Machine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study.

Background: Glioblastoma is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.

Methods: We developed a highly reproducible, personalized prognostication and clinical subgrouping system using machine learning (ML) on routine clinical data, MRI, and molecular measures from 2,838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]).

Distinction of pseudoprogression from true progression in glioblastomas using machine learning based on multiparametric magnetic resonance imaging and O-methylguanine-methyltransferase promoter methylation status.

Background: It is imperative to differentiate true progression (TP) from pseudoprogression (PsP) in glioblastomas (GBMs). We sought to investigate the potential of physiologically sensitive quantitative parameters derived from diffusion and perfusion magnetic resonance imaging (MRI), and molecular signature combined with machine learning in distinguishing TP from PsP in GBMs in the present study.

Methods: GBM patients ( = 93) exhibiting contrast-enhancing lesions within 6 months after completion of standard treatment underwent 3T MRI.

Repeated peripheral infusions of anti-EGFRvIII CAR T cells in combination with pembrolizumab show no efficacy in glioblastoma: a phase 1 trial.

We previously showed that chimeric antigen receptor (CAR) T-cell therapy targeting epidermal growth factor receptor variant III (EGFRvIII) produces upregulation of programmed death-ligand 1 (PD-L1) in the tumor microenvironment (TME). Here we conducted a phase 1 trial (NCT03726515) of CAR T-EGFRvIII cells administered concomitantly with the anti-PD1 (aPD1) monoclonal antibody pembrolizumab in patients with newly diagnosed, EGFRvIII glioblastoma (GBM) (n = 7). The primary outcome was safety, and no dose-limiting toxicity was observed.

CHEX-seq detects single-cell genomic single-stranded DNA with catalytical potential.

Genomic DNA (gDNA) undergoes structural interconversion between single- and double-stranded states during transcription, DNA repair and replication, which is critical for cellular homeostasis. We describe "CHEX-seq" which identifies the single-stranded DNA (ssDNA) in situ in individual cells. CHEX-seq uses 3'-terminal blocked, light-activatable probes to prime the copying of ssDNA into complementary DNA that is sequenced, thereby reporting the genome-wide single-stranded chromatin landscape.

Mismatch repair protein mutations in isocitrate dehydrogenase (IDH)-mutant astrocytoma and IDH-wild-type glioblastoma.

Background: Mutations in mismatch repair (MMR) genes (, , , and are associated with microsatellite instability and a hypermutator phenotype in numerous systemic cancers, and germline MMR mutations have been implicated in multi-organ tumor syndromes. In gliomas, MMR mutations can function as an adaptive response to alkylating chemotherapy, although there are well-documented cases of germline and sporadic mutations, with detrimental effects on patient survival.

Methods: The clinical, pathologic, and molecular features of 18 IDH-mutant astrocytomas and 20 IDH-wild-type glioblastomas with MMR mutations in the primary tumor were analyzed in comparison to 361 IDH-mutant and 906 IDH-wild-type tumors without MMR mutations.

Taming Glioblastoma in "Real Time": Integrating Multimodal Advanced Neuroimaging/AI Tools Towards Creating a Robust and Therapy Agnostic Model for Response Assessment in Neuro-Oncology.

The highly aggressive nature of glioblastoma carries a dismal prognosis despite aggressive multimodal therapy. Alternative treatment regimens, such as immunotherapies, are known to intensify the inflammatory response in the treatment field. Follow-up imaging in these scenarios often mimics disease progression on conventional MRI, making accurate evaluation extremely challenging.

CrOssing fiber Modeling in the Peritumoral Area using dMRI (COMPARI).

Visualization of fiber tracts around the tumor is critical for neurosurgical planning and preservation of crucial structural connectivity during tumor resection. Biophysical modeling approaches estimate fiber tract orientations from differential water diffusivity information of diffusion MRI. However, the presence of edema and tumor infiltration presents a challenge to visualize crossing fiber tracts in the peritumoral region.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model.

Purpose: Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L.

Methods: Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included.

Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput.

We argue that the study of single-cell subcellular organelle omics is needed to understand and regulate cell function. This requires and is being enabled by new technology development.

Brain network mapping and glioma pathophysiology.

Adult diffuse gliomas are among the most difficult brain disorders to treat in part due to a lack of clarity regarding the anatomical origins and mechanisms of migration of the tumours. While the importance of studying networks of glioma spread has been recognized for at least 80 years, the ability to carry out such investigations in humans has emerged only recently. Here, we comprehensively review the fields of brain network mapping and glioma biology to provide a primer for investigators interested in merging these areas of inquiry for the purposes of translational research.

Artificial intelligence-based locoregional markers of brain peritumoral microenvironment.

In malignant primary brain tumors, cancer cells infiltrate into the peritumoral brain structures which results in inevitable recurrence. Quantitative assessment of infiltrative heterogeneity in the peritumoral region, the area where biopsy or resection can be hazardous, is important for clinical decision making. Here, we derive a novel set of Artificial intelligence (AI)-based markers capturing the heterogeneity of tumor infiltration, by characterizing free water movement restriction in the peritumoral region using Diffusion Tensor Imaging (DTI)-based free water volume fraction maps.

Targeting the IL4 receptor with MDNA55 in patients with recurrent glioblastoma: Results of a phase IIb trial.

Background: MDNA55 is an interleukin 4 receptor (IL4R)-targeting toxin in development for recurrent GBM, a universally fatal disease. IL4R is overexpressed in GBM as well as cells of the tumor microenvironment. High expression of IL4R is associated with poor clinical outcomes.

NCCN Guidelines® Insights: Central Nervous System Cancers, Version 2.2022.

The NCCN Guidelines for Central Nervous System (CNS) Cancers focus on management of the following adult CNS cancers: glioma (WHO grade 1, WHO grade 2-3 oligodendroglioma [1p19q codeleted, IDH-mutant], WHO grade 2-4 IDH-mutant astrocytoma, WHO grade 4 glioblastoma), intracranial and spinal ependymomas, medulloblastoma, limited and extensive brain metastases, leptomeningeal metastases, non-AIDS-related primary CNS lymphomas, metastatic spine tumors, meningiomas, and primary spinal cord tumors. The information contained in the algorithms and principles of management sections in the NCCN Guidelines for CNS Cancers are designed to help clinicians navigate through the complex management of patients with CNS tumors. Several important principles guide surgical management and treatment with radiotherapy and systemic therapy for adults with brain tumors.

Distinguishing Progression from Pseudoprogression in Glioblastoma Using F-Fluciclovine PET.

Accurate differentiation between tumor progression (TP) and pseudoprogression remains a critical unmet need in neurooncology. F-fluciclovine is a widely available synthetic amino acid PET radiotracer. In this study, we aimed to assess the value of F-fluciclovine PET for differentiating pseudoprogression from TP in a prospective cohort of patients with suspected radiographic recurrence of glioblastoma.

Association of Autologous Tumor Lysate-Loaded Dendritic Cell Vaccination With Extension of Survival Among Patients With Newly Diagnosed and Recurrent Glioblastoma: A Phase 3 Prospective Externally Controlled Cohort Trial.

Importance: Glioblastoma is the most lethal primary brain cancer. Clinical outcomes for glioblastoma remain poor, and new treatments are needed.

Objective: To investigate whether adding autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) to standard of care (SOC) extends survival among patients with glioblastoma.

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics.

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of: a) number of subjects, b) lack of consistent acquisition protocol, c) data quality, or d) accompanying clinical, demographic, and molecular information.

Laterality and Sex Differences of Human Lateral Habenula Afferent and Efferent Fiber Tracts.

Introduction: The lateral habenula (LHb) is an epithalamic nucleus associated with negative valence and affective disorders. It receives input the stria medullaris (SM) and sends output the fasciculus retroflexus (FR). Here, we use tractography to reconstruct and characterize this pathway.

Risk of intracranial hemorrhage with direct oral anticoagulants vs low molecular weight heparin in glioblastoma: A retrospective cohort study.

Background: Glioblastoma (GBM) is associated with a high incidence of venous thromboembolism (VTE), but there are little data to guide anticoagulation in patients with GBM, in whom the risks of VTE must be balanced against the risk of intracranial hemorrhage (ICH).

Methods: We performed a single-institution retrospective cohort study of patients with GBM diagnosed with VTE from 2014 to 2021 who were treated with low molecular weight heparin (LMWH) or a direct oral anticoagulant (DOAC). The incidence of ICH was compared between the LMWH and DOAC groups.