14670 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations

  Lynch syndrome (LS) predisposes to cancer in adulthood and is caused by heterozygous germline variants in a mismatch repair (MMR) gene. Recent studies show an increased prevalence of LS among children with cancer, suggesting a causal relationship. For LS-spectrum (LSS) cancers, including high-grade gliomas and colorectal cancer, causality has been supported by typical MMR-related tumor characteristics, but for non-LSS cancers, causality is unclear. This dataset contains 5 patients with Lynch Syndrome from the INFORM registry.

  Study EGAS00001007146

• Cachexia - Non-Cachexia Metagenome Analysis

  Cancer cachexia has been linked to gut bacterial alterations, but alterations of gut viruses, mostly bacteriophages, have not yet been explored. We performed shotgun metagenomic sequencing of DNA from stool samples of 78 cachectic and 42 non-cachectic cancer patients. K-mer-based matching to reference databases revealed abundance variations of bacteria and viruses. Beyond bacterial alterations, cachectic patients exhibited significantly lower bacteriophage abundance, predominantly affecting Caudovirales and Siphoviridae species (double-stranded DNA) but also Inoviridae and Microviridae families (single-stranded DNA).

  Study EGAS00001007156

• Multiomic profiling of pleomorphic rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) describes rare soft-tissue tumors that exhibit features of skeletal muscle differentiation. The most common subtypes in children are alveolar and embryonal rhabdomyosarcoma, with the alveolar subtype characterized by PAX3/7 fusions. A lesser known and rarer subtype, pleomorphic rhabdomyosarcoma (PRMS), occurs most frequently in adults vetween the ages of 40 and 50. This pleomorphic subtype is often misdiagnosed and little is known about its molecular characterization. Here, we conducted comprehensive genomic, transcriptomic, and methylation profiling of these tumors.

  Study EGAS00001007230

• Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

  We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrency to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

  Study EGAS00001007288

• H3K27ac ChIP-seq in primary inflammatory (TPP) macrophages

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and identified the molecular mechanism by which the risk haplotype increases expression of the causal gene, ETS2. This mechanism was predicted to alter enhancer activity at the disease-associated locus. We therefore performed H3K27ac ChIP-seq in inflammatory macrophages from minor and major allele homozygotes at the causal allele and investigated the effect on enhancer activity. In doing so, we mechanistically delineated how the risk haplotype increases expression of ETS2.

  Study EGAS00001007562

• Lung_Cell_Atlas__Paediatric_RNA

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008299

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Lung_Cell_Atlas__Paediatric_Spatial

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets

  Study EGAS00001008300

• Khoe-San Genome Project

  The dataset contains BAM files of whole genome sequencing data of African Khoe-San population (n=169, 30X coverage) recruited from South Africa and Namibia. The population captured the true extent of human genetic diversity as represent the earliest diverged human population. The project described a detailed divergence of human population and identified positive selections associated forager lifestyles in Khoe-San population. These findings emphasise an inclusive catalogue with better representation of the earliest human genomic diversity to better advance biomedical research.

  Study EGAS50000001408

• H3Africa - Consortium WGS

  To address gaps in sequence data for some of the African populations being studied in H3Africa projects, additional sequencing has been carried out through various projects and the data are being made available. The first dataset includes a high coverage whole genome sequence dataset generated at the Baylor College of Medicine with samples provided by H3Africa PIs and collaborators, funded by the National Institutes of Health. The sequence data files are accompanied by minimal metadata, including country, ethnic group (where available) and sex.

  Study EGAS00001005972