11765 results for "cancer rna-seq"

in 10.34 milliseconds.

• RNA-Seq of clonal endocrine therapy resistant cell lines

  Study EGAS00001007123

• H005 RNA-seq CLL

  Paired-end RNA sequencing using total RNA from 136 primary lymphoma samples. Sequencing was performed on the Illumina HiSeq2000 with 300bp insert size. The dataset contains FASTQ files.

  Dataset EGAD00001002056

• RNA-Seq Single End

  RNA analysis of six patients 34, 35, 36, 37, 38 and 39 with WGS done on Illumina HiSeq2500. For research purpose and authorised user only.

  Dataset EGAD00001003430

• Microbiome-Host Interactions in Oral Squamous Cell Carcinoma: a Metatranscriptomic Exploratory Study

  Oral cancer (predominantly squamous cell carcinoma; OSCC) is the 14th most prevalent malignancy worldwide, accounting for more than 300,000 new cases and 145,000 deaths annually. Despite advances in cancer treatment modalities, OSCC continues to have poor prognosis with 5-year survival rates less than 50%. Although use of tobacco and alcohol consumption constitute the major risk factors, there is emerging evidence for the role of the microbiome in OSCC. However, studies on the association between the microbiome and OSCC has so far focused on compositional analysis and has been largely limited to the bacterial component of the microbiome. The aim of this study is to characterize the transcriptional activity (function) as well as composition of the multi-kingdom microbiome associated with OSCC and correlate it with the gene expression of the host using ultra-deep metatranscriptome sequencing, which will provide new insight into the role of the microbiome in OSCC and the possible mechanisms by which the tumor’s microbial community may influence on its behavior. This project comprises RNA-Seq data from twenty OSCC tumor/normal tissue pairs and twenty tongue scraping samples from healthy controls. However, due to consent constraints, the human sequences from the control data are filtered out.

  Study phs002678

• Circulating RNAs prior to endometrial cancer diagnosis

  We analyzed circulating RNA levels using small RNA sequencing, targeting RNA in the size range 17 to 47 nucleotides, in samples collected prior to endometrial cancer diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to diagnosis , and 316 matched controls, both from the Janus Serum Bank Cohort in Norway.

  Study EGAS50000000267

• Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics

  10 single-cell placental RNA libraries were generated using the Chromium Single Cell 3′ Reagent Kit (10X Genomics). All single-cell libraries were sequenced with a customized paired end with dual indexing (98/14/8/10-bp) format according to the recommendation by 10X Genomics. The data were aligned using the Cell Ranger Single-Cell Software Suite (version 1.0). Moreover, plasma RNA from 22 samples were extracted using the RNeasy Mini Kit (Qiagen). cDNA reverse transcription, second-strand synthesis, and RNA-sequencing (RNA-seq) library construction were performed using the Ovation RNA-seq System V2 (NuGEN) kit according to the manufacturer’s protocol. For alignment of the plasma RNA library, adaptor sequences and low-quality bases on the fragment ends (i.e., quality score < 5) were trimmed, and reads were aligned to the human reference genome (hg19) using the TopHat (v2.0.4) software. All aligned reads were deposited in bam file format.

  Dataset EGAD00001003705

• Colorectal cancer functional annotation - ChIP

  ChIP-seq data for multiple colorectal cancer cell lines (H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, CTCF)

  Study EGAS50000000207

• RNA-seq of PDAC patient-derived xenograft tumors

  Study EGAS00001007070

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000640

• Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

  We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001998