Neuro-oncology最新文献

Background: Individual-level characteristics underlying population-level variation in glioma risk and outcomes remain incompletely understood. Cancer immunosurveillance, host immunity, and some immunotherapies center on the ability of an individual's immune cells to recognize antigen epitopes presented on MHC molecules. Inter-individual variation in HLA alleles can elicit distinct repertoires of tumor antigen for presentation to immune cells. Therefore, HLA alleles may impact glioma incidence and prognosis.

Methods: HLA class I (HLA-I) alleles were identified using sequencing data from four large glioma cohorts and healthy cohorts, matched on ancestry, and race- and age-matched imputed cohorts developed by the Hardy-Weinberg equilibrium were referred to determine odds ratio incidence estimated by logistic regression. HLA prognostication was quantified by Cox regression.

Results: We analyzed 1,215 cases of glioma patients from non-Hispanic Whites and Asians. The HLA-I allelic frequencies of gliomas generally corresponded to their distribution within each race. However, specific HLA-I alleles were significantly associated with glioma incidence and prognosis, which differ between races but were independent of age and sex. Notably, non-Hispanic White glioma patients exhibited greater HLA homozygosity rates compared with race-matched controls. HLA-C01:02 and HLA-C07:02 displayed opposing effects on glioma prognosis between races. The distinct effects were associated with their capability of presenting specific mutations that appeared at the initial or late phase of glioma progression.

Conclusions: Expression of specific HLA-I alleles are associated with glioma incidence and prognosis within race. HLA-I-homozygosity is a risk factor for glioma in non-Hispanic Whites. These findings may guide development of precision-guided immunotherapies for glioma.

Background: This study proposed a classification system for the interaction between gliomas and white matter tracts, exploring its potential associations with clinical characteristics, tumor pathological subtypes, and patient outcomes.

Methods: Clinical data and diffusion MRI from 360 glioma patients who underwent craniotomy were analyzed. Using automatic fiber tractography, glioma-tract relationships were categorized into three types: displacement, infiltration, and disruption. Double immunohistochemical staining for IDH and MBP was performed on neuronavigation-guided tissue samples to validate the imaging-based classifications. The clinical implications of these classifications on the extent of tumor resection, postoperative motor function, and survival outcomes were evaluated.

Results: Among the patients, 35 (9.7%) were categorized as displacement type, 283 (78.6%) as infiltration type, and 42 (11.7%) as disruption type. Disruption-type tracts were predominantly associated with IDH wild-type gliomas (87.2%), significantly higher than infiltration (28.5%) and displacement types (23.5%) (P < 0.001). Displacement and infiltration types were more common in IDH-mutant gliomas (P < 0.001). Displacement-type tracts were significantly associated with higher rates of complete tumor resection compared to infiltration types (P = 0.015). In corticospinal tract involved cases, displacement-type tumors demonstrated no significant postoperative motor strength changes, whereas infiltration (P < 0.001) and disruption types (P = 0.013) were highly associated with postoperative motor deficits. Histological results aligned with dMRI-based classifications.

Conclusions: This dMRI-based classification of glioma-tract interactions is significantly associated with tumor pathology, resection outcomes, functional prognosis, and survival, providing a valuable tool for personalized and precise surgical planning.

Background: Diffuse midline glioma, characterised by H3K27 alteration (DMG), is the predominant high-grade glioma in children. It commonly originates in the brainstem, yet effective treatments for these patients remain elusive.

Methods: To identify novel therapies for DMG, we conducted high-throughput drug screens (HTS) using biologically active, clinically approved compounds against DMG neurospheres. Multiple primary DMG cultures were utilised in conjunction with in vitro cytotoxicity and clonogenic assays to validate the efficacy of top compounds. Molecularly diverse patient-derived and transgenic DMG orthotopic models were employed to assess therapeutic efficacy alongside pharmacokinetic and immunohistochemical analyses. Mechanistic studies, including RNA sequencing, western blotting, and flow cytometry, were conducted to elucidate the antitumour efficacy of the most promising compound, fenretinide, in DMG cells.

Results: Through HTS, six compounds were identified and validated for their potent cytotoxic activity. However, most of these compounds failed to improve survival in an orthotopic Diffuse Midline Glioma (DMG) model due to limited blood-brain barrier (BBB) penetration. In contrast, fenretinide exhibited effective BBB penetration, significantly enhancing the survival of tumour-bearing animals. Mechanistic studies revealed that fenretinide increased reactive oxygen species (ROS) generation and induced apoptosis by inhibiting PDGFRα. RNA-sequencing further elucidated that fenretinide upregulates the Unfolded Protein Response (UPR) and endoplasmic reticulum (ER) stress pathways while downregulating neurogenesis. The in vivo antitumour efficacy of two fenretinide formulations was demonstrated in PDGFRα-amplified and transgenic DMG models.

Conclusion: This comprehensive study has identified new DMG therapeutic vulnerabilities and highlights fenretinide as a brain-penetrant, anti-DMG agent.

Background: Longitudinal assessment of tumor burden using imaging helps to determine whether there has been a response to treatment both in trial and real-world settings. From a patient and clinical trial perspective alike, the time to develop disease progression, or progression-free survival, is an important endpoint. However, manual longitudinal response assessment is time-consuming and subject to interobserver variability. Automated response assessment techniques based on machine learning (ML) promise to enhance accuracy and reduce reliance on manual measurement. This paper evaluates the quality and performance accuracy of recently published studies.

Methods: Following PRISMA guidelines and the CLAIM checklist, we searched PUBMED, EMBASE, and Web of Science for articles (January 2010-November 2024). Our PROSPERO-registered study (CRD42024496126) focused on adult brain tumor automated treatment response assessment studies using ML methodologies. We determined the extent of development and validation of the tools and employed QUADAS-2 for study appraisal.

Results: Twenty (including seventeen retrospective and three prospective) studies were included. Data extracted included information on the dataset, automated response assessment including pertinent steps within the pipeline (index tests), and reference standards. Only limited conclusions are appropriate given the high bias risk and applicability concerns (particularly regarding reference standards and patient selection), and the low-level evidence. There was insufficient homogenous data for meta-analysis.

Conclusion: The study highlights the potential of ML to improve brain tumor longitudinal treatment response assessment. Interpretation is limited due to study bias and limited evidence of generalizability. Prospective studies with external datasets validating the latest neuro-oncology criteria are now required.

Background: There are no validated tools for the clinical neurological assessment of patients with leptomeningeal metastases (LM). However, clinical examination during the course of the disease guides medical management and is part of response assessment in clinical trials. Because neuroimaging may not always be obtained owing to rapid clinical deterioration, clinical neurological assessment of LM is essential, and standardization is important to minimize rater disagreement.

Methods: The Response Assessment in Neuro-oncology-LM group launched a 2-step process, aiming at improving and standardizing the clinical assessment of patients with LM. We report here on the first step the establishment of a consensus scorecard. The task force had 9 virtual meetings to define general recommendations on neurological assessment and selected domains of interest that should be tested.

Results: Fourteen domains of neurological symptoms and signs were selected: level of consciousness, cognition, nausea and vomiting, vision, eye movement, facial strength, hearing, swallowing, speech, limb strength, limb ataxia, walking, and bladder bowel functions. For each item, a clear instruction on how to perform the assessment is provided with scoring criteria between 0 and 2. The general clinical status of the patient and use of steroids, pain medications, and antiemetics should be documented. Neurological sequelae from previous brain metastases or cancer treatment should be rated at the baseline evaluation; it should be specified when symptoms or signs may be related to a condition other than LM.

Discussion: A revised Neurological Assessment in Neuro-Oncology-LM consensus scorecard for clinical assessment has been established. An international prospective validation study of the proposal is currently ongoing (NCT06417710).

Background: Pediatric high-grade gliomas, such as diffuse midline glioma (DMG), have a poor prognosis and lack curative treatments. Current research models of DMG primarily rely on human DMG cell lines cultured in vitro or xenografted into the brains of immunodeficient mice. However, these models are insufficient to recapitulate the complex cell-cell interactions between DMG and the tumor-immune microenvironment (TIME), therefore fall short of accurately reflecting how efficacious therapeutic agents or combinations will be in the clinical setting.

Methods: To address these challenges, we developed a neuroimmune-competent brain/tumor fusion organoid model system consisting entirely of human cells to investigate the interactions between DMG cells and the primary innate immune cells of the brain, microglia, in the TIME at both cellular and subcellular levels. We generated microglia-containing brain organoids (MiCBOs) that carry morphologically mature, motile microglia and multiple subtypes of neurons to mimic the brain tumor microenvironment. These organoids were then fused with H3K27M mutant, TP53P27R/K132R DMG tumor spheroids to create the MiCBO-tumor fusion (MiCBO-TF) model.

Results: We utilized live imaging methods to simultaneously track the mobility of microglial cell bodies and the motility of their process, as well as the behavior of tumor cells within a human brain tissue environment. Our MiCBO-TF model faithfully recapitulated the diffuse infiltration pattern of DMG into brain tissue and revealed that microglial mobility and interactions with tumor cells are highly influenced by external factors and the surrounding tissue environment.

Conclusions: The MiCBO-TF model represents a powerful platform for both mechanistic investigations and the development of precision medicine approaches for DMG.

Background: The definition of tumor control and treatment failure after Gamma Knife radiosurgery (GKRS) for vestibular schwannoma (VS) is still debated. The lack of knowledge on the dynamics of tumor evolution can lead to misinterpretation and subsequent inappropriate second treatment. The aim of this study was to evaluate the post-GKRS dynamics of the evolution of tumor volume and characterize volumetric patterns.

Methods: We included patients with sporadic VS treated by GKRS with an MRI follow-up of a minimum of 3 years. A clustering was performed in 2 steps: Definition of the patterns of evolution based on a subset of patients with the most comprehensive follow-up, and then the assignment of the remaining patients on a best-fit basis. The minimum length of follow-up was assessed by measuring the consistency of the clusters over time (adjusted rand index and normalized mutual information). An analysis of the discriminant variables was finally performed.

Results: A total of 1607 patients were included (median follow-up: 67 months). Five patterns were defined with 1 pattern gathering almost all cases of treatment failure. The clustering at 5 years afforded the highest consistency with long-term follow-up. Discriminant variables for clusters were as follows: sex, initial symptoms, delay of diagnosis, Koos grading, fundus invasion, and number of isocenters.

Conclusions: The definition of these robust distinct patterns is likely to help the physicians tremendously to distinguish tumor control from potential failure. We advocate for no retreatment decision before 5 years post-GKRS. Further investigations are required to decide if the dynamics of evolution can be predicted at GKRS on an individual basis.

The standard of care for adult patients with gliomas, glioneuronal, and neuronal tumors consists of combinations of surgery, radiotherapy, and chemotherapy. For many systemic cancers, targeted treatments are a major part of the standard treatment; however, the predictive significance of most of the targets for treatment in systemic cancer is less well-established in central nervous system tumors. In 2023 the European Association for NeuroOncology (EANO) Guideline Committee presented evidence-based recommendations for rational testing of molecular targets for targeted treatments. From all targets reviewed, only testing for BRAF V600E mutations was of proven clinical benefit; despite regulatory approvals for tumor agnostic treatment of NTRK gene fusions and high tumor mutational burden (TMB) for patients with adult brain tumors, the evidence of clinical benefit for adult patients was still limited. This guideline has a modular structure, allowing regular updating of individual sections and adding new ones. The present version (Update 1) presents a review of the rationale of testing for PTEN, H3F3A, MTAP, RET and IDH, and presents an update of the text on TMB high and mismatch repair deficiency. It also presents an overview of the therapeutic yield of routine next-generation sequencing for mutations and fusion detection. The Supplemental File II accompanying this version contains an in-depth review of all targets, whereas, in the main manuscript, the final recommendations of the revised and new targets are presented. Updates will be made on a regular basis.

Clinical trials evaluating chimeric antigen receptor (CAR) T-cell therapy in patients with malignant gliomas have shown some early promise in pediatric and adult patients. However, the long-term benefits and safety for patients remain to be established. The ultimate success of CAR T-cell therapy for malignant glioma will require the integration of an in-depth understanding of the immunology of the central nervous system (CNS) parenchyma with strategies to overcome the paucity and heterogeneous expression of glioma-specific antigens. We also need to address the cold (immunosuppressive) microenvironment, exhaustion of the CAR T-cells, as well as local and systemic immunosuppression. Here, we discuss the basics and scientific considerations for CAR T-cell therapies and highlight recent clinical trials. To help identify optimal CAR T-cell administration routes, we summarize our current understanding of CNS immunology and T-cell homing to the CNS. We also discuss challenges and opportunities related to clinical trial design and patient safety/monitoring. Finally, we provide our perspective on future prospects in CAR T-cell therapy for malignant gliomas by discussing combinations and novel engineering strategies to overcome immuno-regulatory mechanisms. We hope this review will serve as a basis for advancing the field in a multiple discipline-based and collaborative manner.

Meningiomas are the most frequent primary intracranial tumors. Hence, they constitute a major share of diagnostic specimens in neuropathology practice. The 2021 WHO Classification of Central Nervous System Tumors ("CNS5") has introduced the first molecular grading parameters for meningioma with oncogenic variants in the TERT promoter and homozygous deletion of CDKN2A/B as markers for CNS WHO grade 3. However, after the publication of the new classification volume, clarifications were requested, not only on novel but also on long-standing questions in meningioma grading that were beyond the scope of the WHO "blue book." In addition, more recent research into possible new molecular grading parameters could not yet be implemented in the 2021 classification but constitutes a compelling body of literature. Hence, the consortium to inform molecular and practical approaches to CNS tumor taxonomy-not official WHO (cIMPACT-NOW) Steering Committee convened a working group to provide such clarification and assess the evidence of possible novel molecular criteria. As a result, this cIMPACT-NOW update provides guidance for more standardized morphological evaluation and interpretation, most prominently pertaining to brain invasion, identifies scenarios in which advanced molecular testing is recommended, proposes to assign CNS WHO grade 2 for cases with CNS WHO grade 1 morphology but chromosomal arm 1p deletion in combination with 22q deletion and/or NF2 oncogenic variants, and discusses areas in which the current evidence is not yet sufficient to result in new recommendations.