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The high affinity and specificity of peptides towards biological targets, in addition to their favorable pharmacological properties, has encouraged the development of many peptide-based pharmaceuticals, including peptide-based positron emission tomography (PET) radiopharmaceuticals. However, the poor in vivo stability of unmodified peptides against proteolysis is a major challenge that must be overcome, as it can result in an impractically short in vivo biological half-life and a subsequently poor bioavailability when used in imaging and therapeutic applications. Consequently, many biologically and pharmacologically interesting peptide-based drugs may never see application. A potential way to overcome this is using peptide analogues designed to mimic the pharmacophore of a native peptide while also containing unnatural modifications that act to maintain or improve the pharmacological properties. This review explores strategies that have been developed to increase the metabolic stability of peptide-based pharmaceuticals. It includes modifications of the C- and/or N-termini, introduction of d- or other unnatural amino acids, backbone modification, PEGylation and alkyl chain incorporation, cyclization and peptide bond substitution, and where those strategies have been, or could be, applied to PET peptide-based radiopharmaceuticals.

ObjectivesSchwannomatosis is a dominantly inherited condition predisposing to schwannomas of mainly spinal and peripheral nerves with some diagnostic overlap with neurofibromatosis-2 (NF2), but the underlying epidemiology is poorly understood. We present the birth incidence and prevalence allowing for overlap with NF2.MethodsSchwannomatosis and NF2 cases were ascertained from the Manchester region of England (population=4.8 million) and from across the UK. Point prevalence and birth incidence were calculated from regional birth statistics. Genetic analysis was also performed on NF2, LZTR1 and SMARCB1 on blood and tumour DNA samples when available.ResultsRegional prevalence for schwannomatosis and NF2 were 1 in 126 315 and 50 500, respectively, with calculated birth incidences of 1 in 68 956 and 1 in 27 956. Mosaic NF2 causes a substantial overlap with schwannomatosis resulting in the misdiagnosis of at least 9% of schwannomatosis cases. LZTR1-associated schwannomatosis also causes a small number of cases that are misdiagnosed with NF2 (1%–2%), due to the occurrence of a unilateral vestibular schwannoma. Patients with schwannomatosis had lower numbers of non-vestibular cranial schwannomas, but more peripheral and spinal nerve schwannomas with pain as a predominant presenting symptom. Life expectancy was significantly better in schwannomatosis (mean age at death 76.9) compared with NF2 (mean age at death 66.2; p=0.004).ConclusionsWithin the highly ascertained North-West England population, schwannomatosis has less than half the birth incidence and prevalence of NF2.

Traumatic brain injury remains a global health problem. Understanding the relative importance of outcome predictors helps optimize our treatment strategies by informing assessment protocols, clinical decisions and trial designs. In this study we establish importance ranking for outcome predictors based on receiver operating indices to identify key predictors of outcome and create simple predictive models. We then explore the associations between key outcome predictors using Bayesian networks to gain further insight into predictor importance. We analyzed the corticosteroid randomization after significant head injury (CRASH) trial database of 10008 patients and included patients for whom demographics, injury characteristics, computer tomography (CT) findings and Glasgow Outcome Scale (GCS) were recorded (total of 13 predictors, which would be available to clinicians within a few hours following the injury in 6945 patients). Predictions of clinical outcome (death or severe disability at 6 months) were performed using logistic regression models with 5-fold cross validation. Predictive performance was measured using standardized partial area (pAUC) under the receiver operating curve (ROC) and we used Delong test for comparisons. Variable importance ranking was based on pAUC targeted at specificity (pAUCSP) and sensitivity (pAUCSE) intervals of 90-100%. Probabilistic associations were depicted using Bayesian networks. Complete AUC analysis showed very good predictive power (AUC = 0.8237, 95% CI: 0.8138-0.8336) for the complete model. Specificity focused importance ranking highlighted age, pupillary, motor responses, obliteration of basal cisterns/3rd ventricle and midline shift. Interestingly when targeting model sensitivity, the highest-ranking variables were age, severe extracranial injury, verbal response, hematoma on CT and motor response. Simplified models, which included only these key predictors, had similar performance (pAUCSP = 0.6523, 95% CI: 0.6402-0.6641 and pAUCSE = 0.6332, 95% CI: 0.62-0.6477) compared to the complete models (pAUCSP = 0.6664, 95% CI: 0.6543-0.679, pAUCSE = 0.6436, 95% CI: 0.6289-0.6585, de Long p value 0.1165 and 0.3448 respectively). Bayesian networks showed the predictors that did not feature in the simplified models were associated with those that did. We demonstrate that importance based variable selection allows simplified predictive models to be created while maintaining prediction accuracy. Variable selection targeting specificity confirmed key components of clinical assessment in TBI whereas sensitivity based ranking suggested extracranial injury as one of the important predictors. These results help refine our approach to head injury assessment, decision-making and outcome prediction targeted at model sensitivity and specificity. Bayesian networks proved to be a comprehensive tool for depicting probabilistic associations for key predictors giving insight into why the simplified model has maintained accuracy.

Atypical meningiomas are common central nervous system neoplasms with high recurrence rate and poorer prognosis compared to their grade I counterparts. Surgical excision and radiotherapy remains the mainstay therapy but medical treatments are limited. We explore new drug candidates using computational drug repurposing based on the gene expression signature of atypical meningioma tissue with subsequent analysis of drug-generated expression profiles. We further explore possible mechanisms of action for the identified drug candidates using ingenuity pathway analysis (IPA). We extracted gene expression profiles for atypical meningiomas (12 samples) and normal meningeal tissue (4 samples) from the Gene Expression Omnibus, which were then used to generate a gene signature comprising of 281 differentially expressed genes. Drug candidates were explored using both the Board Institute Connectivity Map (cmap) and Library of Integrated Network-Based Cellular Signatures (LINCS). Functional analysis of significant differential gene expression for drug candidates was performed with IPA. Using our integrated approach, we identified multiple, already licensed, drug candidates such as emetine, verteporfin, phenoxybenzamine and trazodone. Analysis with IPA revealed that these drugs target signal cascades potentially relevant in pathogenesis of meningiomas, particular examples are the effect on ERK by trazodone, MAP kinases by emetine, and YAP-1 protein by verteporfin. Gene expression profiling and use of drug expression profiles have yielded several plausible drug candidates for treating atypical meningioma, some of which have already been suggested by preceding studies. Although our analyses suggested multiple anti-tumour mechanisms for these drugs, further in vivo studies are required for validation. To our knowledge this is the first study which combines relatively new, yet established computational techniques to identify additional treatments for a difficult to manage cerebral neoplasm. Beyond proposing already approved drug candidates in the management of atypical meningioma the study highlights the promise held by computational techniques in improving our management strategies.

Meningiomas are the most common primary brain tumor and their incidence and prevalence is increasing. This review summarizes current evidence regarding the embryogenesis of the human meninges in the context of meningioma pathogenesis and anatomical distribution. Though not mutually exclusive, chromosomal instability and pathogenic variants affecting the long arm of chromosome 22 (22q) result in meningiomas in neural-crest cell-derived meninges, while variants affecting Hedgehog signaling, PI3K signaling, TRAF7 , KLF4 , and POLR2A result in meningiomas in the mesodermal-derived meninges of the midline and paramedian anterior, central, and ventral posterior skull base. Current evidence regarding the common pathways for genetic pathogenesis and the anatomical distribution of meningiomas is presented alongside existing understanding of the embryological origins for the meninges prior to proposing next steps for this work.

Accurate vascular input function (VIF) derivation is essential in brain dynamic contrast-enhanced (DCE) MRI. The optimum site for VIF estimation is, however, debated. This study sought to compare VIFs extracted from the internal carotid artery (ICA) and its branches with an arrival-corrected vascular output function (VOF) derived from the superior sagittal sinus (VOF SSS ). DCE-MRI datasets from sixty-six patients with different brain tumours were retrospectively analysed and plasma gadolinium-based contrast agent (GBCA) concentration-time curves used to extract VOF/VIFs from the SSS, the ICA, and the middle cerebral artery. Semi-quantitative parameters across each first-pass VOF/VIF were compared and the relationship between these parameters and GBCA dose was evaluated. Through a test–retest study in 12 patients, the repeatability of each semiquantitative VOF/VIF parameter was evaluated; and through comparison with histopathological data the accuracy of kinetic parameter estimates derived using each VOF/VIF and the extended Tofts model was also assessed. VOF SSS provided a superior surrogate global input function compared to arteries, with greater contrast-to-noise ( p  < 0.001), higher peak ( p  < 0.001, repeated-measures ANOVA), and a greater sensitivity to interindividual plasma GBCA concentration. The repeatability of VOF SSS derived semi-quantitative parameters was good to excellent (ICC = 0.717–0.888) outperforming arterial based approaches. In contrast to arterial VIFs, kinetic parameters obtained using a SSS derived VOF permitted detection of intertumoural differences in both microvessel surface area and cell density within resected tissue specimens. These results support the usage of an arrival-corrected VOF SSS as a surrogate vascular input function for kinetic parameter mapping in brain DCE-MRI.

NF2 -related Schwannomatosis ( NF2 SWN) is a rare disease characterised by the growth of multiple nervous system neoplasms, including bilateral vestibular schwannoma (VS). VS tumours are characterised by extensive leucocyte infiltration. However, the immunological landscape in VS and the spatial determinants within the tumour microenvironment that shape the trajectory of disease are presently unknown. In this study, to elucidate the complex immunological networks across VS, we performed imaging mass cytometry (IMC) on clinically annotated VS samples from NF2 SWN patients. We reveal the heterogeneity in neoplastic cell, myeloid cell and T cell populations that co-exist within VS, and that distinct myeloid cell and Schwann cell populations reside within varied spatial contextures across characteristic Antoni A and B histomorphic niches. Interestingly, T-cell populations co-localise with tumour-associated macrophages (TAMs) in Antoni A regions, seemingly limiting their ability to interact with tumorigenic Schwann cells. This spatial landscape is altered in Antoni B regions, where T-cell populations appear to interact with PD-L1 + Schwann cells. We also demonstrate that prior bevacizumab treatment (VEGF-A antagonist) preferentially reduces alternatively activated-like TAMs, whilst enhancing CD44 expression, in bevacizumab-treated tumours. Together, we describe niche-dependent modes of T-cell regulation in NF2 SWN VS, indicating the potential for microenvironment-altering therapies for VS. Bilateral vestibular schwannomas (VS) are the main feature of NF2 -related schwannomatosis, but the immunological landscape of VS is poorly understood. By performing imaging mass cytometry, the authors assess the cellular heterogeneity in VS tumours and reveal niche-dependent modes of T-cell regulation in these neoplasms.

A key limitation of current dynamic contrast enhanced (DCE) MRI techniques is the requirement for full-dose gadolinium-based contrast agent (GBCA) administration. The purpose of this feasibility study was to develop and assess a new low GBCA dose protocol for deriving high-spatial resolution kinetic parameters from brain DCE-MRI. Nineteen patients with intracranial skull base tumours were prospectively imaged at 1.5 T using a single-injection, fixed-volume low GBCA dose, dual temporal resolution interleaved DCE-MRI acquisition. The accuracy of kinetic parameters (v e, K trans , v p ) derived using this new low GBCA dose technique was evaluated through both Monte-Carlo simulations (mean percent deviation, PD, of measured from true values) and an in vivo study incorporating comparison with a conventional full-dose GBCA protocol and correlation with histopathological data. The mean PD of data from the interleaved high-temporal-high-spatial resolution approach outperformed use of high-spatial, low temporal resolution datasets alone (p < 0.0001, t-test). Kinetic parameters derived using the low-dose interleaved protocol correlated significantly with parameters derived from a full-dose acquisition (p < 0.001) and demonstrated a significant association with tissue markers of microvessel density (p < 0.05). Our results suggest accurate high-spatial resolution kinetic parameter mapping is feasible with significantly reduced GBCA dose.

Stereotactic radiosurgery (SRS) is an established, effective therapy against vestibular schwannoma (VS). The mechanisms of tumour response are, however, unknown and in this study we sought to evaluate changes in the irradiated VS tumour microenvironment through a multinuclear MRI approach. Five patients with growing sporadic VS underwent a multi-timepoint comprehensive MRI protocol, which included diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE) MRI and a spiral 23 Na-MRI acquisition for total sodium concentration (TSC) quantification. Post-treatment voxelwise changes in TSC, DTI metrics and DCE-MRI derived microvascular biomarkers (K trans , v e and v p ) were evaluated and compared against pre-treatment values. Changes in tumour TSC and microvascular parameters were observable as early as 2 weeks post-treatment, preceding changes in structural imaging. At 6 months post-treatment there were significant voxelwise increases in tumour TSC ( p  < 0.001) and mean diffusivity ( p  < 0.001, repeated-measures ANOVA) with marked decreases in tumour microvascular parameters ( p  < 0.001, repeated-measures ANOVA). This study presents the first in vivo evaluation of alterations in the VS tumour microenvironment following SRS, demonstrating that changes in tumour sodium homeostasis and microvascular parameters can be imaged as early as 2 weeks following treatment. Future studies should seek to investigate these clinically relevant MRI metrics as early biomarkers of SRS response.

This study aimed to develop and evaluate a new DCE-MRI processing technique that combines LEGATOS, a dual-temporal resolution DCE-MRI technique, with multi-kinetic models. This technique enables high spatial resolution interrogation of flow and permeability effects, which is currently challenging to achieve. Twelve patients with neurofibromatosis type II-related vestibular schwannoma (20 tumours) undergoing bevacizumab therapy were imaged at 1.5 T both before and at 90 days following treatment. Using the new technique, whole-brain, high spatial resolution images of the contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular extracellular fraction (ve), capillary plasma flow (Fp), and the capillary permeability-surface area product (PS) could be obtained, and their predictive value was examined. Of the five microvascular parameters derived using the new method, baseline PS exhibited the strongest correlation with the baseline tumour volume (p = 0.03). Baseline ve showed the strongest correlation with the change in tumour volume, particularly the percentage tumour volume change at 90 days after treatment (p < 0.001), and PS demonstrated a larger reduction at 90 days after treatment (p = 0.0001) when compared to Ktrans or Fp alone. Both the capillary permeability-surface area product (PS) and the extravascular extracellular fraction (ve) significantly differentiated the ‘responder’ and ‘non-responder’ tumour groups at 90 days (p < 0.05 and p < 0.001, respectively). These results highlight that this novel DCE-MRI analysis approach can be used to evaluate tumour microvascular changes during treatment and the need for future larger clinical studies investigating its role in predicting antiangiogenic therapy response.