Neuro-oncology最新文献

Background: Glioma is the most prevalent and lethal tumor of the central nervous system. Routine treatment with Temozolomide (TMZ) would unfortunately result in inevitable recurrence and therapy resistance, severely limiting therapeutic efficacy. Tumor associated astrocytes (TAAs) are key components of the tumor microenvironment and increasing evidence has demonstrated that aberrant expression of Connexin43 (Cx43) was closely associated with glioma progression and TMZ resistance. However, the specific role of Cx43 in mediating TMZ resistance through glioma and astrocyte interactions has not been fully explored.

Methods: The expression and prognostic value of Cx43 were evaluated in tumor samples and clinical databases. ShRNA-medicated knockdown and Gfap-Cre Cx43flox/flox gene mouse were used to assessed the role and functional significance of Cx43 in vitro and in vivo. Moreover, we performed mass spectrometry analysis, chromatin immunoprecipitation, and other biochemical assays to define the molecular mechanisms by which Cx43 promotes TMZ resistance.

Results: We confirmed that upregulation of Cx43 expression between TAAs and glioma cells contributed to TMZ resistance and tumor recurrence. Genetic knockdown or pharmacological inhibition of Cx43 enhanced TMZ-induced cytotoxicity. Mechanistically, elevated Cx43 expression induced β-catenin accumulation at the cell surface of glioma cells, suppressing TCF/LEF transcription, This led to impaired miR-205-5p expression and subsequent activation of E2F1/ERCC1 axis, which eventually led to chemoresistance.

Conclusions: Our study reveals a novel regulatory mechanism in which the Cx43/miR-205-5p/E2F1/ERCC1 axis contributes to TMZ resistance in glioma. These findings further highlight the potential of targeting Cx43 as a therapeutic strategy in glioma.

Background: We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion since its original publication. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation predictor compatible with newer methylation arrays.

Methods: Genome-wide methylation profiles were generated with the Illumina EPICArray. The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. An nomogram was generated by incorporating our methylation predictor with WHO grade and extent of resection.

Results: A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and an external cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperform 2021 WHO grade in predicting early postoperative recurrence. Dichotomizing patients into grade-specific risk subgroups was predictive of outcome within both WHO grades 1 and 2 tumours (p<0.05), while all WHO grade 3 tumours were considered high-risk. Multivariable Cox regression demonstrated benefit of adjuvant radiotherapy in high-risk cases specifically, reinforcing its informative role in clinical decision making. Finally, our next-generation predictor contains nearly 10-fold fewer features than the original model, allowing for targeted arrays.

Conclusions: This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms 2021 WHO grading in predicting time to recurrence. We make this available as a point-and-click tool which will improve prognostication, inform patient selection for RT, and allow for molecularly-stratified clinical trials.

Over recent decades, in vitro and in vivo models have significantly advanced brain cancer research; however, each presents distinct challenges for accurately mimicking in situ conditions. In response, organotypic slice cultures have emerged as a promising model recapitulating precisely specific in vivo phenotypes through an ex vivo approach. Ex vivo organotypic brain slice models can integrate biological relevance and patient-specific variability early in drug discovery, thereby aiming for more precise treatment stratification. However, the challenges of obtaining representative fresh brain tissue, ensuring reproducibility, and maintaining essential central nervous system (CNS)-specific conditions reflecting the in situ situation over time have limited the direct application of ex vivo organotypic slice cultures in robust clinical trials. In this review, we explore the benefits and possible limitations of ex vivo organotypic brain slice cultures in neuro-oncological research. Additionally, we share insights from clinical experts in neuro-oncology on how to overcome these current limitations and improve the practical application of organotypic brain slice cultures beyond academic research.

Consensus recommendation published in 2017 histologically defining atypical neurofibromatous neoplasm of uncertain biologic potential (ANNUBP) and malignant peripheral nerve sheath tumor (MPNST) were codified in the 2021 WHO Classification of Tumors of the Central Nervous System and the 2022 WHO Classification of Tumors of Soft Tissue and Bone. However, given the shift in diagnostic pathology toward the use of integrated histopathologic and genomic approaches, the incorporation of additional molecular strata in the classification of Neurofibromatosis Type 1 (NF1)-associated peripheral nerve sheath tumors should be formalized to aid in accurate diagnosis and early identification of malignant transformation to enable appropriate intervention for affected patients. To this end, we assembled a multi-institutional expert pathology working group as part of a "Symposium on Atypical Neurofibroma: State of the Science". Herein, we provide a suggested framework for adequate interventional radiology and surgical sampling, and recommend molecular profiling for clinically or radiologically worrisome non-cutaneous lesions in patients with NF1 to identify diagnostically-relevant molecular features, including CDKN2A/B inactivation for ANNUBP, as well as SUZ12, EED, or TP53 inactivating mutations, or significant aneuploidy for MPNST. We also propose renaming "low-grade MPNST" to "ANNUBP with increased proliferation" to avoid the use of the "malignant" term in this group of tumors with persistent unknown biologic potential. This refined integrated diagnostic approach for NF1-associated peripheral nerve sheath tumors should continue to evolve in concert with our understanding of these neoplasms.

Background: Artificial intelligence has been proposed for brain metastasis (BM) segmentation but it has not been fully clinically validated. The aim of this study was to develop and evaluate a system for BM segmentation.

Methods: A deep-learning-based BM segmentation system (BMSS) was developed using contrast-enhanced MR images from 488 patients with 10338 brain metastases. A randomized crossover, multi-reader study was then conducted to evaluate the performance of the BMSS for BM segmentation using data prospectively collected from 50 patients with 203 metastases at 5 centers. Five radiology residents and 5 attending radiologists were randomly assigned to contour the same prospective set in assisted and unassisted modes. Aided and unaided Dice similarity coefficients (DSCs) and contouring times per lesion were compared.

Results: The BMSS alone yielded a median DSC of 0.91 (95% confidence interval, 0.90-0.92) in the multi-center set and showed comparable performance between the internal and external sets (P = .67). With BMSS assistance, the readers increased the median DSC from 0.87 (0.87-0.88) to 0.92 (0.92-0.92) (P < .001) with a median time saving of 42% (40-45%) per lesion. Resident readers showed a greater improvement than attending readers in contouring accuracy (improved median DSC, 0.05 [0.05-0.05] vs 0.03 [0.03-0.03]; P < .001), but a similar time reduction (reduced median time, 44% [40-47%] vs 40% [37-44%]; P = .92) with BMSS assistance.

Conclusions: The BMSS can be optimally applied to improve the efficiency of brain metastasis delineation in clinical practice.

Background: Neurocognition can be severely affected in pediatric brain tumor survivors. We analyzed the association of cognitive functioning with radiotherapy dose, postoperative cerebellar mutism syndrome (pCMS), hydrocephalus, intraventricular methotrexate (MTX) application, tumor localization, and biology in pediatric survivors of a posterior fossa tumor.

Methods: Subdomain-specific neurocognitive outcome data from 279 relapse-free survivors of the HIT-2000 trial (241 medulloblastoma and 38 infratentorial ependymoma) using the Neuropsychological Basic Diagnostic tool based on Cattell-Horn-Carroll's model for intelligence were analyzed.

Results: Cognitive performance 5.14 years (mean; range = 1.52-13.02) after diagnosis was significantly below normal for all subtests. Processing speed and psychomotor abilities were most affected. Influencing factors were domain-specific: CSI-dose had a strong impact on most subtests. pCMS was associated with psychomotor abilities (β = -0.25 to -0.16) and processing speed (β = -0.32). Postoperative hydrocephalus correlated with crystallized intelligence (β = -0.20) and short-term memory (β = -0.15), age with crystallized intelligence (β = 0.15) and psychomotor abilities (β = -0.16 and β = -0.17). Scores for fluid intelligence (β = -0.23), short-term memory (β = -0.17) and visual processing (β = -0.25) declined, and scores for selective attention improved (β = 0.29) with time after diagnosis.

Conclusions: The dose of CSI was strongly associated with neurocognitive outcomes. Low psychomotor abilities and processing speed both in patients treated with and without CSI suggest a strong contribution of the tumor and its surgery on these functions. Future research therefore should analyze strategies to both reduce CSI dose and toxicity caused by other treatment modalities.

Background: Following surgery, patients with newly diagnosed glioblastoma frequently enter clinical trials. Nuanced risk assessment is warranted to reduce imbalances between study arms. Here, we aimed (I) to analyze the interactive effects of residual tumor with clinical and molecular factors on outcome and (II) to define a postoperative risk assessment tool.

Methods: The RANO resect group retrospectively compiled an international, seven-center training cohort of patients with newly diagnosed glioblastoma. The combined associations of residual tumor with molecular or clinical factors and survival were analyzed, and recursive partitioning analysis was performed for risk modeling. The resulting model was prognostically verified in a separate external validation cohort.

Results: Our training cohort compromised 1003 patients with newly diagnosed isocitrate dehydrogenase-wildtype glioblastoma. Residual tumor, O6-methylguanine DNA methyltransferase (MGMT) promotor methylation status, age, and postoperative KPS were prognostic for survival and incorporated into regression tree analysis. By individually weighting the prognostic factors, an additive score (range, 0-9 points) integrating these four variables distinguished patients with low (0-2 points), intermediate (3-5 points), and high risk (6-9 points) for inferior survival. The prognostic value of our risk model was retained in treatment-based subgroups and confirmed in an external validation cohort of 258 patients with glioblastoma. Compared to previously postulated models, goodness-of-fit measurements were superior for our model.

Conclusions: The novel RANO risk model serves as an easy-to-use, yet highly prognostic tool for postoperative patient stratification prior to further therapy. The model may serve to guide patient management and reduce imbalances between study arms in prospective trials.

As cancer patients with intracranial metastatic disease experience increasingly prolonged survival, the diagnosis and management of recurrent brain metastasis pose significant challenges in clinical practice. Prior to deciding upon a management strategy, it is necessary to ascertain whether patients have recurrent/progressive disease vs adverse radiation effect, classify the recurrence as local or distant in the brain, evaluate the extent of intracranial disease (size, number and location of lesions, and brain metastasis velocity), the status of extracranial disease, and enumerate the interval from the last intracranially directed intervention to disease recurrence. A spectrum of salvage local treatment options includes surgery (resection and laser interstitial thermal therapy [LITT]) with or without adjuvant radiotherapy in the forms of external beam radiotherapy, intraoperative radiotherapy, or brachytherapy. Nonoperative salvage local treatments also range from single fraction and fractionated stereotactic radiosurgery (SRS/FSRS) to whole brain radiation therapy (WBRT). Optimal integration of systemic therapies, preferably with central nervous system (CNS) activity, may also require reinterrogation of brain metastasis tissue to identify actionable molecular alterations specific to intracranial progressive disease. Ultimately, the selection of the appropriate management approach necessitates a sophisticated understanding of patient, tumor, and prior treatment-related factors and is often multimodal; hence, interdisciplinary evaluation for such patients is indispensable.