Progressive myelin oligodendrocyte glycoprotein-associated demyelination mimicking leukodystrophy

BackgroundMyelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may be associated with relapsing disease, but clinical progression independent of relapse activity is rare.ObjectivesTo report progressive disease in a patient with MOGAD.MethodsA single retrospective case report.ResultsAt 4 years of age, the patient had a single episode of acute disseminated encephalomyelitis. She remained well until age 17 years but over the next 9 years developed progressive spastic quadriparesis, cognitive and bulbar dysfunction. Brain imaging showed a leukodystrophy-like pattern of white matter abnormality with contrast enhancement at different time points. Myelin oligodendrocyte glycoprotein (MOG)-IgG was repeatedly positive by live cell-based assay.ConclusionSecondary progression may be a rare presentation of MOG-IgG-associated disease

A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas

Background Asymptomatic meningioma is a common incidental finding with no consensus on the optimal management strategy. We aimed to develop a prognostic model to guide personalized monitoring of incidental meningioma patients. Methods A prognostic model of disease progression was developed in a retrospective cohort (2007–2015), defined as: symptom development, meningioma-specific mortality, meningioma growth or loss of window of curability. Secondary endpoints included non-meningioma-specific mortality and intervention. Results Included were 441 patients (459 meningiomas). Over a median of 55 months (interquartile range, 37–80), 44 patients had meningioma progression and 57 died (non-meningioma-specific). Forty-four had intervention (at presentation, n = 6; progression, n = 20; nonprogression, n = 18). Model parameters were based on statistical and clinical considerations and included: increasing meningioma volume (hazard ratio [HR] 2.17; 95% CI: 1.53–3.09), meningioma hyperintensity (HR 10.6; 95% CI: 5.39–21.0), peritumoral signal change (HR 1.58; 95% CI: 0.65–3.85), and proximity to critical neurovascular structures (HR 1.38; 95% CI: 0.74–2.56). Patients were stratified based on these imaging parameters into low-, medium- and high-risk groups and 5-year disease progression rates were 3%, 28%, and 75%, respectively. After 5 years of follow-up, the risk of disease progression plateaued in all groups. Patients with an age-adjusted Charlson comorbidity index ≥6 (eg, an 80-year-old with chronic kidney disease) were 15 times more likely to die of other causes than to receive intervention at 5 years following diagnosis, regardless of risk group. Conclusions The model shows that there is little benefit to rigorous monitoring in low-risk and older patients with comorbidities. Risk-stratified follow-up has the potential to reduce patient anxiety and associated health care costs

T-Cell Densities in Brain Metastases Are Associated with Patient Survival Times and Diffusion Tensor MRI Changes

Brain metastases are common and are usually detected by MRI. Diffusion tensor imaging (DTI) is a derivative MRI technique that can detect disruption of white matter tracts in the brain. We have matched preoperative DTI with image-guided sampling of the brain–tumor interface in 26 patients during resection of a brain metastasis and assessed mean diffusivity and fractional anisotropy (FA). The tissue samples were analyzed for vascularity, inflammatory cell infiltration, growth pattern, and tumor expression of proteins associated with growth or local invasion such as Ki67, S100A4, and MMP2, 9, and 13. A lower FA in the peritumoral region indicated more white matter tract disruption and independently predicted longer overall survival times (HR for death = 0.21; 95% confidence interval, 0.06–0.82; P = 0.024). Of all the biological markers studied, only increased density of CD3+ lymphocytes in the same region correlated with decreased FA (Mann–Whitney U, P = 0.037) as well as confounding completely the effect of FA on multivariate survival analyses. We conclude that the T-cell response to brain metastases is not a surrogate of local tumor invasion, primary cancer type, or aggressive phenotype and is associated with patient survival time regardless of these biological factors. Furthermore, it can be assayed by DTI, potentially offering a quick, noninvasive, clinically available method to detect an active immune microenvironment and, in principle, to measure susceptibility to immunotherapy. Significance: These findings show that white matter tract integrity is degraded in areas where T-cell infiltration is highest, providing a noninvasive method to identify immunologically active microenvironments in secondary brain tumors. Cancer Res; 78(3); 610–6. ©2017 AACR

Beyond the WHO classification of meningioma: using molecular diagnostics to guide management.

Meningioma are the most common primary brain tumour. Classically, meningioma are phenotypically grouped using the World Health Organisation (WHO) classification system. However, it is now understood that the WHO approach overfits tumours into three grades, resulting in similarly graded tumours displaying phenotypically distinct behaviour. There is a growing body of research investigating the molecular biology of these tumours, including genomic, transcriptomic, metabolomic, proteomic, and methylomic profiling. Such advancements in molecular profiling of meningioma are providing greater accuracy in prognostication of tumours. Furthermore, a clearer understanding of tumour molecular biology highlights potential targets for pharmacotherapies. Currently, the routine application of in-depth tumour molecular analysis is limited, however as it becomes more widely available it will likely result in improved patient care. This review seeks to explore the important developments in meningioma molecular biology, discussed in the context of their clinical importance

Immune checkpoint inhibitor treatment of brain metastasis associated with a less invasive growth pattern, higher T-cell infiltration and raised tumor ADC on diffusion weighted MRI

BackgroundBrain metastases are the most common intracranial tumors with an increasing incidence. They are an important cause of morbidity and mortality in patients with solid organ cancer and a focus of recent clinical research and experimental interest. Immune checkpoint inhibitors are being increasingly used to treat solid organ cancers.MethodsTo determine whether immune checkpoint inhibitors were biologically effective in the brain, we compared melanoma brain metastasis samples where treatment with ipilimumab had occurred preoperatively to those who had not received any immune modulating therapy and looked for histopathological (invasion, vascularity, metastasis inducing proteins, matrix metalloproteinases, immune cell infiltration, tissue architecture) and advanced MRI differences (diffusion weighted imaging).ResultsCo-localized tissue samples from the same regions as MRI regions of interest showed significantly lower vascularity (density of CD34 + vessels) in the core and higher T-cell infiltration (CD3 + cells) in the leading edge for ipilimumab-treated brain metastasis samples than for untreated cases and this correlated with a higher tumor ADC signal at post-treatment/preoperative MRI brain.ConclusionsTreatment of a melanoma brain metastasis with ipilimumab appears to cause measurable biological changes in the tumor that can be correlated with post-treatment diffusion weighted MRI imaging, suggesting both a mechanism of action and a possible surrogate marker of efficacy

The growth rate and clinical outcomes of radiation induced meningioma undergoing treatment or active monitoring

INTRODUCTION: Radiation induced meningioma (RIM) incidence is increasing in line with improved childhood cancer survival. No optimal management strategy consensus exists. This study aimed to delineate meningioma growth rates from tumor discovery and correlate with clinical outcomes. METHODS: Retrospective study of patients with a RIM, managed at a specialist tertiary neuroscience center (2007–2019). Tumor volume was measured from diagnosis and at subsequent interval scans. Meningioma growth rate was determined using a linear mixed-effects model. Clinical outcomes were correlated with growth rates accounting for imaging and clinical prognostic factors. RESULTS: Fifty-four patients (110 meningiomas) were included. Median duration of follow-up was 74 months (interquartile range [IQR], 41–102 months). Mean radiation dose was 41 Gy (standard deviation [SD] = 14.9) with a latency period of 34.4 years (SD = 13.7). Median absolute growth rate was 0.62 cm(3)/year and the median relative growth rate was 72%/year. Forty meningiomas (between 27 patients) underwent surgical intervention after a median follow-up duration of 4 months (IQR 2–35). Operated RIMs were clinically aggressive, likely to be WHO grade 2 at first resection (43.6%) and to progress after surgery (41%). Median time to progression was 28 months (IQR 13–60.5). A larger meningioma at discovery was associated with growth (HR 1.2 [95% CI 1.0–1.5], P = 0.039) but not progression after surgery (HR 2.2 [95% CI 0.7–6.6], P = 0.181). Twenty-seven (50%) patients had multiple meningiomas by the end of the study. CONCLUSION: RIMs exhibit high absolute and relative growth rates after discovery. Surgery is recommended for symptomatic or rapidly growing meningiomas only. Recurrence risk after surgery is high. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11060-021-03761-3

DNA methylation-based profiling for paediatric CNS tumour diagnosis and treatment: a population-based study

Background: marked variation exists in the use of genomic data in tumour diagnosis, and optimal integration with conventional diagnostic technology remains uncertain despite several studies reporting improved diagnostic accuracy, selection for targeted treatments, and stratification for trials. Our aim was to assess the added value of molecular profiling in routine clinical practice and the impact on conventional and experimental treatments.Methods: this population-based study assessed the diagnostic and clinical use of DNA methylation-based profiling in childhood CNS tumours using two large national cohorts in the UK. In the diagnostic cohort—which included routinely diagnosed CNS tumours between Sept 1, 2016, and Sept 1, 2018—we assessed how the methylation profile altered or refined diagnosis in routine clinical practice and estimated how this would affect standard patient management. For the archival cohort of diagnostically difficult cases, we established how many cases could be solved using modern standard pathology, how many could only be solved using the methylation profile, and how many remained unsolvable.Findings: of 484 patients younger than 20 years with CNS tumours, 306 had DNA methylation arrays requested by the neuropathologist and were included in the diagnostic cohort. Molecular profiling added a unique contribution to clinical diagnosis in 107 (35%; 95% CI 30–40) of 306 cases in routine diagnostic practice—providing additional molecular subtyping data in 99 cases, amended the final diagnosis in five cases, and making potentially significant predictions in three cases. We estimated that it could change conventional management in 11 (4%; 95% CI 2–6) of 306 patients. Among 195 historically difficult-to-diagnose tumours in the archival cohort, 99 (51%) could be diagnosed using standard methods, with the addition of methylation profiling solving a further 34 (17%) cases. The remaining 62 (32%) cases were unresolved despite specialist pathology and methylation profiling.Interpretation: together, these data provide estimates of the impact that could be expected from routine implementation of genomic profiling into clinical practice, and indicate limitations where additional techniques will be required. We conclude that DNA methylation arrays are a useful diagnostic adjunct for childhood CNS tumours