Citations

Abstract Cerebrospinal fluid (CSF) is the biofluid most proximal to the central nervous system (CNS), yet its proteomic organization across neurological disease remains unresolved. We assembled a meta-atlas of 35 CSF proteomic datasets (2016–2026) comprising 10,560 quality-controlled samples spanning neurodegenerative, neuroinflammatory, neuro-oncological, infectious and structural-injury contexts. Meta-analysis of cross-cohort detection defined a 747-protein core mass-spectrometry-accessible CSF proteome that generalizes to held-out cohorts. We derived thirteen consensus meta-programs that transfer across independent cohorts and span the major neural, barrier, immune and plasma compartments. Unexpectedly, these programs are dominated by a single axis of variation opposing complement- and plasma-associated inflammation against neuronal-synaptic homeostasis. This injury–homeostasis axis is diagnosis-spanning and tracks clinical severity and disease activity across diverse neurological conditions. We show that a two-protein C5–NRCAM model can approximate the injury–homeostasis axis, bridging deep proteomic profiling toward bedside assessment.

Abstract Introduction Leptomeningeal disease (LMD) is the seeding of tumor cells in the leptomeninges and the cerebrospinal fluid (CSF) and carries a poor prognosis of 2-4 months. CSF sampling is required to study LMD, but genomic analysis may not be able to identify non-genomic and post-translational modifications. Proteomics can address this gap but is limited by reproducibility and disease heterogeneity. Integrating proteomic with genomic data may prioritize driver genes that promote LMD. Methods 23 patients with breast cancer-associated LMD with matched CSF proteomic and genomic data were studied. Variant allele frequencies (VAFs) for genes TP53, NFE2L2, ERBB2 and PIK3CA were derived, and proteomic profiling was performed on matched CSF. Spearman correlations between driver-gene VAF and protein expression were computed, restricting to genes with VAF>0 in ≥ 3 samples, and Benjamini-Hochberg correction was applied across gene-protein pairs. Proteins significantly associated with VAF were analyzed using over representation analysis (ORA) and gene segment enrichment analysis (GSEA) with KEGG, Gene Ontology, and MSigDB. Results TP53 VAF was associated with upregulation of proteins involved in glycolysis and cell proliferation, with enrichment of hallmark glycolysis (FDR=2.6x10-8), mTORC1 signalling (FDR=8.5x10-8), and reactive oxygen species pathways (FDR=2.7x10-3), and downregulation of complement (FDR=6.8 x 10-6) and coagulation cascades (FDR=0.011). NFE2L2 VAF was associated with epithelial-mesenchymal transition by both GSEA (FDR=2.3x10-9) and ORA (FDR=4.6x10-3), TGF-β signalling (FDR=0.015) and glycoprotein metabolism (FDR=1.6x10-7). ERBB2 VAF was associated with an upregulation of cell-cycle regulation (FDR=6.4x10-10), mTORC1 pathway (FDR=3.2x10-4), and a downregulation of proteins involved in cell-cell adhesion (FDR=4.0x10-9), axon guidance (GSEA FDR=0.025), and developmental growth (GOBP FDR=3.4x10-4). Conclusion Distinct CSF proteomic signatures were associated with specific driver mutations, implicating metabolic and oxidative stress pathways (TP53), stromal remodelling (NFE2L2), and disruption of CNS structural pathways (ERBB2). Validation in prospective LMD cohorts is needed to confirm these mutation-specific signatures and inform diagnostic and therapeutic strategies.

Abstract Background Peritumoral brain edema (PTBE) is a frequent complication of CNS tumors and radiation therapy (RT). PTBE is primarily treated with corticosteroids, but prolonged use is associated with severe toxicities including myopathy and immunosuppression. Bevacizumab, an alternative treatment, is not recommended in patients with thromboembolic events and intracerebral hemorrhage. Plasma kallikrein is a key driver of tumor-related edema. By targeting this pathogenic enzyme, the orally delivered inhibitor, RZ402, may provide therapeutic value by controlling edema and decreasing corticosteroid use. Methods In this single-patient investigational new drug protocol, we report results from use of RZ402 for treatment of cerebral edema related to metastatic melanoma and RT. Results A 74-year-old man with BRAF-wildtype melanoma had a right frontal and basal ganglia hemorrhagic metastasis not amenable to resection, treated with stereotactic RT (30 Gy, 5 fractions), followed by ipilimumab and nivolumab. MRI obtained 5 months after RT showed increased edema associated with midline shift. After 12 weeks of treatment with high-dose dexamethasone (16 mg daily), edema remained persistent and patient was unable to tolerate dose reduction below 4 mg daily. Course was complicated by a pulmonary embolus prompting initiation of anticoagulation, leading to deferral of bevacizumab. Patient was treated with RZ402, which was tolerated well with no reported toxicities. Dexamethasone was discontinued over 4 weeks. Follow up imaging 6 weeks after RZ402 initiation and off dexamethasone demonstrated stability without rebound edema. Patient did experience adrenal insufficiency characterized by severe fatigue, managed with low-dose prednisone. RZ402 was discontinued after 8 weeks of treatment with patient remaining clinically stable. Conclusion Despite persistent edema after prolonged use of corticosteroids, the selective plasma kallikrein inhibitor RZ402 was associated with radiographic stabilization and discontinuation of dexamethasone for this patient. These findings support prospective evaluation of RZ402 in treatment of symptomatic cerebral edema related to CNS tumors.

Abstract Background: Glioma diagnosed during pregnancy and pregnancy following glioma treatment present complex management challenges. The safety of glioma treatment during pregnancy is not well established. The ability to counsel patients on timing of conception after treatment remains limited. The aim of this study was to review our institution’s experience with glioma during and before pregnancy. Methods: In this single-institution study, we retrospectively identified patients diagnosed with glioma during or prior to pregnancy and reviewed treatment course and maternal and neonatal outcomes. Results: Twenty-one female patients were included in our study. Glioma diagnoses included 12 high-grade tumors and 9 low-grade tumors. Cohort A consisted of 8 patients who presented with glioma during pregnancy, of which, 7 underwent glioma treatment during pregnancy. All pregnancies in cohort A were without significant maternal complications and resulted in delivery of a healthy neonate. Cohort B consisted of 13 patients who experienced pregnancy after a prior diagnosis of glioma, totaling 23 pregnancies. Antepartum course was complicated by seizure in three pregnancies. Functionally inconsequential anatomic abnormalities in childhood offspring of cohort B occurred in 5 (27.8%) of the pregnancies. Four of the offspring with anatomic abnormalities had exposure to TMZ prior to conception. Conclusions: In this retrospective series, diagnosis of glioma before or during pregnancy was associated with generally favorable maternal, fetal and childhood outcomes. We observed a higher-than-expected rate of anatomic abnormalities in the post-diagnosis cohort, though none carried meaningful functional consequences. These findings add to the limited literature exploring maternal and fetal outcomes in patients with glioma.

Abstract Background The current treatment of glioblastoma involves resection followed by radiotherapy (RT) and temozolomide. Rapid early progression (REP) of tumor in the surgery-to-radiotherapy interval (SRI) has been described using categorical or semi-quantitative assessments and is associated with inferior clinical outcomes. This study seeks to establish and validate a quantitative definition for REP and examine how REP could inform future therapy. Methods Volumes of tumor and resection cavity at 3 time points—preoperative, postoperative and RT-planning (pre-RT)—were contoured among patients who had undergone standard of care. A minimal, but clinically appreciable, threshold for defining REP based on change in tumor volume was established, validated, and subsequently used to assess actionable predictors of REP and its prognostic value. Results An increase of >2 cc in volume or a new satellite tumor between the post-operative to planning MRI was found to be a sensitive, pragmatic, and statistically significant cutoff for REP (P = .002). Actionable predictors such as SRI of 6 weeks and a > 5 cc residual immediate post-operative tumor volume were found to be statistically significant predictors of REP. REP was also found to be a statistically significant prognostic indicator for overall survival (P = .002) and progression-free survival. Conclusion These findings support that an increase in tumor volume between post-operative and pre-RT MRI of >2 cc is the ideal working definition of REP in this clinical setting. Furthermore, REP could serve as a prognostic ­biomarker to track treatment response. Additionally, 2 actionable predictors of REP, post-op residual tumor volume and SRI, are identified.

ABSTRACT Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method– independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Abstract Background Isocitrate dehydrogenase (IDH)-mutant gliomas are infiltrative tumors with limited treatment options at recurrence. Early studies suggest IDH inhibition has therapeutic activity. We evaluated clinical outcomes associated with IDH-1 inhibitor ivosidenib in recurrent IDH-1-mutant gliomas and molecular predictors of response. Methods We retrospectively analyzed adults treated with ivosidenib from January 2021 to August 2025 with predominantly recurrent, pretreated CNS WHO grade 2-4 astrocytoma IDH-mutant or grade 2-3 oligodendroglioma, IDH-mutant and 1p/19q codeleted. Prior anticancer treatments, toxicities, enhancement status at ivosidenib initiation, and genomic alterations were collected. The primary endpoint was progression-free survival (PFS); secondary analyses evaluated associations between PFS, genomic complexity, and CDKN2A/B homozygous deletion. Results Ninety-two adults, median age 43, were included: 61 astrocytomas and 31 oligodendrogliomas, mostly grade 2. Before ivosidenib, 69 had surgery, 64 chemotherapy, and 64 radiation. Median time from diagnosis to ivosidenib was 4.8 years, with median of two prior progressions. Median treatment duration was 5.8 months. Median PFS was 15.2, 4.6, and 2.1 months for astrocytoma grades 2-4, 14.0 and 6.9 months for oligodendroglioma grades 2-3. Increasing genomic complexity was associated with shorter PFS in univariate analysis. Patients without CDKN2A/B homozygous deletion had median PFS of 19.2 months. Two patients with homozygous deletion had median PFS of 0.6 months. Conclusions In this retrospective analysis of predominantly recurrent IDH-1-mutant glioma, ivosidenib was associated with longer PFS in lower-grade, non-enhancing tumors that received little or no prior anticancer treatment and less complex genomic profiles. These findings support a context-dependent benefit of IDH inhibition in recurrent disease.

ABSTRACT IDH-mutant astrocytomas maintain telomeres through the alternative lengthening of telomeres (ALT) pathway, producing extreme inter-arm telomere length heterogeneity, yet how this heterogeneity shapes structural genome evolution remains unknown. Using Oxford Nanopore long-read sequencing of 20 IDH-mutant astrocytomas, we profiled structural variants (SVs), copy number variants, extrachromosomal DNA (ecDNA) and measured allele-specific telomere lengths from individual long reads. We identified pervasive complex rearrangements, including chromothripsis and foldback events consistent with breakage-fusion-bridge cycles, and widespread ecDNAs. SV breakpoints were enriched at telomeric and centromeric regions regardless of local telomere length, revealing constitutive structural fragility. Arm-level telomere length analysis uncovered a dual-mode model: arms with short telomeres preferentially harbored breakage-associated events, while arms with long ALT-maintained telomeres were enriched for ecDNA and amplification-associated events. These findings identify chromosome-arm-specific telomere length as a determinant of structural genome evolution in ALT-driven tumors.