Background There is a critical need for objective and reliable biomarkers of outcome in meningiomas beyond WHO classification. Loss of H3K27me3 has been reported as a prognostically unfavorable alteration in meningiomas. We sought to independently evaluate the reproducibility and prognostic value of H3K27me3 loss by immunohistochemistry (IHC) in a multi-center study. Methods IHC staining for H3K27me3 and analyses of whole slides from 181 meningiomas across three centers was performed. Staining was analyzed by dichotomization into loss and retained immunoreactivity, and using a 3-tiered scoring system in 151 cases with clear staining. Associations of grouping with outcome was performed using Kaplan-Meier survival estimates. Results A total of 21 of 151 tumours (13.9%) demonstrated complete loss of H3K27me3 staining in tumour with retained endothelial staining. Overall, loss of H3K27me3 portended a worse outcome with shorter times to recurrence in our cohort, particularly for WHO grade 2 tumours which were enriched in our study. There were no differences in recurrence-free survival (RFS) for WHO grade 3 patients with retained versus loss of H3K27me3. Scoring by a 3-tiered system did not add further insights into the prognostic value of this H3K27me3 loss. Overall, loss of H3K27me3 was not independently associated with RFS after controlling for WHO grade, extent of resection, sex, age, and recurrence status of tumour on multivariable Cox regression analysis. Conclusions Loss of H3K27me3 identifies a subset of WHO grade 2 and possibly WHO grade 1 meningiomas with increased recurrence risk. Pooled analyses of a larger cohort of samples with standardized reporting of clinical definitions and staining patterns is warranted.
Magnetic Resonance Imaging (MRI) evidence of spinal cord compression plays a central role in the diagnosis of degenerative cervical myelopathy (DCM). There is growing recognition that deep learning models may assist in addressing the increasing volume of medical imaging data and provide initial interpretation of images gathered in a primary-care setting. We aimed to develop and validate a deep learning model for detection of cervical spinal cord compression in MRI scans. Patients undergoing surgery for DCM as a part of the AO Spine CSM-NA or CSM-I prospective cohort studies were included in our study. Patients were divided into a training/validation or holdout dataset. Images were labelled by two specialist physicians. We trained a deep convolutional neural network using images from the training/validation dataset and assessed model performance on the holdout dataset. The training/validation cohort included 201 patients with 6588 images and the holdout dataset included 88 patients with 2991 images. On the holdout dataset the deep learning model achieved an overall AUC of 0.94, sensitivity of 0.88, specificity of 0.89, and f1-score of 0.82. This model could improve the efficiency and objectivity of the interpretation of cervical spine MRI scans.
Liquid biopsy, as a non-invasive technique for cancer diagnosis, has emerged as a major step forward in conquering tumors. Current practice in diagnosis of central nervous system (CNS) tumors involves invasive acquisition of tumor biopsy upon detection of tumor on neuroimaging. Liquid biopsy enables non-invasive, rapid, precise and, in particular, real-time cancer detection, prognosis and treatment monitoring, especially for CNS tumors. This approach can also uncover the heterogeneity of these tumors and will likely replace tissue biopsy in the future. Key components of liquid biopsy mainly include circulating tumor cells (CTC), circulating tumor nucleic acids (ctDNA, miRNA) and exosomes and samples can be obtained from the cerebrospinal fluid, plasma and serum of patients with CNS malignancies. This review covers current progress in application of liquid biopsies for diagnosis and monitoring of CNS malignancies.
Purpose: Older patients with glioblastoma (GBM) are underrepresented in clinical trials. Several abbreviated and standard chemoradiotherapy regimens are advocated with no consensus on the optimal approach. Our objective was to quantitatively evaluate which of these regimens would provide the most favorable survival outcomes in older patients with GBM using a network metaanalysis.Experimental Design: MEDLINE, Embase, Google Scholar, and the Cochrane Library were searched. Patients >60 years of age with histologically confirmed GBM were included. Primary outcome of interest was the pooled HR from randomized controlled trials (RCTs). Secondary outcomes of interest included pooled HR from studies controlling for MGMT promoter methylation status, and safety.Results: Fourteen studies, including 5 RCTs, reporting 4,561 patients were included. Using highest quality data from RCTs, our network-based approach demonstrated that standard radiotherapy (SRT) and temozolomide (TMZ) provided similar survival benefit when compared with hypofractionated radiotherapy (HRT) and TMZ [HR ¼ 0.90; 95% confidence interval (CI), 0.43-1.87], TMZ alone (HR 1.25; 95% CI, 0.69-2.26), HRT alone (HR ¼ 1.34; 95% CI, 0.73-2.45), or SRT alone (HR ¼ 1.43; 95% CI, 0.87-2.36). HRT-TMZ had the highest probability (85%) of improving survival in older patients with GBM followed by SRT-TMZ (72%). Pooled analysis of trials controlling for MGMT promoter methylation status demonstrated that TMZ monotherapy confers similar survival benefit to combined chemoradiotherapy.Conclusions: Statistical comparisons using a network approach demonstrates that the common treatment regimens for older patients with GBM in previous RCTs confer similar survival benefits. Adjustments for MGMT promoter methylation status demonstrated that radiotherapy alone was inferior to TMZ-based approaches. Head-to-head comparison of TMZ monotherapy to combined TMZ and radiation is warranted.
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