16498 results for "sec+and+unspecified+malignant+neoplasm"

in 13.97 milliseconds.

• Healthspan and lifespan extension by fecal microbiota transplantation in progeroid mice

  The gut microbiome is emerging as a key regulator of several metabolic, immune and neuroendocrine pathways. Gut microbiome deregulation has been implicated in major conditions such as obesity, type 2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease or cancer, but its precise role in aging remains to be elucidated. Here, we characterize the gut microbiome profile of accelerated aging and show that its external modulation is sufficient to extend healthspan and lifespan. We found that two different mouse models of progeria present with intestinal dysbiosis, which is characterized, among other alterations, by an increment in proteobacteria, cyanobacteria and a loss in verrucomicrobia, whereas long-lived humans (i.e., centenarians) exhibit a remarkable increase in verrucomicrobia and a reduction in proteobacteria. Fecal microbiota transplantation proved to be effective to enhance healthspan and lifespan in both progeroid mouse models and, more importantly, the solely transplantation with the verrucomicrobia Akkermansia muciniphila was sufficient to exert beneficial effects. Our results demonstrate that intestinal dysbiosis is a phenotype associated with accelerated aging and its correction provides health benefits. Moreover, metabolomic analysis of ileal content points to the restoration of secondary bile acids as a possible mechanism for the beneficial outcome of reestablishing a healthy microbiome. Our results suggest the existence of a link between gut aging and the microbiota, and can help to gain insight into the rationale for microbiome-based interventions against age-related diseases. Mouse sequence data have been deposited in ENA (https://www.ebi.ac.uk/ena) under accession number PRJEB34214

  Study EGAS00001003656

• scRNAseq for patients with immunodeficiency and HCs

  The NFAT family of transcription factors plays central roles in adaptive immunity in murine models, however, their contribution to human immune homeostasis remains poorly defined. In a multigenerational pedigree, we identified three patients carrying germline biallelic missense variants in NFATC1, presenting with recurrent infections, hypogammaglobulinemia and decreased antibody responses. The compound heterozygous NFATC1 variants identified in the patients caused decreased stability and reduced binding of DNA and interacting proteins. We observed defects in early activation and proliferation of T and B cells from these patients, amenable to reconstitution upon genetic rescue. Following stimulation, T-cell activation and proliferation were impaired, reaching that of healthy controls with delay indicative of an adaptive capacity of the cells. Assessment of the metabolic capacity of patient T cells, revealed that NFATc1-dysfunction rendered T cells unable to engage in glycolysis following stimulation, although oxidative metabolic processes were intact. We hypothesized that NFATc1-mutant T cells could compensate for the energy deficit due to defective glycolysis by enhanced lipid metabolism as an adaptation, leading to a delayed, but not lost activation responses. Indeed, we observed increased 13C-labelled palmitate incorporation into citrate indicating higher fatty acid oxidation and we demonstrated that metformin and rosiglitazone improved patient T-cell effector functions. Collectively, enabled by our molecular dissection of NFATC1 mutations and extending the role of NFATc1 in human immunity beyond receptor signaling, and reveal evidence of metabolic plasticity in the context of impaired glycolysis observed in patient T cells to remedy delayed effector responses.

  Study EGAS00001007271

• shallow WGS and deep targeted panel on ctDNA in rhabdomyosarcomas

  The genomic spectrum of rhabdomyosarcoma (RMS) progression from primary to relapse is not fully understood. In this study we investigate 35 patients with relapsed RMS from two contributing institutions, 18 fusion-positive (FP-RMS) and 17 fusion-negative RMS (FN-RMS). Targeted DNA or whole exome sequencing (WES) was used to detect alterations in paired primary/relapsed samples. In 10 cases, circulating tumor DNA (ctDNA) from multiple timepoints through clinical care and progression was analyzed for feasibility of liquid biopsy in monitoring treatment response/relapse. ctDNA alterations were evaluated using a targeted custom RMS panel (36 genes) at high coverage for single nucleotide variation and fusion detection, and a shallow whole genome sequencing for copy number variation. FP-RMS had a stable genome with relapse, with the most common secondary alterations : CDKN2A/B, MYCN and CDK4 alterations, being already present at diagnosis and impacting overall survival. FP-RMS lacking major secondary events at baseline acquired recurrent MYCN and AKT1 alterations. FN-RMS acquired a higher number of new alterations, most commonly SMARCA2 missense mutations. ctDNA analyses detected pathognomonic variants in all RMS patients at diagnosis, regardless of FP/FN or type of alterations, while at relapse selected alterations were confirmed in 86% of FP-RMS and 100% FN-RMS. Moreover, a higher number of fusion reads was detected with increased disease burden and at relapse in patients following a fatal outcome. These results underscore patterns of tumor progression within a relatively stable genomic landscape and provide rationale for using liquid biopsy to monitor treatment response.

  Study EGAS00001007399

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy

  In this prospective study, custom genome-wide exome and whole transcriptome sequencing (NGS) was used to identify genomic events and associated expression changes in advanced Small Cell Lung Cancer (SCLC) and attempt to prescribe systemic therapy based on the results. Tumor/normal pairs were sequenced from 12 patients with advanced SCLC for this study.

  Study phs001366

• The Influence of Gut Microbiota on the Speciation and Toxicity of Mercury During Pregnancy

  There are few studies that have characterized maternal gut microbiota and fetal methylmercury exposure, yet microbes likely modulate this relationship. The primary objective of our pilot study was to determine associations between gut microbial taxa and mercury concentrations in multiple biomarkers (stool, hair, and cord blood). Our secondary objective was to determine the contribution of gut microbial mercury methylation to stool methylmercury.

  Study phs000970

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• Constrained hypermutation and absence of TERT promoter mutations in Lynch syndrome-associated urothelial cancer

  Lynch syndrome is a hereditary condition characterized by defective DNA mismatch repair and high incidence of several cancers, including urothelial cancers (UC) of the upper urinary tract and bladder. We set out to study the somatic landscape of LS-associated urothelial cancer (LS-UC) by analyzing 41 surgical tumor samples and 3 urine DNA samples from 34 LS-UC patients.

  Study EGAS50000000831

• Longitudinal Single-cell Genomic Analysis of Initial and Recurrent Meningioma

  This study investigates the genomic evolution of meningioma through single-cell whole genome sequencing analysis of paired tumor samples. We analyzed tumor tissues from initial and recurrent meningiomas from the same patients to understand clonal evolution and tumor progression. The research aims to characterize copy number alterations and genomic heterogeneity at single-cell resolution across different time points of tumor development.

  Study EGAS50000000860

• Evaluation of novel therapies using primary cultured gynecological cancer cells and search for predictors of efficacy

  The objective of this study is to establish an optimal method to evaluate the anti-tumor efficacy and biological activity of the novel therapies under investigation in our department using cancer tissues and cells derived from patients with gynecological malignancies in vitro and to evaluate them in practice. This research will contribute to the development of new treatments for gynecological cancer.

  Study JGAS000809