B cells orchestrate tolerance to the neuromyelitis optica autoantigen AQP4.

Neuromyelitis optica is a paradigmatic autoimmune disease of the central nervous system, in which the water-channel protein AQP4 is the target antigen1. The immunopathology in neuromyelitis optica is largely driven by autoantibodies to AQP42. However, the T cell response that is required for the generation of these anti-AQP4 antibodies is not well understood. Here we show that B cells endogenously express AQP4 in response to activation with anti-CD40 and IL-21 and are able to present their endogenous AQP4 to T cells with an AQP4-specific T cell receptor (TCR). A population of thymic B cells emulates a CD40-stimulated B cell transcriptome, including AQP4 (in mice and humans), and efficiently purges the thymic TCR repertoire of AQP4-reactive clones. Genetic ablation of Aqp4 in B cells rescues AQP4-specific TCRs despite sufficient expression of AQP4 in medullary thymic epithelial cells, and B-cell-conditional AQP4-deficient mice are fully competent to raise AQP4-specific antibodies in productive germinal-centre responses. Thus, the negative selection of AQP4-specific thymocytes is dependent on the expression and presentation of AQP4 by thymic B cells. As AQP4 is expressed in B cells in a CD40-dependent (but not AIRE-dependent) manner, we propose that thymic B cells might tolerize against a group of germinal-centre-associated antigens, including disease-relevant autoantigens such as AQP4.

A region-resolved proteomic map of the human brain enabled by high-throughput proteomics.

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).

The glioblastoma multiforme tumor site promotes the commitment of tumor-infiltrating lymphocytes to the TH17 lineage in humans.

Although glioblastoma multiforme (GBM) is not an invariably cold tumor, checkpoint inhibition has largely failed in GBM. In order to investigate T cell-intrinsic properties that contribute to the resistance of GBM to endogenous or therapeutically enhanced adaptive immune responses, we sorted CD4+ and CD8+ T cells from the peripheral blood, normal-appearing brain tissue, and tumor bed of nine treatment-naive patients with GBM. Bulk RNA sequencing of highly pure T cell populations from these different compartments was used to obtain deep transcriptomes of tumor-infiltrating T cells (TILs). While the transcriptome of CD8+ TILs suggested that they were partly locked in a dysfunctional state, CD4+ TILs showed a robust commitment to the type 17 T helper cell (TH17) lineage, which was corroborated by flow cytometry in four additional GBM cases. Therefore, our study illustrates that the brain tumor environment in GBM might instruct TH17 commitment of infiltrating T helper cells. Whether these properties of CD4+ TILs facilitate a tumor-promoting milieu and thus could be a target for adjuvant anti-TH17 cell interventions needs to be further investigated.

Amino acid PET vs. RANO MRI for prediction of overall survival in patients with recurrent high grade glioma under bevacizumab therapy.

PURPOSE: To summarize evidence on the comparative value of amino acid (AA) PET and conventional MRI for prediction of overall survival (OS) in patients with recurrent high grade glioma (rHGG) under bevacizumab therapy. METHODS: Medical databases were screened for studies with individual data on OS, follow-up MRI, and PET findings in the same patient. MRI images were assessed according to the RANO criteria. A receiver operating characteristic curve analysis was used to predict OS at 9 months. RESULTS: Five studies with a total of 72 patients were included. Median OS was significantly lower in the PET-positive than in the PET-negative group. PET findings predicted OS with a pooled sensitivity and specificity of 76% and 71%, respectively. Corresponding values for MRI were 32% and 82%. Area under the curve and sensitivity were significantly higher for PET than for MRI. CONCLUSION: For monitoring of patients with rHGG under bevacizumab therapy, AA-PET should be preferred over RANO MRI.

Resolving spatial response heterogeneity in glioblastoma.

PURPOSE: Spatial intratumoral heterogeneity poses a significant challenge for accurate response assessment in glioblastoma. Multimodal imaging coupled with advanced image analysis has the potential to unravel this response heterogeneity. METHODS: Based on automated tumor segmentation and longitudinal registration with follow-up imaging, we categorized contrast-enhancing voxels of 61 patients with suspected recurrence of glioblastoma into either true tumor progression (TP) or pseudoprogression (PsP). To allow the unbiased analysis of semantically related image regions, adjacent voxels with similar values of cerebral blood volume (CBV), FET-PET, and contrast-enhanced T1w were automatically grouped into supervoxels. We then extracted first-order statistics as well as texture features from each supervoxel. With these features, a Random Forest classifier was trained and validated employing a 10-fold cross-validation scheme. For model evaluation, the area under the receiver operating curve, as well as classification performance metrics were calculated. RESULTS: Our image analysis pipeline enabled reliable spatial assessment of tumor response. The predictive model reached an accuracy of 80.0% and a macro-weighted AUC of 0.875, which takes class imbalance into account, in the hold-out samples from cross-validation on supervoxel level. Analysis of feature importances confirmed the significant role of FET-PET-derived features. Accordingly, TP- and PsP-labeled supervoxels differed significantly in their 10th and 90th percentile, as well as the median of tumor-to-background normalized FET-PET. However, CBV- and T1c-related features also relevantly contributed to the model's performance. CONCLUSION: Disentangling the intratumoral heterogeneity in glioblastoma holds immense promise for advancing precise local response evaluation and thereby also informing more personalized and localized treatment strategies in the future.

The role of molecular tumor boards in neuro-oncology: a nationwide survey.

BACKGROUND: In neuro-oncology, the inclusion of tumor patients in the molecular tumor board has only become increasingly widespread in recent years, but so far there are no standards for indication, procedure, evaluation, therapy recommendations and therapy implementation of neuro-oncological patients. The present work examines the current handling of neuro-oncological patients included in molecular tumor boards in Germany. METHODS: We created an online based survey with questions covering the handling of neuro-oncologic patient inclusion, annotation of genetic analyses, management of target therapies and the general role of molecular tumor boards in neuro-oncology in Germany. We contacted all members of the Neuro-Oncology working group (NOA) of the German Cancer Society (DKG) by e-mail. RESULTS: 38 responses were collected. The majority of those who responded were specialists in neurosurgery or neurology with more than 10 years of professional experience working at a university hospital. Molecular tumor boards (MTB) regularly take place once a week and all treatment disciplines of neuro-oncology patients take part. The inclusions to the MTB are according to distinct tumors and predominantly in case of tumor recurrence. An independently MTB member mostly create the recommendations, which are regularly implemented in the tumor treatment. Recommendations are given for alteration classes 4 and 5. Problems exist mostly within the cost takeover of experimental therapies. The experimental therapies are mostly given in the department of medical oncology. CONCLUSIONS: Molecular tumor boards for neuro-oncological patients, by now, are not standardized in Germany. Similarities exists for patient inclusion and interpretation of molecular alterations; the time point of inclusion and implementation during the patient treatment differ between the various hospitals. Further studies for standardization and harmonisation are needed. In summary, most of the interviewees envision great opportunities and possibilities for molecular-based neuro-oncological therapy in the future.

Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma.

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.

Detection of SARS-CoV-2-RNA in post-mortem samples of human eyes.

PURPOSE: To detect SARS-CoV-2 RNA in post-mortem human eyes. Ocular symptoms are common in patients with COVID-19. In some cases, they can occur before the onset of respiratory and other symptoms. Accordingly, SARS-CoV-2 RNA has been detected in conjunctival samples and tear film of patients suffering from COVID-19. However, the detection and clinical relevance of intravitreal SARS-CoV-2 RNA still remain unclear due to so far contradictory reports in the literature. METHODS: In our study 20 patients with confirmed diagnosis of COVID-19 were evaluated post-mortem to assess the conjunctival and intraocular presence of SARS-CoV-2 RNA using sterile pulmonary and conjunctival swabs as well as intravitreal biopsies (IVB) via needle puncture. SARS-CoV-2 PCR and whole genome sequencing from the samples of the deceased patients were performed. Medical history and comorbidities of all subjects were recorded and analyzed for correlations with viral data. RESULTS: SARS-CoV-2 RNA was detected in 10 conjunctival (50%) and 6 vitreal (30%) samples. SARS-CoV-2 whole genome sequencing showed the distribution of cases largely reflecting the frequency of circulating lineages in the Munich area at the time of examination with no preponderance of specific variants. Especially there was no association between the presence of SARS-CoV-2 RNA in IVBs and infection with the variant of concern (VOC) alpha. Viral load in bronchial samples correlated positively with load in conjunctiva but not the vitreous. CONCLUSION: SARS-CoV-2 RNA can be detected post mortem in conjunctival tissues and IVBs. This is relevant to the planning of ophthalmologic surgical procedures in COVID-19 patients, such as pars plana vitrectomy or corneal transplantation. Furthermore, not only during surgery but also in an outpatient setting it is important to emphasize the need for personal protection in order to avoid infection and spreading of SARS-CoV-2. Prospective studies are needed, especially to determine the clinical relevance of conjunctival and intravitreal SARS-CoV-2 detection concerning intraocular affection in active COVID-19 state and in post-COVID syndrome.

High expression of estrogen receptor alpha and aromatase in glial tumor cells is associated with gender-independent survival benefits in glioblastoma patients.

INTRODUCTION: Glioblastoma multiforme (GBM) is a highly malignant glial tumor, affecting men more often than women. The reason for this gender-specific predominance remains unclear, raising the question whether these effects are subject to hormonal control. The purpose of this study was to examine the expression of estrogen receptor alpha (ERα) and aromatase in human GBM tissue samples in relation to patient survival and furthermore to investigate the effect of standard chemotherapy in combination with estradiol treatment on glioblastoma tumor cell lines in vitro. METHODS: 60 tissue samples (31 male, 29 female) of GBM patients were analysed with immunohistochemistry for ERα and aromatase for survival analyses. The cell lines LN18 and LN229 were treated with 17ß-estradiol (E2) in different dosing regimens and the cell viability was measured with MTT assay. After estradiol pre-treatment Temozolomide was added and tested again. RESULTS: High expression of ERα and aromatase in the GBM tissue samples was associated with significantly longer survival times of GBM patients, regardless of gender and body-mass-index. The treatment with high concentrations of estradiol resulted in lower tumor cell viability, compared to control. The cells significantly showed a stronger sensitivity against Temozolomid (TMZ) after estradiol pre-treatment. CONCLUSION: ERα-expression of glial tumour cells seems to play an important prognostic role as a biomarker in GBM, as well as the expression of the enzyme Aromatase. The combined treatment of GBM with standard chemotherapy and estradiol may be beneficial to patient's survival.

Correction to: Prognostic Value of Tumor Volume in Glioblastoma Patients: Size Also Matters for Patients with Incomplete Resection.

Due to a metadata tagging error the names of Stephanie E. Combs and Jan S. Kirschke were indexed incorrectly. Stephanie E. is the author's given name, and Jan S. is the author's given name.

Prognostic Value of Tumor Volume in Glioblastoma Patients: Size Also Matters for Patients with Incomplete Resection.

BACKGROUND: Incomplete resection of glioblastoma is discussed controversially in the era of combined radiochemotherapy. OBJECTIVE: The aim of this study was to analyze the benefit of subtotal tumor resection for glioblastoma patients as this was recently questioned in the era of radiochemotherapy. METHODS: Overall, 209 patients undergoing surgery for newly diagnosed WHO grade IV gliomas were retrospectively analyzed, and pre- and postoperative tumor volumes were manually segmented (cm3). Survival analyses were performed, including prognostic factors such as age, Karnofsky performance score (KPS), O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, and adjuvant treatment regimen. RESULTS: Pre- and postoperative tumor volume is significantly associated with pre- and postoperative KPS, as well as age (p < 0.001). Postoperative tumor volume remained a significant prognostic factor in a multivariate analysis, independent of other prognostic factors (hazard ratio 1.0365, 95% confidence interval 1.0235-1.0497, p < 0.001). CONCLUSIONS: In the era of molecularly-driven radiochemotherapy, glioblastoma surgery remains a major prognostic factor. Even in situations in which a gross total resection cannot be achieved, maximum safe reduction of tumor burden should be attempted.

CXCL9 and CXCL10 predict survival and are regulated by cyclooxygenase inhibition in advanced serous ovarian cancer.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are associated with improved survival in several epithelial cancers. The two chemokines CXCL9 and CXCL10 facilitate chemotactic recruitment of TILs, and their intratumoral accumulation is a conceivable way to improve TIL-dependent immune intervention in cancer. However, the prognostic impact of CXCL9 and CXCL10 in high-grade serous ovarian cancer (HGSC) is largely unknown. METHODS: One hundred and eighty four cases of HGSC were immunohistochemically analyzed for CXCL9, CXCL10. TILs were assessed using CD3, CD56 and FOXP3 staining. Chemokine regulation was investigated using the ovarian cancer cell lines OV-MZ-6 and SKOV-3. RESULTS: High expression of CXCL9 and CXCL10 was associated with an approximately doubled overall survival (n=70, CXCL9: HR 0.41; P=0.006; CXCL10: HR 0.46; P=0.010) which was confirmed in an independent validation set (n=114; CXCL9: HR 0.60; P=0.019; CXCL10: HR 0.52; P=0.005). Expression of CXCR3 ligands significantly correlated with TILs. In human ovarian cancer cell lines the cyclooxygenase (COX) metabolite Prostaglandin E2 was identified as negative regulator of chemokine secretion, whereas COX inhibition by indomethacin significantly upregulated CXCL9 and CXCL10. In contrast, celecoxib, the only COX inhibitor prospectively evaluated for therapy of ovarian cancer, suppressed NF-κB activation and inhibited chemokine release. CONCLUSION: Our results support the notion that CXCL9 and CXCL10 exert tumour-suppressive function by TIL recruitment in human ovarian cancer. COX inhibition by indomethacin, not by celecoxib, may be a promising approach to concomitantly improve immunotherapies.

Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model.

Background: The diffuse growth pattern of glioblastoma is one of the main challenges for accurate treatment. Computational tumor growth modeling has emerged as a promising tool to guide personalized therapy. Here, we performed clinical and biological validation of a novel growth model, aiming to close the gap between the experimental state and clinical implementation. Methods: One hundred and twenty-four patients from The Cancer Genome Archive (TCGA) and 397 patients from the UCSF Glioma Dataset were assessed for significant correlations between clinical data, genetic pathway activation maps (generated with PARADIGM; TCGA only), and infiltration (Dw) as well as proliferation (ρ) parameters stemming from a Fisher-Kolmogorov growth model. To further evaluate clinical potential, we performed the same growth modeling on preoperative magnetic resonance imaging data from 30 patients of our institution and compared model-derived tumor volume and recurrence coverage with standard radiotherapy plans. Results: The parameter ratio Dw/ρ (P < .05 in TCGA) as well as the simulated tumor volume (P < .05 in TCGA/UCSF) were significantly inversely correlated with overall survival. Interestingly, we found a significant correlation between 11 proliferation pathways and the estimated proliferation parameter. Depending on the cutoff value for tumor cell density, we observed a significant improvement in recurrence coverage without significantly increased radiation volume utilizing model-derived target volumes instead of standard radiation plans. Conclusions: Identifying a significant correlation between computed growth parameters and clinical and biological data, we highlight the potential of tumor growth modeling for individualized therapy of glioblastoma. This might improve the accuracy of radiation planning in the near future.

Quantitative Assessment of Tumor Contact with Neurogenic Zones and Its Effects on Survival: Insights beyond Traditional Predictors.

So far, the cellular origin of glioblastoma (GBM) needs to be determined, with prevalent theories suggesting emergence from transformed endogenous stem cells. Adult neurogenesis primarily occurs in two brain regions: the subventricular zone (SVZ) and the subgranular zone (SGZ) of the hippocampal dentate gyrus. Whether the proximity of GBM to these neurogenic niches affects patient outcome remains uncertain. Previous studies often rely on subjective assessments, limiting the reliability of those results. In this study, we assessed the impact of GBM's relationship with the cortex, SVZ and SGZ on clinical variables using fully automated segmentation methods. In 177 glioblastoma patients, we calculated optimal cutpoints of minimal distances to the SVZ and SGZ to distinguish poor from favorable survival. The impact of tumor contact with neurogenic zones on clinical parameters, such as overall survival, multifocality, MGMT promotor methylation, Ki-67 and KPS score was also examined by multivariable regression analysis, chi-square test and Mann-Whitney-U. The analysis confirmed shorter survival in tumors contacting the SVZ with an optimal cutpoint of 14 mm distance to the SVZ, separating poor from more favorable survival. In contrast, tumor contact with the SGZ did not negatively affect survival. We did not find significant correlations with multifocality or MGMT promotor methylation in tumors contacting the SVZ, as previous studies discussed. These findings suggest that the spatial relationship between GBM and neurogenic niches needs to be assessed differently. Objective measurements disprove prior assumptions, warranting further research on this topic.

Postmortem Minimally Invasive Autopsy in Critically Ill COVID-19 Patients at the Bedside: A Proof-of-Concept Study at the ICU.

BACKGROUND: Economic restrictions and workforce cuts have continually challenged conventional autopsies. Recently, the COVID-19 pandemic has added tissue quality and safety requirements to the investigation of this disease, thereby launching efforts to upgrade autopsy strategies. METHODS: In this proof-of-concept study, we performed bedside ultrasound-guided minimally invasive autopsy (US-MIA) in the ICU of critically ill COVID-19 patients using a structured protocol to obtain non-autolyzed tissue. Biopsies were assessed for their quality (vitality) and length of biopsy (mm) and for diagnosis. The efficiency of the procedure was monitored in five cases by recording the time of each step and safety issues by swabbing personal protective equipment and devices for viral contamination. FINDINGS: Ultrasound examination and tissue procurement required a mean time period of 13 min and 54 min, respectively. A total of 318 multiorgan biopsies were obtained from five patients. Quality and vitality standards were fulfilled, which not only allowed for specific histopathological diagnosis but also the reliable detection of SARS-CoV-2 virions in unexpected organs using electronic microscopy and RNA-expressing techniques. INTERPRETATION: Bedside multidisciplinary US-MIA allows for the fast and efficient acquisition of autolytic-free tissue and offers unappreciated potential to overcome the limitations of research in postmortem studies.

Fluorescein-stained confocal laser endomicroscopy versus conventional frozen section for intraoperative histopathological assessment of intracranial tumors.

BACKGROUND: The aim of this clinical trial was to compare Fluorescein-stained intraoperative confocal laser endomicroscopy (CLE) of intracranial lesions and evaluation by a neuropathologist with routine intraoperative frozen section (FS) assessment by neuropathology. METHODS: In this phase II noninferiority, prospective, multicenter, nonrandomized, off-label clinical trial (EudraCT: 2019-004512-58), patients above the age of 18 years with any intracranial lesion scheduled for elective resection were included. The diagnostic accuracies of both CLE and FS referenced with the final histopathological diagnosis were statistically compared in a noninferiority analysis, representing the primary endpoint. Secondary endpoints included the safety of the technique and time expedited for CLE and FS. RESULTS: A total of 210 patients were included by 3 participating sites between November 2020 and June 2022. Most common entities were high-grade gliomas (37.9%), metastases (24.1%), and meningiomas (22.7%). A total of 6 serious adverse events in 4 (2%) patients were recorded. For the primary endpoint, the diagnostic accuracy for CLE was inferior with 0.87 versus 0.91 for FS, resulting in a difference of 0.04 (95% confidence interval -0.10; 0.02; P = .367). The median time expedited until intraoperative diagnosis was 3 minutes for CLE and 27 minutes for FS, with a mean difference of 27.5 minutes (standard deviation 14.5; P < .001). CONCLUSIONS: CLE allowed for a safe and time-effective intraoperative histological diagnosis with a diagnostic accuracy of 87% across all intracranial entities included. The technique achieved histological assessments in real time with a 10-fold reduction of processing time compared to FS, which may invariably impact surgical strategy on the fly.

Imaging meningioma biology: Machine learning predicts integrated risk score in WHO grade 2/3 meningioma.

Background: Meningiomas are the most common primary brain tumors. While most are benign (WHO grade 1) and have a favorable prognosis, up to one-fourth are classified as higher-grade, falling into WHO grade 2 or 3 categories. Recently, an integrated risk score (IRS) pertaining to tumor biology was developed and its prognostic relevance was validated in a large, multicenter study. We hypothesized imaging data to be reflective of the IRS. Thus, we assessed the potential of a machine learning classifier for its noninvasive prediction using preoperative magnetic resonance imaging (MRI). Methods: In total, 160 WHO grade 2 and 3 meningioma patients from 2 university centers were included in this study. All patients underwent surgery with histopathological workup including methylation analysis. Preoperative MRI scans were automatically segmented, and radiomic parameters were extracted. Using a random forest classifier, 3 machine learning classifiers (1 multiclass classifier for IRS and 2 binary classifiers for low-risk and high-risk prediction, respectively) were developed in a training set (120 patients) and independently tested in a hold-out test set (40 patients). Results: Multiclass IRS classification had a test set area under the curve (AUC) of 0.7, mostly driven by the difficulties in clearly separating medium-risk from high-risk patients. Consequently, a classifier predicting low-risk IRS versus medium-/high-risk showed a very high test accuracy of 90% (AUC 0.88). In particular, "sphericity" was associated with low-risk IRS classification. Conclusion: The IRS, in particular molecular low-risk, can be predicted from imaging data with high accuracy, making this important prognostic classification accessible by imaging.