Citations

Abstract Brain metastases (BMs) are a common and often fatal progression of systemic cancers, affecting up to 25% of patients. Despite advances in surgical resection and radiotherapy, the median survival remains limited to 10–16 months. While genomic profiling has enabled the development of targeted therapies, there remains a paucity of prognostic tools for clinical use. To address this, we explored the utility of DNA methylation profiling—an epigenetic marker increasingly recognized for its diagnostic and prognostic value. We profiled fresh-frozen tissue from 327 surgically resected BM samples of lung, breast, melanoma, and gastrointestinal (GI) origin using the Illumina Infinium MethylationEPIC BeadChip array. Unsupervised analysis via partitioning around medoids (PAM) clustering identified five robust groups. Four of these correlated closely with primary tumor origin. However, a distinct “Poly-Origin Cluster” emerged, comprising tumors from multiple primary sites with a shared epigenetic signature. Poly-Origin tumors showed improved survival outcomes compared to origin-aligned clusters (20.2 vs. 10.1 months, p=0.0018), independent of clinical covariates. Notably, these tumors were enriched for immune cell infiltration—including CD14+ macrophages, CD19+ B-cells, and CD56+ NK cells—based on deconvolution analysis, and exhibited reduced genomic instability as measured by copy number variation. These tumors were enriched for pathways related to cell signaling. We validated the prognostic significance of the Poly-Origin methylation signature in a publicly available independent cohort (n=96), and found that high signature concordance correlated with extended survival. Finally, we demonstrated the feasibility of detecting this signature in plasma-derived cell-free DNA using cfMeDIP-seq, with high classification accuracy (AUC = 0.98). These findings reveal a clinically meaningful subtypes of BM not captured by tissue origin or mutation status alone. Our work suggests that DNA methylation profiling may be a powerful tissue- and liquid biopsy–based tool that holds promise as a non-invasive prognostic biomarker in the management of brain metastasis.

Abstract Pediatric high-grade gliomas (pHGG) are aggressive primary brain neoplasms with a dismal prognosis, making them the leading cause of brain tumor-related deaths in children. pHGGs occur in specific anatomical locations at specific ages underscoring their origin in neurodevelopment and the critical importance of the brain tumor microenvironment. Many pHGGs originate from oligodendroglial precursor cells (OPCs) and, like OPCs, neuronal activity promotes the proliferation of pHGGs. Neuronal activity drives pHGG growth through electrochemical communication with pHGG cells. In turn, pHGGs increase neuronal excitability and remodel functional neural circuits. The interconnected network of glioma cells and neurons is fundamental to pHGG progression. Using single-nuclei RNA sequencing of mice harboring murine H3K27M-altered Diffused Midline Glioma (DMG), we observed gene expression changes indicating an increase in axonogenesis processes in glioma-associated neurons (GANs), primarily driven by EphA signaling. EphA4, EphA5, and EphA7 are overexpressed in GANs while the ligand, EphrinA1, is overexpressed in H3K27M gliomas. Performing in vitro neurite outgrowth and co-culture assays, we observed increased axonogenesis in neurons in the presence of DMG cells and DMG-conditioned media. We developed a two-color in vivo imaging method to study neuron-glioma interactions over time in freely behaving mice enabling us to record the frequency, pattern, and synchronicity of calcium transients in neurons, glioma cells, and their coactivity, giving us a comprehensive view of the changes in neuron-glioma circuit dynamics over time. We have observed increasing neuronal activity and synchronicity throughout the disease. We have also observed that gliomas also exhibit increased levels of activity and synchronicity as the tumor progresses. We verified our findings through longitudinal in vivo local field potential recordings, finding an increase in all power bands, especially in high-gamma activity over time. Ongoing experiments will test how glioma-induced axonogenesis contributes to the observed evolution of malignant circuit dynamics over time. Taken together, our data shows as gliomas progress, the neuron-glioma malignant circuitry evolves through axonogenesis driven by EphA signaling.

Abstract A major barrier in understanding adult diffuse gliomas lies in the inability to track tumor evolution in real time. To address this, we employed a novel method known as continuous lineage tracing, which integrates CRISPR/Cas9-based expressed DNA barcoding with single-cell RNA sequencing, enabling a phylogenetic approach to studying tumor development. Patient-derived glioma-initiating cell lines were engineered with expressed barcodes targeted by CRISPR/Cas9 and implanted into mice to create intracranial xenografts. Tumors underwent single-cell RNA sequencing; expressed barcodes were used to infer clonal relationships, and transcriptomic profiles enabled cell state classification. Phylogenetic lineage trees were reconstructed using lineage inference algorithms to characterize cell fitness, expansion, and plasticity. Our analysis uncovered extensive intra-clonal cell state heterogeneity, indicating active phenotype switching prior to therapy. We identified consistent transcriptional programs associated with tumor engraftment and in vivo clonal advantage. Lineage tracing revealed gene expression signatures linked to key phenotypes: fitness, enriched for neural-mesenchymal and injury-response pathways; expansion, associated with RNA splicing; and plasticity, correlated with cell cycle and DNA repair programs. Glioma stem cells appeared to span a transcriptional continuum from undifferentiated, high-fitness states to more differentiated, low-fitness states, with high-fitness cells potentially representing transitional phenotypes. We then validated these findings in a cohort of 185 surgically resected gliomas with matched bulk RNA and proteomic data. Phylogenetic gene signatures differed markedly between IDH-mutant and IDH-wildtype tumors. When stratified by tumor type, both fitness and expansion signatures were significantly associated with overall survival in GBM (median 12.6 months, p=0.041) and oligodendrogliomas (median 66 months, p=0.027). This study demonstrates the utility of continuous lineage tracing to reconstruct tumor evolution and identify transcriptional programs linked to tumor growth and prognosis. Our approach provides a powerful framework for dissecting glioma biology and identifying potential therapeutic vulnerabilities.

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 BACKGROUND Tumor Treating Field (TTF) therapy exerts antineoplastic effects through application of alternating electrical fields that disrupt mitotic machinery and induce DNA damage and activation of cell cycle checkpoints. However, despite extensive utilization in clinical practice for the management of glioblastoma, molecular markers for TTF sensitivity have proven elusive. METHODS To assess impact of molecular alterations on TTF response, we evaluated our institutional cohort of IDH wild type glioblastomas (n=449) for whom chromosomal microarray data was available. RESULTS A total of 142 patients were found to have undergone TTF treatment (31.6%) with improved overall survival (OS) (p=0.0049, univariate analysis). We assessed TTF treatment responses when stratified by alterations in the MDM2/4-TP53 axis, as well as the CDK4/6-RB1 axis, given well-described roles for these pathways on cellular responses to DNA damage and mitotic stressors. On univariate analysis, MDM2/4 amplified tumors treated with TTFs demonstrated significantly improved OS compared to untreated tumors (p=0.0012), and while MDM2/4-unaltered, TP53 intact tumors showed OS benefit from TTFs (p=0.0192), TP53-altered tumors did not demonstrate such benefit (p=0.6591). We confirmed these findings with multivariate Cox regression after adjusting for age and sex, where TTF therapy improved OS in MDM2/4 amplified tumors (HR 0.3881, p=0.0062) and a signal towards improved OS was seen in TP53 intact tumors (HR 0.7552, p=0.0509) but no such benefit was seen in TP53-altered tumors (HR 1.0025, p=0.9916). TTF therapy appeared to demonstrate improved OS in CDK4/6 amplified tumors (p=0.0116) on univariate analysis, with continued signal towards this effect on multivariate Cox regression (HR 0.5975, p=0.0870). CONCLUSIONS TP53 intact status and MDM2/4 amplification may represent previously unappreciated molecular markers for sensitivity to TTF therapy in IDH wild type glioblastoma. Confirmatory work with multi-institutional collaborations and evaluation of other potential prognostic factors are currently underway.

Abstract Glioblastoma (GBM) is the most aggressive primary brain tumor, with a dismal median survival of 12–15 months. Recent evidence shows that neurons form functional synapses with GBM cells, promoting invasion and growth. Microglia, the brain’s resident immune cells, can modulate synaptic connections; however, their role in neuron-glioma synaptic interactions remains poorly understood. Here, we co-cultured patient-derived GBM cells with either human iPSC-derived microglia-like cells or HMC3 microglia in five-month-old iPSC-derived cortical organoids, assessing GBM calcium activity over 30 minutes using GCaMP6s-based imaging. Compared to GBM-only controls, cells grown with microglia displayed elevated mean ΔF/F0 (t-test, p = 6.536×10^-6,****) and higher calcium peak counts (p = 0.0002181 by t-test, ***). Tumor region- specific single-cell transcriptomic analysis of the Darmanis et. al dataset, containing GBM samples from four patients revealed eight distinct immune subclusters and highlighted a spatial dichotomy in immune function, with upregulation of complement and phagocytic signals in the tumor core, and unique ligand–receptor interactions in the periphery. CellChat analysis identified SEMA4D–PLXNB1 as a candidate ligand–receptor pair enriched between immune and neoplastic cells at the tumor periphery. Resident microglia exhibited significantly higher SEMA4D expression, while neoplastic cells showed elevated PLXNB1. These data suggest that microglia intensify GBM calcium signaling and engage in SEMA4D–PLXNB1 signaling. Future studies will determine the impact of these observations on neuron-gioma synapses and whether genetic ablation of PLXNB1 disrupts microglia-driven calcium signaling and slows tumor progression, offering mechanistic insight into the interplay of immune cells, neurons, and GBM.

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 Diffuse midline and diffuse hemispheric glioma contain the driver mutations H3.3 K27M and G34R/V, respectively. These mutations alter histone methylations, suggesting that dysregulation of gene expression may contribute to tumor formation. We recently reported that these mutations also inhibit the phosphorylation of H3.3 at Serine 31. Importantly, H3.3 S31A mice developed high-grade gliomas – similar to those from G34R and K27M mice – indicating that loss of phosphoS31 promotes gliomagenesis. Chk1, a key kinase in DNA damage response and mitotic fidelity, phosphorylates H3.3 S31. H3.3 S31 is phosphorylated at the pericentromere in metaphase and is typically absent during interphase. Reduction of S31 phosphorylation by H3.3 K27M, G34R, G34V, or S31A was sufficient to induce mitotic errors leading to aneuploidy. Using CRISPR/Cas9, we generated novel H3.3 WT/WT and WT/S31A lines from glioma patient-derived SF-8628 (H3.3 WT/K27M) and KNS-42 (H3.3 WT/G34V) cells. Immunofluorescence of metaphase spreads revealed H3.3 phosphoS31 at the pericentromeres as expected. Interestingly, total Chk1 and active Chk1 (pS296) were significantly enriched at the pericentromeres of H3.3 K27M and G34V cells, as compared to H3.3 WT cells. While total ATR and active ATR (pT1989) were present at the pericentromere, their levels were unaltered by the H3.3 mutations. Surface plasmon resonance of purified proteins revealed that Chk1 has two binding affinities for H3.3 - likely corresponding to the previously identified Chk1 phosphorylation sites (T11 and S31) on H3.3. Chk1 binding at one site was unaffected by H3.3 K27M, while the second site showed an altered dissociation from H3.3 K27M. In summary, our data suggest that the low pericentromeric pS31 levels associated with H3.3 glioma mutations result from Chk1 recognizing the mutant histone, but without completing a phosphorylation cycle, becoming trapped at the pericentromere. This result suggests that H3.3 mutations, by trapping Chk1, may impede Chk1 activities beyond just reducing H3.3 phosphorylation.

Abstract INTRODUCTION Brain metastases (BM) are the most common intracranial tumor, with a poor prognosis of 10-16 months, and lung adenocarcinoma (LUAD) is the most common source. Currently, we cannot reliably predict which patients will develop BMs clinically, so most are detected after they develop and growing to cause deficits. Here, we use tumor DNA methylomes to predict which patients are likely to develop BM through the course of disease and we use both cerebrospinal fluid (CSF) and plasma methylomes for BM liquid biopsy, enabling their early detection and treatment. METHODS DNA methylomes were acquired from 419 tumor and plasma samples from 363 LUAD and BM patients. We built DNA methylation-based models that predict BM development and that also identify BMs non-invasively from CSF and plasma in discovery data subsets. A nomogram was built that predicts BM risk using methylation scores and clinical stage together. Models were evaluated in independent validation sets. RESULTS Our model predicting BM development was accurate (Univariable Cox: HR=5.7, 95% CI=1.9-17.2), p=0.0023), independent of clinical factors (Multivariable Cox: HR=8.9, 95% CI=2.0-40.5, p=0.0046), and more predictive than cancer staging used currently clinically (AUC=0.81 versus 0.65). Our combinatorial nomogram using methylation and staging data together showed enhanced BM prediction (Univariable Cox: HR=17.2, 95% CI=4.1-71.3, p<0.0001; AUROC=0.82). Our models identifying BM through biofluid methylomes accurately distinguished BM from differential diagnoses of gliomas and lymphomas in plasma (AUROC=0.80, 95% CI=0.68-0.93) and with greater accuracy in CSF (AUROC=0.93, 95% CI=0.71-1.0). CONCLUSION Overall, we show the first approaches for robust molecular prediction of BM development and for reliable liquid biopsy of BM. This work is expected to transform cancer management by identifying high-risk lung cancer patients after initial treatment for inclusion in screening protocols using neuroimaging and liquid biopsy, to identify BM development early with less advanced disease and more optimal therapeutic outcomes.

Abstract Cerebrospinal fluid (CSF) cell-free DNA (cfDNA) is under evaluation as a liquid biopsy tool across multiple neuro-oncologic indications, including diagnosing lesions of uncertain etiology, delineating progression from pseudoprogression, and confirming suspected leptomeningeal disease (LMD). We evaluated the real-world performance of CSF cfDNA sequencing for identification of variant alleles (VA) using targeted panel sequencing (PredicineCARE) and/or copy number alterations (CNA) using low-pass whole-genome sequencing (LPWGS; PredicineSCORE) in a diverse cohort across three aforementioned indications. From 82 adult patients, 93 samples (92.4% from lumbar puncture and 7.6% from ventriculoperitoneal shunt taps) were analyzed. For CNS progression, gliomas were most frequently evaluated (60%); for LMD, metastatic disease was most common (86.7%). Median CSF volume utilized for analysis was 4.60 mL (range: 0.40-7.50 mL). Median cfDNA yield was 0.29 ng/mL (range: 0.00–1037.74 ng/mL). For lesions of uncertain etiology (n=40 patients, 1 sample/patient), VAs were identified in 10 samples (25%); an additional 10 samples had sufficient cfDNA for LPWGS (25%). 50% of samples in this indication had insufficient cfDNA for testing. For suspected progression (n=26 patients, 35 samples), VAs were identified in 6 samples (17.1%); an additional 14 samples underwent LPWGS (40%); 15 had insufficient cfDNA for further testing (42.9%). For suspected LMD (n=16 patients, 18 samples), VAs were quantifiable in 4 samples (22.2%); LPWGS could be performed in an additional 9 (50%); 5 had insufficient cfDNA (27.8%). Across indications, identification of known tumor-associated alterations in CSF, including those confirmed previously by tissue, served as a non-surgical diagnostic adjunct. In some patients, targetable mutations could be identified via CSF. Conversely, absence of such alterations and/or low cfDNA yields may lower suspicion for active neuro-oncologic disease, when evaluated alongside clinical history. Despite modest cell-free DNA yield, CSF cfDNA evaluation provides valuable information to aid clinical decision-making across neuro-oncologic indications.