10175 results for "cancer rna-seq"

in 33.98 milliseconds.

• Breast cancer sequencing data

  Dac EGAC00001003293

• EAC Genomic data

  Study EGAS00001004887

• Pearl study

  Study EGAS00001005523

• SMC Breast Cancer DAC

  Dac EGAC00001002381

• National Cancer Center Singapore

  Dac EGAC00001001550

• Radboudumc Cancer Genomics DAC

  Dac EGAC00001001102

• Charbonneau Cancer Institute DAC

  Dac EGAC00001001165

• Charbonneau Cancer Institute DAC

  Dac EGAC00001001280

• Cancer Data Access Commitee

  Dac EGAC00001001436

• DAC Barretos Cancer Hospital

  Dac EGAC00001001592

• Spatial Characterization Breast Cancer

  Dac EGAC00001001673

• Gene expression and Cancer

  Dac EGAC00001001727

• Charbonneau Cancer Institute DAC

  Dac EGAC00001002096

• Breast cancer bone metastases

  Dac EGAC00001002771

• Breast cancer bone metastases

  Dac EGAC00001002772

• DAC Synergie Lyon Cancer

  Dac EGAC00001002795

• Breast cancer bone metastases

  Dac EGAC00001003035

• DAC - Pediatric Solid Cancer

  Dac EGAC00001003088

• Cancer Team Data Access Committee

  Dac EGAC00001003407

• Leukemia sequencing study

  Study EGAS00001006901

• Sequencing of Ovarian Cancer

  Study EGAS00001007489

• Sequencing of Breast Cancer

  Study EGAS00001007490

• DAC Barretos Cancer Hospital

  Dac EGAC50000000013

• ATAC-Seq of CD4 T cell subsets

  Blood samples were taken from 4 age-matched healthy volunteers (two males and two females), and naïve CD4 T cells were isolated using the naïve CD4+ T Cell Isolation Kit II, human (Miltenyi Biotec). Two hundred thousand cells were plated in a 96-well plate, activated with Dynabeads Human T-activator CD3/CD28 (bead-to-cell ratio of 1:1, as recommended by the manufacturer) (ThermoFisher Scientific) and polarized towards CD4 T cell subtypes (Teff, Th1, Th2, rTh17, pTh17, and Treg cells) with specific cocktails of recombinant cytokines and neutralizing antibodies (see details in the material and methods) for each subset. At day 4 post-stimulation, forty thousand cells were used to perform ATAC-Seq on CD4 T cell subtypes. Again, crude nuclei of live CD4+ T cell subsets were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007345

• Identification of the mutational consequences of precancerous liver disease (including alcohol abuse) on the genomes of human adult stem cells.

  Stem cells are believed to be the cells-of-origin cancer. Nevertheless, their genome remains remarkably stable during life. To increase insight into how these cells can drive tumorigenesis, we set out to determine the genomic integrity of human adult stem cells from patients with liver disease associated with increased cancer risk. To this end, we characterized genome-wide mutation profiles of single ASCs from livers of patients with alcoholic liver disease, non-alcoholic liver disease and primary sclerosing cholangitis. The patients included in our study received a liver transplant due to their liver disease. Strikingly, we found that ASCs in these livers maintain a stable genome and have comparable mutation rates as healthy human liver ASCs. We did observe more nonsense and nonsynonymous mutations in COSMIC cancer genes that are hit by dominant mutations in tumors in comparison to healthy ASCs (n.s.), including two ASCs in alcoholic liver disease patients with a nonsense mutation in PTPRK. Next, we sequenced 5 biopsies of an alcoholic tumour to identify the mutational patterns in the tumour-initiating ASC. We found that the mutational patterns are, again, similar to healthy liver, but the mutational load is slightly higher. This suggests that the increased cancer risk in the liver disease patients is not caused by an increased mutational load, but rather that the precancerous liver environment promotes outgrowth of cells that would normally be selected against.

  Study EGAS00001002983