17244 results for "free coins in fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..xwWa"

in 129.32 milliseconds.

• Cholesterol homeostasis and lipid raft dynamics at the basis of tumor-induced immune dysfunction in chronic lymphocytic leukemia

  Autologous T-cell therapies show limited efficacy in chronic lymphocytic leukemia (CLL), where acquired immune dysfunction prevails. In CLL, disturbed mitochondrial metabolism has been linked to defective T-cell activation and proliferation. Recent research suggests that lipid metabolism regulates mitochondrial function and differentiation in T cells, yet its role in CLL remains unexplored. This comprehensive study compares T-cell lipid metabolism in CLL patients and healthy donors, revealing critical dependence on exogenous cholesterol for human T-cell expansion following TCR-mediated activation. Using multi-omics and functional assays, we found that T cells present in viably frozen samples of patients with CLL (CLL T cells) showed impaired adaptation to cholesterol deprivation and inadequate upregulation of key lipid metabolism transcription factors. CLL T cells exhibited altered lipid storage, with increased triacylglycerols and decreased cholesterol, and inefficient fatty acid oxidation (FAO). Functional consequences of reduced FAO in T cells were studied using samples from patients with inherent FAO disorders. Reduced FAO was associated with lower T-cell activation but did not affect proliferation. This implicates low cholesterol levels as a primary factor limiting T-cell proliferation in CLL. Consequently, CLL T cells displayed fewer and less clustered lipid rafts, potentially explaining the impaired immune synapse formation observed in these patients. Our findings highlight significant disruptions in lipid metabolism as drivers of functional deficiencies in CLL T cells, underscoring the pivotal role of cholesterol in T-cell proliferation. This study suggests that modulating cholesterol metabolism could enhance T-cell function in CLL, presenting novel immunotherapeutic approaches to improve outcome in this challenging disease.

  Study EGAS50000000933

• A Genome-Wide Association Study of Sporadic ALS in an Irish Population (SIALS) and Sequencing and Analysis of an Irish Human Genome

  Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by loss of motor neurons. Epidemiological studies indicate that 2-5% of cases are familial, usually with an autosomal dominant pattern of inheritance. For a portion of these, causative genes have been identified. The remaining 95% of ALS cases are described as sporadic, and believed to result from a combination of genetic and environmental factors. This study utilized samples from Irish patients with sporadic ALS and Irish control individuals. The aim of the study was to identify susceptibility alleles for ALS in the Irish population. Genome-wide, single-nucleotide polymorphism (SNP) genotyping was undertaken using Illumina 550K version 3 chips. Genotyping data are available on 221 SALS patients and 211 controls. Future work will aim to examine ALS genetic risk at individual sequence level. As an initial step, as of September 2010 we have made available the human genome sequence from a single anonymous male control individual from the SIALS collection. Recent studies generating complete human sequences from Asian, African and European subgroupings have revealed population specific variation and illuminated disease susceptibility loci. The Irish population is of interest because of its location at the periphery of Europe and also the impact its emigrants have had on the genetics of populations in a number of other countries. We have identified sequence variants that may be specific to this population and have identified potentially novel disease associated variants. We describe a novel method for improving SNP calling accuracy at low genome coverage using haplotype information. Overall we demonstrate utility in generating whole genome sequences to test general principles and reveal specific instances of human biology. With increasing access to low cost sequencing we would predict that similar studies will emerge.

  Study phs000127

• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• RNA sequencing of Notch inhibitor treated HCC PDX models across timepoints

  To study the effect of Notch inhibition on the transcriptional profiles our PDX models, we generated bulk RNA-seq data for two Notch inhibition sensitive and three Notch inhibition insensitive models across multiple timepoints (8h, 24h, 48h, 7d, 17d) using anti-JAG1, anti-Notch2, anti-Notch1 or anti-gD antibodies. 3-5 samples were collected for each treatment condition, resulting in a total of 96 samples. Isolated RNA was used as input for library preparation using TruSeq RNA Sample Preparation Kit v2 (Illumina). The libraries were multiplexed and sequenced on Illumina HiSeq 2500 (Illumina) to produce FASTQ files.

  Dataset EGAD50000000737

• Variant calling for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains whole exome sequencing data from tumor samples processed with the Vegan pipeline. In the absence of matching germline samples, variant calling is performed using two panel of normals (one for female and one for male). It includes SNP and CNV calling.

  Dataset EGAD50000002235

• GenomeDenmark Phase 2 - MHC haplotypes

  The MHC vcf call set was generated using a modified AsmVar and BayesTyper pipeline. In contrast to the original pipeline, where variant calling is performed using alignment of collapsed assemblies to a reference genome, the MHC call set was produced using alignment of phased MHC haplotypes. Two iterations of BayesTyper was run, a first iteration for each haplotype seperately and a second iteration performing joint variant calling on all haplotypes. The sample IDs for the fathers and mothers are TrioID-01 and TrioID-02, respectively, and the IDs for the children are TrioID-0x, where x is a number between 3 and 7.

  Dataset EGAD00001003455

• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• Next Generation Mendelian Genetics: Familial Combined Hyperlipidemia

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. The research study procedures included the collection of a fasting blood sample, 2 medical history/life style questionnaires and a measurement of subjects' waist circumference that were completed many years ago. Blood samples were analyzed for metabolic markers including cholesterol, HDL, triglycerides and APOE. Genetic tests targeted known and novel genes and polymorphisms associated with carotid artery disease.

  Study phs000538

• Molecular genetic analysis of inherited kidney dysfunction

  Samples were chosen for sequencing from a set of probands from pedigrees with apparently inherited forms of focal segmental glomerulosclerosis (FSGS). Several genes have been identified which when mutated cause FSGS under both recessive and dominant inheritance patterns. These known genes are estimated to explain less than 50% of inherited FSGS. We chose samples from individuals in which previous analyses of known disease genes failed to identify likely disease-causing mutations.

  Study phs000484

• Genome Sequencing of Large, Multigenerational CEPH/Utah Families

  Blood-derived DNA samples were collected from 603 members of large, multigenerational families, collected as part of the Centre d'Etude du Polymorphisme Humain (CEPH) consortium. These DNA samples were sequenced (using Illumina HiSeq technology) to a median genome-wide depth of 30X. Sequenced reads from each individual were aligned to the human reference genome (hg19), generating CRAM files for each individual. Variant calls in VCF format were obtained using the Genome Analysis Toolkit (GATK).

  Study phs001872