11932 results for "cancer rna-seq"

in 15.34 milliseconds.

• Single cell RNA sequencing of colorectal cancer with diverse tissue dissociation protocols or fresh vs. frozen cell preparations.

  To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.

  Dataset EGAD00001005191

• Colorectal adenomas and carcinomas NKI-AvL TGO series Gut2009

  Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. These CRC-related genomic alterations often result in specific RNA-expression patterns. RNA isolated from fresh frozen specimen of 32 adenomas and 29 CRCs was obtained from the previously published study (Carvalho et al. 2009) and RNA-sequencing was performed with the aim to examine RNA expression changes in colorectal adenoma-to-carcinoma progression.

  Study EGAS00001002758

• Shallow nanopore RNA sequencing enables transcriptome profiling for precision cancer medicine (Hipo_021)

  Study EGAS00001006317

• Replication data for RNA-SEQUENCING: A RELIABLE TOOL TO UNVEIL TRANSCRIPTIONAL LANDSCAPE OF PAEDIATRIC B-OTHER ACUTE LYMPHOBLASTIC LEUKAEMIA

  This dataset contains the raw data of the RNA-seq experiments described in the paper "RNA-Sequencing: a reliable tool to unveil transcriptional landscape of pediatric B-other acute lymphoblastic leukemia" It contains the raw data from 60 pediatric patients diagnosed with B cell progenitor acute lymphoblastic leukemia lacking the main genetic alterations. RNA material was extracted from bone marrow or periphereal blood and RNA libraries were prepared using Illumina® TruSeq™ stranded mRNA kit following manufacturer's instructions and were sequenced in a NextSeq 550 using a v2 HighOutput 150 cycle kit 2x75bp. Funding: Instituto de Salud Carlos III (ISCIII), PI21/00213 

  Dataset EGAD50000000981

• Identification of differentially expressed protein-coding genes in HCC and adjacent non-cancerous tissues

  Twenty samples were collected in pairs, i.e., HCC tissue and adjacent non-cancerous tissue. The collected tissue samples were stored in liquid nitrogen. First, 50 mg of tissue was lysed in TRIzol (Invitrogen) to extract RNA following the manufacturer’s instructions. Next, ribosomal RNA was depleted using a RiboZero Gold kit (Epicentre Bio-technologies). RNA integrity was assessed with an Agilent Bioanalyzer 2100. An RNA-Seq library was generated with the rRNA-depleted samples using an Illumina standard RNA Sample Prep kit according to the manufacturer’s instructions. The library was subsequently sequenced on an Illumina HiSeq2500 as 125-bp paired-ends with approximately 300-bp size selection.

  Dataset EGAD00001003397

• RNA sequencing datasets from isolated human subcutaneous and visceral adipocytes from obese and lean people

  94 human adipocyte samples isolated from whole adipose tissues using collagenase digestion of tissue and flotation of lipid-laden adipocytes, followed by RNA isolation and RNA sequencing (SMARTer Stranded Total RNA-Seq library preparation, HiSeq 4000 100-bp paired-end reads). Adipocyte samples comprise subcutaneous and visceral adipocytes isolated from obese and lean people (N=24 obese-subcutaneous, N=24 obese-visceral, N=22 control-subcutaneous, N=24 control-visceral). Human adipocyte RNA sequencing data are provided as BAM files.

  Dataset EGAD00001010195

• Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

  Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

  Study EGAS00001002854

• TPM for IMpower133 (GO30081)

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from IMpower133 (GO30081).

  Dataset EGAD50000000196

• RNA-seq data of CRC-PDX tumors after drug treatment

  We obtained bulk RNAseq data of CRC-PDX tumors after administration of drug or vehicle to clarify the mechanisms of action.

  Dataset EGAD50000000849

• Convergent genetic adaptation in human tumors developed under systemic hypoxia and in populations living at high altitudes

  Genomic files, including whole-exome and RNA-seq data from tumors and cell lines, were generated and analyzed in this study.

  Dac EGAC50000000484

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Study EGAS50000000526

• Melanoma transcriptome profiling

  This dataset includes transcriptome profiling of 68 early-passage metastatic melanoma cell lines. The data are provided as paired-end RNA seq fastq files.

  Dataset EGAD00001006270

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• HDAC inhibitor quisinostat in synovial sarcoma cell lines

  An RNA Seq study of the effects of HDAC inhibitor Quisinostat on six different synovial sarcoma cell lines

  Dataset EGAD00001003810

• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

  Study phs003302

• Tumor Profiler Ovarian Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA and scDNA data of the ovarian cancer cohort.

  Study EGAS50000000885

• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• Integrated RNA-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005512

• Whole Exome and RNA-Sequencing of Germline, Small Bowel Carcinoid Primary Tumor, and Liver Metastasis Trios

  This dataset includes trios of germline/constitutional, primary tumor (small bowel carcinoid), and metastatic tumor (liver) trios for 5 patients (i.e. 15 samples total). Constitutional, primary tumor, and metastatic tumor samples all underwent whole exome sequencing (WES or WXS). Primary and metastatic tumor samples underwent RNA sequencing (RNA-seq).

  Dataset EGAD00001010036

• Healthy human B-lymphopoiesis RNA-Seq reference using FACS sorted bone marrow aspirates

  To define a transcriptomic reference of human B lymphopoiesis, bone marrow aspirates were obtained from n=4 healthy donors (study registration DRKS00023583). After immunodensity cell separation, samples were FACS-sorted into 7 established lymphopoietic differentiation stages. RNA was extracted from 5,000-320,000 cells per differentiation stage and subjected to ultra-low-input RNA sequencing after generation of stranded sequencing libraries.

  Dataset EGAD00001010917

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  This dataset contains paired-end fastq files for single-cell RNA-seq of 16 NPM1 mutated AML patients. 19 fastq pairs are included, with two samples split into two lanes and a second (technical) replicate for one patient. Libraries were constructed using 10x Genomics Chromium Next GEM Single cell 3’ v3.1 and sequencing was performed using Illumina NovaSeq6000.

  Dataset EGAD50000000478

• RNA-Seq profiles from the CheckMate-649 Clinical Trial

  This dataset contains RNA sequencing (RNAseq) data of 814 patients from the CheckMate 649 clinical trial whose ICF allows data deposition into a public repository. Gene expression profiling was performed retrospectively using RNAseq on a subset of baseline tumor samples. Paired-end FASTQ files were processed on Seven Bridges platform (Seven Bridges Genomics).

  Dataset EGAD50000001105

• Characterizing Immune Profiles in Extrapulmonary Tuberculosis via RNA Sequencing

  This dataset provides insight into the immune response in extrapulmonary tuberculosis (EPTB), using bulk RNA-seq data to analyze different disease severities. Hierarchical clustering identified three distinct levels of severity, revealing disease progression driven by interferon and IL-1β-mediated signaling. Additionally, the dataset helped develop a diagnostic gene expression signature for both EPTB and pulmonary TB.

  Dataset EGAD50000000943