14982 results for "cancer studies using rna-seq"

in 17.49 milliseconds.

• NHLBI GO-ESP Family Studies: Idiopathic Bronchiectasis of unknown etiology that is not related to cystic fibrosis or classic primary ciliary dyskinesia or immune deficiency or any other known causes

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The major goal of this project is to apply next generation resequencing technology to identify disease-causing variants that cause bronchiectasis of unknown etiology (e.g. non cystic fibrosis (CF), classic primary ciliary dyskinesia (PCD), immune deficiency, or any other known cause of bronchiectasis), i.e., "idiopathic bronchiectasis." As part of our ongoing efforts to define the genetic cause of rare lung diseases, we have also studied families in whom diagnosis of PCD or other known etiologies could not be confirmed. We have systematically collected and stored the DNA and phenotypic data on each of the families in our cohort. The phenotypic data includes age, gender, ethnicity information, clinical data pertaining to the airways disease, including neonatal respiratory distress, otitis media, sinusitis and bronchiectasis, ciliary ultrastructure analysis, and microbial colonization (status of nontuberculosis mycobacterium). During the course of our study, we have acquired 98 unrelated patients in whom bronchiectasis seemed to be of unknown causes. We will be using 11 unrelated patients, 5 unrelated affected sib-pairs, and 3 affected sibs from a family from this cohort, based on 1) development of bronchiectasis in the absence of smoking, 2) a good family pedigree with available DNA, and 3) a family history of bronchiectasis and/or occurrence of airways disease in a sibling. Classic CF, PCD and immune deficiency were ruled out, based on the tests described above. Alpha-1 antiprotease deficiency work up was negative and none of the patients were tobacco users or smokers.

  Study phs000518

• Single Cell and Spatial Transcriptomics Studies of Fibrosis in Prospective Registry in IBD Study at MGH and GI Disease and Endoscopy Registry

  Stricturing disease or fibrosis is a common complication of inflammatory bowel disease (IBD), often requiring surgical intervention. This process is caused by the abnormal deposition of extracellular matrix in the context of inflammation, and thus involves crosstalk between multiple cell types including fibroblasts and immune cells. To understand the cellular interactions involved in fibrosis, we performed single cell and spatial transcriptomic analyses of biopsy or resection samples from IBD patients, diverticulitis patients or controls.For single cell analyses, intestinal samples were processed within three hours of collection by first stripping the epithelial layer with EDTA and then enzymatically digesting the underlying tissue. Cells from both the epithelial and tissue fractions were separately loaded in two channels on a 10x Chromium controller and libraries were generated with the 3'v3 Chemistry pipeline before sequencing on an Illumina sequencer. The resulting sequence data was demultiplexed and analyzed with the CellRanger pipeline to generate raw fastq files and processed gene-count matrices for each sample.For spatial transcriptomic analyses, intestinal resection samples were snap frozen in OCT (optimal cutting temperature embedding medium). Blocks were cut into 10μm sections in a cryostat and transferred to a 10x Genomics Visium slide v1. Spatially barcoded libraries were prepared according to manufacturer's instructions and sequencing on an Illumina sequencer. The resulting sequence data was processed with the SpaceRanger pipeline to generate fastq files and processed barcode-count matrices. Using the samples deposited here, we defined 68 fine-grained cell types across the ileum and colon of control and fibrotic intestinal tissues. We show that intestinal strictures were characterized by increased immune cells - including IgG+ plasma cells and CCR7hiCD4+ T cells - and inflammatory fibroblasts. We also define the transcriptional differences associated with fibrosis, with inflammatory fibroblasts in particular showing broad changes in gene expression. Spatial transcriptomics showed that key subsets colocalize within diseased tissues and identified additional populations such as interstitial cells of Cajal and enteric neurons. Further, we mapped gene expression onto intestinal biogeography, finding that known genetic risk loci are enriched within discrete spatial modules, defined by the presence of inflammatory fibroblasts and lymphoid follicles. Altogether, our datasets chart the key transcriptomic and cellular networks in stricturing CD and highlight the spatial organization of multicellular genetic risk factors.

  Study phs003943

• Breast cancer bone metastases

  Dac EGAC00001003238

• Cancer Genetics Data Access Commitee

  Dac EGAC00001001742

• Pan Cancer Plasma cfRNA DAC

  Dac EGAC00001003176

• Data Access Commitee FGFR Cancer

  Dac EGAC00001003273

• Breast Cancer Cell Line Data Access Committee

  Dac EGAC00000000015

• Leeds Cancer Genomics

  Dac EGAC00001001156

• SMC Colon cancer team

  Dac EGAC00001001277

• Breast cancer bone metastases

  Dac EGAC00001001548

• PBL Cancer Data Committee

  Dac EGAC00001001870

• bladder cancer data access commitee

  Dac EGAC00001002016

• Cancer Proteomics Mass Spectrometry group

  Dac EGAC00001002236

• OV cancer cell lines DAC

  Dac EGAC00001002307