Flick, M

Abstract Background Fibroblast growth factor-inducible 14 (Fn14) belongs to the TNFR superfamily. Fn14 overexpression can drive receptor-autonomous signaling, increase both cell invasion and tumor-associated macrophages/microglia (TAMMs) recruitment, and correlates with reduced survival in glioblastoma (GBM) patients and rat gliomas. While prior studies report Fn14 expression in non-tumor cells within the GBM tumor microenvironment (TME), their relative contributions to glioma pathobiology remain unclear. Methods Using tumor-host pairings of Fn14-positive and -knockout (-KO) cells and mice, we examined the role of Fn14 in glioma biology. Mouse glioma and human GBM datasets were analyzed at the cellular, protein, and transcriptomic levels to assess Fn14-associated changes in the glioma TME and survival outcomes. Results Fn14 was found to be highly expressed in tumor cells and TAMMs in human GBM and 2 well-characterized murine glioma models. Fn14 KO in both tumor and host cells increased overall survival. Notably, this survival benefit was greater in the glioma model characterized by a more immunologically activated TME. Immunophenotyping revealed that Fn14 loss reshapes the tumor-immune landscape, reducing the presence of immunosuppressive macrophages and exhausted T-cells, suggesting that Fn14 modulates both innate and adaptive immune responses. These findings were supported by analyses of human GBM datasets, where high Fn14 expression correlated with immunosuppressive shifts and poor patient responses to immune checkpoint inhibitor therapy. Conclusions This study provides the first description of the contributions of both tumor- and host-derived Fn14 expression to tumor immunity and survival and identifies Fn14 as an important mediator of innate and adaptive immune responses in gliomas.

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.