BRAIN UK: Accessing NHS tissue archives for neuroscience research

A comprehensive spatiotemporal map of dystrophin isoform expression in the developing and adult human brain

Mutations in the dystrophin gene (DMD) cause the severe muscle-wasting disease Duchenne muscular dystrophy (DMD). Additionally, there is a high incidence of intellectual disability and neurobehavioural comorbidities in individuals with DMD. Similar behavioural abnormalities are found in mdx dystrophic mouse models. Unlike muscle, several dystrophin isoforms are expressed in the human brain, but a detailed map of regional and cellular localisation of dystrophin isoforms is missing. This is crucial in understanding the neuropathology of DMD individuals, and for evaluating the translatability of pre-clinical findings in DMD mouse models receiving genetic therapy interventions. Here, we provide a comprehensive dystrophin expression profile in human brains from early development to adulthood. We reveal expression of dp427p2, dp427c, dp427m and dp40 isoforms in human embryonic brains, not previously reported. We also detected dp427p2 expression and developmental regulation in human brain across the lifespan. In addition we showed by in situ hybridisation that dp140 was greatly downregulated in adult brains. Importantly, our data also demonstrate expression of DMD transcripts in human motor neurons and co-expression of different dystrophin isoforms within single neurons in both developing and adult brains. Finally, we show localisation of DMD transcripts with GAD1+ GABAergic-associated transcripts in neurons including cerebellar Purkinje cells and interneurons, as well as in the majority of neocortical and hippocampal SLC17A7+ glutamatergic neurons, suggesting a role for dystrophin in signalling at the neuronal inhibitory and excitatory synapses.

An analysis of RNA quality metrics in human brain tissue

Human brain tissue studies have used a range of metrics to assess RNA quality but there are few large-scale cross-comparisons of presequencing quality metrics with RNA-seq quality. We analyzed how postmortem interval (PMI) and RNA integrity number (RIN) before RNA-seq relate to RNA quality after sequencing (percent of counts in top 10 genes [PTT], 5' bias, and 3' bias), and with individual gene counts across the transcriptome. We analyzed 4 human cerebrocortical tissue sets (1 surgical, 3 autopsy), sequenced with varying protocols. Postmortem interval and RIN had a low inverse correlation (down to r = -0.258, P < .001 across the autopsy cohorts); both PMI and RIN showed consistent and opposing correlations with PTT (up to r = 0.215, P < .001 for PMI and down to r = -0.677, P < .001 for RIN across the autopsy cohorts). Unlike PMI, RIN showed consistent correlations with measurements of 3' and 5' bias in autopsies (r = -0.366, P < .001 with 3' bias). RNA integrity number correlated with 3933 genes across the 4 datasets vs 138 genes for PMI. Neuronal and immune response genes correlated positively and negatively with RIN, respectively. Thus, different gene sets have divergent relationships with RIN. These analyses suggest that conventional metrics of RNA quality have varying values and that PMI has an overall modest effect on RNA quality.

A mini review of leveraging biobanking in the identification of novel biomarkers in neurological disorders: insights from a rapid single-cell sequencing pipeline

Recent successes in the identification of biomarkers and therapeutic targets for diagnosing and managing neurological diseases underscore the critical need for cutting-edge biobanks in the conduct of high-caliber translational neuroscience research. Biobanks dedicated to neurological disorders are particularly timely, given the increasing prevalence of neurological disability among the rising aging population. Translational research focusing on disorders of the central nervous system (CNS) poses distinct challenges due to the limited accessibility of CNS tissue pre-mortem. Nevertheless, technological breakthroughs, including single-cell and single-nucleus methodologies, offer unprecedented insights into CNS pathophysiology using minimal input such as cerebrospinal fluid (CSF) cells and brain biopsies. Moreover, assays designed to detect factors that are released by CNS resident cells and diffuse into the CSF and/or bloodstream (such as neurofilament light chain [NfL], glial fibrillar acidic protein [GFAP] and amyloid beta peptides), and systemic factors that cross the blood-brain barrier to target CNS-specific molecules (e.g., autoantibodies that bind either the NMDA receptor [NMDAR] or myelin oligodendrocyte glycoprotein [MOG]), are increasingly deployed in clinical research and practice. This review provides an overview of current biobanking practices in neurological disorders and discusses ongoing challenges to biomarker discovery. Additionally, it outlines a rapid consenting and processing pipeline ensuring fresh paired blood and CSF specimens for single-cell sequencing that might more accurately reflect in vivo pathways. In summary, augmenting biobank rigor and establishing innovative research pipelines using patient samples will undoubtedly accelerate biomarker discovery in neurological disorders.

An analysis of RNA quality metrics in human brain tissue

Human brain tissue studies have historically used a range of metrics to assess RNA quality. However, few large-scale cross-comparisons of pre-sequencing quality metrics with RNA-seq quality have been published. Here, we analyze how well metrics gathered before RNA sequencing (post-mortem interval (PMI) and RNA integrity number RIN) relate to analyses of RNA quality after sequencing (Percent of counts in Top Ten genes (PTT), 5' bias, and 3' bias) as well as with individual gene counts across the transcriptome. We conduct this analysis across four different human cortical brain tissue collections sequenced with varying library preparation protocols. PMI and RIN have a low inverse correlation, and both PMI and RIN show consistent and opposing correlations with PTT. Unlike PMI, RIN shows strong consistent correlations with measurements of 3' and 5' bias, and RIN also correlates with 3,933 genes across datasets, in comparison to 138 genes for PMI. Neuronal and immune response genes correlate positively and negatively with RIN respectively, suggesting that different gene sets have divergent relationships with RIN in brain tissue. In summary, these analyses suggest that conventional metrics of RNA quality have varying degrees of value, and that PMI has an overall minimal but reproducible effect on RNA quality.

Targeting MERTK on tumour cells and macrophages: a potential intervention for sporadic and NF2-related meningioma and schwannoma tumours

Meningioma and schwannoma are common tumours of the nervous system. They occur sporadically or as part of the hereditary NF2-related schwannomatosis syndrome. There is an unmet need for new effective drug treatments for both tumour types. In this paper, we demonstrate overexpression/activation of TAM (TYRO3/AXL/MERTK) receptors (TAMs) and overexpression/release of ligand GAS6 in patient-derived meningioma tumour cells and tissue. For the first time, we reveal the formation of MERTK/TYRO3 heterocomplexes in meningioma and schwannoma tissue. We demonstrate the dependence of AXL and TYRO3 expression on MERTK in both tumour types, as well as interdependency of MERTK and AXL expression in meningioma. We show that MERTK and AXL contribute to increased proliferation and survival of meningioma and schwannoma cells, which we inhibited in vitro using the MERTK/FLT3 inhibitor UNC2025 and the AXL inhibitor BGB324. UNC2025 was effective in both tumour types with superior efficacy over BGB324. Finally, we found that TAMs are expressed by tumour-associated macrophages in meningioma and schwannoma tumours and that UNC2025 strongly depleted macrophages in both tumour types.

Recurrent adamantinomatous craniopharyngiomas show MAPK pathway activation, clonal evolution and rare TP53-loss-mediated malignant progression

The two types of craniopharyngioma, adamantinomatous (ACP) and papillary (PCP), are clinically relevant tumours in children and adults. Although the biology of primary craniopharyngioma is starting to be unravelled, little is known about the biology of recurrence. To fill this gap in knowledge, we have analysed through methylation array, RNA sequencing and pERK1/2 immunohistochemistry a cohort of paired primary and recurrent samples (32 samples from 14 cases of ACP and 4 cases of PCP). We show the presence of copy number alterations and clonal evolution across recurrence in 6 cases of ACP, and analysis of additional whole genome sequencing data from the Children's Brain Tumour Network confirms chromosomal arm copy number changes in at least 7/67 ACP cases. The activation of the MAPK/ERK pathway, a feature previously shown in primary ACP, is observed in all but one recurrent cases of ACP. The only ACP without MAPK activation is an aggressive case of recurrent malignant human craniopharyngioma harbouring a CTNNB1 mutation and loss of TP53. Providing support for a functional role of this TP53 mutation, we show that Trp53 loss in a murine model of ACP results in aggressive tumours and reduced mouse survival. Finally, we characterise the tumour immune infiltrate showing differences in the cellular composition and spatial distribution between ACP and PCP. Together, these analyses have revealed novel insights into recurrent craniopharyngioma and provided preclinical evidence supporting the evaluation of MAPK pathway inhibitors and immunomodulatory approaches in clinical trials in against recurrent ACP.

Decision making for health-related research outcomes that alter diagnosis: A model from paediatric brain tumours

AIMS

The question of how to handle clinically actionable outcomes from retrospective research studies is poorly explored. In neuropathology, this problem is exacerbated by ongoing refinement in tumour classification. We sought to establish a disclosure threshold for potential revised diagnoses as determined by the neuro-oncology speciality.

METHODS

As part of a previous research study, the diagnoses of 73 archival paediatric brain tumour samples were reclassified according to the WHO 2016 guidelines. To determine the disclosure threshold and clinical actionability of pathology-related findings, we conducted a result-evaluation approach within the ethical framework of BRAIN UK using a surrogate clinical multidisciplinary team (MDT) of neuro-oncology specialists.

RESULTS

The MDT identified key determinants impacting decision-making, including anticipated changes to patient management, time elapsed since initial diagnosis, likelihood of the patient being alive and absence of additional samples since cohort inception. Ultimately, none of our research findings were considered clinically actionable, largely due to the cohort's historic archival and high-risk nature. From this experience, we developed a decision-making framework to determine if research findings indicating a change in diagnosis require reporting to the relevant clinical teams.

CONCLUSIONS

Ethical issues relating to the use of archival tissue for research and the potential to identify actionable findings must be carefully considered. We have established a structured framework to assess the actionability of research data relating to patient diagnosis. While our specific findings are most applicable to the pathology of poor prognostic brain tumour groups in children, the model can be adapted to a range of disease settings, for example, other diseases where research is dependent on retrospective tissue cohorts, and research findings may have implications for patients and families, such as other tumour types, epilepsy-related pathology, genetic disorders and degenerative diseases.

Practical Application of Deep Learning in Diagnostic Neuropathology-Reimagining a Histological Asset in the Era of Precision Medicine

In the past few decades, neuropathology has experienced several paradigm shifts with the introduction of new technologies. Deep learning, a rapidly progressing subfield of machine learning, seems to be the next innovation to alter the diagnostic workflow. In this review, we will explore the recent changes in the field of neuropathology and how this has led to an increased focus on molecular features in diagnosis and prognosis. Then, we will examine the work carried out to train deep learning models for various diagnostic tasks in neuropathology, as well as the machine learning frameworks they used. Focus will be given to both the challenges and successes highlighted therein, as well as what these trends may tell us about future roadblocks in the widespread adoption of this new technology. Finally, we will touch on recent trends in deep learning, as applied to digital pathology more generally, and what this may tell us about the future of deep learning applications in neuropathology.

Adult brain tumour research in 2024: Status, challenges and recommendations

In 2015, a groundswell of brain tumour patient, carer and charity activism compelled the UK Minister for Life Sciences to form a brain tumour research task and finish group. This resulted, in 2018, with the UK government pledging £20m of funding, to be paralleled with £25m from Cancer Research UK, specifically for neuro-oncology research over the subsequent 5 years. Herein, we review if and how the adult brain tumour research landscape in the United Kingdom has changed over that time and what challenges and bottlenecks remain. We have identified seven universal brain tumour research priorities and three cross-cutting themes, which span the research spectrum from bench to bedside and back again. We discuss the status, challenges and recommendations for each one, specific to the United Kingdom.

Extracting structured information from unstructured histopathology reports using generative pre-trained transformer 4 (GPT-4)

Deep learning applied to whole-slide histopathology images (WSIs) has the potential to enhance precision oncology and alleviate the workload of experts. However, developing these models necessitates large amounts of data with ground truth labels, which can be both time-consuming and expensive to obtain. Pathology reports are typically unstructured or poorly structured texts, and efforts to implement structured reporting templates have been unsuccessful, as these efforts lead to perceived extra workload. In this study, we hypothesised that large language models (LLMs), such as the generative pre-trained transformer 4 (GPT-4), can extract structured data from unstructured plain language reports using a zero-shot approach without requiring any re-training. We tested this hypothesis by utilising GPT-4 to extract information from histopathological reports, focusing on two extensive sets of pathology reports for colorectal cancer and glioblastoma. We found a high concordance between LLM-generated structured data and human-generated structured data. Consequently, LLMs could potentially be employed routinely to extract ground truth data for machine learning from unstructured pathology reports in the future. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy

BACKGROUND

Glioblastoma (GBM) brain tumors lacking IDH1 mutations (IDHwt) have the worst prognosis of all brain neoplasms. Patients receive surgery and chemoradiotherapy but tumors almost always fatally recur.

RESULTS

Using RNA sequencing data from 107 pairs of pre- and post-standard treatment locally recurrent IDHwt GBM tumors, we identify two responder subtypes based on longitudinal changes in gene expression. In two thirds of patients, a specific subset of genes is upregulated from primary to recurrence (Up responders), and in one third, the same genes are downregulated (Down responders), specifically in neoplastic cells. Characterization of the responder subtypes indicates subtype-specific adaptive treatment resistance mechanisms that are associated with distinct changes in the tumor microenvironment. In Up responders, recurrent tumors are enriched in quiescent proneural GBM stem cells and differentiated neoplastic cells, with increased interaction with the surrounding normal brain and neurotransmitter signaling, whereas Down responders commonly undergo mesenchymal transition. ChIP-sequencing data from longitudinal GBM tumors suggests that the observed transcriptional reprogramming could be driven by Polycomb-based chromatin remodeling rather than DNA methylation.

CONCLUSIONS

We show that the responder subtype is cancer-cell intrinsic, recapitulated in in vitro GBM cell models, and influenced by the presence of the tumor microenvironment. Stratifying GBM tumors by responder subtype may lead to more effective treatment.

Ribogenesis boosts controlled by HEATR1-MYC interplay promote transition into brain tumour growth

Cell commitment to tumourigenesis and the onset of uncontrolled growth are critical determinants in cancer development but the early events directing tumour initiating cell (TIC) fate remain unclear. We reveal a single-cell transcriptome profile of brain TICs transitioning into tumour growth using the brain tumour (brat) neural stem cell-based Drosophila model. Prominent changes in metabolic and proteostasis-associated processes including ribogenesis are identified. Increased ribogenesis is a known cell adaptation in established tumours. Here we propose that brain TICs boost ribogenesis prior to tumour growth. In brat-deficient TICs, we show that this dramatic change is mediated by upregulated HEAT-Repeat Containing 1 (HEATR1) to promote ribosomal RNA generation, TIC enlargement and onset of overgrowth. High HEATR1 expression correlates with poor glioma patient survival and patient-derived glioblastoma stem cells rely on HEATR1 for enhanced ribogenesis and tumourigenic potential. Finally, we show that HEATR1 binds the master growth regulator MYC, promotes its nucleolar localisation and appears required for MYC-driven ribogenesis, suggesting a mechanism co-opted in ribogenesis reprogramming during early brain TIC development.

Histological examination of choroid plexus epithelia changes in schizophrenia

BACKGROUND

The choroid plexus (CP) produces and secretes most of the cerebrospinal fluid (CSF) of the central nervous system. The CP is suggested to be regulated by descending neurons and by circulating factors and is involved in the interaction between central and peripheral inflammation. Quantitative imaging has demonstrated volumetric CP changes in psychosis, schizophrenia and depression. This study histologically examines CP epithelial cell morphology in these illnesses to identify the biological source of such volumetric changes.

METHODS

Formalin-fixed paraffin-embedded (FFPE) blocks were obtained bilaterally from the lateral ventricles of 13 cases of sex- and age-matched brains from each of schizophrenia (SZ) with psychosis, major depressive disorder (MDD) and matched controls (NPD). FFPE blocks were sectioned at 7 μm and routinely stained for H&E. Morphological analysis of 180 CP epithelia/case was conducted blindly on digital images collected at x600 magnification. Calcification was assessed in all CP regions manually.

RESULTS

Analysis with a General Linear Model demonstrated a significant effect of diagnosis on somal width (p = 0.006, R2 = 0.33 R2(adj) = 0.25) demonstrating increased somal width in SZ without psychotic medication versus controls (p = 0.032), but not in medicated SZ cases. No effects were observed in calcification.

DISCUSSION

The epithelial cells that were examined were attached to the CP fibrous surface, so width expansion describes the primary methods for these cells to expand with adherence to this surface in SZ. The interaction of antipsychotic medication and diagnosis demonstrates that this is an illness-specific change mediated through the DA-system with likely neuronal origin. CP alterations were not found in MDD where they are instead generally associated with heightened allostatic load that was unknown in this cohort.

Clinical impact of anti-inflammatory microglia and macrophage phenotypes at glioblastoma margins

Glioblastoma is a devastating brain cancer for which effective treatments are required. Tumour-associated microglia and macrophages promote glioblastoma growth in an immune-suppressed microenvironment. Most recurrences occur at the invasive margin of the surrounding brain, yet the relationships between microglia/macrophage phenotypes, T cells and programmed death-ligand 1 (an immune checkpoint) across human glioblastoma regions are understudied. In this study, we performed a quantitative immunohistochemical analysis of 15 markers of microglia/macrophage phenotypes (including anti-inflammatory markers triggering receptor expressed on myeloid cells 2 and CD163, and the low-affinity-activating receptor CD32a), T cells, natural killer cells and programmed death-ligand 1, in 59 human IDH1-wild-type glioblastoma multi-regional samples (n = 177; 1 sample at tumour core, 2 samples at the margins: the infiltrating zone and leading edge). Assessment was made for the prognostic value of markers; the results were validated in an independent cohort. Microglia/macrophage motility and activation (Iba1, CD68), programmed death-ligand 1 and CD4+ T cells were reduced, and homeostatic microglia (P2RY12) were increased in the invasive margins compared with the tumour core. There were significant positive correlations between microglia/macrophage markers CD68 (phagocytic)/triggering receptor expressed on myeloid cells 2 (anti-inflammatory) and CD8+ T cells in the invasive margins but not in the tumour core (P < 0.01). Programmed death-ligand 1 expression was associated with microglia/macrophage markers (including anti-inflammatory) CD68, CD163, CD32a and triggering receptor expressed on myeloid cells 2, only in the leading edge of glioblastomas (P < 0.01). Similarly, there was a positive correlation between programmed death-ligand 1 expression and CD8+ T-cell infiltration in the leading edge (P < 0.001). There was no relationship between CD64 (a receptor for autoreactive T-cell responses) and CD8+/CD4+ T cells, or between the microglia/macrophage antigen presentation marker HLA-DR and microglial motility (Iba1) in the tumour margins. Natural killer cell infiltration (CD335+) correlated with CD8+ T cells and with CD68/CD163/triggering receptor expressed on myeloid cells 2 anti-inflammatory microglia/macrophages at the leading edge. In an independent large glioblastoma cohort with transcriptomic data, positive correlations between anti-inflammatory microglia/macrophage markers (triggering receptor expressed on myeloid cells 2, CD163 and CD32a) and CD4+/CD8+/programmed death-ligand 1 RNA expression were validated (P < 0.001). Finally, multivariate analysis showed that high triggering receptor expressed on myeloid cells 2, programmed death-ligand 1 and CD32a expression at the leading edge were significantly associated with poorer overall patient survival (hazard ratio = 2.05, 3.42 and 2.11, respectively), independent of clinical variables. In conclusion, anti-inflammatory microglia/macrophages, CD8+ T cells and programmed death-ligand 1 are correlated in the invasive margins of glioblastoma, consistent with immune-suppressive interactions. High triggering receptor expressed on myeloid cells 2, programmed death-ligand 1 and CD32a expression at the human glioblastoma leading edge are predictors of poorer overall survival. Given substantial interest in targeting microglia/macrophages, together with immune checkpoint inhibitors in cancer, these data have major clinical implications.

Resilience of Neural Cellularity to the Influence of Low Educational Level

BACKGROUND

Education is believed to contribute positively to brain structure and function, as well as to cognitive reserve. One of the brain regions most impacted by education is the medial temporal lobe (MTL), a region that houses the hippocampus, which has an important role in learning processes and in consolidation of memories, and is also known to undergo neurogenesis in adulthood. We aimed to investigate the influence of education on the absolute cell numbers of the MTL (comprised by the hippocampal formation, amygdala, and parahippocampal gyrus) of men without cognitive impairment.

METHODS

The Isotropic Fractionator technique was used to allow the anisotropic brain tissue to be transformed into an isotropic suspension of nuclei, and therefore assess the absolute cell composition of the MTL. We dissected twenty-six brains from men aged 47 to 64 years, with either low or high education.

RESULTS

A significant difference between groups was observed in brain mass, but not in MTL mass. No significant difference was found between groups in the number of total cells, number of neurons, and number of non-neuronal cells. Regression analysis showed that the total number of cells, number of neurons, and number of non-neuronal cells in MTL were not affected by education.

CONCLUSIONS

The results indicate a resilience of the absolute cellular composition of the MTL of typical men to low schooling, suggesting that the cellularity of brain regions is not affected by formal education.