168 research outputs found

    Temporal course of cerebrospinal fluid dynamics and amyloid accumulation in the aging rat brain from three to thirty months

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    <p>Abstract</p> <p>Background</p> <p>Amyloid accumulation in the brain parenchyma is a hallmark of Alzheimer's disease (AD) and is seen in normal aging. Alterations in cerebrospinal fluid (CSF) dynamics are also associated with normal aging and AD. This study analyzed CSF volume, production and turnover rate in relation to amyloid-beta peptide (Aβ) accumulation in the aging rat brain.</p> <p>Methods</p> <p>Aging Fischer 344/Brown-Norway hybrid rats at 3, 12, 20, and 30 months were studied. CSF production was measured by ventriculo-cisternal perfusion with blue dextran in artificial CSF; CSF volume by MRI; and CSF turnover rate by dividing the CSF production rate by the volume of the CSF space. Aβ40 and Aβ42 concentrations in the cortex and hippocampus were measured by ELISA.</p> <p>Results</p> <p>There was a significant linear increase in total cranial CSF volume with age: 3-20 months (<it>p </it>< 0.01); 3-30 months (<it>p </it>< 0.001). CSF production rate increased from 3-12 months (<it>p </it>< 0.01) and decreased from 12-30 months (<it>p </it>< 0.05). CSF turnover showed an initial increase from 3 months (9.40 day<sup>-1</sup>) to 12 months (11.30 day<sup>-1</sup>) and then a decrease to 20 months (10.23 day<sup>-1</sup>) and 30 months (6.62 day<sup>-1</sup>). Aβ40 and Aβ42 concentrations in brain increased from 3-30 months (<it>p </it>< 0.001). Both Aβ42 and Aβ40 concentrations approached a steady state level by 30 months.</p> <p>Conclusions</p> <p>In young rats there is no correlation between CSF turnover and Aβ brain concentrations. After 12 months, CSF turnover decreases as brain Aβ continues to accumulate. This decrease in CSF turnover rate may be one of several clearance pathway alterations that influence age-related accumulation of brain amyloid.</p

    Oracle-based optimization applied to climate model calibration

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    In this paper, we show how oracle-based optimization can be effectively used for the calibration of an intermediate complexity climate model. In a fully developed example, we estimate the 12 principal parameters of the C-GOLDSTEIN climate model by using an oracle- based optimization tool, Proximal-ACCPM. The oracle is a procedure that finds, for each query point, a value for the goodness-of-fit function and an evaluation of its gradient. The difficulty in the model calibration problem stems from the need to undertake costly calculations for each simulation and also from the fact that the error function used to assess the goodness-of-fit is not convex. The method converges to a Fbest fit_ estimate over 10 times faster than a comparable test using the ensemble Kalman filter. The approach is simple to implement and potentially useful in calibrating computationally demanding models based on temporal integration (simulation), for which functional derivative information is not readily available

    Combination therapy in a xenograft model of glioblastoma: enhancement of the antitumor activity of temozolomide by an MDM2 antagonist

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    OBJECTIVE Improvement in treatment outcome for patients with glioblastoma multiforme (GBM) requires a multifaceted approach due to dysregulation of numerous signaling pathways. The murine double minute 2 (MDM2) protein may fulfill this requirement because it is involved in the regulation of growth, survival, and invasion. The objective of this study was to investigate the impact of modulating MDM2 function in combination with front-line temozolomide (TMZ) therapy in GBM. METHODS The combination of TMZ with the MDM2 protein-protein interaction inhibitor nutlin3a was evaluated for effects on cell growth, p53 pathway activation, expression of DNA repair proteins, and invasive properties. In vivo efficacy was assessed in xenograft models of human GBM. RESULTS In combination, TMZ/nutlin3a was additive to synergistic in decreasing growth of wild-type p53 GBM cells. Pharmacodynamic studies demonstrated that inhibition of cell growth following exposure to TMZ/nutlin3a correlated with: 1) activation of the p53 pathway, 2) downregulation of DNA repair proteins, 3) persistence of DNA damage, and 4) decreased invasion. Pharmacokinetic studies indicated that nutlin3a was detected in human intracranial tumor xenografts. To assess therapeutic potential, efficacy studies were conducted in a xenograft model of intracranial GBM by using GBM cells derived from a recurrent wild-type p53 GBM that is highly TMZ resistant (GBM10). Three 5-day cycles of TMZ/nutlin3a resulted in a significant increase in the survival of mice with GBM10 intracranial tumors compared with single-agent therapy. CONCLUSIONS Modulation of MDM2/p53-associated signaling pathways is a novel approach for decreasing TMZ resistance in GBM. To the authors' knowledge, this is the first study in a humanized intracranial patient-derived xenograft model to demonstrate the efficacy of combining front-line TMZ therapy and an inhibitor of MDM2 protein-protein interactions

    The place of VEGF inhibition in the current management of renal cell carcinoma

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    Vascular endothelial growth factor (VEGF) is overexpressed in around 80% of patients with clear cell carcinoma of the kidney owing to the inactivation of von Hippel Lindau gene activity. VEGF stimulates angiogenesis and acts as an autocrine growth factor. A number of different agents are now available which target VEGF and its signalling pathways. A significant body of evidence has accumulated demonstrating that antagonism of VEGF and its downstream pathways is clinically useful in a significant proportion of patients with metastatic clear cell carcinoma of the kidney. Enough data is now available to recommend that patients with metastatic clear cell carcinoma of the kidney should at some point during the course of their disease be offered entry into a clinical trial enabling exposure to a targeted inhibitor of VEGF or its signalling pathways. Assuming early clinical trial data is substantiated by ongoing registration studies, efforts should be made to minimise the time taken between licensing and general availability of these active agents

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

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    Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types
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