Neuro-oncology advances最新文献

Background: Glioblastoma is characterized by rapid tumor growth and high invasiveness. The tumor microenvironment of glioblastoma is highly immunosuppressive with both intrinsic and adaptive resistance mechanisms that result in disease recurrence despite current immunotherapeutic strategies.

Methods: In this systematic review of clinical trials involving immunotherapy for glioblastoma using ClinicalTrials.gov and PubMed databases from 2016 and onward, we explore immunotherapeutic modalities involving immune checkpoint blockade (ICB).

Results: A total of 106 clinical trials were identified, 18 with clinical outcomes. ICB in glioblastoma has failed to improve overall survival compared to the current standard of care, including those therapies inhibiting multiple checkpoints. Among all immune checkpoint trials, targets included programmed cell death protein-1 (PD-1) (35/48), PD-L1 (12/48), cytotoxic T-lymphocyte-associated protein-4 (6/48), TIGIT (2/48), B7-H3 (2/48), and TIM-3 (1/48). Preliminary results from combination immunotherapies (32.1% of all trials) demonstrated improved treatment efficacy compared to monotherapy, specifically those combining checkpoint therapy with another immunotherapy modality.

Conclusions: Clinical trials involving ICB strategies for glioblastoma have not demonstrated improved survival. Comparison of therapeutic efficacy across trials was limited due to heterogeneity in the study population and outcome operationalization. Standardization of future trials could facilitate comparison across immunotherapy modalities for robust meta-analysis. Current immunotherapy trials have shifted focus toward combination strategies; preliminary results suggest that they are more encouraging than mono-modality immunotherapies. Given the intrinsic heterogeneity of glioblastoma, the utilization of immune markers will be key for the development of future immunotherapy approaches.

Background: Radiologically presumed diffuse lower-grade glioma (dLGG) are typically non or minimal enhancing tumors, with hyperintensity in T2w-images. The aim of this study was to test the clinical usefulness of deep learning (DL) in IDH mutation prediction in patients with radiologically presumed dLGG.

Methods: Three hundred and fourteen patients were retrospectively recruited from 6 neurosurgical departments in Sweden, Norway, France, Austria, and the United States. Collected data included patients' age, sex, tumor molecular characteristics (IDH, and 1p19q), and routine preoperative radiological images. A clinical model was built using multivariable logistic regression with the variables age and tumor location. DL models were built using MRI data only, and 4 DL architectures used in glioma research. In the final validation test, the clinical model and the best DL model were scored on an external validation cohort with 155 patients from the Erasmus Glioma Dataset.

Results: The mean age in the recruited and external cohorts was 45.0 (SD 14.3) and 44.3 years (SD 14.6). The cohorts were rather similar, except for sex distribution (53.5% vs 64.5% males, P-value = .03) and IDH status (30.9% vs 12.9% IDH wild-type, P-value <.01). Overall, the area under the curve for the prediction of IDH mutations in the external validation cohort was 0.86, 0.82, and 0.87 for the clinical model, the DL model, and the model combining both models' probabilities.

Conclusions: In their current state, when these complex models were applied to our clinical scenario, they did not seem to provide a net gain compared to our baseline clinical model.

Background: Malignant peripheral nerve sheath tumors (MPNSTs) can arise from atypical neurofibromas (ANF). Loss of the polycomb repressor complex 2 (PRC2) is a common event. Previous studies on PRC2-regulated genes in MPNST used genetic add-back experiments in highly aneuploid MPNST cell lines which may miss PRC2-regulated genes in NF1-mutant ANF-like precursor cells. A set of PRC2-regulated genes in human Schwann cells (SCs) has not been defined. We hypothesized that PRC2 loss has direct and indirect effects on gene expression resulting in MPNST, so we sought to identify PRC2-regulated genes in immortalized human Schwann cells (iHSCs).

Methods: We engineered NF1-deficient iHSCs with loss of function SUZ12 or EED mutations. RNA sequencing revealed 1327 differentially expressed genes to define PRC2-regulated genes. To investigate MPNST pathogenesis, we compared genes in iHSCs to consistent gene expression differences between ANF and MPNSTs. Chromatin immunoprecipitation sequencing was used to further define targets. Methylome and proteomic analyses were performed to further identify enriched pathways.

Results: We identified potential PRC2-regulated drivers of MPNST progression. Pathway analysis indicates many upregulated cancer-related pathways. We found transcriptional evidence for activated Notch and Sonic Hedgehog (SHH) signaling in PRC2-deficient iHSCs. Functional studies confirm that Notch signaling is active in MPNST cell lines, patient-derived xenografts, and transient cell models of PRC2 deficiency. A combination of MEK and γ-secretase inhibition shows synergy in MPNST cell lines.

Conclusions: We identified PRC2-regulated genes and potential drivers of MPNSTs. Our findings support the Notch pathway as a druggable target in MPNSTs. Our identification of PRC2-regulated genes and pathways could result in more novel therapeutic approaches.

Background: High-grade glioma (HGG) of the spinal cord constitutes rare tumors in the pediatric population. Knowledge of the molecular profile of this pediatric HGG (pedHGG) subgroup is limited and the clinical outcome is poor. Therefore, the aim of this study is to provide more profound investigations of molecular characteristics and clinical features of these tumors.

Methods: Between January 2015 and October 2023, 17 spinal tumors with HGG histology were analyzed by the Individualized Therapy For Relapsed Malignancies in Childhood (INFORM) precision oncology registry. Comprehensive molecular profiling (including next-generation sequencing approaches and DNA methylation analysis) was performed. Clinical data provided by the treating centers were evaluated regarding treatment approaches and outcomes.

Results: Subgroup classification based on DNA methylation analysis revealed molecular HGG subgroups in 12/17 cases, while 2/17 were classified as molecular low-grade glioma (LGG) and 3/17 were not unequivocally classifiable. Typical genetic alterations described in pedHGG usually presenting at other localizations were also present in the counterparts located in the spinal cohort. Alterations that might serve as a promising target for personalized therapy approaches were identified in a subset of tumors.

Conclusion: With this cohort of 12 molecularly confirmed spinal pedHGG cases, we provide a compilation of genomic as well as clinical features of this rare subgroup, contributing to a better understanding and eventually to future treatment approaches.

Background: Glioblastoma is the most aggressive malignant brain tumor with poor survival due to its invasive nature driven by cell migration, with unclear linkage to transcriptomic information. The aim of this study was to develop a physics-based framework connecting to transcriptomics to predict patient-specific glioblastoma cell migration.

Methods and results: We applied a physics-based motor-clutch model, a cell migration simulator (CMS), to parameterize the migration of glioblastoma cells and define physical biomarkers on a patient-by-patient basis. We reduced the 11-dimensional parameter space of the CMS into 3 principal physical parameters that govern cell migration: motor number-describing myosin II activity, clutch number-describing adhesion level, and F-actin polymerization rate. Experimentally, we found that glioblastoma patient-derived (xenograft) cell lines across mesenchymal (MES), proneural, and classical subtypes and 2 institutions (N = 13 patients) had optimal motility and traction force on stiffnesses around 9.3 kPa, with otherwise heterogeneous and uncorrelated motility, traction, and F-actin flow. By contrast, with the CMS parameterization, we found that glioblastoma cells consistently had balanced motor/clutch ratios to enable effective migration and that MES cells had higher actin polymerization rates resulting in higher motility. The CMS also predicted differential sensitivity to cytoskeletal drugs between patients. Finally, we identified 18 genes that correlated with the physical parameters, suggesting transcriptomic data alone could potentially predict the mechanics and speed of glioblastoma cell migration.

Conclusions: We describe a general physics-based framework for parameterizing individual glioblastoma patients and connecting to clinical transcriptomic data that can potentially be used to develop patient-specific anti-migratory therapeutic strategies.

Background: Gliomas, the most frequent malignant primary brain tumors, lack curative treatments. Understanding glioma-specific molecular alterations is crucial to develop novel therapies. Among them, the biological consequences of the isocitrate dehydrogenase 1 gene mutation (IDH1 ^R132H) remain inconclusive despite its early occurrence and widespread expression.

Methods: We thus employed CRISPR/Cas adenine base editors, which allow precise base pair alterations with minimal undesirable effects, to correct the IDH1 ^R132H mutation.

Results: Successful correction of the IDH1 ^R132H mutation in primary patient-derived cell models led to reduced IDH1 ^R132H protein levels and decreased production of 2-hydroxyglutarate, but increased proliferation. A dual adeno-associated virus split intein system was used to successfully deliver the base editor in vitro and in vivo.

Conclusions: Taken together, our study provides a strategy for a precise genetic intervention to target the IDH1 ^R132H mutation, enabling the development of accurate models to study its impact on glioma biology and serving as a framework for an in vivo gene therapy.

Background: Biological sex is an important risk factor for glioblastoma (GBM), with males having a higher incidence and poorer prognosis. The mechanisms for this sex bias are thought to be both tumor intrinsic and tumor extrinsic. MicroRNAs (miRNAs), key posttranscriptional regulators of gene expression, have been previously linked to sex differences in various cell types and diseases, but their role in the sex bias of GBM remains unknown.

Methods: We leveraged previously published paired miRNA and mRNA sequencing of 39 GBM patients (22 male, 17 female) to identify sex-biased miRNAs. We further interrogated a separate single-cell RNA-sequencing dataset of 110 GBM patients to examine whether differences in miRNA target gene expression were tumor cell-intrinsic or tumor cell extrinsic. Results were validated in a panel of patient-derived cell models.

Results: We identified 10 sex-biased miRNAs (p _adjusted < .1), of which 3 were more highly expressed in males and 7 more highly expressed in females. Of these, miR-644a was higher in females, and increased expression of miR-644a target genes was significantly associated with decreased overall survival (HR 1.3, P = .02). Furthermore, analysis of an independent single-cell RNA-sequencing dataset confirmed sex-specific expression of miR-644a target genes in tumor cells (P < 10^-15). Among patient-derived models, miR-644a was expressed a median of 4.8-fold higher in females compared to males.

Conclusions: Our findings implicate miR-644a as a candidate tumor cell-intrinsic regulator of sex-biased gene expression in GBM.

Background: Depression is common among glioma patients, and antidepressants are frequently prescribed to manage symptoms. Understanding the impact of antidepressants on glioma patient survival is crucial for informing treatment strategies.

Methods: A systematic search was conducted in PubMed and EMBASE databases for studies published from January 1994 to March 2024. The search strategy included terms related to overall survival, prognosis, antidepressants, and gliomas. A manual search was performed in the reference lists. According to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline, 2 authors independently extracted data. Statistical analysis was performed using Review Manager (version 5.4.1) software, employing a random effects model based on study heterogeneity. The primary outcome was overall survival (OS). Hazard ratios (HRs) were used to present survival differences between the 2 arms. HRs after correcting for confounders were prioritized for extraction.

Results: Seven retrospective cohort studies involving 5579 patients were analyzed. Selective serotonin reuptake inhibitors (SSRIs) showed no significant survival difference in all glioma patients (HR = 1.34, 95% confidence interval [CI]: 0.66-2.70) and in GBM patients (HR = 1.05, 95% CI: 0.45-2.46), while non-SSRIs had an unfavorable impact on OS in GBMs (HR = 3.54, 95% CI: 2.51-4.99). When considering LGG, both SSRIs and non-SSRIs usage demonstrated associations with poorer survival outcomes (SSRIs: HR = 3.26, 95%CI: 2.19-4.85; Non-SSRIs: HR = 7.71, 95% CI: 4.25-14.00).

Conclusions: Antidepressant use was not significantly associated with better survival outcomes, emphasizing the need for reconsidering the real effects of antidepressant medication. Future clinical research should address patient heterogeneity to better clarify the effects of antidepressants on glioma survival.

Background: In the present study, early response assessment by o-(2-[¹⁸F]fluoroethyl)-l-tyrosine (FET) positron emission tomography (PET) and contrast-enhanced magnetic resonance imaging (MRI) were investigated in a phase II open-label single-center study of nivolumab plus bevacizumab for recurrent high-grade astrocytic glioma.

Methods: Twenty patients with nonresectable first recurrence of high-grade astrocytic glioma after EORTC/NCIC protocol underwent [¹⁸F]FET PET/MRI at baseline and after 2 cycles of treatment. Whole brain values of contrast-enhancing volume on MRI (CEV), of the mean (TBR_mean) and maximal tumor-to-background ratio (TBR_max), and of metabolically active volume (MTV) on [¹⁸F]FET PET were obtained. Regional changes in [¹⁸F]FET uptake were assessed by parametric response mapping (PRM). Prediction of overall survival (OS) and response (OS > 11 months) were assessed by Cox and receiver operating characteristic (ROC) analysis, respectively. Also, MRI (response assessment in neuro-oncology [RANO] 2.0) and PET-based (PET RANO 1.0) response assessment criteria were compared.

Results: In ROC analysis responders were separated (P < .05) from nonresponders by lower MTV at follow-up (AUC 0.771, cutoff 18.3 mL), larger decrease in MTV (AUC 0.757, cutoff -5.3 mL), larger decrease in both TBR_max (AUC 0.814, cutoff -0.53) and relative TBR_max (AUC 0.829, cutoff -11%) and smaller PRM progressive volume (AUC 0.843, cutoff 4.0 mL). Change in CEV did not predict response. RANO 2.0 and PET RANO response assessment criteria had similar and only borderline prognostic values.

Conclusions: The study indicates that [¹⁸F]FET PET is superior to contrast-enhanced MRI for early response assessment in patients with recurrent high-grade astrocytic glioma treated with nivolumab and bevacizumab.