12056 results for "cancer rna-seq"

in 14.70 milliseconds.

• 112 "KOREAN" never-smoker female adenocarcinoma exome-seq

  All sequencing was performed within the DNAlink (Korea) by using the Solexa sequencing technology (Illumina, San Diego, CA). 1 ug of genomic DNA was sheared to an average size of 150 bp by using the Covaris System. The libraries were prepared by using TruSeq DNA Sample Prep Kit (Illumina). The purified DNA library was hybridized with the SureSelect Human All Exon V3 probe set (Agilent Technologies) to capture 50 Mb of targeted exons following the manufacturer’s instructions. Exome capture was carried out using the Agilent SureSelect Human All Exon 50Mb Kit. The captured exome libraries were sequenced on the Illumina HiSeq2000 using the manufacturer’s recommended protocols.

  Dataset EGAD00001005126

• 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

• 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

• 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

• Targeted NGS panel

  The mutational status of 121 genes recurrently altered in B-cell lymphoma was examined in 55 of 56 diagnostic and 10 of 12 relapse samples using a custom targeted NGS panel. Libraries were generated from 150 ng of DNA using molecular-barcoded library adapters (ThruPLEX Tag- seq kit; Takara) coupled with a custom hybridization capture-based method (SureSelectXT Target Enrichment System Capture strategy, Agilent Technologies). The quality of the libraries was determined using the Bioanalyzer high sensitivity DNA kit (Agilent) and quantified by PCR using the KAPA library quantification kit (KAPA Biosystems). Finally, the libraries were pooled and sequenced in the MiSeq instrument (Illumina).

  Dataset EGAD00001010842

• 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

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• CNA differences between RNA-based subtypes of PDAC

  Pancreatic ductal adenocarcinomas (PDAC) have a dismal prognosis with a 5-year survival of <5%. Chemoresistance and recurrences, seen in approximately 70% of PDAC patients, may partly be explained by intratumor heterogeneity (ITH) through which tumors may develop ‘escape routes’. In the Pancreas Multibiopsy (PM)-project we have obtained multiple fragments from pancreatic and other peri-ampullary carcinomas in order to reveal potential ITH and identify genetic aberrations that predict outcome after surgery and response to chemotherapy. CNA-profiles were used to complement the characterization of liabilities in PDAC that we identified previously using RNAseq in the form of epithelial, secretory, compound pancreatic, and mesenchymal subgroups that showed survival outcomes. Comparison of CNA-profiles between these transcriptomics-based subgroups (with 8, 3, 6, and 6 tumors respectively per group) showed differences, ranging from ‘quiet’(i.e. hardly any CNA) to ‘wild’(i.e. lots of CNA), but these were not statistically significant (Chi2 0.09). When differentiating between the classical and basal-like molecular subtypes of PDAC differences in CNA (high or low) were even less statistically significant (Chi2 0.292).

  Study EGAS50000001218