Barajas, Ramon

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 BACKGROUND Standard of care surgery for high grade glioma (HGG) 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. Multi-parametric MRI (mpMRI) has recently been used to map regional biological heterogeneity of neuronal and immune signatures in HGG, and continues to offer a promising strategy for non-invasive surveillance of tumor progression. Here, we present a graph network analysis relating mpMRI to biological signatures in the NE tumor rim and show the utility of communities of imaging features for discriminating tumor phenotypes. METHODS 53 mpMRI features across 101 spatially-localized RNA-sequenced biopsy samples from 64 patients with IDH-wt HGG were represented as nodes within a Neo4j graph network. Modularity optimization was used to identify communities of densely connected nodes. Communities of nodes representing high proportions of NE samples (one-tailed test) were kept for further analysis. Gene set enrichment analysis (GSEA) on samples within selected imaging communities was analyzed for biological process enrichment using clusterProfiler. Single sample GSEA (ssGSEA) using ssGSEA2 was used to annotate neuronal and immune cell states across samples within selected communities. mpMRI feature selection within each community identified the most relevant imaging features for isolating samples classified into neuronal and immune cell states. RESULTS 11 imaging communities gathered a high proportion of NE samples. Three NE communities showed significant enrichment of neuronal signatures, while one showed significant enrichment of immune pathways. One neuronal-predominant community showed unique upregulation of 14 pathways related to neuronal migration/astrocyte projection. CONCLUSION Network imaging communities can identify clusters of NE glioma samples showing contrasting neuronal and immune signatures, including distinct upregulation of migration and projection pathways. Mapping these imaging feature communities to specific biological processes implicated in glioma progression may aid treatment planning and prognostication for glioma patients.

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.

Abstract BACKGROUND High-grade glioma (HGG) is the most common and aggressive form of primary brain cancer with poor prognosis. Standard of care surgery employs Magnetic Resonance Imaging (MRI) to identify the contrast enhancing (CE) core for resection, leaving behind an unresected non-enhancing (NE) invasive rim of tumor which borders healthy brain tissue and invariably contributes to recurrence. Recent multi-omic analyses identified predominant neuronal and immune signatures within NE tumor; understanding these signatures could provide key insights to combatting recurrence and improving patient outcomes. To this end, we utilized a novel graph database method to integrate multi-omic data from a unique dataset of multi-regional spatially-localized biopsies from the CE core and invasive NE rim from a large cohort of patients with HGG. MATERIAL AND METHODS 159 IDH-wildtype tumor biopsy samples from the NE and CE regions of 74 glioma patients were profiled by bulk RNA sequencing. Differentially expressed genes (DEG) (n=1159) across NE and CE samples were selected using EdgeR. Samples were hierarchically clustered (method = median) for each DEG and represented as nodes in a Neo4j graph network. Edges were generated between nodes sharing ≥ 1 sample. Modularity optimization was used to identify communities of densely connected nodes. Genes occurring exclusively within NE communities were localized by cell type using external single-cell RNA sequencing datasets and selected as candidate source nodes for NE network random walks. RBFOX1 was selected as a source (walk length = 5; 10,000 walks/source node). Random walks traversing samples with significantly elevated RBFOX1 expression (one-tailed test) were kept for analysis. Genes occurring at significantly high frequency (one-tailed test) within random walks were ranked by correlation with RBFOX1 expression in NE samples and analyzed by gene set enrichment analysis (GSEA) for biological processes using clusterProfiler. RESULTS RBFOX1, a neurodevelopmental regulator, was upregulated (logFC = 1.85) in NE samples and uniquely occurred in NE communities. We show RBFOX1 is differential expressed in the aggressive Neuronal glioma subtype and enriched in neuroepithelial/astrocyte subpopulations across single cell HGG datasets. NE network random walks identified 201 DEGs associated with RBFOX1. GSEA revealed upregulation of neurodevelopmental signatures and downregulation of proliferative pathways amongst RBFOX1’s network. CONCLUSION RBFOX1’s genetic network within NE tumor represents neurodevelopmental processes potentially underlying glioma invasiveness within the NE region. As such, understanding the mechanistic role of key genes within the RBFOX1 network may provide insight into novel strategies for targeting these invasive cells within an aggressive subtype of glioma in the NE rim.

Abstract BACKGROUND High-grade glioma (HGG) is the most common and aggressive form of primary brain cancer with poor prognosis. Standard of care surgery employs Magnetic Resonance Imaging to identify the contrast enhancing (CE) core for resection, typically leaving behind a non-enhancing (NE) invasive rim of tumor which invariably contributes to recurrence. Recent multi-omics analyses identified predominant neuronal and immune signatures within NE tumor, which could provide key insights for combatting recurrence. We present the novel application of graph network analyses to integrate multi-omic data from a unique dataset of multi-regional spatially-localized CE and NE biopsy samples from a large cohort of patients with HGG. MATERIAL AND METHODS 159 IDH-wildtype tumor biopsy samples from NE and CE regions of 74 glioma patients were profiled by RNA sequencing. Differentially expressed genes (DEGs) across NE and CE samples (n = 1159) were determined using the EdgeR package, and represented as nodes within a Neo4j graph network. Samples were hierarchically clustered for each gene (method = median), and edges were generated between gene nodes sharing ≥ 1 sample. Modularity optimization was used to identify communities of densely connected nodes. Genes occurring exclusively within NE communities were localized by cell type using external single-cell RNA sequencing datasets and identified as source node candidates for NE network random walks. These were performed with CSF2RA nodes as source (walk length = 5; 10,000 walks/source node). Random walks traversing samples with significantly elevated CSF2RA expression (one-tailed test) were kept for analysis. Genes occurring at high frequency (one-tailed test) within random walks were ranked by correlation with CSF2RA expression in NE samples and analyzed by gene set enrichment analysis (GSEA) for biological processes using clusterProfiler. RESULTS CSF2RA, an immune signaling receptor gene, was upregulated (logFC = 0.789) in NE samples and uniquely occurred within NE communities. We show its differential expression within the immune-enriched Glycolytic/Plurimetabolic (GPM) glioma subtype and confirm its enrichment in myeloid populations across single cell HGG datasets. NE network random walks identified 46 DEGs associated with CSF2RA. GSEA revealed upregulation of proliferative and metabolic signatures and downregulation of signaling pathways within CSF2RA’s network. CONCLUSION CSF2RA’s genetic network in NE tumor represents a potential mechanism for immunologic facilitation of glioma progression within this region. Given the expression of CSF2 ligand by glioma cells, which plays a crucial role in recruiting myeloid cells during peripheral cancer progression, modulating the expression of key genes in the CSF2RA network may be a promising approach for perturbing the crosstalk signals between immune and tumor cells in the NE region.

Abstract Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both “ideal” and “minimum standard” protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.