioma immune score (Spearman r = 0.68, P < 0.01)) and strongly correlated with infiltration degreee of macrophages both in lower grade gliomas (LGG) and GBM. Knocking down LTBP2 obviously reduced proliferation and enhanced sensitivity to temozolomide in U87 and U251 cells. Nude mice with lower expression of LTBP2 had slower tumor growth, and accompanied by less tumor-associated macrophages (TAMs) infiltration detected by IHC staining in vivo. Finally, low LTBP2 expression glioma patients who received chemotherapy survived longer than patients with high LTBP2 expression.

CONCLUSION

LTBP2 could be used as a prognostic marker, and high LTBP2 expression related to abundant TAMs infiltration and with a worse response to chemotherapy.

Comprehensive Bioinformatics Analysis Reveals the Potential Role of the hsa_circ_0001081/miR-26b-5p Axis in Regulating COL15A1 and TRIB3 within Hypoxia-Induced miRNA/mRNA Networks in Glioblastoma Cells

Background/Objectives: The intrinsic molecular heterogeneity of glioblastoma (GBM) is one of the main reasons for its resistance to conventional treatment. Mesenchymal GBM niches are associated with hypoxic signatures and a negative influence on patients' prognosis. To date, competing endogenous RNA (ceRNA) networks have been shown to have a broad impact on the progression of various cancers. In this study, we decided to construct hypoxia-specific microRNA/ messengerRNA (miRNA/mRNA) networks with a putative circular RNA (circRNA) regulatory component using available bioinformatics tools. Methods: For ceRNA network construction, we combined publicly available data deposited in the Gene Expression Omnibus (GEO) and interaction pairs obtained from miRTarBase and circBank; a differential expression analysis of GBM cells was performed with limma and deseq2. For the gene ontology (GO) enrichment analysis, we utilized clusterProfiler; GBM molecular subtype analysis was performed in the Glioma Bio Discovery Portal (Glioma-BioDP). Results: We observed that miR-26b-5p, generally considered a tumor suppressor, was upregulated under hypoxic conditions in U-87 MG cells. Moreover, miR-26b-5p could potentially inhibit TRIB3, a gene associated with tumor proliferation. Protein-protein interaction (PPI) network and GO enrichment analyses identified a hypoxia-specific subcluster enriched in collagen-associated terms, with six genes highly expressed in the mesenchymal glioma group. This subcluster included hsa_circ_0001081/miR-26b-5p-affected COL15A1, a gene downregulated in hypoxic U-87 MG cells yet highly expressed in the mesenchymal GBM subtype. Conclusions: The interplay between miR-26b-5p, COL15A1, and TRIB3 suggests a complex regulatory mechanism that may influence the extracellular matrix composition and the mesenchymal transformation in GBM. However, the precise impact of the hsa_circ_0001081/miR-26b-5p axis on collagen-associated processes in hypoxia-induced GBM cells remains unclear and warrants further investigation.

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

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

Unveiling the Inflammatory Landscape of Recurrent Glioblastoma through Histological-Based Assessments

The glioblastoma (GBM) tumor microenvironment consists of a heterogeneous mixture of neoplastic and non-neoplastic cells, including immune cells. Tumor recurrence following standard-of-care therapy results in a rich landscape of inflammatory cells throughout the glioma-infiltrated cortex. Immune cells consisting of glioma-associated macrophages and microglia (GAMMs) overwhelmingly constitute the bulk of the recurrent glioblastoma (rGBM) microenvironment, in comparison to the highly cellular and proliferative tumor microenvironment characteristic of primary GBM. These immune cells dynamically interact within the tumor microenvironment and can contribute to disease progression and therapy resistance while also providing novel targets for emerging immunotherapies. Within these varying contexts, histological-based assessments of immune cells in rGBM, including immunohistochemistry (IHC) and immunofluorescence (IF), offer a critical way to visualize and examine the inflammatory landscape. Here, we exhaustively review the available body of literature on the inflammatory landscape in rGBM as identified through histological-based assessments. We highlight the heterogeneity of immune cells throughout the glioma-infiltrated cortex with a focus on microglia and macrophages, drawing insights from canonical and novel immune-cell histological markers to estimate cell phenotypes and function. Lastly, we discuss opportunities for immunomodulatory treatments aiming to harness the inflammatory landscape in rGBM.

Complex Diagnostic Challenges in Glioblastoma: The Role of 18F-FDOPA PET Imaging

Glioblastoma multiforme (GBM) remains one of the most aggressive and lethal forms of brain cancer, characterized by rapid proliferation and diffuse infiltration into the surrounding brain tissues. Despite advancements in therapeutic approaches, the prognosis for GBM patients is poor, with median survival times rarely exceeding 15 months post-diagnosis. An accurate diagnosis, treatment planning, and monitoring are crucial for improving patient outcomes. Core imaging modalities such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are indispensable in the initial diagnosis and ongoing management of GBM. Histopathology remains the gold standard for definitive diagnoses, guiding treatment by providing molecular and genetic insights into the tumor. Advanced imaging modalities, particularly positron emission tomography (PET), play a pivotal role in the management of GBM. Among these, 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-FDOPA) PET has emerged as a powerful tool due to its superior specificity and sensitivity in detecting GBM and monitoring treatment responses. This introduction provides a comprehensive overview of the multifaceted role of 18F-FDOPA PET in GBM, covering its diagnostic accuracy, potential as a biomarker, integration into clinical workflows, impact on patient outcomes, technological and methodological advancements, comparative effectiveness with other PET tracers, and its cost-effectiveness in clinical practice. Through these perspectives, we aim to underscore the significant contributions of 18F-FDOPA PET to the evolving landscape of GBM management and its potential to enhance both clinical and economic outcomes for patients afflicted with this formidable disease.

Histomolecular Validation of [18F]-FACBC in Gliomas Using Image-Localized Biopsies

BACKGROUND

Gliomas have a heterogeneous nature, and identifying the most aggressive parts of the tumor and defining tumor borders are important for histomolecular diagnosis, surgical resection, and radiation therapy planning. This study evaluated [18F]-FACBC PET for glioma tissue classification.

METHODS

Pre-surgical [18F]-FACBC PET/MR images were used during surgery and image-localized biopsy sampling in patients with high- and low-grade glioma. TBR was compared to histomolecular results to determine optimal threshold values, sensitivity, specificity, and AUC values for the classification of tumor tissue. Additionally, PET volumes were determined in patients with glioblastoma based on the optimal threshold. [18F]-FACBC PET volumes and diagnostic accuracy were compared to ce-T1 MRI. In total, 48 biopsies from 17 patients were analyzed.

RESULTS

[18F]-FACBC had low uptake in non-glioblastoma tumors, but overall higher sensitivity and specificity for the classification of tumor tissue (0.63 and 0.57) than ce-T1 MRI (0.24 and 0.43). Additionally, [18F]-FACBC TBR was an excellent classifier for IDH1-wildtype tumor tissue (AUC: 0.83, 95% CI: 0.71-0.96). In glioblastoma patients, PET tumor volumes were on average eight times larger than ce-T1 MRI volumes and included 87.5% of tumor-positive biopsies compared to 31.5% for ce-T1 MRI.

CONCLUSION

The addition of [18F]-FACBC PET to conventional MRI could improve tumor classification and volume delineation.

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

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

RPS24 alternative splicing is a marker of cancer progression and epithelial-mesenchymal transition

Although alternative splicing (AS) is a major mechanism that adds diversity to gene expression patterns, its precise role in generating variability in ribosomal proteins, known as ribosomal heterogeneity, remains unclear. The ribosomal protein S24 (RPS24) gene, encoding a ribosomal component, undergoes AS; however, in-depth studies have been challenging because of three microexons between exons 4 and 6. We conducted a detailed analysis of RPS24 AS isoforms using a direct approach to investigate the splicing junctions related to these microexons, focusing on four AS isoforms. Each of these isoforms showed tissue specificity and relative differences in expression among cancer types. Significant differences in the proportions of these RPS24 AS isoforms between cancerous and normal tissues across diverse cancer types were also observed. Our study highlighted a significant correlation between the expression levels of a specific RPS24 AS isoform and the epithelial-mesenchymal transition process in lung and breast cancers. Our research contributes to a better understanding of the intricate regulatory mechanisms governing AS of ribosomal protein genes and highlights the biological implications of RPS24 AS isoforms in tissue development and tumorigenesis.

Ultrasound-mediated delivery of doxorubicin to the brain results in immune modulation and improved responses to PD-1 blockade in gliomas

Given the marginal penetration of most drugs across the blood-brain barrier, the efficacy of various agents remains limited for glioblastoma (GBM). Here we employ low-intensity pulsed ultrasound (LIPU) and intravenously administered microbubbles (MB) to open the blood-brain barrier and increase the concentration of liposomal doxorubicin and PD-1 blocking antibodies (aPD-1). We report results on a cohort of 4 GBM patients and preclinical models treated with this approach. LIPU/MB increases the concentration of doxorubicin by 2-fold and 3.9-fold in the human and murine brains two days after sonication, respectively. Similarly, LIPU/MB-mediated blood-brain barrier disruption leads to a 6-fold and a 2-fold increase in aPD-1 concentrations in murine brains and peritumoral brain regions from GBM patients treated with pembrolizumab, respectively. Doxorubicin and aPD-1 delivered with LIPU/MB upregulate major histocompatibility complex (MHC) class I and II in tumor cells. Increased brain concentrations of doxorubicin achieved by LIPU/MB elicit IFN-γ and MHC class I expression in microglia and macrophages. Doxorubicin and aPD-1 delivered with LIPU/MB results in the long-term survival of most glioma-bearing mice, which rely on myeloid cells and lymphocytes for their efficacy. Overall, this translational study supports the utility of LIPU/MB to potentiate the antitumoral activities of doxorubicin and aPD-1 for GBM.

A prognostic neural epigenetic signature in high-grade glioma

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target with roles in proliferation and invasion. Resistance to KIF11 inhibitors, which has mainly been studied in animal models, presents significant challenges. We use lineage-tracing barcodes and single-cell RNA sequencing to analyze resistance in patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lose their neural lineage identity and become mesenchymal, which is associated with poor prognosis. Conversely, cells subjected to long-term ispinesib treatment exhibit a proneural phenotype. We generate patient-derived xenografts and show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Moreover, treatment of human ex vivo GBM slices with ispinesib demonstrates phenotypic alignment with in vitro responses, underscoring the clinical relevance of our findings. Finally, using retrospective lineage tracing, we identify drugs that are synergistic with ispinesib.

Predicting glioblastoma recurrence using multiparametric MR imaging of non-enhancing peritumoral regions at baseline

Background

To assess the feasibility of multiparametric magnetic resonance imaging in predicting tumor recurrence in nonenhancing peritumoral regions in patients with glioblastoma at baseline.

Methods

Fifty-eight patients with recurrent glioblastoma underwent multiparametric magnetic resonance imaging, including T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging. Nonenhancing peritumoral regions with glioblastoma recurrence were identified by coregistering preoperative and post-recurrent magnetic resonance images. Regions of interest were placed in nonenhancing peritumoral regions with and without tumor recurrence to calculate the apparent diffusion coefficient value, and relative ratios of T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and cerebral blood volume values.

Results

Significant lower relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative apparent diffusion coefficient but higher relative cerebral blood volume values were found in the nonenhancing peritumoral regions with tumor recurrence than without recurrence (all P < 0.05). The threshold values ≥ 0.89 for relative cerebral blood volume provide the optimal performance for predicting the nonenhancing peritumoral regions with future tumor recurrence, with the sensitivity, specificity, and accuracy of 84.7%, 83.6%, and 85.8%, respectively. The combination of relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative cerebral blood volume can provide better predictive performance than relative cerebral blood volume (P = 0.015).

Conclusion

The combined use of T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging can effectively estimate the risk of future tumor recurrence at baseline.

Comprehensive understanding of glioblastoma molecular phenotypes: classification, characteristics, and transition

Among central nervous system-associated malignancies, glioblastoma (GBM) is the most common and has the highest mortality rate. The high heterogeneity of GBM cell types and the complex tumor microenvironment frequently lead to tumor recurrence and sudden relapse in patients treated with temozolomide. In precision medicine, research on GBM treatment is increasingly focusing on molecular subtyping to precisely characterize the cellular and molecular heterogeneity, as well as the refractory nature of GBM toward therapy. Deep understanding of the different molecular expression patterns of GBM subtypes is critical. Researchers have recently proposed tetra fractional or tripartite methods for detecting GBM molecular subtypes. The various molecular subtypes of GBM show significant differences in gene expression patterns and biological behaviors. These subtypes also exhibit high plasticity in their regulatory pathways, oncogene expression, tumor microenvironment alterations, and differential responses to standard therapy. Herein, we summarize the current molecular typing scheme of GBM and the major molecular/genetic characteristics of each subtype. Furthermore, we review the mesenchymal transition mechanisms of GBM under various regulators.

MT-125 Inhibits Non-Muscle Myosin IIA and IIB, Synergizes with Oncogenic Kinase Inhibitors, and Prolongs Survival in Glioblastoma

We have identified a NMIIA and IIB-specific small molecule inhibitor, MT-125, and have studied its effects in GBM. MT-125 has high brain penetrance and retention and an excellent safety profile; blocks GBM invasion and cytokinesis, consistent with the known roles of NMII; and prolongs survival as a single agent in murine GBM models. MT-125 increases signaling along both the PDGFR- and MAPK-driven pathways through a mechanism that involves the upregulation of reactive oxygen species, and it synergizes with FDA-approved PDGFR and mTOR inhibitors in vitro . Combining MT-125 with sunitinib, a PDGFR inhibitor, or paxalisib, a combined PI3 Kinase/mTOR inhibitor significantly improves survival in orthotopic GBM models over either drug alone, and in the case of sunitinib, markedly prolongs survival in ∼40% of mice. Our results provide a powerful rationale for developing NMII targeting strategies to treat cancer and demonstrate that MT-125 has strong clinical potential for the treatment of GBM.

Highlights

MT-125 is a highly specific small molecule inhibitor of non-muscle myosin IIA and IIB, is well-tolerated, and achieves therapeutic concentrations in the brain with systemic dosing.Treating preclinical models of glioblastoma with MT-125 produces durable improvements in survival.MT-125 stimulates PDGFR- and MAPK-driven signaling in glioblastoma and increases dependency on these pathways.Combining MT-125 with an FDA-approved PDGFR inhibitor in a mouse GBM model synergizes to improve median survival over either drug alone, and produces tumor free, prolonged survival in over 40% of mice.

Peritumoral Brain Zone in Astrocytoma: Morphology, Molecular Aspects, and Clinical Manifestations (Review)

A peritumoral brain zone is an area between a tumor and nontumorous brain tissue with tumor cell infiltration. The identification of this area is sufficiently difficult due to the lack of clear morphological or some other criteria. Besides, its dimensions may vary considerably. In the present review, we have analyzed the available data on the morphological structure and metabolism of peritumoral zone in astrocytomes, and considered the main molecular and genetic aspects and clinical manifestations. Exploration of the peritumoral zone is of great importance for determining the extent of resection to prevent recurrence and to reveal the causes and mechanisms of continued tumor growth.

The growth factor EPIREGULIN promotes basal progenitor cell proliferation in the developing neocortex

Neocortex expansion during evolution is linked to higher numbers of neurons, which are thought to result from increased proliferative capacity and neurogenic potential of basal progenitor cells during development. Here, we show that EREG, encoding the growth factor EPIREGULIN, is expressed in the human developing neocortex and in gorilla cerebral organoids, but not in the mouse neocortex. Addition of EPIREGULIN to the mouse neocortex increases proliferation of basal progenitor cells, whereas EREG ablation in human cortical organoids reduces proliferation in the subventricular zone. Treatment of cortical organoids with EPIREGULIN promotes a further increase in proliferation of gorilla but not of human basal progenitor cells. EPIREGULIN competes with the epidermal growth factor (EGF) to promote proliferation, and inhibition of the EGF receptor abrogates the EPIREGULIN-mediated increase in basal progenitor cells. Finally, we identify putative cis-regulatory elements that may contribute to the observed inter-species differences in EREG expression. Our findings suggest that species-specific regulation of EPIREGULIN expression may contribute to the increased neocortex size of primates by providing a tunable pro-proliferative signal to basal progenitor cells in the subventricular zone.

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

Intratumoral heterogeneity poses a significant challenge to the diagnosis and treatment of glioblastoma (GBM). This heterogeneity is further exacerbated during GBM recurrence, as treatment-induced reactive changes produce additional intratumoral heterogeneity that is ambiguous to differentiate on clinical imaging. There is an urgent need to develop non-invasive approaches to map the heterogeneous landscape of histopathological alterations throughout the entire lesion for each patient. We propose to predictively fuse Magnetic Resonance Imaging (MRI) with the underlying intratumoral heterogeneity in recurrent GBM using machine learning (ML) by leveraging image-localized biopsies with their associated locoregional MRI features. To this end, we develop BioNet, a biologically-informed neural network model, to predict regional distributions of three tissue-specific gene modules: proliferating tumor, reactive/inflammatory cells, and infiltrated brain tissue. BioNet offers valuable insights into the integration of multiple implicit and qualitative biological domain knowledge, which are challenging to describe in mathematical formulations. BioNet performs significantly better than a range of existing methods on cross-validation and blind test datasets. Voxel-level prediction maps of the gene modules by BioNet help reveal intratumoral heterogeneity, which can improve surgical targeting of confirmatory biopsies and evaluation of neuro-oncological treatment effectiveness. The non-invasive nature of the approach can potentially facilitate regular monitoring of the gene modules over time, and making timely therapeutic adjustment. These results also highlight the emerging role of ML in precision medicine.

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

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

Intrinsic and Microenvironmental Drivers of Glioblastoma Invasion

Gliomas are diffusely infiltrating brain tumors whose prognosis is strongly influenced by their extent of invasion into the surrounding brain tissue. While lower-grade gliomas present more circumscribed borders, high-grade gliomas are aggressive tumors with widespread brain infiltration and dissemination. Glioblastoma (GBM) is known for its high invasiveness and association with poor prognosis. Its low survival rate is due to the certainty of its recurrence, caused by microscopic brain infiltration which makes surgical eradication unattainable. New insights into GBM biology at the single-cell level have enabled the identification of mechanisms exploited by glioma cells for brain invasion. In this review, we explore the current understanding of several molecular pathways and mechanisms used by tumor cells to invade normal brain tissue. We address the intrinsic biological drivers of tumor cell invasion, by tackling how tumor cells interact with each other and with the tumor microenvironment (TME). We focus on the recently discovered neuronal niche in the TME, including local as well as distant neurons, contributing to glioma growth and invasion. We then address the mechanisms of invasion promoted by astrocytes and immune cells. Finally, we review the current literature on the therapeutic targeting of the molecular mechanisms of invasion.

Molecular and immunological features of TREM1 and its emergence as a prognostic indicator in glioma

Triggering receptor expressed on myeloid cells 1 (TREM1), which belongs to the Ig-like superfamily expressed on myeloid cells, is reportedly involved in various diseases but has rarely been studied in glioma. In this study, the prognostic value and functional roles of TREM2 in glioma were analyzed. TERM1 was observed to be significantly upregulated in GBM compared to in other grade gliomas and was associated with poor prognosis. Increased TREM1 accompanied distinct mutation and amplification of driver oncogenes. Moreover, gene ontology and KEGG analyses showed that TREM1 might play a role in immunologic biological processes in glioma. TREM1 was also found to be tightly correlated with immune checkpoint molecules. xCell research revealed a link between TREM1 expression and multiple immune cell types, especially monocytes and macrophages. Single-cell analysis and immunofluorescence results showed that macrophages expressed TREM1. In vitro, inhibition of TREM1 signaling could result in a decrease in tumor-promoting effects of monocytes/TAMs. In summary, TREM1 may be a potential independent prognostic factor and immune target, which might provide new avenues to improve the efficacy of immunotherapy in glioma patients.

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Single-nucleus expression characterization of non-enhancing region of recurrent high-grade glioma

Background

Non-enhancing (NE) infiltrating tumor cells beyond the contrast-enhancing (CE) bulk of tumor are potential propagators of recurrence after gross total resection of high-grade glioma.

Methods

We leveraged single-nucleus RNA sequencing on 15 specimens from recurrent high-grade gliomas (n = 5) to compare prospectively identified biopsy specimens acquired from CE and NE regions. Additionally, 24 CE and 22 NE biopsies had immunohistochemical staining to validate RNA findings.

Results

Tumor cells in NE regions are enriched in neural progenitor cell-like cellular states, while CE regions are enriched in mesenchymal-like states. NE glioma cells have similar proportions of proliferative and putative glioma stem cells relative to CE regions, without significant differences in % Ki-67 staining. Tumor cells in NE regions exhibit upregulation of genes previously associated with lower grade gliomas. Our findings in recurrent GBM paralleled some of the findings in a re-analysis of a dataset from primary GBM. Cell-, gene-, and pathway-level analyses of the tumor microenvironment in the NE region reveal relative downregulation of tumor-mediated neovascularization and cell-mediated immune response, but increased glioma-to-nonpathological cell interactions.

Conclusions

This comprehensive analysis illustrates differing tumor and nontumor landscapes of CE and NE regions in high-grade gliomas, highlighting the NE region as an area harboring likely initiators of recurrence in a pro-tumor microenvironment and identifying possible targets for future design of NE-specific adjuvant therapy. These findings also support the aggressive approach to resection of tumor-bearing NE regions.

Investigative needle core biopsies for multi-omics in Glioblastoma

Glioblastoma (GBM) is a primary brain cancer with an abysmal prognosis and few effective therapies. The ability to investigate the tumor microenvironment before and during treatment would greatly enhance both understanding of disease response and progression, as well as the delivery and impact of therapeutics. Stereotactic biopsies are a routine surgical procedure performed primarily for diagnostic histopathologic purposes. The role of investigative biopsies - tissue sampling for the purpose of understanding tumor microenvironmental responses to treatment using integrated multi-modal molecular analyses ('Multi-omics") has yet to be defined. Secondly, it is unknown whether comparatively small tissue samples from brain biopsies can yield sufficient information with such methods. Here we adapt stereotactic needle core biopsy tissue in two separate patients. In the first patient with recurrent GBM we performed highly resolved multi-omics analysis methods including single cell RNA sequencing, spatial-transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics from biopsy tissue that was obtained from a single procedure. In a second patient we analyzed multi-regional core biopsies to decipher spatial and genomic variance. We also investigated the utility of stereotactic biopsies as a method for generating patient derived xenograft models in a separate patient cohort. Dataset integration across modalities showed good correspondence between spatial modalities, highlighted immune cell associated metabolic pathways and revealed poor correlation between RNA expression and the tumor MHC Class I immunopeptidome. In conclusion, stereotactic needle biopsy cores are of sufficient quality to generate multi-omics data, provide data rich insight into a patient's disease process and tumor immune microenvironment and can be of value in evaluating treatment responses.

One sentence summary

Integrative multi-omics analysis of stereotactic needle core biopsies in glioblastoma.

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol

Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.

Revealing the biology behind MRI signatures in high grade glioma

Magnetic resonance imaging (MRI) measurements are routinely collected during the treatment of high-grade gliomas (HGGs) to characterize tumor boundaries and guide surgical tumor resection. Using spatially matched MRI and transcriptomics we discovered HGG tumor biology captured by MRI measurements. We strategically overlaid the spatially matched omics characterizations onto a pre-existing transcriptional map of glioblastoma multiforme (GBM) to enhance the robustness of our analyses. We discovered that T1+C measurements, designed to capture vasculature and blood brain barrier (BBB) breakdown and subsequent contrast extravasation, also indirectly reveal immune cell infiltration. The disruption of the vasculature and BBB within the tumor creates a permissive infiltrative environment that enables the transmigration of anti-inflammatory macrophages into tumors. These relationships were validated through histology and enrichment of genes associated with immune cell transmigration and proliferation. Additionally, T2-weighted (T2W) and mean diffusivity (MD) measurements were associated with angiogenesis and validated using histology and enrichment of genes involved in neovascularization. Furthermore, we establish an unbiased approach for identifying additional linkages between MRI measurements and tumor biology in future studies, particularly with the integration of novel MRI techniques. Lastly, we illustrated how noninvasive MRI can be used to map HGG biology spatially across a tumor, and this provides a platform to develop diagnostics, prognostics, or treatment efficacy biomarkers to improve patient outcomes.

Single-cell transcriptomic and neuropathologic analysis reveals dysregulation of the integrated stress response in progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is a sporadic neurodegenerative tauopathy variably affecting brainstem and cortical structures and characterized by tau inclusions in neurons and glia. The precise mechanism whereby these protein aggregates lead to cell death remains unclear. To investigate the contribution of these different cellular abnormalities to PSP pathogenesis, we performed single-nucleus RNA sequencing and analyzed 45,559 high quality nuclei targeting the subthalamic nucleus and adjacent structures from human post-mortem PSP brains with varying degrees of pathology compared to controls. Cell-type specific differential expression and pathway analysis identified both common and discrete changes in numerous pathways previously implicated in PSP and other neurodegenerative disorders. This included EIF2 signaling, an adaptive pathway activated in response to diverse stressors, which was the top activated pathway in vulnerable cell types. Using immunohistochemistry, we found that activated eIF2α was positively correlated with tau pathology burden in vulnerable brain regions. Multiplex immunofluorescence localized activated eIF2α positivity to hyperphosphorylated tau (p-tau) positive neurons and ALDH1L1-positive astrocytes, supporting the increased transcriptomic EIF2 activation observed in these vulnerable cell types. In conclusion, these data provide insights into cell-type-specific pathological changes in PSP and support the hypothesis that failure of adaptive stress pathways play a mechanistic role in the pathogenesis and progression of PSP.

Current Knowledge about the Peritumoral Microenvironment in Glioblastoma

Glioblastoma is a deadly disease, with a mean overall survival of less than 2 years from diagnosis. Recurrence after gross total surgical resection and adjuvant chemo-radiotherapy almost invariably occurs within the so-called peritumoral brain zone (PBZ). The aim of this narrative review is to summarize the most relevant findings about the biological characteristics of the PBZ currently available in the medical literature. The PBZ presents several peculiar biological characteristics. The cellular landscape of this area is different from that of healthy brain tissue and is characterized by a mixture of cell types, including tumor cells (seen in about 30% of cases), angiogenesis-related endothelial cells, reactive astrocytes, glioma-associated microglia/macrophages (GAMs) with anti-inflammatory polarization, tumor-infiltrating lymphocytes (TILs) with an "exhausted" phenotype, and glioma-associated stromal cells (GASCs). From a genomic and transcriptomic point of view, compared with the tumor core and healthy brain tissue, the PBZ presents a "half-way" pattern with upregulation of genes related to angiogenesis, the extracellular matrix, and cellular senescence and with stemness features and downregulation in tumor suppressor genes. This review illustrates that the PBZ is a transition zone with a pre-malignant microenvironment that constitutes the base for GBM progression/recurrence. Understanding of the PBZ could be relevant to developing more effective treatments to prevent GBM development and recurrence.

From signalling pathways to targeted therapies: unravelling glioblastoma's secrets and harnessing two decades of progress

Glioblastoma, a rare, and highly lethal form of brain cancer, poses significant challenges in terms of therapeutic resistance, and poor survival rates for both adult and paediatric patients alike. Despite advancements in brain cancer research driven by a technological revolution, translating our understanding of glioblastoma pathogenesis into improved clinical outcomes remains a critical unmet need. This review emphasises the intricate role of receptor tyrosine kinase signalling pathways, epigenetic mechanisms, and metabolic functions in glioblastoma tumourigenesis and therapeutic resistance. We also discuss the extensive efforts over the past two decades that have explored targeted therapies against these pathways. Emerging therapeutic approaches, such as antibody-toxin conjugates or CAR T cell therapies, offer potential by specifically targeting proteins on the glioblastoma cell surface. Combination strategies incorporating protein-targeted therapy and immune-based therapies demonstrate great promise for future clinical research. Moreover, gaining insights into the role of cell-of-origin in glioblastoma treatment response holds the potential to advance precision medicine approaches. Addressing these challenges is crucial to improving outcomes for glioblastoma patients and moving towards more effective precision therapies.

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma

Glioblastoma (GBM) is a deadly brain tumor, and the kinesin motor KIF11 is an attractive therapeutic target because of its dual roles in proliferation and invasion. The clinical utility of KIF11 inhibitors has been limited by drug resistance, which has mainly been studied in animal models. We used multiplexed lineage tracing barcodes and scRNA-seq to analyze drug resistance time courses for patient-derived GBM neurospheres treated with ispinesib, a potent KIF11 inhibitor. Similar to GBM progression in patients, untreated cells lost their neural lineage identity and transitioned to a mesenchymal phenotype, which is associated with poor prognosis. In contrast, cells subjected to long-term ispinesib treatment exhibited a proneural phenotype. We generated patient-derived xenografts to show that ispinesib-resistant cells form less aggressive tumors in vivo, even in the absence of drug. Finally, we used lineage barcodes to nominate drug combination targets by retrospective analysis of ispinesib-resistant clones in the drug-naïve setting and identified drugs that are synergistic with ispinesib.

Dissecting Intra-tumor Heterogeneity in the Glioblastoma Microenvironment Using Fluorescence-Guided Multiple Sampling

The treatment of the most aggressive primary brain tumor in adults, glioblastoma (GBM), is challenging due to its heterogeneous nature, invasive potential, and poor response to chemo- and radiotherapy. As a result, GBM inevitably recurs and only a few patients survive 5 years post-diagnosis. GBM is characterized by extensive phenotypic and genetic heterogeneity, creating a diversified genetic landscape and a network of biological interactions between subclones, ultimately promoting tumor growth and therapeutic resistance. This includes spatial and temporal changes in the tumor microenvironment, which influence cellular and molecular programs in GBM and therapeutic responses. However, dissecting phenotypic and genetic heterogeneity at spatial and temporal levels is extremely challenging, and the dynamics of the GBM microenvironment cannot be captured by analysis of a single tumor sample. In this review, we discuss the current research on GBM heterogeneity, in particular, the utility and potential applications of fluorescence-guided multiple sampling to dissect phenotypic and genetic intra-tumor heterogeneity in the GBM microenvironment, identify tumor and non-tumor cell interactions and novel therapeutic targets in areas that are key for tumor growth and recurrence, and improve the molecular classification of GBM.

Image-based models of T-cell distribution identify a clinically meaningful response to a dendritic cell vaccine in patients with glioblastoma

BACKGROUND

Glioblastoma is an extraordinarily heterogeneous tumor, yet the current treatment paradigm is a "one size fits all" approach. Hundreds of glioblastoma clinical trials have been deemed failures because they did not extend median survival, but these cohorts are comprised of patients with diverse tumors. Current methods of assessing treatment efficacy fail to fully account for this heterogeneity.

METHODS

Using an image-based modeling approach, we predicted T-cell abundance from serial MRIs of patients enrolled in the dendritic cell (DC) vaccine clinical trial. T-cell predictions were quantified in both the contrast-enhancing and non-enhancing regions of the imageable tumor, and changes over time were assessed.

RESULTS

A subset of patients in a DC vaccine clinical trial, who had previously gone undetected, were identified as treatment responsive and benefited from prolonged survival. A mere two months after initial vaccine administration, responsive patients had a decrease in model-predicted T-cells within the contrast-enhancing region, with a simultaneous increase in the T2/FLAIR region.

CONCLUSIONS

In a field that has yet to see breakthrough therapies, these results highlight the value of machine learning in enhancing clinical trial assessment, improving our ability to prospectively prognosticate patient outcomes, and advancing the pursuit towards individualized medicine.

Spatially resolved transcriptomic profiles reveal unique defining molecular features of infiltrative 5ALA-metabolizing cells associated with glioblastoma recurrence

BACKGROUND

Spatiotemporal heterogeneity originating from genomic and transcriptional variation was found to contribute to subtype switching in isocitrate dehydrogenase-1 wild-type glioblastoma (GBM) prior to and upon recurrence. Fluorescence-guided neurosurgical resection utilizing 5-aminolevulinic acid (5ALA) enables intraoperative visualization of infiltrative tumors outside the magnetic resonance imaging contrast-enhanced regions. The cell population and functional status of tumor responsible for enhancing 5ALA-metabolism to fluorescence-active PpIX remain elusive. The close spatial proximity of 5ALA-metabolizing (5ALA +) cells to residual disease remaining post-surgery renders 5ALA + biology an early a priori proxy of GBM recurrence, which is poorly understood.

METHODS

We performed spatially resolved bulk RNA profiling (SPRP) analysis of unsorted Core, Rim, Invasive margin tissue, and FACS-isolated 5ALA + /5ALA - cells from the invasive margin across IDH-wt GBM patients (N = 10) coupled with histological, radiographic, and two-photon excitation fluorescence microscopic analyses. Deconvolution of SPRP followed by functional analyses was performed using CIBEROSRTx and UCell enrichment algorithms, respectively. We further investigated the spatial architecture of 5ALA + enriched regions by analyzing spatial transcriptomics from an independent IDH-wt GBM cohort (N = 16). Lastly, we performed survival analysis using Cox Proportinal-Hazards model on large GBM cohorts.

RESULTS

SPRP analysis integrated with single-cell and spatial transcriptomics uncovered that the GBM molecular subtype heterogeneity is likely to manifest regionally in a cell-type-specific manner. Infiltrative 5ALA + cell population(s) harboring transcriptionally concordant GBM and myeloid cells with mesenchymal subtype, -active wound response, and glycolytic metabolic signature, was shown to reside within the invasive margin spatially distinct from the tumor core. The spatial co-localization of the infiltrating MES GBM and myeloid cells within the 5ALA + region indicates PpIX fluorescence can effectively be utilized to resect the immune reactive zone beyond the tumor core. Finally, 5ALA + gene signatures were associated with poor survival and recurrence in GBM, signifying that the transition from primary to recurrent GBM is not discrete but rather a continuum whereby primary infiltrative 5ALA + remnant tumor cells more closely resemble the eventual recurrent GBM.

CONCLUSIONS

Elucidating the unique molecular and cellular features of the 5ALA + population within tumor invasive margin opens up unique possibilities to develop more effective treatments to delay or block GBM recurrence, and warrants commencement of such treatments as early as possible post-surgical resection of the primary neoplasm.

Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic and targetable tissue states

Glioblastoma (GBM) diffusely infiltrates the brain and intermingles with non-neoplastic brain cells, including astrocytes, neurons and microglia/myeloid cells. This complex mixture of cell types forms the biological context for therapeutic response and tumor recurrence. We used single-nucleus RNA sequencing and spatial transcriptomics to determine the cellular composition and transcriptional states in primary and recurrent glioma and identified three compositional 'tissue-states' defined by cohabitation patterns between specific subpopulations of neoplastic and non-neoplastic brain cells. These tissue-states correlated with radiographic, histopathologic, and prognostic features and were enriched in distinct metabolic pathways. Fatty acid biosynthesis was enriched in the tissue-state defined by the cohabitation of astrocyte-like/mesenchymal glioma cells, reactive astrocytes, and macrophages, and was associated with recurrent GBM and shorter survival. Treating acute slices of GBM with a fatty acid synthesis inhibitor depleted the transcriptional signature of this pernicious tissue-state. These findings point to therapies that target interdependencies in the GBM microenvironment.

The evolutionary cancer genome theory and its reasoning

Oncogenesis and the origin of cancer are still not fully understood despite the efforts of histologists, pathologists, and molecular geneticists to determine how cancer develops. Previous embryogenic and gene- and genome-based hypotheses have attempted to solve this enigma. Each of them has its kernel of truth, but a unifying, universally accepted theory is still missing. Fortunately, a unicellular cell system has been found in amoebozoans, which exhibits all the basic characteristics of the cancer life cycle and demonstrates that cancer is not a biological aberration but a consequence of molecular and cellular evolution. The impressive systemic similarities between the life cycle of Entamoeba and the life cycle of cancer demonstrate the deep homology of cancer to the amoebozoans, metazoans, and fungi ancestor that branched into the clades of Amoebozoa, Metazoa, and Fungi (AMF) and shows that the roots of oncogenesis and tumorigenesis lie in an ancient gene network, which is conserved in the genome of all metazoans and humans. This evolutionary gene network theory of cancer (evolutionary cancer genome theory) integrates previous findings and hypotheses and is one step further along the road to a universal cancer cell theory. It supports genetic cancer medicine and recommends soma-to-germ transitions-referred to as epithelial-to-mesenchymal transition in cancer-and cancer germline as potential targets. According to the evolutionary cancer genome theory, cancer exploits an ancient gene network module of premetazoan origin.