IgG4 Overexpression Is Rare in Meningiomas with a Prominent Inflammatory Component: A Review of 16 Cases

Meningiomas with prominent inflammation are traditionally classified as “lymphoplasmacyte‐rich meningioma” (LPM). Both inflammatory and neoplastic meningeal proliferations have recently been linked to IgG4 disease, although a potential association with LPM has not been previously explored. Sixteen meningiomas with inflammatory cells outnumbering tumor cells were further characterized by CD3, CD20, CD68 and/or CD163, CD138, kappa, lambda, IgG and IgG4 immunostains. There were 11 female and 4 male patients, ranging from 22 to 78 (median 59) years of age. Tumors consisted of 10 World Health Organization (WHO) grade I, 5 grade II and 1 grade III LPMs. Immunohistochemically, the most numerous cell type was the macrophage in all cases followed by CD3‐positive T cells and fewer CD20‐positive B cells. Plasma cells ranged from moderate‐marked (N = 5) to rare (N = 7), or absent (N = 4). Maximal numbers of IgG4 plasma cells per high power field (HPF) ranged from 0 to 32, with only two cases having counts exceeding 10/HPF. The IgG4/IgG ratio was increased focally in only two cases (30% and 31%). Additionally, plasma cells represented only a minor component in most examples, whereas macrophages predominated, suggesting that “inflammation‐rich meningioma” may be a more accurate term. The inflammatory stimulus for most cases remains to be elucidated.     

Disturbed function of the blood–cerebrospinal fluid barrier aggravates neuro-inflammation

Multiple sclerosis (MS) is a chronic neuro-inflammatory disorder, which is marked by the invasion of the central nervous system by monocyte-derived macrophages and autoreactive T cells across the brain vasculature. Data from experimental animal models recently implied that the passage of leukocytes across the brain vasculature is preceded by their traversal across the blood–cerebrospinal fluid barrier (BCSFB) of the choroid plexus. The correlation between the presence of leukocytes in the CSF of patients suffering from MS and the number of inflammatory lesions as detected by magnetic resonance imaging suggests that inflammation at the choroid plexus contributes to the disease, although in a yet unknown fashion. We here provide first insights into the involvement of the choroid plexus in the onset and severity of the disease and in particular address the role of the tight junction protein claudin-3 (CLDN3) in this process. Detailed analysis of human post-mortem brain tissue revealed a selective loss of CLDN3 at the choroid plexus in MS patients compared to control tissues. Importantly, mice that lack CLDN3 have an impaired BCSFB and experience a more rapid onset and exacerbated clinical signs of experimental autoimmune encephalomyelitis, which coincides with enhanced levels of infiltrated leukocytes in their CSF. Together, this study highlights a profound role for the choroid plexus in the pathogenesis of multiple sclerosis, and implies that CLDN3 may be regarded as a crucial and novel determinant of BCSFB integrity.     

Embryonal tumor with abundant neuropil and true rosettes (ETANTR), ependymoblastoma,and medulloepithelioma share molecular similarity and comprise a single clinicopathological entity

Three histological variants are known within the family of embryonal rosette-forming neuroepithelial brain tumors. These include embryonal tumor with abundant neuropil and true rosettes (ETANTR), ependymoblastoma (EBL), and medulloepithelioma (MEPL). In this study, we performed a comprehensive clinical, pathological, and molecular analysis of 97 cases of these rare brain neoplasms, including genome-wide DNA methylation and copy number profiling of 41 tumors. We identified uniform molecular signatures in all tumors irrespective of histological patterns, indicating that ETANTR, EBL, and MEPL comprise a single biological entity. As such, future WHO classification schemes should consider lumping these variants into a single diagnostic category, such as embryonal tumor with multilayered rosettes (ETMR). We recommend combined LIN28A immunohistochemistry and FISH analysis of the 19q13.42 locus for molecular diagnosis of this tumor category. Recognition of this distinct pediatric brain tumor entity based on the fact that the three histological variants are molecularly and clinically uniform will help to distinguish ETMR from other embryonal CNS tumors and to better understand the biology of these highly aggressive and therapy-resistant pediatric CNS malignancies, possibly leading to alternate treatment strategies.     

Outcome Prediction in Moderate and Severe Traumatic Brain Injury: A Focus on Computed Tomography Variables

Background

With this study we aimed to design validated outcome prediction models in moderate and severe traumatic brain injury (TBI) using demographic, clinical, and radiological parameters.

Methods

Seven hundred consecutive moderate or severe TBI patients were included in this observational prospective cohort study. After inclusion, clinical data were collected, initial head computed tomography (CT) scans were rated, and at 6 months outcome was determined using the extended Glasgow Outcome Scale. Multivariate binary logistic regression analysis was applied to evaluate the association between potential predictors and three different outcome endpoints. The prognostic models that resulted were externally validated in a national Dutch TBI cohort.

Results

In line with previous literature we identified age, pupil responses, Glasgow Coma Scale score and the occurrence of a hypotensive episode post-injury as predictors. Furthermore, several CT characteristics were associated with outcome; the aspect of the ambient cisterns being the most powerful. After external validation using Receiver Operating Characteristic (ROC) analysis our prediction models demonstrated adequate discriminative values, quantified by the area under the ROC curve, of 0.86 for death versus survival and 0.83 for unfavorable versus favorable outcome. Discriminative power was less for unfavorable outcome in survivors: 0.69.

Conclusions

Outcome prediction in moderate and severe TBI might be improved using the models that were designed in this study. However, conventional demographic, clinical and CT variables proved insufficient to predict disability in surviving patients. The information that can be derived from our prediction rules is important for the selection and stratification of patients recruited into clinical TBI trials.