14676 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• RNA-Seq Profiles from CA017-003 Clinical Trial

  The dataset contains RNAseq profiles of 182 patients from the CA017-003 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNAseq libraries (50PE, 50M) were constructed using Illumina TruSeq RNA Access method. Fastq files are included.

  Dataset EGAD50000000991

• Single-cell TCR sequencing of gluten-specific T cells from 20 celiac disease patients uploaded on 2021_Data access committee

  In order to characterize the T cell receptor (TCR) repertoire of gluten specific T cells, we performed high-throughput DNA sequencing of rearranged TCR-α and TCR-β genes of the single HLA-DQ2.5:DQ2.5-gluten tetramer binding CD4+ T cells isolated from blood, biopsies and T cell line from celiac disease patients.

  Dataset EGAD00001006977

• Single-nucleus mRNA-Sequencing of prenatal and postnatal samples from the brain and its border regions

  Single-nucleus mRNA Sequencing of prenatal and postnatal samples from the brain and its border regions. Most samples were multiplexed with several samples run in one 10X reaction. A separate immune cell dataset was combined with published data from Braun et al 2023 and Yang et al 2021 integrated using harmony is included.

  Dataset EGAD50000000044

• Transcriptome analysis of patient-derived Schwann cells isolated from human sural nerve biopsies

  This dataset contains the transcriptome analysis of human Schwann cell cultures obtained from sural nerve biopsies from six patients with polyneuropathies (N=3/patient, totalN=18) as well as the nerve fascicles from where they were isolated (N=1/patient, totalN=6). In addition, this dataset includes 8 samples out of commercial human Schwann cell cultures and one sample of a fibroblast culture, which serve as controls for further analysis.

  Dataset EGAD50000001021

• High-grade serous ovarian carcinoma tumour exome sequencing variants

  Tumour variants (in VCF format) from exome sequencing (using Agilent SureSelect and TWIST library preparation systems followed by sequencing on Illumina HiSeq and NovaSeq platforms) of 108 high-grade serous ovarian tumour samples. Germline variants from EGAD00001006030 for these individuals were used to call somatic and tumour-only variants separately, creating two VCF files per sample (except for one sample without paired germline data- somatic variant file only provided). The dataset comprises 215 VCF variant files.

  Dataset EGAD50000001132

• PASCAL-MID Targeted amplicon sequencing of CD34+ HSPCs (CGD)

  High-throughput amplicon sequencing were performed on CD34+ hematopoietic stem and progenitor cells (HSPCs) derived from 4 healthy donors and one unaffected heterozygous carrier of a CYBB c.252G>A variant causing X-linked granulomatous disease. Targeted genome editing were performed in the HSPCs of CYBA and CYBB genes using CRISPR-Cas9 and recombinant AAV6. To assess gene editing outcomes in CD34+ HSPCs, the targeted loci were amplified from genomic DNA and sequenced on an Illumina iSeq100.

  Dataset EGAD50000001651

• RNA-seq FASTQ files studied in Generation of hypoimmunogenic induced pluripotent stem cells by CRISPR-Cas9 system and detailed evaluation for clinical application

  This data set contains 12 paired fastq files (RNA-seq) from one wild-type iPS cell, two HLA-KO iPS clones and three CD14+ monocytes differentiated from them. The RNA-seq libraries were generated with Illumina TruSeq Stranded Total RNA library prep kit. The libraries were sequenced with Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD50000001700

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Tumor implantation and expansion were performed in two 6-week-old NOD/SCID mice. Once tumors reached an average volume of approximately 700 mm³, mice were randomly assigned to one of two treatment arms: vehicle (physiological saline, intraperitoneally, twice weekly) or cetuximab (20 mg/kg, intraperitoneally, twice weekly). After 1 week of treatment, mice were sacrificed, and tumors were harvested and preserved in sCelLiVE® Buffer for downstream single-cell RNA sequencing analysis.

  Dataset EGAD50000002103