Sereduk, Christopher

Abstract High-grade gliomas (HGG) have significant spatial heterogeneity, complicating therapeutic approaches. While multiparametric MRI (mpMRI) enables noninvasive assessment of this heterogeneity, most predictive models lack biological interpretability when used to classify or predict outcomes. Here, we developed an unsupervised framework that identifies novel mpMRI feature patterns through dimensional reduction, linking them to clinically relevant molecular signatures. We analyzed 18 advanced mpMRI features from 73 stereotactic biopsies across 20 HGG patients. Imaging data were normalized, followed by dimensional reduction using an iterative UMAP across varying parameters. Density-based clustering was used to generate stable image-derived clusters through consensus co-clustering. RNA-seq data from matched biopsies were analyzed using DESeq2 and GSEA to identify differentially expressed genes and enriched pathways. We then constructed a network linking specific imaging features to these transcriptional signatures. Validation was performed in an independent cohort, allowing us to extend clusters across full brain mpMRI. Unsupervised clustering of mpMRI features produced nine stable image-based clusters. These clusters were not fully explained by contrast enhancement, metabolic class, or tumor purity, shown by intraclass correlation (ICC) analyses, suggesting they capture novel biological variation. Transcriptomic analysis showed each cluster was associated with distinct gene expression patterns and enriched biological pathways, including neuronal differentiation, immune chemotaxis, and chromatin remodeling. Key imaging features (sRCBV, MTT, K2)—combined in cluster-specific patterns—enabled construction of an interpretable imaging–transcriptomic network. This was validated in an independent cohort. We then applied to full brain mpMRI, mapping spatially distinct regions to biological trends and patient outcomes. Addressing a research gap in imaging HGG, we present an interpretable network that connects specific patterns of mpMRI to clinically meaningful molecular signatures. This approach advances our understanding of tumor heterogeneity and supports future translational work in precision patient care.

Abstract BACKGROUND Glioblastoma (GBM) is a molecularly and phenotypically heterogeneous tumor, with regional invasion patterns driving treatment resistance and universal recurrence. In infiltrative regions, GBM cells adopt at least two predominant invasive phenotypes: Neuronal-enriched (NEU), with synaptic and neurodevelopment programs, and Glycolytic/Plurimetabolic (GPM), with heightened immune and metabolic activity. These subtypes differ in therapeutic vulnerability and microenvironmental interactions; features not captured by conventional contrast-enhanced (T1+C) MRI due to minimal blood-brain barrier (BBB) disruption. Our group sought to develop predictive models to distinguish variability of NEU/GPM subtypes within infiltrative GBM, utilizing graph convolutional networks (GCN), advanced multiparametric MRI (mpMRI), and spatially-matched image-localized biopsies with transcriptomic profiling. METHODS We analyzed 18 mpMRI features —including conventional, diffusion-weighted, and Dynamic Susceptibility Contrast (DSC) perfusion MRI— of 101 image-localized biopsies from MRI non-enhancing infiltrative margins of 64 GBM patient tumors. Features were hierarchically clustered per modality; each cluster was represented as a node in a Neo4j graph. Edges connected nodes sharing overlapping samples. Nodes were annotated with NEU or GPM subtype proportion. GCNs were trained to classify subtype-enriched nodes using graph topology and node features. RESULTS GCNs achieved high predictive performance on held-out test data (AUC = 0.95 for NEU, 0.88 for GPM; 70:30 train-test split) with similar 5-fold cross-validation performance and generalized well to an independent cohort (AUC > 0.85, n = 45). Importantly, performance was robust without relying on T1+C imaging, enabling prediction beyond BBB-disrupted regions. GCNs outperformed traditional classifiers (logistic regression, random forest). CONCLUSION Our results demonstrate that GCN-modeling of mpMRI features enables non-invasive prediction of invasive GBM subtypes at the tumor margin. Unlike convolutional neural networks (CNN), which rely on spatial continuity, GCNs leverage relational structure between heterogeneous imaging features, making them ideal for modeling sparse, non-grid data. This may support non-invasive regional vulnerability detection, surgical targeting, and improved response assessment.

Abstract Glioma stem cells (GSCs) are key drivers of glioblastoma (GBM) progression, therapy resistance, and recurrence, making them critical therapeutic targets. While the lineage-defining transcription factor OLIG2 is critical for GSC maintenance, the molecular co-regulators and downstream pathways it engages remain poorly defined. Here, we identify a previously unrecognized, functionally significant interaction between OLIG2 and STAT5B, uncovering a novel regulatory axis in GSCs. Using proximity ligation assay (PLA), we demonstrate that OLIG2 interacts with STAT5 in human and mouse GSC models, particularly in EGFRvIII-mutant cells. We find that OLIG2 preferentially partners with STAT5B and not STAT5A. Knockdown studies in GSCs reveal that OLIG2 and STAT5B co-regulate critical oncogenes BIRC5 and NUSAP1, both of which are required for sphere formation and migration capacity of EGFRvIII positive GSCs. In orthotopic xenograft models, knockdown of either STAT5B or OLIG2 significantly prolongs survival reduces expression of stemness and invasion markers, SOX2, VIMENTIN, and NUSAP1. In contrast, STAT5A knockdown fails to recapitulate these phenotypes, underscoring the role of OLIG2-STAT5B signaling in GSCs. These findings reveal a novel OLIG2-STAT5B transcriptional circuit that plays a role in GSC stemness maintenance, invasion, and tumor growth, particularly in EGFRvIII-driven gliomas. Targeting this axis may offer a new avenue for GBM treatment.

Abstract Glioblastoma (GBM) invasion is shaped by dynamic clonal evolution within the spatial and cellular architecture of the brain. To investigate this process, we integrated multiparametric MRI, whole-exome sequencing (WES), bulk RNA-seq and single-nucleus RNA-seq (snRNA-seq) from 69 IDH-wildtype GBM patients, using spatially resolved biopsies from contrast-enhancing (CE) core tumor and non-enhancing (NE) invasive regions. Phylogenetic analysis revealed distinct clonal architectures. CE-enriched clones carried truncal mutations in conanical drivers of cell cycle and RTK signaling (TP53, PTEN, EGFR, PDGFRA/B), and private alterations in DNA repair genes (CDH11, PAX7, RAD51B). In contrast, NE-enriched clones exhibited private mutations in MAPK and Hippo pathways components (STAG2, BRAF, MAP2K3, CTNNA1), suggesting region-specific evolutionary trajectories. Furthermore, snRNAseq cell-cell communication analysis uncovered enriched ligand-receptor signaling in NE regions between malignant cells and brain-resident populations, including PTN—PTPRZ1 (myeloid), NRG-ERBB4 and SLIT-ROBO (neuronal, astrocytic, and oligodendrocytic). Bulk RNAseq deconvolution confirmed increased representation of neurons and glial cells in biopsies harboring NE-specific clones. These findings define a unique population of GBM clones localized at the infiltrative margin, marked by private MAPK/Hippo mutations and enhanced intracellular communication with the surrounding brain microenvironment. The recurrent engagement of neural-glial signaling pathways suggests that these NE-associated clones co-opt normal cellular networks to support invasion, immune evasion, and persistence following surgical resection. This study establishes a mechanistic link between spatial clonal evolution and tumor-host communication at the GBM infiltrative region and provide a framework for targeting cell-cell signaling circuits that sustain invasive tumor ecosystems and escape therapeutic treatment.

Abstract IDH-wildtype glioblastoma (GBM) is the most malignant primary adult brain tumor, with a five-year survival rate below 5%. Despite maximal treatment, including surgical resection, radiotherapy, and temozolomide (TMZ), recurrence is universal, driven by profound intratumoral heterogeneity, diffuse invasion, and therapy resistance. A hallmark of IDH-wildtype GBM is frequent alteration of epidermal growth factor receptor (EGFR), including amplification (50%), the EGFRvIII deletion variant (25%), and extracellular missense mutations such as G598V and A289V (10–15%). These missense mutations increase ligand affinity and receptor activity, yet their downstream signaling consequences and role in shaping the tumor phenotypes remain poorly defined. Recent pathway-based subclassifications identified four subtypes in IDH-wildtype GBM. Notably, neuronal (NEU) and glycolytic/plurimetabolic (GPM) subtypes predominate the invasive tumor margins. NEU programs are enriched in synaptic and neurodifferentiation signals, while GPM programs are associated with metabolic adaptation, angiogenesis, and immune evasion. Here, we show EGFR-G598V and EGFR-A289V mutations differentially regulate these invasive subtypes identities. Transcriptional analysis reveals EGFR G598V upregulates metabolic and inflammatory pathways consistent with the GPM phenotype, while EGFR A289V activates genes involved in neuronal differentiation and synaptic function, aligning with the NEU subtype. Phosphoproteomics and kinase-substrate analysis further uncovered distinct kinases to be functionally activated/inhibited in EGFR A289V-expressing cells and G598V cells. Mechanistic studies revealed EGFR A289V induces sustained EGFR phosphorylation at Y992, activating PLCγ2 via the SRC-family kinase LCK. This cascade drives calcium release, CAMK1 activation, and STAT5 phosphorylation, defining a novel EGFR A289V–LCK/PLCγ2/CAMK1/STAT5 axis. In addition, Y1068 phosphorylation is also constitutively active in EGFR A289V, resulting in increased BRAF activation. In contrast, EGFR G598V activates MAPK6 and CAMK2 inducing AKT2 activation, reinforcing GPM-associated signaling. These findings uncover mutation-specific signaling networks that drive subtype fate in invasive GBM and highlight unique pathway(s) as tractable targets for subtype-directed therapy in EGFR-mutant GBM.

Abstract High-grade gliomas represent the most common type of primary adult malignant brain tumor. IDH1/2 mutations are linked to lower-grade gliomas and better patient outcomes; however, molecular profiling has revealed additional alterations that drive aggression. CDKN2A/B loss in IDH-mutant astrocytoma is recognized as a key marker of grade 4 tumor biology, yet there remain no effective targeted therapies in aggressive gliomas. Here, we analyzed a cohort of patient-derived IDH-mutant astrocytoma with whole-exome and RNA sequencing data and identified several candidate genes and pathways concurrently regulated with CDKN2A/B loss, revealing an enhanced signature related to vascular processes. We sought to elucidate the angiogenic mechanisms and functional outcomes associated with high-grade behavior following CDKN2A/B loss in IDH-mutant astrocytoma to inform future therapeutic strategies. We used grade 4 IDH-mutant astrocytoma patient-derived xenograft (PDX) and established cell lines harboring homozygous CDKN2A/B deletion. We re-expressed the cell cycle regulators p14, p15, and p16 using a Tet-inducible lentiviral system and confirmed reduced proliferation compared to parental lines. Re-expression of p14, p15, or p16 also resulted in decreased glioma cell migration and invasion. Intriguingly, re-expressing these regulators reduced VEGF secretion. HUVEC cells cultured with conditioned media (CM) from the re-expression glioma lines decreased canonical activation of PI3K/Akt and Stat3 signaling and a diminished capacity to promote endothelial migration, invasion, and tube formation. Furthermore, in vivo Matrigel plug assays using CM from the re-expression lines showed a decreased ability to recruit endothelial cells, pericytes, and form vascular organized structures. We identified the WT1 transcription factor as an upstream regulator of angiogenesis. WT1 expression was inversely correlated with CDKN2A/B expression in patient data, and knockdown of WT1 in astrocytoma cells reduced VEGF secretion and impaired ability to promote endothelial migration. Taken together, our findings reveal a novel role for WT1 in VEGF-driven angiogenesis in IDH-mutant astrocytoma with CDKN2A/B homozygous deletion.

Abstract The intra- and inter-patient heterogeneity in high-grade glioma (HGG) continues to contribute to its poor prognosis. Clinical biopsies are often harvested from limited regions and typically are not image localized. Thus, they fail to capture the diversity within tumor regions, immune expression or normal cell abundances that play key roles in tumor development. It is important to gain an understanding of these subpopulation ecologies, their spatial resolution, and interactions between them that may then be exploited for future therapeutic benefit. Further, these may differ by patient characteristics such as sex, age at diagnosis and treatment status. Using an ongoing image-localized biopsy collection protocol, we have so far evaluated the bulk transcriptomics of 202 multi-regional biopsies from 58 patients to characterize HGG heterogeneity. These samples were processed through Monocle, a reverse graph embedding algorithm that groups samples into states and orders them along developmental trajectories. Deconvolution methods were previously used to predict relative abundances of 7 normal, 6 glioma, and 5 immune cell subpopulations for each sample, which we have now overlaid on the Monocle graph. Monocle classified HGG into 4 main states along a three-pronged trajectory. These states reveal distinct population ecologies with associated enriched gene pathways. We also note significant immune pathway enrichments that differ between state and patient-reported sex. Together, these algorithms reveal a simple transcriptomic trajectory that helps us understand the development and evolution of HGG. Characterizing the in vivo diversity within and between high grade gliomas is important for understanding prognosis, stratifying future treatments and ultimately improving patient outcome.

Abstract Diffuse gliomas represent the most common type of primary adult malignant brain tumor historically diagnosed and graded from histologic criteria alone. Gliomas harboring isocitrate dehydrogenase (IDH) 1 or 2 mutations are associated with lower grade tumors and portend a favorable prognosis relative to IDH-wildtype glioma. However, the loss of CDKN2A/B in IDH-mutant astrocytoma confers an aggressive high grade phenotype and is the strongest implicated molecular alteration associated poor clinical survival, thus is now sufficient to define a grade 4 tumor regardless of histologic grade. However, there remains no effective therapies targeted at molecular subgroups in aggressive gliomas to date. Here, we sought to elucidate the biologic pathways and functional outcomes associated with the acquisition of high-grade behavior under loss of CDKN2A/B in IDH-mutant astrocytoma to inform future therapeutic strategies. We analyzed a cohort of patient IDH-mutant astrocytomas with RNA sequencing data and found the increased expression of regulators of embryonic nervous system development and signaling concurrent with CDKN2A/B loss. Using grade 4 IDH-mutant astrocytoma patient-derived (PDX) and cell-lines harboring CDKN2A/B homozygous deletion, we stably re-expressed p14ARF, p15INK4B, and p16INK4A using a Tet-inducible system. IDH-mutant cell lines with re-expression of p14, p15, or p16 displayed differential transcription factor activation, impaired neurosphere capability, decreased colony formation, and lower neurosphere proliferation. Intriguingly, RNA-seq data revealed CUX2, a transcription factor known to control neuronal precursor behavior, as the likely candidate regulating the differential expression profile across CDKN2A/B status. We observed increased CUX2 expression in cell lines stably re-expressing p14, p15, and p16. We validated the CUX2 signature across publicly available datasets of IDH-mutant astrocytoma where CUX2 expression negatively correlated with loss of CDKN2A/B in patient tumors. Together our work suggests CUX2 deficiency in IDH-mutant astrocytoma with CDKN2A/B deletion enables an increased neuronal stem-like phenotype in these grade 4 tumors.

Abstract BACKGROUND High-grade glioma (HGG) is the most common and aggressive form of primary brain cancer. Standard of care surgery employs Magnetic Resonance Imaging to identify the contrast enhancing (CE) core for resection, leaving a non-enhancing (NE) invasive rim of tumor which contributes to recurrence. The hypoxic tumor microenvironment is thought to drive invasion into healthy brain, and understanding cellular responses to hypoxia may provide insight into combatting recurrence. Here, we apply a graph network to integrate regionally heterogeneous data from a unique dataset of spatially-localized CE and NE biopsies from a large cohort of patients with HGG to identify gene networks regulating hypoxia response and invasion. METHODS RNA-sequencing of 1159 differentially expressed genes across 159 IDH-wt biopsies (74 patients) from NE/CE regions were represented as nodes in a Neo4j graph network. Candidate genes for network random walks occurred exclusively within NE communities detected by modularity optimization and were localized by cell-type using single-cell RNA-sequencing (scRNAseq). CSF2RA was selected as source (walk length = 5; 10,000 walks/source node). Frequently occurring genes (one-tailed test) in walks were ranked by correlation with CSF2RA expression in NE samples and analyzed by gene set enrichment analysis for biological processes (clusterProfiler). CSF2RA and hypoxia gene expression were visualized with DoHeatmap in composite NE/CE scRNAseq profiles. RESULTS CSF2RA, an immune receptor, was upregulated (logFC = 0.789) in NE samples, scRNAseq myeloid populations, and Glycolytic/Plurimetabolic glioma subtype. CSF2RA random walk genes (n=46) enriched metabolic/proliferative signatures. CSF2RA expression correlated negatively with hypoxia genes globally and regionally (NE/CE), while NE/CE scRNAseq revealed distinct cellular expression patterns of CSF2RA and hypoxia response genes. CONCLUSION CSF2RA expression may prime NE glioma cells for invasion by altering hypoxia response. The genetic network bridging CSF2RA and hypoxia response may be a targetable mechanism of tumor recurrence.

Abstract BACKGROUND High-grade glioma (HGG) is the most common and aggressive form of primary brain cancer. Standard of care surgery employs Magnetic Resonance Imaging to identify the contrast enhancing (CE) core for resection, leaving a non-enhancing (NE) invasive rim of tumor which contributes to recurrence. Recent multi-omics analyses identified predominant neuronal and immune signatures within NE tumor. Here, we apply a graph network to integrate regionally heterogeneous data from a unique dataset of spatially-localized CE and NE biopsies from a large cohort of patients with HGG. METHODS RNA-sequencing of 1159 differentially expressed genes across 159 IDH-wt biopsies (74 patients) from NE/CE regions were represented as nodes in a Neo4j network. Candidate genes for network random walks occurred exclusively within NE communities detected by modularity optimization and localized by cell-type using single-cell RNA-sequencing (scRNAseq). CSF2RA and RBFOX1 were selected as sources (walk length = 5; 10,000 walks/source node). Frequently occurring genes (one-tailed test) in walks were ranked by correlation with CSF2RA/RBFOX1 expression in NE samples and analyzed by gene set enrichment analysis for biological processes (clusterProfiler). Random walk genes were visualized (DoHeatmap) against composite NE/CE scRNAseq profiles. RESULTS CSF2RA and RBFOX1 were upregulated in NE samples (logFC = 0.789, 1.85). Upregulation of CSF2RA, an immune receptor, in the Glycolytic/Plurimetabolic and RBFOX1, a neurodevelopmental regulator, in the Neuronal glioma subtypes were observed in NE samples (ANOVA p < 0.05). CSF2RA walk genes (n=46) enriched metabolic/proliferative signatures, while RBFOX1 walk genes (n=201) showed neurodevelopmental upregulation. scRNAseq localized CSF2RA to monocytes/macrophages while RBFOX1 was expressed in distinct astrocyte/neuroepithelial populations. CONCLUSION CSF2RA and RBFOX1’s gene networks modulate immune and neurodevelopmental processes influencing glioma progression in NE tumor. Understanding the region-specific roles of these networks may offer strategies for targeting cells in the invasive glioma rim.