Glioblastoma hijacks neuronal mechanisms for brain invasion.

Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma cells forms a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs). Other subpopulations appear unconnected, and their biological role remains unclear. Here, we demonstrate that whole-brain colonization is fueled by glioblastoma cells that lack connections with other tumor cells and astrocytes yet receive synaptic input from neurons. This subpopulation corresponds to neuronal and neural-progenitor-like tumor cell states, as defined by single-cell transcriptomics, both in mouse models and in the human disease. Tumor cell invasion resembled neuronal migration mechanisms and adopted a Lévy-like movement pattern of probing the environment. Neuronal activity induced complex calcium signals in glioblastoma cells followed by the de novo formation of TMs and increased invasion speed. Collectively, superimposing molecular and functional single-cell data revealed that neuronal mechanisms govern glioblastoma cell invasion on multiple levels. This explains how glioblastoma's dissemination and cellular heterogeneity are closely interlinked.

Autonomous rhythmic activity in glioma networks drives brain tumour growth.

Diffuse gliomas, particularly glioblastomas, are incurable brain tumours1. They are characterized by networks of interconnected brain tumour cells that communicate via Ca2+ transients2-6. However, the networks' architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca2+ oscillations and are particularly connected to others. Their autonomous periodic Ca2+ transients preceded Ca2+ transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca2+ activity generates a vulnerability7 that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs.

Rapid Tumor DNA Analysis of Cerebrospinal Fluid Accelerates Treatment of Central Nervous System Lymphoma.

Delays and risks associated with neurosurgical biopsies preclude timely diagnosis and treatment of central nervous system (CNS) lymphoma and other CNS neoplasms. We prospectively integrated targeted rapid genotyping of cerebrospinal fluid (CSF) into the evaluation of 70 patients with CNS lesions of unknown etiology. Participants underwent genotyping of CSF-derived DNA using a qPCR-based approach for parallel detection of single-nucleotide variants in the MYD88, TERT promoter, IDH1, IDH2, BRAF and H3F3A genes within 80 minutes of sample acquisition. Canonical mutations were detected in 42% of patients with neoplasms, including cases of primary and secondary CNS lymphoma, glioblastoma, IDH-mutant brainstem glioma and H3K27M-mutant diffuse midline glioma. Genotyping results eliminated the need for surgical biopsies in 7/33 (21.2%) cases of newly diagnosed neoplasms, resulting in significantly accelerated initiation of disease-directed treatment (median 3 vs 12 days; p = 0.027). This assay was then implemented in a Clinical Laboratory Improvement Amendments (CLIA) environment, with 2-day median turnaround for diagnosis of central nervous system lymphoma from 66 patients across 4 clinical sites. Our study prospectively demonstrates that targeted rapid CSF genotyping influences oncologic management for suspected CNS tumors.

Glutamatergic synaptic input to glioma cells drives brain tumour progression.

A network of communicating tumour cells that is connected by tumour microtubes mediates the progression of incurable gliomas. Moreover, neuronal activity can foster malignant behaviour of glioma cells by non-synaptic paracrine and autocrine mechanisms. Here we report a direct communication channel between neurons and glioma cells in different disease models and human tumours: functional bona fide chemical synapses between presynaptic neurons and postsynaptic glioma cells. These neurogliomal synapses show a typical synaptic ultrastructure, are located on tumour microtubes, and produce postsynaptic currents that are mediated by glutamate receptors of the AMPA subtype. Neuronal activity including epileptic conditions generates synchronised calcium transients in tumour-microtube-connected glioma networks. Glioma-cell-specific genetic perturbation of AMPA receptors reduces calcium-related invasiveness of tumour-microtube-positive tumour cells and glioma growth. Invasion and growth are also reduced by anaesthesia and the AMPA receptor antagonist perampanel, respectively. These findings reveal a biologically relevant direct synaptic communication between neurons and glioma cells with potential clinical implications.

Deep-learning-based reconstruction of undersampled MRI to reduce scan times: a multicentre, retrospective, cohort study.

BACKGROUND: The extended acquisition times required for MRI limit its availability in resource-constrained settings. Consequently, accelerating MRI by undersampling k-space data, which is necessary to reconstruct an image, has been a long-standing but important challenge. We aimed to develop a deep convolutional neural network (dCNN) optimisation method for MRI reconstruction and to reduce scan times and evaluate its effect on image quality and accuracy of oncological imaging biomarkers. METHODS: In this multicentre, retrospective, cohort study, MRI data from patients with glioblastoma treated at Heidelberg University Hospital (775 patients and 775 examinations) and from the phase 2 CORE trial (260 patients, 1083 examinations, and 58 institutions) and the phase 3 CENTRIC trial (505 patients, 3147 examinations, and 139 institutions) were used to develop, train, and test dCNN for reconstructing MRI from highly undersampled single-coil k-space data with various acceleration rates (R=2, 4, 6, 8, 10, and 15). Independent testing was performed with MRIs from the phase 2/3 EORTC-26101 trial (528 patients with glioblastoma, 1974 examinations, and 32 institutions). The similarity between undersampled dCNN-reconstructed and original MRIs was quantified with various image quality metrics, including structural similarity index measure (SSIM) and the accuracy of undersampled dCNN-reconstructed MRI on downstream radiological assessment of imaging biomarkers in oncology (automated artificial intelligence-based quantification of tumour burden and treatment response) was performed in the EORTC-26101 test dataset. The public NYU Langone Health fastMRI brain test dataset (558 patients and 558 examinations) was used to validate the generalisability and robustness of the dCNN for reconstructing MRIs from available multi-coil (parallel imaging) k-space data. FINDINGS: In the EORTC-26101 test dataset, the median SSIM of undersampled dCNN-reconstructed MRI ranged from 0·88 to 0·99 across different acceleration rates, with 0·92 (95% CI 0·92-0·93) for 10-times acceleration (R=10). The 10-times undersampled dCNN-reconstructed MRI yielded excellent agreement with original MRI when assessing volumes of contrast-enhancing tumour (median DICE for spatial agreement of 0·89 [95% CI 0·88 to 0·89]; median volume difference of 0·01 cm3 [95% CI 0·00 to 0·03] equalling 0·21%; p=0·0036 for equivalence) or non-enhancing tumour or oedema (median DICE of 0·94 [95% CI 0·94 to 0·95]; median volume difference of -0·79 cm3 [95% CI -0·87 to -0·72] equalling -1·77%; p=0·023 for equivalence) in the EORTC-26101 test dataset. Automated volumetric tumour response assessment in the EORTC-26101 test dataset yielded an identical median time to progression of 4·27 months (95% CI 4·14 to 4·57) when using 10-times-undersampled dCNN-reconstructed or original MRI (log-rank p=0·80) and agreement in the time to progression in 374 (95·2%) of 393 patients with data. The dCNN generalised well to the fastMRI brain dataset, with significant improvements in the median SSIM when using multi-coil compared with single-coil k-space data (p<0·0001). INTERPRETATION: Deep-learning-based reconstruction of undersampled MRI allows for a substantial reduction of scan times, with a 10-times acceleration demonstrating excellent image quality while preserving the accuracy of derived imaging biomarkers for the assessment of oncological treatment response. Our developments are available as open source software and hold considerable promise for increasing the accessibility to MRI, pending further prospective validation. FUNDING: Deutsche Forschungsgemeinschaft (German Research Foundation) and an Else Kröner Clinician Scientist Endowed Professorship by the Else Kröner Fresenius Foundation.

PerSurge (NOA-30) phase II trial of perampanel treatment around surgery in patients with progressive glioblastoma.

BACKGROUND: Glioblastoma is the most frequent and a particularly malignant primary brain tumor with no efficacy-proven standard therapy for recurrence. It has recently been discovered that excitatory synapses of the AMPA-receptor subtype form between non-malignant brain neurons and tumor cells. This neuron-tumor network connectivity contributed to glioma progression and could be efficiently targeted with the EMA/FDA approved antiepileptic AMPA receptor inhibitor perampanel in preclinical studies. The PerSurge trial was designed to test the clinical potential of perampanel to reduce tumor cell network connectivity and tumor growth with an extended window-of-opportunity concept. METHODS: PerSurge is a phase IIa clinical and translational treatment study around surgical resection of progressive or recurrent glioblastoma. In this multicenter, 2-arm parallel-group, double-blind superiority trial, patients are 1:1 randomized to either receive placebo or perampanel (n = 66 in total). It consists of a treatment and observation period of 60 days per patient, starting 30 days before a planned surgical resection, which itself is not part of the study interventions. Only patients with an expected safe waiting interval are included, and a safety MRI is performed. Tumor cell network connectivity from resected tumor tissue on single cell transcriptome level as well as AI-based assessment of tumor growth dynamics in T2/FLAIR MRI scans before resection will be analyzed as the co-primary endpoints. Secondary endpoints will include further imaging parameters such as pre- and postsurgical contrast enhanced MRI scans, postsurgical T2/FLAIR MRI scans, quality of life, cognitive testing, overall and progression-free survival as well as frequency of epileptic seizures. Further translational research will focus on additional biological aspects of neuron-tumor connectivity. DISCUSSION: This trial is set up to assess first indications of clinical efficacy and tolerability of perampanel in recurrent glioblastoma, a repurposed drug which inhibits neuron-glioma synapses and thereby glioblastoma growth in preclinical models. If perampanel proved to be successful in the clinical setting, it would provide the first evidence that interference with neuron-cancer interactions may indeed lead to a benefit for patients, which would lay the foundation for a larger confirmatory trial in the future. TRIAL REGISTRATION: EU-CT number: 2023-503938-52-00 30.11.2023.

Repeat surgery of recurrent glioma for molecularly informed treatment in the age of precision oncology: A risk-benefit analysis.

PURPOSE: Surgery for recurrent glioma provides cytoreduction and tissue for molecularly informed treatment. With mostly heavily pretreated patients involved, it is unclear whether the benefits of repeat surgery outweigh its potential risks. METHODS: Patients receiving surgery for recurrent glioma WHO grade 2-4 with the goal of tissue sampling for targeted therapies were analyzed retrospectively. Complication rates (surgical, neurological) were compared to our institutional glioma surgery cohort. Tissue molecular diagnostic yield, targeted therapies and post-surgical survival rates were analyzed. RESULTS: Between 2017 and 2022, tumor board recommendation for targeted therapy through molecular diagnostics was made for 180 patients. Of these, 70 patients (38%) underwent repeat surgery. IDH-wildtype glioblastoma was diagnosed in 48 patients (69%), followed by IDH-mutant astrocytoma (n = 13; 19%) and oligodendroglioma (n = 9; 13%). Gross total resection (GTR) was achieved in 50 patients (71%). Tissue was processed for next-generation sequencing in 64 cases (91%), and for DNA methylation analysis in 58 cases (83%), while immunohistochemistry for mTOR phosphorylation was performed in 24 cases (34%). Targeted therapy was recommended in 35 (50%) and commenced in 21 (30%) cases. Postoperatively, 7 patients (11%) required revision surgery, compared to 7% (p = 0.519) and 6% (p = 0.359) of our reference cohorts of patients undergoing first and second craniotomy, respectively. Non-resolving neurological deterioration was documented in 6 cases (10% vs. 8%, p = 0.612, after first and 4%, p = 0.519, after second craniotomy). Median survival after repeat surgery was 399 days in all patients and 348 days in GBM patients after repeat GTR. CONCLUSION: Surgery for recurrent glioma provides relevant molecular diagnostic information with a direct consequence for targeted therapy under a reasonable risk of postoperative complications. With satisfactory postoperative survival it can therefore complement a multi-modal glioma therapy approach.

Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes.

OBJECTIVES: Radiomic features have demonstrated encouraging results for non-invasive detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data has led to poor generalizability. Here, we assessed the influence of different MRI-intensity normalization techniques on the performance of radiomics-based models for predicting molecular glioma subtypes. METHODS: Preoperative MRI-data from n = 615 patients with newly diagnosed glioma and known isocitrate dehydrogenase (IDH) and 1p/19q status were pre-processed using four different methods: no normalization (naive), N4 bias field correction (N4), N4 followed by either WhiteStripe (N4/WS), or z-score normalization (N4/z-score). A total of 377 Image-Biomarker-Standardisation-Initiative-compliant radiomic features were extracted from each normalized data, and 9 different machine-learning algorithms were trained for multiclass prediction of molecular glioma subtypes (IDH-mutant 1p/19q codeleted vs. IDH-mutant 1p/19q non-codeleted vs. IDH wild type). External testing was performed in public glioma datasets from UCSF (n = 410) and TCGA (n = 160). RESULTS: Support vector machine yielded the best performance with macro-average AUCs of 0.84 (naive), 0.84 (N4), 0.87 (N4/WS), and 0.87 (N4/z-score) in the internal test set. Both N4/WS and z-score outperformed the other approaches in the external UCSF and TCGA test sets with macro-average AUCs ranging from 0.85 to 0.87, replicating the performance of the internal test set, in contrast to macro-average AUCs ranging from 0.19 to 0.45 for naive and 0.26 to 0.52 for N4 alone. CONCLUSION: Intensity normalization of MRI data is essential for the generalizability of radiomic-based machine-learning models. Specifically, both N4/WS and N4/z-score approaches allow to preserve the high model performance, yielding generalizable performance when applying the developed radiomic-based machine-learning model in an external heterogeneous, multi-institutional setting. CLINICAL RELEVANCE STATEMENT: Intensity normalization such as N4/WS or N4/z-score can be used to develop reliable radiomics-based machine learning models from heterogeneous multicentre MRI datasets and provide non-invasive prediction of glioma subtypes. KEY POINTS: • MRI-intensity normalization increases the stability of radiomics-based models and leads to better generalizability. • Intensity normalization did not appear relevant when the developed model was applied to homogeneous data from the same institution. • Radiomic-based machine learning algorithms are a promising approach for simultaneous classification of IDH and 1p/19q status of glioma.

Evaluation of risdiplam efficacy in 5q spinal muscular atrophy: A systematic comparison of electrophysiologic with clinical outcome measures.

BACKGROUND: To assess compound muscle action potential (CMAP) amplitudes as electrophysiologic markers in relation to clinical outcome in adult patients with 5q-linked spinal muscular atrophy (SMA) before and during treatment with risdiplam. METHODS: In this monocentric longitudinal cohort study, CMAP of 18 adult patients with SMA type 2 or 3 were assessed at baseline (T0 ) and after 10 months (T10 ) of risdiplam treatment. CMAP amplitudes of the median, ulnar, peroneal, and tibial nerves were compared with established clinical outcome scores, and with the course of disease before start of treatment. RESULTS: During a pharmacotherapy-naive pre-treatment period of 328 ± 46 days, Revised Upper Limb Module (RULM) score and peroneal nerve CMAP amplitudes decreased, while CMAP of tibial and upper limb nerves remained unchanged. CMAP amplitudes positively correlated with clinical scores (Hammersmith Functional Motor Scale-Expanded [HFMSE], RULM) at T0 . During risdiplam treatment, HFMSE and Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP INTEND) scores increased, paralleled by marked increase of CMAP amplitudes in both median nerves (T10 -T0 ; right: Δ = 1.4 ± 1.4 mV, p = 0.0003; left: Δ = 1.3 ± 1.4 mV, p = 0.0007), but not in ulnar, peroneal, or tibial nerves. A robust increase of median nerve CMAP amplitudes correlated well with an increase in the HFMSE score (T10 -T0 ). Median nerve CMAP amplitudes at T0 were associated with subsequent risdiplam-related improvement of HFMSE and CHOP INTEND scores at T10 . CONCLUSIONS: Median nerve CMAP amplitudes increase with risdiplam treatment in adult SMA patients, and should be further evaluated as potential easy-to-use electrophysiologic markers in assessing and monitoring clinical response to therapy.

Integrated genetic analyses of immunodeficiency-associated Epstein-Barr virus- (EBV) positive primary CNS lymphomas.

Immunodeficiency-associated primary CNS lymphoma (PCNSL) represents a distinct clinicopathological entity, which is typically Epstein-Barr virus-positive (EBV+) and carries an inferior prognosis. Genetic alterations that characterize EBV-related CNS lymphomagenesis remain unclear precluding molecular classification and targeted therapies. In this study, a comprehensive genetic analysis of 22 EBV+ PCNSL, therefore, integrated clinical and pathological information with exome and RNA sequencing (RNASeq) data. EBV+ PCNSL with germline controls carried a median of 55 protein-coding single nucleotide variants (SNVs; range 24-217) and 2 insertions/deletions (range 0-22). Genetic landscape was largely shaped by aberrant somatic hypermutation with a median of 41.01% (range 31.79-53.49%) of SNVs mapping to its target motifs. Tumors lacked established SNVs (MYD88, CD79B, PIM1) and copy number variants (CDKN2A, HLA loss) driving EBV- PCNSL. Instead, EBV+ PCNSL were characterized by SOCS1 mutations (26%), predicted to disinhibit JAK/STAT signaling, and mutually exclusive gain-of-function NOTCH pathway SNVs (26%). Copy number gains were enriched on 11q23.3, a locus directly targeted for chromosomal aberrations by EBV, that includes SIK3 known to protect from cytotoxic T-cell responses. Losses covered 5q31.2 (STING), critical for sensing viral DNA, and 17q11 (NF1). Unsupervised clustering of RNASeq data revealed two distinct transcriptional groups, that shared strong expression of CD70 and IL1R2, previously linked to tolerogenic tumor microenvironments. Correspondingly, deconvolution of bulk RNASeq data revealed elevated M2-macrophage, T-regulatory cell, mast cell and monocyte fractions in EBV+ PCNSL. In addition to novel insights into the pathobiology of EBV+ PCNSL, the data provide the rationale for the exploration of targeted therapies including JAK-, NOTCH- and CD70-directed approaches.

Conventional and emerging treatments of astrocytomas and oligodendrogliomas.

PURPOSE: Astrocytomas and oligodendrogliomas are mainly diffuse primary brain tumors harboring a diagnostic and prognostically favorable isocitrate dehydrogenase mutation. They are still incurable besides growing molecular knowledge and therapy options. Circumscribed astrocytomas are also discussed here, although they represent a separate entity despite similarities in the nomenclature. METHODS: We reviewed clinical trials, preclinical approaches as well as guideline recommendations form the major scientific Neuro-Oncology organizations for astrocytomas and oligodendrogliomas according to PRISMA guidelines. RESULTS: After histopathological diagnosis and eventually a maximal safe resection, patients with good prognostic factors may be followed by magnetic resonance imaging (MRI). If further treatment is necessary, either after diagnosis or at progression, diffuse astrocytomas and oligodendrogliomas are mainly treated with combined radiochemotherapy or maximal safe resection followed by combined radiochemotherapy according to current guidelines based on randomized trials. Circumscribed gliomas like pilocytic astrocytomas, CNS WHO grade 1, or pleomorphic xanthoastrocytomas, CNS WHO grade 2, are often treated with surgery alone. Current approaches for therapy optimization include decision of the best chemotherapy regimen. The IDH mutation presents a rational target for small molecule inhibition and immune therapy in diffuse astrocytomas and oligodendrogliomas, while the BRAF pathway is frequently mutated and treatable in circumscribed gliomas. CONCLUSION: Despite establishment of standard treatment approaches for gliomas that include resection, radio- and chemotherapy, there is a lack of effective treatments for progressive disease. Immune- and targeted therapies are currently investigated.

Oligosarcomas, IDH-mutant are distinct and aggressive.

Oligodendrogliomas are defined at the molecular level by the presence of an IDH mutation and codeletion of chromosomal arms 1p and 19q. In the past, case reports and small studies described gliomas with sarcomatous features arising from oligodendrogliomas, so called oligosarcomas. Here, we report a series of 24 IDH-mutant oligosarcomas from 23 patients forming a distinct methylation class. The tumors were recurrences from prior oligodendrogliomas or developed de novo. Precursor tumors of 12 oligosarcomas were histologically and molecularly indistinguishable from conventional oligodendrogliomas. Oligosarcoma tumor cells were embedded in a dense network of reticulin fibers, frequently showing p53 accumulation, positivity for SMA and CALD1, loss of OLIG2 and gain of H3K27 trimethylation (H3K27me3) as compared to primary lesions. In 5 oligosarcomas no 1p/19q codeletion was detectable, although it was present in the primary lesions. Copy number neutral LOH was determined as underlying mechanism. Oligosarcomas harbored an increased chromosomal copy number variation load with frequent CDKN2A/B deletions. Proteomic profiling demonstrated oligosarcomas to be highly distinct from conventional CNS WHO grade 3 oligodendrogliomas with consistent evidence for a smooth muscle differentiation. Expression of several tumor suppressors was reduced with NF1 being lost frequently. In contrast, oncogenic YAP1 was aberrantly overexpressed in oligosarcomas. Panel sequencing revealed mutations in NF1 and TP53 along with IDH1/2 and TERT promoter mutations. Survival of patients was significantly poorer for oligosarcomas as first recurrence than for grade 3 oligodendrogliomas as first recurrence. These results establish oligosarcomas as a distinct group of IDH-mutant gliomas differing from conventional oligodendrogliomas on the histologic, epigenetic, proteomic, molecular and clinical level. The diagnosis can be based on the combined presence of (a) sarcomatous histology, (b) IDH-mutation and (c) TERT promoter mutation and/or 1p/19q codeletion, or, in unresolved cases, on its characteristic DNA methylation profile.

Diagnostic biomarkers from proteomic characterization of cerebrospinal fluid in patients with brain malignancies.

Recent technological advances in molecular diagnostics through liquid biopsies hold the promise to repetitively monitor tumor evolution and treatment response of brain malignancies without the need of invasive surgical tissue accrual. Here, we implemented a mass spectrometry-based protein analysis pipeline which identified hundreds of proteins in 251 cerebrospinal fluid (CSF) samples from patients with four types of brain malignancies (glioblastoma, lymphoma, brain metastasis, and leptomeningeal disease [LMD]) and from healthy individuals with a focus on glioblastoma in a retrospective and confirmatory prospective observational study. CSF proteome deregulation via disruption of the blood brain barrier appeared to be largely conserved across brain tumor entities. CSF analysis of glioblastoma patients identified two proteomic clusters that correlated with tumor size and patient survival. By integrating CSF data with proteomic analyses of matching glioblastoma tumor tissue and primary glioblastoma cells, we identified potential CSF biomarkers for glioblastoma, in particular chitinase-3-like protein 1 (CHI3L1) and glial fibrillary acidic protein (GFAP). Key findings were validated in a prospective cohort consisting of 35 glioma patients. Finally, in LMD patients who frequently undergo repeated CSF work-up, we explored our proteomic pipeline as a mean to profile consecutive CSF samples. Therefore, proteomic analysis of CSF in brain malignancies has the potential to reveal biomarkers for diagnosis and therapy monitoring.

Cerebrospinal fluid proteomic profiling in nusinersen-treated patients with spinal muscular atrophy.

Promising results from recent clinical trials on the approved antisense oligonucleotide nusinersen in pediatric patients with 5q-linked spinal muscular atrophy (SMA) still have to be confirmed in adult patients but are hindered by a lack of sensitive biomarkers that indicate an early therapeutic response. Changes in the overall neurochemical composition of cerebrospinal fluid (CSF) under therapy may yield additive diagnostic and predictive information. With this prospective proof-of-concept and feasibility study, we evaluated non-targeted CSF proteomic profiles by mass spectrometry along with basic CSF parameters of 10 adult patients with SMA types 2 or 3 before and after 10 months of nusinersen therapy, in comparison with 10 age- and gender-matched controls. These data were analyzed by bioinformatics and correlated with clinical outcomes assessed by the Hammersmith Functional Rating Scale Expanded (HFMSE). CSF proteomic profiles of SMA patients differed from controls. Two groups of SMA patients were identified based on unsupervised clustering. These groups differed in age and expression of proteins related to neurodegeneration and neuroregeneration. Intraindividual CSF differences in response to nusinersen treatment varied between patients who clinically improved and those who did not. Data are available via ProteomeXchange with identifier PXD016757. Comparative CSF proteomic analysis in adult SMA patients before and after treatment with nusinersen-identified subgroups and treatment-related changes and may therefore be suitable for diagnostic and predictive analyses.

Noninvasive Characterization of Tumor Angiogenesis and Oxygenation in Bevacizumab-treated Recurrent Glioblastoma by Using Dynamic Susceptibility MRI: Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial.

Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dynamic susceptibility contrast agent-enhanced (DSC) MRI and evaluate its potential for predicting outcome from administration of bevacizumab. Materials and Methods In this secondary analysis of the prospective randomized phase II/III European Organization for Research and Treatment of Cancer 26101 trial conducted between October 2011 and December 2015 in 596 patients with first recurrence of glioblastoma, the subset of patients with availability of anatomic MRI and DSC MRI at baseline and first follow-up was analyzed. Patients were allocated into those administered bevacizumab (hereafter, the BEV group; either bevacizumab monotherapy or bevacizumab with lomustine) and those not administered bevacizumab (hereafter, the non-BEV group with lomustine monotherapy). Contrast-enhanced tumor volume, noncontrast-enhanced T2 fluid-attenuated inversion recovery (FLAIR) signal abnormality volume, Gaussian-normalized relative cerebral blood volume (nrCBV), Gaussian-normalized relative blood flow (nrCBF), and tumor metabolic rate of oxygen (nTMRO2) was quantified. The predictive ability of these imaging parameters was assessed with multivariable Cox regression and formal interaction testing. Results A total of 254 of 596 patients were evaluated (mean age, 57 years ± 11; 155 men; 161 in the BEV group and 93 in non-BEV group). Progression-free survival was longer in the BEV group (3.7 months; 95% confidence interval [CI]: 3.0, 4.2) compared with the non-BEV group (2.5 months; 95% CI: 1.5, 2.9; P = .01), whereas OS was not different (P = .15). The nrCBV decreased for the BEV group (-16.3%; interquartile range [IQR], -39.5% to 12.0%; P = .01), but not for the non-BEV group (1.2%; IQR, -17.9% to 23.3%; P = .19) between baseline and first follow-up. An identical pattern was observed for both nrCBF and nTMRO2 values. Contrast-enhanced tumor and noncontrast-enhanced T2 FLAIR signal abnormality volumes decreased for the BEV group (-66% [IQR, -83% to -35%] and -33% [IQR, -71% to -5%], respectively; P < .001 for both), whereas they increased for the non-BEV group (30% [IQR, -17% to 98%], P = .001; and 10% [IQR, -13% to 82%], P = .02, respectively) between baseline and first follow-up. None of the assessed MRI parameters were predictive for OS in the BEV group. Conclusion Bevacizumab treatment decreased tumor volumes, angiogenesis, and oxygenation, thereby reflecting its effectiveness for extending progression-free survival; however, these parameters were not predictive of overall survival (OS), which highlighted the challenges of identifying patients that derive an OS benefit from bevacizumab. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Dillon in this issue.

cMyc and ERK activity are associated with resistance to ALK inhibitory treatment in glioblastoma.

BACKGROUND: Anaplastic lymphoma kinase (ALK) is expressed in ~ 60% of glioblastomas and conveys tumorigenic functions. Therefore, ALK inhibitory strategies with alectinib are conceivable for patients with glioblastoma. The aims of this preclinical study were to investigate efficacy as well as to understand and potentially overcome primary and acquired resistance mechanisms of alectinib in glioblastoma. METHODS: Efficacy of alectinib was analyzed dependent on ALK expression in different glioblastoma initiating cells and after lentiviral knockdown of ALK. Alectinib resistant cells were generated by continuous treatment with increasing alectinib doses over 3 months. M-RNA, phospho-protein and protein regulation were analyzed to decipher relevant pathways associated to treatment or resistance and specifically inhibited to evaluate rational salvage therapies. RESULTS: Alectinib reduced clonogenicity and proliferation and induced apoptosis in ALK expressing glioblastoma initiating cells, whereas cells without ALK expression or after ALK depletion via knockdown showed primary resistance against alectinib. High expression of cMyc and activation of the ERK1/2 pathway conferred resistance against alectinib in ALK expressing glioblastoma cells. Pharmacological inhibition of these pathways by cMyc inhibitor or MEK inhibitor, trametinib, overcame alectinib resistance and re-sensitized resistant cells to continued alectinib treatment. The combination of alectinib with radiotherapy demonstrated synergistic effects in inhibition of clonogenicity in non-resistant and alectinib resistant glioblastoma cells. CONCLUSION: The data offer rationales for alectinib treatment in ALK expressing glioblastoma and for the use of ALK expression status as potential biomarker for alectinib treatment. In addition, the results propose MEK inhibition or radiotherapy as reasonable salvage treatments after acquired alectinib resistance.

Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly rely on manual two-dimensional measurements of contrast-enhancing (CE) target lesions and thus restrict both reliability and accurate assessment of tumour burden and treatment response. We aimed to develop a framework relying on artificial neural networks (ANNs) for fully automated quantitative analysis of MRI in neuro-oncology to overcome the inherent limitations of manual assessment of tumour burden. METHODS: In this retrospective study, we compiled a single-institution dataset of MRI data from patients with brain tumours being treated at Heidelberg University Hospital (Heidelberg, Germany; Heidelberg training dataset) to develop and train an ANN for automated identification and volumetric segmentation of CE tumours and non-enhancing T2-signal abnormalities (NEs) on MRI. Independent testing and large-scale application of the ANN for tumour segmentation was done in a single-institution longitudinal testing dataset from the Heidelberg University Hospital and in a multi-institutional longitudinal testing dataset from the prospective randomised phase 2 and 3 European Organisation for Research and Treatment of Cancer (EORTC)-26101 trial (NCT01290939), acquired at 38 institutions across Europe. In both longitudinal datasets, spatial and temporal tumour volume dynamics were automatically quantified to calculate time to progression, which was compared with time to progression determined by RANO, both in terms of reliability and as a surrogate endpoint for predicting overall survival. We integrated this approach for fully automated quantitative analysis of MRI in neuro-oncology within an application-ready software infrastructure and applied it in a simulated clinical environment of patients with brain tumours from the Heidelberg University Hospital (Heidelberg simulation dataset). FINDINGS: For training of the ANN, MRI data were collected from 455 patients with brain tumours (one MRI per patient) being treated at Heidelberg hospital between July 29, 2009, and March 17, 2017 (Heidelberg training dataset). For independent testing of the ANN, an independent longitudinal dataset of 40 patients, with data from 239 MRI scans, was collected at Heidelberg University Hospital in parallel with the training dataset (Heidelberg test dataset), and 2034 MRI scans from 532 patients at 34 institutions collected between Oct 26, 2011, and Dec 3, 2015, in the EORTC-26101 study were of sufficient quality to be included in the EORTC-26101 test dataset. The ANN yielded excellent performance for accurate detection and segmentation of CE tumours and NE volumes in both longitudinal test datasets (median DICE coefficient for CE tumours 0·89 [95% CI 0·86-0·90], and for NEs 0·93 [0·92-0·94] in the Heidelberg test dataset; CE tumours 0·91 [0·90-0·92], NEs 0·93 [0·93-0·94] in the EORTC-26101 test dataset). Time to progression from quantitative ANN-based assessment of tumour response was a significantly better surrogate endpoint than central RANO assessment for predicting overall survival in the EORTC-26101 test dataset (hazard ratios ANN 2·59 [95% CI 1·86-3·60] vs central RANO 2·07 [1·46-2·92]; p<0·0001) and also yielded a 36% margin over RANO (p<0·0001) when comparing reliability values (ie, agreement in the quantitative volumetrically defined time to progression [based on radiologist ground truth vs automated assessment with ANN] of 87% [266 of 306 with sufficient data] compared with 51% [155 of 306] with local vs independent central RANO assessment). In the Heidelberg simulation dataset, which comprised 466 patients with brain tumours, with 595 MRI scans obtained between April 27, and Sept 17, 2018, automated on-demand processing of MRI scans and quantitative tumour response assessment within the simulated clinical environment required 10 min of computation time (average per scan). INTERPRETATION: Overall, we found that ANN enabled objective and automated assessment of tumour response in neuro-oncology at high throughput and could ultimately serve as a blueprint for the application of ANN in radiology to improve clinical decision making. Future research should focus on prospective validation within clinical trials and application for automated high-throughput imaging biomarker discovery and extension to other diseases. FUNDING: Medical Faculty Heidelberg Postdoc-Program, Else Kröner-Fresenius Foundation.

Routine RNA sequencing of formalin-fixed paraffin-embedded specimens in neuropathology diagnostics identifies diagnostically and therapeutically relevant gene fusions.

Molecular markers have become pivotal in brain tumor diagnostics. Mutational analyses by targeted next-generation sequencing of DNA and array-based DNA methylation assessment with copy number analyses are increasingly being used in routine diagnostics. However, the broad variety of gene fusions occurring in brain tumors is marginally covered by these technologies and often only assessed by targeted assays. Here, we assessed the feasibility and clinical value of investigating gene fusions in formalin-fixed paraffin-embedded (FFPE) tumor tissues by next-generation mRNA sequencing in a routine diagnostic setting. After establishment and optimization of a workflow applicable in a routine setting, prospective diagnostic application in a neuropathology department for 26 months yielded relevant fusions in 66 out of 101 (65%) analyzed cases. In 43 (43%) cases, the fusions were of decisive diagnostic relevance and in 40 (40%) cases the fusion genes rendered a druggable target. A major strength of this approach was its ability to detect fusions beyond the canonical alterations for a given entity, and the unbiased search for any fusion event in cases with uncertain diagnosis and, thus, uncertain spectrum of expected fusions. This included both rare variants of established fusions which had evaded prior targeted analyses as well as the detection of previously unreported fusion events. While the impact of fusion detection on diagnostics is highly relevant, it is especially the detection of "druggable" fusions which will most likely provide direct benefit to the patients. The wider application of this approach for unbiased fusion identification therefore promises to be a major advance in identifying alterations with immediate impact on patient care.

The miRNA biogenesis pathway prevents inappropriate expression of injury response genes in developing and adult Schwann cells.

Proper function of the nervous system depends on myelination. In peripheral nerves, Schwann cells (SCs) myelinate axons and the miRNA biogenesis pathway is required for developmental myelination and myelin maintenance. However, regulatory roles of this pathway at different stages of myelination are only partially understood. We addressed the requirement of the core miRNA biogenesis pathway components Dgcr8, Drosha, and Dicer in developing and adult SCs using mouse mutants with a comparative genetics and transcriptomics approach. We found that the microprocessor components Dgcr8 and Drosha are crucial for axonal radial sorting and to establish correct SC numbers upon myelination. Transcriptome analyses revealed a requirement of the microprocessor to prevent aberrantly increased expression of injury-response genes. Those genes are predicted targets of abundant miRNAs in sciatic nerves (SNs) during developmental myelination. In agreement, Dgcr8 and Dicer are required for proper maintenance of the myelinated SC state, where abundant miRNAs in adult SNs are predicted to target injury-response genes. We conclude that the miRNA biogenesis pathway in SCs is crucial for preventing inappropriate activity of injury-response genes in developing and adult SCs.

The Human Cytomegalovirus UL116 Gene Encodes an Envelope Glycoprotein Forming a Complex with gH Independently from gL.

UNLABELLED: Human cytomegalovirus (HCMV) is a major cause of morbidity and mortality in transplant patients and is the leading viral cause of birth defects after congenital infection. HCMV infection relies on the recognition of cell-specific receptors by one of the viral envelope glycoprotein complexes. Either the gH/gL/gO or the gH/gL/UL128/UL130/UL131A (Pentamer) complex has been found to fulfill this role, accounting for HCMV entry into almost all cell types. We have studied the UL116 gene product, a putative open reading frame identified by in silico analysis and predicted to code for a secreted protein. Virus infection experiments in mammalian cells demonstrated that UL116 is expressed late in the HCMV replication cycle and is a heavily glycosylated protein that first localizes to the cellular site of virus assembly and then inserts into the virion envelope. Transient-transfection studies revealed that UL116 is efficiently transported to the plasma membrane when coexpressed with gH and that gL competes with UL116 for gH binding. Further evidence for gH/UL116 complex formation was obtained by coimmunoprecipitation experiments on both transfected and infected cells and biochemical characterization of the purified complex. In summary, our results show that the product of the UL116 gene is an HCMV envelope glycoprotein that forms a novel gH-based complex alternative to gH/gL. Remarkably, the gH/UL116 complex is the first herpesvirus gH-based gL-less complex. IMPORTANCE: HCMV infection can cause severe disease in immunocompromised adults and infants infected in utero The dissection of the HCMV entry machinery is important to understand the mechanism of viral infection and to identify new vaccine antigens. The gH/gL/gO and gH/gL/UL128/UL130/UL131 (Pentamer) complexes play a key role in HCMV cell entry and tropism. Both complexes are formed by an invariant gH/gL scaffold on which the other subunits assemble. Here, we show that the UL116 gene product is expressed in infected cells and forms a heterodimer with gH. The gH/UL116 complex is carried on the infectious virions, although in smaller amounts than gH/gL complexes. No gH/UL116/gL ternary complex formed in transfected cells, suggesting that the gH/UL116 complex is independent from gL. This new gH-based gL-free complex represents a potential target for a protective HCMV vaccine and opens new perspectives on the comprehension of the HCMV cell entry mechanism and tropism.