Normal Brain Research Articles

Comparison of data-driven thresholding methods using directed functional brain networks.

Over the past two centuries, intensive empirical research has been conducted on the human brain. As an electroencephalogram (EEG) records millisecond-to-millisecond changes in the electrical potentials of the brain, it has enormous potential for identifying useful information about neuronal transactions. The EEG data can be modelled as graphs by considering the electrode sites as nodes andthe linear and nonlinear statistical dependencies among them as edges (with weights). The graph theoretical modelling of EEG data results in functional brain networks (FBNs), which are fully connected (complete) weighted undirected/directed networks. Since various brain regions are interconnected via sparse anatomical connections, the weak links can be filtered out from the fullyconnected networks using a process called thresholding. Multiple researchers in the past decades proposed many thresholding methods to gather more insights about the influential neuronal connections of FBNs. This paper reviews various thresholding methods used in the literature for FBN analysis. The analysis showed that data-driven methods are unbiased since no arbitrary user-specified threshold is required. The efficacy of four data-driven thresholding methods, namely minimum spanning tree (MST), minimum connected component (MCC), union of shortest path trees (USPT), and orthogonal minimum spanning tree (OMST), in characterizing cognitive behavior of the normal human brain is analysed using directed FBNs constructed from EEG data of different cognitive load states. The experimental results indicate that both MCC and OMST thresholding methods can detect cognitive load-induced changes in the directed functional brain networks.

TYROBP serve as potential immune-related signature genes in the acute phase of intracerebral hemorrhage

The development of intracerebral hemorrhage (ICH) is a dynamic process and intervention during the acute phase of ICH is critical for subsequent recovery. Therefore, it is crucial to screen potential signature genes and therapeutic target genes in the acute phase of ICH. In this study, based on the results of mRNA sequencing in mouse ICH and mRNA sequencing of human ICH from online databases, top five potential signature genes after ICH, Tyrobp, Itgb2, Tlr2, Ptprc and Itgam, were screened. Quantitative PCR results showed higher mRNA expression of Tyrobp, Itgb2, Tlr2, Ptprc, and Itgam in the 1-, 3- and 5-day mouse ICH groups compared to the sham-operated group. Immune infiltration correlation analysis shows that the top-ranked signature gene, Tyrobp, is negatively correlated with M2 macrophages and plasma cells, and Western blot analysis shows higher expression of the Tyrobp protein in the 1-, 3-, and 5-day mouse ICH groups compared to the sham-operated group. Furthermore, immunohistochemistry revealed that TYROBP protein expression was significantly higher in human ICH tissues than in normal brain tissues. Our results suggest that Tyrobp is a signature gene in the acute phase of ICH and may be a potential target for the treatment of the acute phase of ICH.

Sex chromosomes and hormones independently influence healthy brain development but act similarly after cranial radiation

The course of normal development and response to pathology are strongly influenced by biological sex. For instance, female childhood cancer survivors who have undergone cranial radiation therapy (CRT) tend to display more pronounced cognitive deficits than their male counterparts. Sex effects can be the result of sex chromosome complement (XX vs. XY) and/or gonadal hormone influence. The contributions of each can be separated using the four-core genotype mouse model (FCG), where sex chromosome complement and gonadal sex are decoupled. While studies of FCG mice have evaluated brain differences in adulthood, it is still unclear how sex chromosome and sex hormone effects emerge through development in both healthy and pathological contexts. Our study utilizes longitudinal MRI with the FCG model to investigate sex effects in healthy development and after CRT in wildtype and immune-modified Ccl2-knockout mice. Our findings in normally developing mice reveal a relatively prominent chromosome effect prepubertally, compared to sex hormone effects which largely emerge later. Spatially, sex chromosome and hormone influences were independent of one another. After CRT in Ccl2-knockout mice, both male chromosomes and male hormones similarly improved brain outcomes but did so more separately than in combination. Our findings highlight the crucial role of sex chromosomes in early development and identify roles for sex chromosomes and hormones after CRT-induced inflammation, highlighting the influences of biological sex in both normal brain development and pathology.

Brain age prediction via cross-stratified ensemble learning

As an important biomarker of neural aging, the brain age reflects the integrity and health of the human brain. Accurate prediction of brain age could help to understand the underlying mechanism of neural aging. In this study, a cross-stratified ensemble learning algorithm with staking strategy was proposed to obtain brain age and the derived predicted age difference (PAD) using T1-weighted magnetic resonance imaging (MRI) data. The approach was characterized as by implementing two modules: one was three base learners of 3D-DenseNet, 3D-ResNeXt, 3D-Inception-v4; another was 14 secondary learners of liner regressions. To evaluate performance, our method was compared with single base learners, regular ensemble learning algorithms, and state-of-the-art (SOTA) methods. The results demonstrated that our proposed model outperformed others models, with three metrics of mean absolute error (MAE), root mean-squared error (RMSE), and coefficient of determination (R2) of 2.9405 years, 3.9458 years, and 0.9597, respectively. Furthermore, there existed significant differences in PAD among the three groups of normal control (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD), with an increased trend across NC, MCI, and AD. It was concluded that the proposed algorithm could be effectively used in computing brain aging and PAD, and offering potential for early diagnosis and assessment of normal brain aging and AD.

Heparan sulfate proteoglycans in pathological protein aggregation and brain functionality

Proteoglycans are highly specialized proteins with specific interactive modules in their core proteins, allowing them to engage with a diverse range of cellular and structural proteins, contributing to many varied roles in cell processes. This review examines the roles of heparan sulfate (HS) proteoglycans (HSPGs) in the assembly of pathological protein aggregates in brain tissues, which negatively impact cognitive brain function. While HSPGs play roles in normal brain development, they also contribute to the abnormal accumulation and persistence of protein aggregates in Alzheimer’s and Parkinson’s diseases (AD and PD), prolonging their neurotoxic effects. HSPG-mediated effects on the innate immune system may also contribute to the development of neuroinflammation and pathogenesis of neurodegenerative changes in the central nervous system. These pathological developments lead to impaired cognition, permanent memory loss in dementia and AD, and an inability of the brain to exert normal neuromuscular control, affecting motor functions and body movement in PD. A deeper understanding of the properties of HS in these degenerative processes is essential for the development of therapeutic measures to treat these conditions. Significant improvements in neuroimaging, next-generation glycosaminoglycan analytical techniques, and functional glycomics hold great promise for elucidating the complexities of HS structure and function. These advancements may significantly aid in the development of HS biotherapeutics to treat these debilitating conditions, which are increasingly impacting the aging global population. While a number of promising therapeutic candidates have already emerged, further research is required to optimize their biotherapeutic applications in this challenging area of pathobiology, bioregulation, and the recovery of neural function.

Raman and autofluorescence spectroscopy for in situ identification of neoplastic tissue during surgical treatment of brain tumors.

Raman spectroscopy (RS) is a promising method for brain tumor detection. Near-infrared autofluorescence (AF) acquired during RS provides additional useful information for tumor identification and was investigated in comparison with RS for delineating brain tumors in situ. Raman spectra were acquired together with AF in situ within the solid tumor and at the tumor border during routine brain tumor surgeries (218 spectra; glioma WHO II-III, n = 6; GBM, n = 10; metastases, n = 10; meningioma, n = 3). Tissue classification for tumor identification in situ was trained on ex vivo data (375 spectra; glioma/GBM patients, n = 20; metastases, n = 11; meningioma, n = 13; and epileptic hippocampi, n = 4). Both in situ and ex vivo data showed that AF intensity in brain tumors was lower than that in border regions and normal brain tissue. Moreover, a positive correlation was observed between the AF intensity and the intensity of the Raman band corresponding to lipids at 1437cm- 1, while a negative correlation was found with the intensity of the protein band at 1260cm- 1. The classification of in situ AF and RS datasets matched the surgeon's evaluation of tissue type, with correct rates of 0.83 and 0.84, respectively. Similar correct rates were achieved in comparison to histopathology of tissue biopsies resected in selected measurement positions (AF: 0.80, RS: 0.83). Spectroscopy was successfully integrated into existing neurosurgical workflows, and in situ spectroscopic data could be classified based on ex vivo data. RS confirmed its ability to detect brain tumors, while AF emerged as a competitive method for intraoperative tumor delineation.

Pathologic Substrates of Structural Brain Network Resilience and Topology in Parkinson Disease Decedents.

In Parkinson disease (PD), α-synuclein spreading through connected brain regions leads to neuronal loss and brain network disruptions. With diffusion-weighted imaging (DWI), it is possible to capture conventional measures of brain network organization and more advanced measures of brain network resilience. We aimed to investigate which neuropathologic processes contribute to regional network topologic changes and brain network resilience in PD. Using a combined postmortem MRI and histopathology approach, PD and control brain donors with available postmortem in situ 3D T1-weighted MRI, DWI, and brain tissue were selected from the Netherlands Brain Bank and Normal Aging Brain Collection Amsterdam. Probabilistic tractography was performed, and conventional network topologic measures of regional eigenvector centrality and clustering coefficient, and brain network resilience (change in global efficiency upon regional node failure) were calculated. PSer129 α-synuclein, phosphorylated-tau, β-amyloid, neurofilament light-chain immunoreactivity, and synaptophysin density were quantified in 8 cortical regions. Group differences and correlations were assessed with rank-based nonparametric tests, with age, sex, and postmortem delay as covariates. Nineteen clinically defined and pathology-confirmed PD (7 F/12 M, 81 ± 7 years) and 15 control (8 F/7 M, 73 ± 9 years) donors were included. With regional conventional measures, we found lower eigenvector centrality only in the parahippocampal gyrus in PD (d = -1.08, 95% CI 0.003-0.010, p = 0.021), which did not associate with underlying pathology. No differences were found in regional clustering coefficient. With the more advanced measure of brain network resilience, we found that the PD brain network was less resilient to node failure of the dorsal anterior insula compared with the control brain network (d = -1.00, 95% CI 0.0012-0.0015, p = 0.018). This change was not directly driven by neuropathologic processes within the dorsal anterior insula or in connected regions but was associated with higher Braak α-synuclein staging (rs = -0.40, p = 0.036). Although our cohort might suffer from selection bias, our results highlight that regional network disturbances are more complex to interpret than previously believed. Regional neuropathologic processes did not drive regional topologic changes, but a global increase in α-synuclein pathology had a widespread effect on brain network reorganization in PD.

Enhanced brain tumor classification using EfficientNetB0 and SVM with pareto search algorithm optimization

Classifying tumors by type, grade, and stage is crucial for treatment decisions and predicting outcomes. Deep learning, especially Convolutional Neural Networks (CNNs), has significantly advanced tumor classification by effectively analyzing complex patterns in magnetic resonance (MR) images. This work presents a hybrid image classification method using the EfficientNetB0 model and Support Vector Machine (SVM) to categorize brain MR images into pituitary tumor, glioma tumor, meningioma tumor, and normal brain. EfficientNetB0 model extracts deep features from the images, which are then classified by a linear SVM. To significantly enhance classification accuracy for brain images, we use the Pareto algorithm to determine the penalty parameter C for the linear SVM. The testing results showed that the proposed system achieved a classification accuracy of 99.30%, recall of 99.30%, precision of 99.30%, and F1-score of 99.30%, with a high specificity of 99.77%. These results demonstrate that the combination of the Pareto algorithm and SVM significantly contributes to improved classification accuracy for brain images.

Single-cell dissection of the human blood-brain barrier and glioma blood-tumor barrier

The blood-brain barrier (BBB) serves as a crucial vascular specialization, shielding and nourishing brain neurons and glia while impeding drug delivery. Here, we conducted single-cell mRNA sequencing of human cerebrovascular cells from 13 surgically resected glioma samples and adjacent normal brain tissue. The transcriptomes of 103,230 cells were mapped, including 57,324 endothelial cells (ECs) and 27,703 mural cells (MCs). Both EC and MC transcriptomes originating from lower-grade glioma were indistinguishable from those of normal brain tissue, whereas transcriptomes from glioblastoma (GBM) displayed a range of abnormalities. Among these, we identified LOXL2-dependent collagen modification as a common GBM-dependent trait and demonstrated that inhibiting LOXL2 enhanced chemotherapy efficacy in both murine and human patient-derived xenograft (PDX) GBM models. Our comprehensive single-cell RNA sequencing-based molecular atlas of the human BBB, coupled with insights into its perturbations in GBM, holds promise for guiding future investigations into brain health, pathology, and therapeutic strategies.

Neuroimaging in Nonsyndromic Craniosynostosis: Key Concepts to Unlock Innovation.

Craniosynostoses (CRS) are caused by the premature fusion of one or more cranial sutures, with isolated nonsyndromic CRS accounting for most of the clinical manifestations. Such premature suture fusion impacts both skull and brain morphology and involves regions far beyond the immediate area of fusion. The combined use of different neuroimaging tools allows for an accurate depiction of the most prominent clinical-radiological features in nonsyndromic CRS but can also contribute to a deeper investigation of more subtle alterations in the underlying nervous tissue organization that may impact normal brain development. This review paper aims to provide a comprehensive framework for a better understanding of the present and future potential applications of neuroimaging techniques for evaluating nonsyndromic CRS, highlighting strategies for optimizing their use in clinical practice and offering an overview of the most relevant technological advancements in terms of diagnostic performance, radiation exposure, and cost-effectiveness.

Comparative dosimetric analysis of normal brain tissue in patients with Nasopharyngeal carcinoma at different stages after radiation therapy

IntroductionRadiotherapy (RT) is the main treatment for patients with nasopharyngeal carcinoma (NPC). NPC patients at different stages have varying levels of damage to normal brain tissue after RT. No study has yet thoroughly analyzed the variations in radiation dosages in the brain for different stages of NPC patients treated with RT. This study aims to examine these variations. Methods1446 NPC patients’ CT and RTdose data were retrospectively reviewed. Analysis of the radiation dosage was executed on these 803 patients. The RTdose images for several patient groups were averaged after registering each patient’s RTdose data to the CT brain template created in our earlier study. The voxel-based (VB) analysis was used to examine the dose variations in the brains of three groups of NPC patients: the early-stage group, the stage III group, and the stage IV group. ResultsAs the disease progresses from early to advanced stages, the intensity and volume of radiation in the brain increase. The normal brain tissue accepted a substantially larger dosage in more advanced NPC patients. Differences in brain regions between stage III and early-stage patients were minimal compared to any other two groups. Brain regions exhibited substantial variations between the stage IV group and all other patient groups were broadly distributed. ConclusionOur findings highlight the critical role of NPC staging in the therapeutic strategy, emphasizing the heterogeneity of radiation-induced tissue damage across disease stages and implying the need to develop stage-specific RT plans.

ORY-1001 inhibits glioblastoma cell growth by downregulating the Notch/HES1 pathway via suppressing lysine-specific demethylase 1 expression

To explore the inhibitory effect ORY-1001, a lysine-specific histone demethylase 1 (LSD1) inhibitor, on growth of glioblastoma (GBM) and the underlying mechanism. We analyzed LSD1 expressions in GBM and normal brain tissues based on data from TCGA and HPA databases. Female BALB/c mouse models bearing xenografts derived from U87 cells or cells with lentivirus-mediated LSD1 silencing or Notch overexpression were treated with saline or 400 µg/kg ORY-1001 by gavage every 7 days, and GBM formation and survival time of the mice were recorded. The effect of ORY-1001 on GBM cell viability was assessed, and its effect on LSD1 expression was analyzed with Western blotting. The genes and pathways associated with LSD1 were analyzed using bioinformatics methods. Western blotting and qRT-PCR were used to detect Notch/HES1 pathway expression after LSD1 silencing and ORY-1001 treatment. The impact of ORY-1001 on viability of U87 cells with Notch1 silencing or overexpression was assessed, and the regulatory effects of ORY-1001 on Notch/HES1 pathway were analyzed using chromatin immunoprecipitation assay. A high expression of LSD1 in GBM was negatively correlated with patient survival (P < 0.001). ORY-1001 and LSD1 silencing obviously reduced tumor burden and prolonged the survival time of GBM-bearing mice. ORY-1001 treatment significantly inhibited the viability and dose-dependently decreased LSD1 expression in GBM cells, and such inhibitory effect of ORY-1001 was attenuated by LSD1 silencing. The Notch pathway enriched the differential genes related to LSD1, and Notch/HES1 pathway expression was significantly down-regulated after LSD1 silencing and ORY-1001 treatment. Notch1 overexpression significantly attenuated the anti-tumor effect of ORY-1001 on GBM. Mechanistically, ORY-1001 disrupted the interaction between LSD1 and the Notch pathway target genes including Notch3, HES1 and CR2. ORY-1001 down-regulates the Notch/HES1 pathway by inhibiting LSD1 expression to suppress the growth of GBM in mice.

Examining The Relationship Between Lateral Ventricle Volumetric Index and Linear Indexes in Childhood and Adolescence: A Retrospective MRI Study

Objective: Indexes obtained from two-dimensional and three-dimensional measurements are used to evaluate the brain's lateral ventricle (LV) structure. However, there were limited studies on how well the Evans index (EI) and the Bicaudate index (BI), which estimate LV volume, represent the LV volumetric index (LVVI) in the childhood and adolescence period. This study investigated the relationship between LVVI and linear indexes (EI and BI) in the pediatric period regarding age and sex factors. Method: This study was performed retrospectively in 588 individuals (267 [45.4%] females) aged 1-18 years with normal brain magnetic resonance images (MRI) between 2012 and 2021. LVVI was obtained by segmenting three-dimensional T1-weighted MRIs with volBrain1.0. LVVI was obtained by dividing the LV absolute volume by the total intracranial volume. We made linear measurements for EI and BI with the 3D Slicer. In this study, we compared the data obtained from individuals in 16 different age ranges between 1-18 years old with SPSS (ver.28). Results: In our study, we found the mean value of LVVI to be 0.656±0.372%. The mean values of EI and BI were 0.242±0.025 and 0.070±0.022, respectively. In the pediatric population, we found that mean values of EI and BI were significantly higher in males than in females (p

Anterior odontoid screw fixation of a type III odontoid fracture aided by transoral digital manipulation: illustrative case.

Odontoid process fractures make up 10%-20% of all cervical spine fractures, with type III fractures having a considerable amount of heterogeneity. Most simple type III fractures can be managed nonoperatively. However, 21% of complex type III fractures with significant displacement and angulation are inadequately treated with external immobilization and require surgery. Achieving a reduction via traction can pose a great challenge during intraoperative manipulation, especially when presentation is delayed. A 36-year-old male patient, who presented 2 weeks after a motor vehicle crash, had a Glasgow Coma Scale score of 14 and intact motor and sensory function. A craniocervical computed tomograpy scan revealed a normal brain with a type III odontoid fracture. The patient underwent anterior odontoid screw fixation (AOSF) aided by a transoral digital manipulation to achieve a reduction of the irreducible proximal fracture segment at 8 weeks postinjury. The treatment resulted in preserved neurological function and a satisfactory odontoid fracture reduction. Delayed presentation of a complex type III odontoid fracture can be challenging to treat; however, AOSF with the aid of transoral digital manipulation of the irreducible proximal segment can help to achieve good reduction and fusion with the preservation of neurological function in a young patient. https://thejns.org/doi/10.3171/CASE24294.

Gene Expression Profile Identifies LncRNA AL355974.3 As a Potential Glioma Biomarker.

Glioma is a central nervous system tumor arising from glial cells. Despite significant advances in diagnosis and treatment, most patients with high-grade gliomas have a poor prognosis. Many studies have shown that long noncoding RNAs (lncRNAs) may play important roles in the development, progression and treatment of many tumors, including gliomas. Molecularly targeted therapy may be a new direction for the adjuvant treatment of glioma. Therefore, we hope that by studying differentially expressed lncRNAs (DElncRNAs) in glioma, we can discover lncRNAs that can serve as biomarkers for glioma and provide better therapeutic modalities for glioma patients. First, the expression of lncRNAs in 5 normal brain (NB) tissues and 10 glioma tissues was examined by RNA sequencing (RNA-seq). Next, we performed Kaplan-Meier analysis of data from The Cancer Genome Atlas (TCGA) database to assess the prognostic value of these variables. Finally, functional analysis of the DElncRNAs was performed by means of Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. RNA sequencing analysis revealed 85 upregulated miRNAs and 71 downregulated lncRNAs in low-grade glioma (LGG) and 50 upregulated lncRNAs and 70 downregulated lncRNAs in glioblastoma (GBM). Among them, AL355974.3 was the most upregulated lncRNA. LINC00632 was the most downregulated lncRNA. Second, LGG patients with higher AL355974.3 expression had worse overall survival according to Kaplan-Meier analysis of the TCGA database. Finally, bioinformatics analysis revealed that the target genes of these DElncRNAs were enriched in various biological processes and signaling pathways, such as cell metabolic and developmental processes. Our findings provide evidence that AL355974.3 may be a new biomarker for glioma.

MicroRNA-124-3p targets Sp1 transcription factor to regulate glioma progression in rats

Gliomas are the most prevalent malignancies of the central nervous system (CNS). Downregulation of microRNA‑124 (miR‑124) has been identified in glioma; however, its biological functions in glioma are not yet fully understood. Specificity protein 1 (SP1) is a type of transcription factor that is involved in cancer progression. In this study, we examined the targeting of Sp1 mRNA by miR-124-3p in a rat glioma model. After confirming and selecting the binding of Sp1 to miR-124 with the help of bioinformatics methods, adult male Wistar rats were used to induce glioma by microinjection of 1 × 106 C6 cells into the striatum area of brain. The rats were divided into 3 groups; intact, sham and glioma groups. The presence of glioma was confirmed 21 days after implantation through histological analysis. The expression levels of miR-124 and SP1 genes in the experimental groups were examined using quantitative real-time polymerase chain reaction (qRT-PCR). Our data showed that the expression of miR-124 was significantly downregulated in glioma group compared to the sham and intact group, while the expression of SP1 was significantly upregulated. We found that the expression levels of miR-124 and Sp1 were decreased and increased in C6 cell line compared to the normal brain tissue cell line, respectively. The results indicated that Sp1 was identified as a direct target of miR‑124 through luciferase reporter assays. In summary, this study demonstrated for the first time that miR-124 expression is downregulated and Sp1 expression is upregulated in an animal model of glioma, which, in turn, may be involved in the development of glioma brain cancer.

A cross-shaped terahertz metamaterial absorber for brain cancer detection.

The article presents, for the first time, a terahertz metamaterial absorber (TMA) designed in the shape of a cross consisting of four orthogonally positioned horn-shaped patches in succession, to detect brain cancer cells. The design exhibits the property of mu-negative material, indicating magnetic resonance. The proposed TMA has achieved an impressive absorption rate of 99.43% at 2.334 THz and a high Q-factor of 47.15. The sensing capability has been investigated by altering the refractive index of the surrounding medium in the range of 1.3 to 1.48, resulting in a sensitivity of 0.502 THz/RIU. The proposed TMA exhibits complete polarization insensitivity, highlighting this as one of its advantageous features. The adequate sensing capability of the proposed TMA in differentiating normal and cancerous brain cells makes it a viable candidate for an early and efficient brain cancer detector. This research can be the foundation for future research on using THz radiation for brain cancer detection.

Methodological considerations on diffusion MRI tractography in infants aged 0-2 years: a scoping review.

Diffusion MRI (dMRI) enables studying the complex architectural organization of the brain's white matter (WM) through virtual reconstruction of WM fiber tracts (tractography). Despite the anticipated clinical importance of applying tractography to study structural connectivity and tract development during the critical period of rapid infant brain maturation, detailed descriptions on how to approach tractography in young infants are limited. Over the past two decades, tractography from infant dMRI has mainly been applied in research settings and focused on diffusion tensor imaging (DTI). Only few studies used techniques superior to DTI in terms of disentangling information on the brain's organizational complexity, including crossing fibers. While more advanced techniques may enhance our understanding of the intricate processes of normal and abnormal brain development and extensive knowledge has been gained from application on adult scans, their applicability in infants has remained underexplored. This may partially be due to the higher technical requirements versus the need to limit scan time in young infants. We review various previously described methodological practices for tractography in the infant brain (0-2 years-of-age) and provide recommendations to optimize advanced tractography approaches to enable more accurate reconstructions of the brain WM's complexity. IMPACT: Diffusion tensor imaging is the technique most frequently used for fiber tracking in the developing infant brain but is limited in capability to disentangle the complex white matter organization. Advanced tractography techniques allow for reconstruction of crossing fiber bundles to better reflect the brain's complex organization. Yet, they pose practical and technical challenges in the fast developing young infant's brain. Methods on how to approach advanced tractography in the young infant's brain have hardly been described. Based on a literature review, recommendations are provided to optimize tractography for the developing infant brain, aiming to advance early diagnosis and neuroprotective strategies.

Pediatric glioma immune profiling identifies TIM3 as a therapeutic target in BRAF fusion pilocytic astrocytoma.

Despite being the leading cause of cancer-related childhood mortality, pediatric gliomas have been relatively understudied, and the repurposing of immunotherapies has not been successful. Whole-transcriptome sequencing, single-cell sequencing, and sequential multiplex immunofluorescence were used to identify an immunotherapeutic strategy that could be applied to multiple preclinical glioma models. MAPK-driven pediatric gliomas have a higher IFN signature relative to other molecular subgroups. Single-cell sequencing identified an activated and cytotoxic microglia (MG) population designated MG-Act in BRAF-fused, MAPK-activated pilocytic astrocytoma (PA), but not in high-grade gliomas or normal brain. T cell immunoglobulin and mucin domain 3 (TIM3) was expressed on MG-Act and on the myeloid cells lining the tumor vasculature but not normal brain vasculature. TIM3 expression became upregulated on immune cells in the PA microenvironment, and anti-TIM3 reprogrammed ex vivo immune cells from human PAs to a proinflammatory cytotoxic phenotype. In a genetically engineered murine model of MAPK-driven, low-grade gliomas, anti-TIM3 treatment increased median survival over IgG- and anti-PD-1-treated mice. Single-cell RNA-Seq data during the therapeutic window of anti-TIM3 revealed enrichment of the MG-Act population. The therapeutic activity of anti-TIM3 was abrogated in mice on the CX3CR1 MG-KO background. These data support the use of anti-TIM3 in clinical trials of pediatric low-grade, MAPK-driven gliomas.

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis

BackgroundPrecisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology.MethodsLongitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer’s Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer’s Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777–88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels.ResultsAmong the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers.ConclusionA normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term.Trial registrationClinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.