14982 results for "cancer studies using rna-seq"

in 18.34 milliseconds.

• TCR β-chain repertoire characterization of regulatory and conventional T cells in breast tumors from breast cancer patients.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001004671

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055

• TCR β-chain repertoire characterization of regulatory and conventional T cells in peripheral blood from breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001002699

• CAGEKID: Cancer Genomics of the Kidney - Targeted Sequencing

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001007004

• LLDeep DAG2+ scRNA-seq in PBMCs

  Single cell transcriptomics of PBMCs of 47 donors from the Lifelines Deep cohort (general population, Northern part of the Netherlands). Cells of five or six different donors were pooled together in one sample pool, resulting in eight different sample pools. In total, 28.855 cells were captured and their transcriptomes were sequenced to an average depth of 74k. Genotype data was available for each donor, which allowed us to use the Demuxlet method that uses variable SNPs between the pooled individuals to determine which cell belongs to which individual. Since genotype information is lacking of 2 individuals, the transcriptome of only 45 individuals could be retrieved.

  Dataset EGAD00010001315

• Single-cell multi-omics analysis of COVID-19 patients with pre-existing autoimmune diseases

  Single-cell analysis of the transcriptome, T cell immune receptors, and surface proteome (CITE-seq) from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with pre-existing autoimmune diseases (rheumatoid arthritis n = 5, psoriasis n = 4, or multiple sclerosis n = 3), as well as COVID-19 patients without pre-existing autoimmunity as controls (n = 10) to investigate altered immune responses.

  Dataset EGAD00001007982

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006796

• Single-cell T-cell receptor sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell T-cell receptor sequencing (scTCR-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007014

• Whole-genome plasma DNA sequencing in CRC patients under anti-EGFR therapy

  In this study we performed whole genome sequencing of plasma DNA (plasma-Seq) of 19 plasma-DNA samples from a total of 10 patients treated with anti-EGFR therapy. We demonstrated that development of resistance to anti-EGFR therapies is frequently associated with focal amplifications of KRAS, MET, and ERBB2. We also showed that focal KRAS amplifications can be acquired in tumor genomes of patients under cytotoxic chemotherapy. Furthermore, we provide evidence that specific chromosomal polysomies, such as overrepresentations of 12p and 7p, harboring KRAS and EGFR, respectively, determine responsiveness to anti-EGFR therapy.

  Dataset EGAD00001000748

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006797

• Single Cell RNASeq for ARMS tumors

  6 samples from 3 mice related to Alveolar Rhabdomysarcoma. In this study, we employ scRNA-seq to analyze ARMS tumors from a conditional mouse model of ARMS. The conditional knock-in mouse model of ARMS, in which the Pax3-Foxo1 allele is activated in the skeletal muscle cell lineage via Myf6Cre (Myf6CrePax3P3Fm/P3FmTrp53F2-10/F2-10; referred to hereafter as GEMM-ARMS) has been described previously23,24. These mice also carry Cre-activated reporters, eYFP to label Pax3::Foxo1-expressing cells and dsRED2 to labels Myh2-expressing cells. Some tumors are derived from GEMM-ARMS mice, and some are allografts of GEMM-ARMS tumors into immunodeficient mice

  Dataset EGAD50000002241

• ATAC-seq of uncultured CD112high and CD112low long-term(LT) human hematopoietic stem cells (HSC) from umbilical cord blood

  ATAC-sequencing was performed to establish chromatin accessibility signatures that underlie the differential in vitro priming and regeneration phenotypes of CD112high and CD112low LT-HSC. CD112high and CD112low LT-HSC from 2-3 independent human umbilical cord blood pools were prospectively isolated for DNA extraction, library preparation and sequencing.

  Study EGAS00001005121

• scRNA-seq to study interactions between HSPCs, BMSCs and immune microenvironment

  Mechanisms of clonal evolution in myeloid neoplasms remain incompletely understood. Darwinian theory predicts that the (micro)environment of clone-propagating stem cells may contribute to clonal selection. Here, we provide data fitting this model, establishing a relationship between stromal niche inflammation, inflammatory stress in HSPCs, clonal resistance and leukemic evolution in human MDS.

  Study EGAS00001008181

• The tissue origin of highly elevated cell-free DNA in patients with and without cancer

  Forty years ago, the first measurements of cell free DNA (cfDNA) from cancer patients revealed that its total concentration was often elevated compared to healthy controls. The basis for this increase, and in particular the source of the extra cfDNA in such patients, has never been determined. To address this issue, we assessed methylation patterns of cfDNA from 57 individuals, 34 of whom had unequivocally elevated cfDNA concentrations (i.e., >15 ng/mL of plasma). We found that the excess cfDNA in cancer patients did not come from either neoplastic cells or surrounding cells from the tumor's tissue of origin. Instead, 80% of the cfDNA was derived from neutrophils, B cells or T cells, with neutrophils accounting for ~2/3. B cells contributed more than T cells despite the great excess of T cells over B cells in the blood. To see if this result was generalizable to other clinical situations in which elevated cfDNA concentrations have been described, we evaluated nine patients before and one day following surgery. After surgical resection, cfDNA concentration increased by an average of 16.1-fold, as expected. The majority of this increase (55%) was contributed by leukocytes, though damaged hepatocytes contributed a substantial minority (31% of increase). These data suggest that the elevated concentrations of cfDNA in cancer patients, as with patients after surgery, arises largely from dying leukocytes—not from the neoplastic cells or the tissue of origin of the cancer.

  Study EGAS00001005400