1013 results for "1993+article+mouse+line+professor+BA+psychology"

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• DIAMOND PCR : plasma DNA LINE-1 targeted bisulfite sequencing, a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Dataset EGAD50000000646

• Longitudinal single-cell transcriptomic study in patient-derived xenografts of pediatric T-ALL

  In this study, we conducted single cell full length total RNA sequencing (VASA-seq) on 13 matched pediatric T-ALL PDX samples at initial diagnosis and relapse, along with 5 non-relapsing PDX samples collected at initial diagnosis. We identified a subpopulation of T-ALL cells with stem-like cell features that expands substantially at relapse indicating resistance to first-line therapy. Chemotherapy resistance was further validated through functional testing: Two samples were subjected to in-vitro drug testing, treated with Cytarabine for three days, followed by single-cell transcriptomic analysis using 10x Genomics. Additionally, in-vivo drug testing was conducted on one sample, involving re-engraftment into mice and treatment with a combination of Vincristine, Doxorubicin, and Dexamethasone. Single-cell transcriptomic analysis using 10x Genomics was performed after 0, 15 and 30 days of treatment.

  Dataset EGAD50000000831

• Platinum Genomes

  Improvement of variant calling in next-generation sequence data requires a comprehensive, genome-wide catalogue of high-confidence variants called in a set of genomes for use as a benchmark. We generated deep, whole-genome sequence data of seventeen individuals in a three-generation pedigree and called variants in each genome using a range of currently available algorithms. We used haplotype transmission information to create a phased "platinum" variant catalogue of 4.7 million single nucleotide variants (SNVs) plus 0.7 million small (1-50bp) insertions and deletions (indels) that are consistent with the pattern of inheritance in the parents and eleven children of this pedigree. Platinum genotypes are highly concordant with the current catalogue of the National Institute of Standards and Technology for both SNVs (>99.99%) and indels (99.92%), and add a validated truth catalogue that has 26% more SNVs and 45% more indels. Analysis of 334,652 SNVs that were consistent between informatics pipelines yet inconsistent with haplotype transmission ("non-platinum") revealed that the majority of these variants are de novo and cell-line mutations or reside within previously unidentified duplications and deletions. The reference materials from this study are a resource for objective assessment of the accuracy of variant calls throughout genomes.

  Study phs001224

• Whole genome sequencing of core-binding factor leukemia

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study phs000414

• The Genomic Landscape of Core-Binding Factor Acute Myeloid Leukemias

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study EGAS00001000349

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• A Protein Neddylation Inhibitor MLN4924 Suppresses Patient-Derived Glioblastoma Cells via Inhibition of ERK and AKT Signaling

  Glioblastoma is a highly aggressive and lethal brain tumor, with limited treatment options. Abnormal activation of the neddylation pathway is observed in glioblastoma, and the NEDD8-activating enzyme (NAE) inhibitor, MLN4924 was previously shown to be effective in glioblastoma cell line models. However, its effect has not been tested in patient-derived glioblastoma stem cells. Immunohistochemistry and public data were analyzed to determine whether NEDD8 pathway proteins are important in glioblastoma development and patient survival. The effects of MLN4924 were evaluated in 4 glioblastoma cell lines and 15 patient-derived glioblastoma stem cells using high content analysis. Immunoblot analysis assessed the NEDD8 pathway proteins and biomarkers. Whole transcriptome analysis identified pathways associated with MLN4924 sensitivity. NAE1 and UBA3 levels increased in glioblastoma patients; high NEDD8 levels were associated with poor clinical outcomes. Glioblastoma cell lines and patient-derived stem cells were highly susceptible to MLN4924, while normal human astrocytes were resistant. Genomic analyses indicated that MLN4924 sensitive cells exhibited enrichment of ERK and AKT signaling. We verified that MLN4924 inhibits ERK and AKT phosphorylation in MLN4924 sensitive cells. Our findings suggest that patient-derived glioblastoma stem cells in the context of ERK and AKT activation are sensitive and highly regulated by neddylation inhibition.

  Study EGAS00001004018

• Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

  This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

  Study phs002652

• Genetics and Functional Studies of Autosomal Recessive Neurological Disorders

  Neurological conditions account for over 6% of the global disease burden. There are more than 600 neurological disorders, and cognitive dysfunction, also referred to as intellectual disability (ID), occupies a prominent position in this list. Cognitive dysfunction arises from the failure of neuronal cells to organize into a complex network and remodel this network in response to learning and experience. It is manifested by deficits in adaptive behaviors in everyday social and practical skills. Due to its high prevalence and the lifetime cost of care per individual, in the range of $1-2 million in United Sates (CDC), it presents a significant health burden. Genetic and functional studies of the genes and protein determinants of ID have helped to elucidate the molecular pathways of human brain development in health and disease. However, the identity of a large number of essential molecular and cellular components still remain elusive. The objectives of our study are to expand the genetic repertoire of causal ID genes and characterize their role in neuronal structure and cognitive function. The rationale is that identification and functional elucidation of causative gene variants that lead to cognitive dysfunction will be essential for understanding brain function and for developing improved diagnostic tools and efficacious preventive and therapeutic agents for neurological disorders, including ID. There are 3 aims of our comprehensive research program: 1) Ascertain and clinically phenotype members of extended families segregating autosomal recessive intellectual disability (ARID); 2) identify new ARID genes and gene products; and 3) determine the functions of prioritized novel ARID genes using multifaceted approaches, including analysis of spatiotemporal expression patterns in mouse brain, targeting in cultured rat hippocampal neurons, effects on cell morphology and synapse abundance, synaptic transmission and plasticity in neuronal cells by electrophysiology and live-cell imaging assays. The project will advantageously combine human clinical assessment, genetic and functional analyses relevant to brain development and function. Impact: Execution of the proposed studies will generate new knowledge that is clinically relevant, with high potential to impact ID molecular diagnosis, prognoses, and identify novel therapeutic targets to slow progression, delay onset, and possibly devising precision medicine approaches for ID.

  Study phs003298

• 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