tbuckley/cabot-search huggingface dataset:
Phosphatidylserine phospholipase A1 enables GPR34-dependent immune cell accumulation in the peritoneal cavity
Authors: Hanson Tam, Ying Xu, Jinping An, Torsten Schöneberg, Angela Schulz, Jagan R. Muppidi, Jason G. Cyster
Journal: The Journal of Experimental Medicine (2024)

The peritoneal cavity (PerC) is an important site for immune responses to infection and cancer metastasis. Yet few ligand-receptor axes are known to preferentially govern immune cell accumulation in this compartment. GPR34 is a lysophosphatidylserine (lysoPS)-responsive receptor that frequently harbors gain-of-function mutations in mucosa-associated B cell lymphoma. Here, we set out to test the impact of a GPR34 knock-in (KI) allele in the B-lineage. We report that GPR34 KI promotes the PerC accumulation of plasma cells (PC) and memory B cells (MemB). These KI cells migrate robustly to lysoPS ex vivo, and the KI allele synergizes with a Bcl2 transgene to promote MemB but not PC accumulation. Gene expression and labeling studies reveal that GPR34 KI enhances PerC MemB proliferation. Both KI PC and MemB are specifically enriched at the omentum, a visceral adipose tissue containing fibroblasts that express the lysoPS-generating PLA1A enzyme. Adoptive transfer and chimera experiments revealed that KI PC and MemB maintenance in the PerC is dependent on stromal PLA1A. These findings provide in vivo evidence that PLA1A produces lysoPS that can regulate GPR34-mediated immune cell accumulation at the omentum.
Intracranial administration of anti-PD-1 and anti-CTLA-4 immune checkpoint-blocking monoclonal antibodies in patients with recurrent high-grade glioma
Authors: Johnny Duerinck, Louise Lescrauwaet, Iris Dirven, Jacomi Del’haye, Latoya Stevens, Xenia Geeraerts, Freya Vaeyens, Wietse Geens, Stefanie Brock, Anne-Marie Vanbinst, Hendrik Everaert, Ben Caljon, Michaël Bruneau, Laetitia Lebrun, Isabelle Salmon, Marc Kockx, Sandra Tuyaerts, Bart Neyns
Journal: Neuro-Oncology (2024)

Abstract Background Recurrent high-grade glioma (rHGG) lacks effective life-prolonging treatments and the efficacy of systemic PD-1 and CTLA-4 immune checkpoint inhibitors is limited. The multi-cohort Glitipni phase I trial investigates the safety and feasibility of intraoperative intracerebral (iCer) and postoperative intracavitary (iCav) nivolumab (NIVO) ± ipilimumab (IPI) treatment following maximal safe resection (MSR) in rHGG. Materials and methods Patients received 10 mg IV NIVO within 24 h before surgery, followed by MSR, iCer 5 mg IPI and 10 mg NIVO, and Ommaya catheter placement in the resection cavity. Biweekly postoperative iCav administrations of 1–5–10 mg NIVO (cohort 4) or 10 mg NIVO plus 1–5–10 mg IPI (cohort 7) were combined with 10 mg IV NIVO for 11 cycles. Results 42 rHGG patients underwent MSR with iCer NIVO + IPI. 16 pts were treated in cohort 4 (postoperative iCav NIVO at escalating doses) while 28 patients were treated in cohort 7 (intra and postoperative iCav NIVO and escalating doses of IPI). The most common TRAE was fatigue; no grade 5 AE occurred. Dose-limiting toxicity was grade 3 neutrophilic pleocytosis (4 pts) receiving iCav NIVO plus 5 or 10 mg IPI. PFS and OS did not significantly differ between cohorts (median OS: 42 [95% CI 26–57] vs. 35 [29–40] weeks; 1-year OS rate: 37% vs. 29%). Baseline B7–H3 expression significantly correlated with worse survival. OS compared favorably to a historical pooled cohort (n = 469) of Belgian rHGG pts treated with anti-VEGF therapies (log-rank P = .015). Conclusion Intraoperative iCer IPI + NIVO with postoperative iCav NIVO ± IPI up to biweekly doses of 1 mg IPI + 10 mg NIVO is feasible and safe, showing encouraging OS in rHGG patients. ClinicalTrials.gov registration: NCT03233152
Maternal Diabetes and Cardiac Left Ventricular Structure and Function in the Infant: A Copenhagen Baby Heart Study
Authors: Jonas Ghouse, Magdalena Hansson, Ruth Ottilia B. Vøgg, Anne-Sophie Sillesen, Sofie Pærregaard, Anna Axelsson Raja, Niels Vejlstrup, Ruth Frikke-Schmidt, Nina Øyen, Aparna Kulkarni, Magnus T. Jensen, Finn Stener Jørgensen, Karin Sundberg, Olav B. Petersen, Jan Wohlfahrt, Peter Damm, Morten Salling Olesen, Elisabeth R. Mathiesen, Kasper Iversen, Henning Bundgaard, Heather A. Boyd
Journal: Diabetes Care (2024)

OBJECTIVE Prenatal exposure to maternal diabetes is associated with an increased risk of offspring heart defects. We evaluated associations with subtle infant cardiac changes. RESEARCH DESIGN AND METHODS In a cohort of 25,486 infants with transthoracic echocardiography within 60 days of birth, we investigated associations between maternal preexisting diabetes and gestational diabetes mellitus (GDM) and infant left ventricular (LV) structural and functional parameters, using linear regression to estimate adjusted mean differences (aMDs) between groups. RESULTS Infants exposed to maternal preexisting diabetes (n = 198) had thicker LV posterior walls (aMD 0.19 mm; 95% CI 0.11, 0.27), smaller LV internal diameters in systole (aMD −0.27 mm; 95% CI −0.45, −0.18) and diastole (aMD −0.37 mm; 95% CI −0.59, −0.09), reduced stroke volumes (aMD −0.36 mL; 95% CI −0.61, −0.11), and increased heart rates (aMD 3.14 bpm; 95% CI 1.10, 6.18) and mitral valve early peak velocities (aMD 2.17 cm/s; 95% CI 0.31, 4.04) than unexposed infants (n = 24,639). Infants born to mothers with GDM (n = 649) had significantly smaller LV internal diameters in systole (aMD −0.13 mm; 95% CI −0.22, −0.03) and similar structural and functional changes as children exposed to preexisting diabetes, albeit with smaller nonsignificant aMDs. Higher third-trimester HbA1c levels were associated with smaller LV internal diameters and stroke volumes in infants exposed to preexisting diabetes and with lower heart rates in infants exposed to GDM. CONCLUSIONS Maternal preexisting diabetes and, to a lesser extent, GDM were associated with changes in infant LV structure and function.
Publisher Correction: Allogeneic CD5-specific CAR-T therapy for relapsed/refractory T-ALL: a phase 1 trial
Authors: Jing Pan, Yue Tan, Lingling Shan, Samuel Seery, Biping Deng, Zhuojun Ling, Jinlong Xu, Jiajia Duan, Zelin Wang, Kai Wang, Xinjian Yu, Qinlong Zheng, Xiuwen Xu, Guang Hu, Taochao Tan, Ying Yuan, Zhenglong Tian, Fangrong Yan, Yajing Han, Jiecheng Zhang, Xiaoming Feng
Journal: Nature Medicine (2024)
Review of Chronic Pruritus
Authors: Chaker Ben Salem, Nadia Ghariani
Journal: JAMA (2024)

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The Insulin-like Growth Factor System and Aging
Authors: Cheryl A Conover, Claus Oxvig
Journal: Endocrine Reviews (2024)

Abstract There is strong evidence that insulin-like growth factor (IGF) signaling is involved in fundamental aspects of the aging process. However, the extracellular part of the IGF system is complex with various receptors, ligand effectors, high affinity IGF binding proteins, proteinases and endogenous inhibitors that all, along with their biological context, must be considered. The IGF system components are evolutionarily conserved, underscoring the importance of understanding this system in physiology and pathophysiology. This review will briefly describe the different components of the IGF system and then discuss past and current literature regarding the IGFs and aging, with a focus on cellular senescence, model organisms of aging, centenarian genetics, and three age-related diseases - pulmonary fibrosis, Alzheimer’s disease, and macular degeneration - in appropriate murine models and in humans. Commonalities in mechanism suggest conditions where IGF system components may be disease drivers and potential targets in promoting healthy aging in humans.
P11.09.B STRUCTURAL REORGANIZATION IN MOTOR-ELOQUENT GLIOMA PATIENTS EXHIBITING MOTOR DEFICITS
Authors: Z Gong, H Zhang, M Schwendner, A Schröder, B Meyer, S Ille, S Krieg
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Recent advancements in navigated transcranial magnetic stimulation (nTMS) have significantly improved the localization of motor functions in human subjects. Although previous studies have demonstrated the occurrence of tumor-induced motor plasticity, the detailed mechanisms of motor function plasticity and reorganization in patients with tumors affecting motor-eloquent regions are not fully elucidated. Our study aims to investigate the functional plasticity of motor functions in patients with gliomas located within motor-eloquent regions, providing deeper insights into the mechanisms of functional plasticity. MATERIAL AND METHODS In this research, we studied 60 glioma patients with tumors located in the motor-eloquent region. These patients were categorized into two groups depending on whether they experienced motor impairments in the upper extremities. We utilized nTMS, including Motor Evoked Potentials (MEP), to outline the control regions of motor function in terms of area, localization, and Center of Gravity (CoG). These identified regions also acted as seeds for tracing the Corticospinal Tract (CST). RESULTS The study unveiled significant variations in cortical and subcortical motor function localizations between the groups. Patients with motor impairments exhibited a broader cortical distribution connected to motor functions and increased volumes of CST, reflecting compensatory adaptations with different fractional anisotropy (FA) values (FA 0.15, p=0.02; FA 0.10, p=0.04). The analysis of the CST also showed overlapping regions, particularly within the hand-knob areas, which is indicative of these areas acting as critical motor output pathways. Despite varying degrees of functional impairment, all patients maintained some degree of motor output capability. CONCLUSION These findings suggest that motor-eloquent gliomas induce significant cortical and subcortical reorganization of motor functions. A persistent network of CST fibers, crucial for preserving motor function, highlights a complex interplay between cortical adaptation and subcortical reorganization. This study underscores the resilience of motor pathways and their pivotal role in functional recovery and plasticity, emphasizing the clinical relevance of nTMS in the therapeutic planning and monitoring of patients with motor-eloquent gliomas.
OS10.4.A CXCL1 MEDIATES LEPTOMENINGEAL METASTASIS GROWTH
Authors: A Osman, J Remsik, A Wijetunga, J Snyder, B Manoranjan, A Nobre, M Freret, D Guber, K Chabot, S Piedrafita-Ortiz, X Tong, H Wang, M Li, J Yang, A Boire
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Leptomeningeal metastasis (LM) is a fatal neurological complication of cancer characterized by the entry of metastatic cancer cells originated from solid or hematologic tumors into the cerebrospinal fluid (CSF)-filled leptomeningeal compartment encasing the brain and the spinal cord. LM occurs in 5-20% in patients with solid tumors, especially those with breast cancer, lung cancer, melanoma. Untreated LM patients succumb within 4-6 weeks after diagnosis, or 2-5 months when they are treated with the current available therapies. To date, the only efficacious life-prolonging intervention was the application of proton craniospinal irradiation (pCSI) as demonstrated in the recent clinical trial, NCT04343573, with an average overall survival of 9 months. While a cohort of pCSI-treated patients survived over 18 months (responders), another cohort did not respond to pCSI and succumbed to the disease within 3 months post-treatment (non-responders). In this project, we aimed to characterize the molecular basis of pCSI response to turn the non-responders into responders. MATERIAL AND METHODS We performed proteomic analyses on serially collected CSF from LM patients at baseline (before pCSI), and multiple time points post-treatment. We further established syngeneic mouse models of LM-CSI to define the molecular basis of pCSI resistance. RESULTS We found that pCSI resulted in a significant drop in the levels of the chemokine CXCL1, a CXC-motif chemokine with elevated baseline levels after the onset of LM. Patients with significantly higher CSF CXCL1 levels prior to pCSI had worse central nervous system (CNS) progression-free survival. Using our preclinical LM mouse models, we found that both the cancer and host cells, namely macrophages, choroid plexus epithelial cells, and leptomeningeal fibroblasts, were a source of CXCL1. Genetic manipulation of Cxcl1expression in cancer cells or host revealed that the CXCL1 produced by the cancer cells was an essential factor for their growth in the leptomeninges. Moreover, we found that a subset of cancer cells expressed a receptor for CXCL1 - CXCR2 - and transcriptomic profiling of this rare population revealed an enrichment in pathways associated with cell cycle progression. Finally, intrathecally delivered CXCR2 antagonist hampered the LM growth. CONCLUSION Our results indicate that CXCL1/CXCR2 signaling axis regulates LM growth and suggests interruption of this signaling axis as a possible actionable therapeutic intervention to halt LM progression.
P02.15.A INVESTIGATING THE ROLE OF CELLULAR SENESCENCE IN BRIDGING GLIOBLASTOMA AND ALZHEIMER’S DISEASE
Authors: E Krause, L Greutter, D Romanovskaia, P Stepper, A Wöhrer
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND With changing demographics, age-related diseases like neurodegenerative disorders and cancer are becoming increasingly prevalent. We previously demonstrated that over 50% of glioblastoma (GB) patients show Alzheimer’s Disease (AD)-like changes in the tumor-adjacent cortex. However, whether these diseases are biologically linked remains unclear. Here, we investigate cellular senescence, a hallmark of aging, as a shared mechanism. MATERIAL AND METHODS We utilized single cell and single nucleus RNA sequencing datasets from 110 GB patients (GBmap core atlas) and 89 individuals with varying stages of AD (SEA-AD MTG atlas). Following data integration, we assessed senescent cells using three established gene lists, performed differential gene expression and conducted gene set enrichment analysis. Senescence scores were compared across different cell types and patients. Co-expression modules with senescence-associated genes were identified using weighted gene co-expression network analysis (WGCNA). Quantitative neuropathological analysis of published measurements (Iba1, AT8, 6E10) complemented the molecular findings. RESULTS Senescence was found in both GB and AD patient cells including cell types of the microenvironment. Notably, the variability in scores per patient was significantly higher in GB as compared to AD cell types, indicating greater inter-patient heterogeneity. Microglia were specifically enriched for senescence gene sets among glial cells. Subset analysis of microglia through data harmonization identified a proinflammatory GB microglia subtype that shared high similarity with AD microglia and had highest senescence scores. Notably, the increase in senescent microglia was associated with progression to advanced disease stages in both diseases. WGCNA identified 3 consensus modules of senescence-associated genes that were coexpressed with disease-specific genes, like PTEN implicated phosphorylation in the AD module and SPP1 for extracellular matrix remodeling in the GB module. All senescence associated modules showed increased expression in more advanced disease stages. Quantitative analysis of immunohistochemistry measurements in the AD dataset confirmed that samples with a high senescence score showed a significantly higher density of tau pathology and an altered microglia morphology. CONCLUSION Our study identifies cellular senescence as one connection between GB and AD pathology by utilizing atlas-level transcriptomic datasets. Particularly microglia upregulate senescence signatures with disease progression. The co-expression of senescence-associated genes within disease-specific modules underscores the complexity of senescence in this context.
Predicting Phylogenetic Bootstrap Values via Machine Learning
Authors: Julius Wiegert, Dimitri Höhler, Julia Haag, Alexandros Stamatakis
Journal: Molecular Biology and Evolution (2024)

Abstract Estimating the statistical robustness of the inferred tree(s) constitutes an integral part of most phylogenetic analyses. Commonly, one computes and assigns a branch support value to each inner branch of the inferred phylogeny. The still most widely used method for calculating branch support on trees inferred under maximum likelihood (ML) is the Standard, nonparametric Felsenstein bootstrap support (SBS). Due to the high computational cost of the SBS, a plethora of methods has been developed to approximate it, for instance, via the rapid bootstrap (RB) algorithm. There have also been attempts to devise faster, alternative support measures, such as the SH-aLRT (Shimodaira–Hasegawa-like approximate likelihood ratio test) or the UltraFast bootstrap 2 (UFBoot2) method. Those faster alternatives exhibit some limitations, such as the need to assess model violations (UFBoot2) or unstable behavior in the low support interval range (SH-aLRT). Here, we present the educated bootstrap guesser (EBG), a machine learning-based tool that predicts SBS branch support values for a given input phylogeny. EBG is on average 9.4 (σ=5.5) times faster than UFBoot2. EBG-based SBS estimates exhibit a median absolute error of 5 when predicting SBS values between 0 and 100. Furthermore, EBG also provides uncertainty measures for all per-branch SBS predictions and thereby allows for a more rigorous and careful interpretation. EBG can, for instance, predict SBS support values on a phylogeny comprising 1,654 SARS-CoV2 genome sequences within 3 h on a mid-class laptop. EBG is available under GNU GPL3.
P10.22.B PREDICTING INTRAOPERATIVE 5-ALA-INDUCED TUMOR FLUORESCENCE VIA MRI AND DEEP LEARNING IN GLIOMAS WITH RADIOGRAPHIC LOWER-GRADE CHARACTERISTICS
Authors: E Suero Molina, G Azemi, Z Özdemir, C Russo, A Valls Chavarria, S Liu, C Thomas, W Stummer, A Di Ieva
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Lower-grade gliomas typically exhibit 5-aminolevulinic acid (5-ALA)-induced fluorescence in only 20-30% of cases, a rate that can be increased by doubling the administered dose of 5-ALA. Fluorescence can depict anaplastic foci, which can be precisely resected to avoid undergrading. We aimed to analyze whether a deep learning model can predict intraoperative fluorescence based on preoperative magnetic resonance imaging (MRI). Material and Methods: The MRI images of gliomas lacking high-grade characteristics (necrosis, extended contrast-enhancement, a.o.) consisted of T1, T1-post gadolinium, and FLAIR sequences. The preprocessed MRIs were fed into an encoder-decoder convolutional neural network (U-Net), pre-trained for tumor segmentation using those three MRI sequences. We used the outputs of the bottleneck layer of the U-Net in the Variational Autoencoder (VAE) as features for classification. We identified and utilized the most effective features in a Random Forest classifier using the principal component analysis (PCA) and the partial least square discriminant analysis (PLS-DA) algorithms. We evaluated the performance of the classifier using a 10-fold cross-validation procedure. RESULTS We evaluated a cohort of 163 glioma patients categorized as fluorescent (n=83) or non-fluorescent (n=80). Our proposed approach’s performance was evaluated using metrics such as mean balanced accuracy, mean sensitivity, and mean specificity. The optimal results were obtained by employing top-performing features selected by PCA, resulting in a mean balanced accuracy of 80% and mean sensitivity and specificity of 84% and 76%, respectively. CONCLUSION Our findings highlight the potential of a U-Net model, coupled with a random forest classifier, for intraoperative fluorescence prediction. We achieved good accuracy using advanced techniques such as deep learning-based tumor segmentation and Variational Autoencoder for radiomics feature extraction. While the model can still be improved, it has the potential for evaluating when to administer 5-ALA to gliomas lacking typical high-grade radiographic features.
P08.06.B TARGETED PLASMA METABOLOMICS DETECTS A METABOLIC SIGNATURE POTENTIALLY RELEVANT FOR DIAGNOSIS AND PROGNOSIS IN PATIENTS WITH GLIOBLASTOMA
Authors: M Pantalone, C Söderberg Naucler, G Stragliotto
Journal: Neuro-Oncology (2024)

Abstract BACKGROUND Glioblastoma diagnosis is made initially with radiological examination and pathological examination of the resected tumor. Debut symptoms may vary and be mild in the beginning therefore diagnosis can be delayed. Additional un-invasive diagnostic strategies can be useful for diagnosis and clinical follow up. Moreover, despite glioblastoma being almost invariably fatal, there are no clinically established plasma biomarkers to define prognosis in patients with glioblastoma. MATERIAL AND METHODS In this study we employed flow injection analysis tandem mass spectrometry to compare the plasma metabolic profile of patients with GBM (n=51) and healthy controls (n=24). RESULTS Principal Component Analysis (PCA) and Partial Least Discriminant Analysis (PLS-DA) highlighted a distinctive glioblastoma signature. The best confusion matrix from the ROC curve built on two metabolites, GLU and GLN-LYS, provided specificity of 87% and sensitivity of 92%, with positive and negative predictive values of 95% and 88%, respectively. Multivariate survival analyses revealed that higher levels of ALA, MET, ORN, PHE, TYR were to be associated with a shorter overall survival. CONCLUSION These results are currently being evaluated prospectively and at different stages of disease in a larger cohort of patients with glioblastoma to identify plasma metabolic markers relevant for recurrence development.