Citations

Abstract Triggering receptor expressed on myeloid cells 2 (TREM2) is a critical modulator of phagocytosis, inflammation, and survival for microglia and other macrophages. In neurodegenerative disorders, microglia expressing TREM2 play a protective role at distinct phases of disease progression, enabling uptake of toxic protein aggregates and dead neurons. TREM2 is also highly expressed on tumor-associated macrophages in a variety of cancers, promoting an immunosuppressive microenvironment. We and others have previously investigated the role of TREM2 in gliomas with confounding results, suggesting TREM2 could be pro-tumorigenic or anti-tumorigenic depending on experimental context (Peshoff, et al. Neuro Oncol. and Zheng, et al. Neuro Oncol.) In this study, we aim to resolve these findings by investigating the role of TREM2 across progression of gliomas with unique genetic drivers using immunocompetent mouse models. We employ syngeneic glioma stem cell lines generated via retroviral vectors expressing a dominant negative p53 along with amplification of human PDGFB or oncogenic HRAS G12V to model proneural and mesenchymal glioblastomas, respectfully. In contrast to our previous results demonstrating enhanced GL261 and CT2A growth in Trem2-/- mice, we demonstrate that Trem2 deficiency results in decreased tumor volume and improved survival when mice are challenged with Ras-driven, but not PDGFB-driven, gliomas. Furthermore, Trem2-/- mice display a more immunostimulatory microenvironment with increased T cell infiltration to mesenchymal-like tumors. We employ an in vitro co-culture system of primary mouse microglia with glioma stem cells to understand how microglia sense and respond to different genetic subtypes. We find that TREM2-mediated processes including microglial phagocytosis, chemotaxis, and survival are impacted by glioma genetic drivers. Together, these results indicate discrepancies in the literature regarding the function of TREM2 in gliomas may be explained by tumor genetics behind the cell lines used, which can provide a framework for understanding subtypes of gliomas that could respond to TREM2-modulating therapy.

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 Purpose: CD4 T-cell immunity is associated with improved survival in patients with breast cancer. We previously reported a phase I trial evaluating a folate receptor alpha (FRα) vaccine administered with cyclophosphamide (CP), demonstrating excellent safety and immunogenicity. To simplify the vaccine strategy for ease of use, we report here the results of a randomized phase II trial evaluating a lower vaccine dose alongside the original dose, administered with or without CP pretreatment. Patients and Methods: Patients with triple-negative breast cancer who completed all systemic and local therapies were assigned to receive either low-dose (825 μg) or high-dose (2.5 mg) vaccine peptides plus GM-CSF in six 4-week cycles, with or without CP prior to vaccination. Safety was monitored, and immunogenicity was evaluated before and after vaccination. Results: A total of 80 patients were dosed with vaccine, and 58 patients were evaluable for immunogenicity. Vaccination was well tolerated and elicited immunity in 83% of patients. Levels of FRα-specific T cells were high, persistent, and comparable with T-cell levels against tetanus toxoid. No differences in immunity were observed between the two doses. CP pretreatment also did not affect the immune responses. Recurrences occurred in eight evaluable patients and were unrelated to the treatment arm. No patients died during the study because of their disease. Conclusions: The reduced-dose FRα vaccine is as effective as the original dose and does not require CP to generate maximal immunity. These findings may inform the design of trials testing efficacy in triple-negative breast cancer or other cancers.

Importance Treatment for cognitive dysfunction due to postacute sequelae of long COVID (ie, symptoms of fatigue, malaise, weakness, confusion that persist beyond 12 weeks after an initial COVID infection) remains a significant unmet need. Objective To test evidence-based rehabilitation strategies for improving cognitive symptoms in persons with long COVID. Design, Setting, and Participants This was a 5-arm, multicenter, randomized clinical trial of 3 remotely delivered interventions conducted between August 17, 2023, and June 10, 2024. The study took place at 22 trial sites and included the screening of individuals with cognitive long COVID. Interventions Participants were randomized to 1 of 5 arms: adaptive computerized cognitive training (BrainHQ [Posit Science]), cognitive-behavioral rehabilitation involving both group and individual counseling sessions (PASC-Cognitive Recovery [PASC-CoRE]) paired with BrainHQ, and transcranial direct current stimulation (tDCS) paired with BrainHQ. Two comparator arms were included as follows: unstructured computer puzzles and games (active comparator) and sham tDCS paired with BrainHQ. The interventions occurred 5 times per week over 10 weeks. Main Outcomes and Measures Cognitive and behavioral in-person assessments were performed at baseline, midintervention, at the end of intervention, and 3 months after the end of the intervention. The primary outcome measure was the modified Everyday Cognition Scale 2 (ECog2) completed at the end of the intervention compared to the baseline visit based on participant self-report looking back over the prior 7 days. Results A total of 378 individuals were screened, from which there were 328 participants (median [IQR] age, 48.0 [37.0-58.0] years; 241 female [73.5%]; race: 15 Asian [4.6%], 47 Black [14.3%], and 235 White [71.6%]; ethnicity: 52 Hispanic [15.9%]). None of the 3 active interventions demonstrated benefits on the modified ECog2 in the intention-to-treat population by the end of the intervention period. The adjusted differences in mean change were 0.0 (95% CI, −0.2 to 0.2) for BrainHQ vs active comparator, 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs active comparator, 0.0 (95% CI, −0.2 to 0.2) for tDCS-active + BrainHQ vs tDCS-sham + BrainHQ, and 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs BrainHQ alone. Secondary participant-reported outcomes and neuropsychological tests showed no differential benefits for any treatment arm. All 5 arms demonstrated some improvements over time on the modified ECog2 and on secondary outcomes. There were no serious adverse events attributable to the interventions. Conclusions and Relevance This phase 2 randomized clinical trial failed to demonstrate differential benefits for online cognitive training, a structured cognitive rehabilitation program, and tDCS for cognitive long COVID. Trial Registration ClinicalTrials.gov Identifier: NCT05965739 .

The treatment landscape of invasive early-stage and metastatic breast cancer is evolving constantly. These NCCN Guidelines Insights focus on recent updates included in the most recent version (version 5.2025) of the NCCN Guidelines for Breast Cancer specific to workup, locoregional therapy, surveillance, and systemic neoadjuvant/adjuvant therapy recommendations for invasive, nonmetastatic breast cancer.

The NCCN Guidelines for Prostate Cancer provide a framework on which to base decisions for patients with prostate cancer across the disease spectrum. The Guidelines sections included in this article focus on metastatic castration-sensitive prostate cancer (mCSPC), nonmetastatic castration-resistant prostate cancer (CRPC), and metastatic CRPC (mCRPC). For patients with mCSPC, disease characteristics, such as whether metastases arose synchronously or metachronously and the degree of metastatic burden, impact therapy decisions, including how much treatment intensification is appropriate and when prostate-directed and/or metastasis-directed therapy should be considered. In the mCRPC setting, androgen deprivation therapy is continued with the sequential or concurrent addition of certain androgen receptor pathway inhibitors, chemotherapies, immunotherapies, radiopharmaceuticals, and/or targeted therapies. The NCCN Prostate Cancer Panel emphasizes a shared decision-making approach in all disease settings based on patient preferences, prior treatment exposures, biomarkers, the extent and location of metastases, symptoms, and potential side effects.

Abstract This brief report details the initial findings from a Phase 1b/2 trial of TN-201, an adeno-associated virus serotype 9 (AAV9) gene therapy for MYBPC3-associated hypertrophic cardiomyopathy (HCM), a condition with significant morbidity, increased risk of mortality, and no approved therapy for the majority of patients. TN-201 was well tolerated, and changes to the management of potential immune responses resulted in a shorter period of immunosuppression. These results show consistent transduction and expression of TN-201 in cardiomyocytes, corresponding with increases in MyBP-C levels, reductions or stabilization of cardiac biomarkers, and reductions in key measures of left ventricular (LV) hypertrophy.