11754 results for "cancer rna-seq"

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• Molecular landscape of blastic plasmacytoid dendritic cell neoplasm

  Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is an aggressive malignancy assumed to originate from plasmacytoid dendritic cells (pDCs), which mostly affects the skin, bone marrow and lymph nodes and sequentially other organ systems. We applied paired WES/RNA-seq combined with genome-wide copy-number analysis to characterize 47 BPDCN patients regarding mutational drivers, cytogenetic aberrations and gene-expression profiles.

  Study EGAS00001006166

• Genetic regulation of gene expression in human brain cell types

  We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

  Study EGAS00001006345

• A brain precursor atlas reveals the acquisition of developmental-like states in adult cerebral tumours

  We generated a single-cell RNA-seq atlas capturing over 100,000 cells spanning all stages of the mouse cerebral development. By examining data from over 100 cerebral tumour samples, our study reveals that, despite the phenotypic/genotypic differences between the tumour types, they are all comprised of developmental sublineages that map most closely to embryonic or juvenile stages of development.

  Study EGAS00001006237

• Whole Genome, RNA, and ChIP Sequencing of matched brain tumor-normal pairs (ICGC)

  Whole Genome Seq: Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009);duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Paired-end RNA sequencing reads were mapped to the hg19 assembly of the human reference genome using BWA.Each ChIP-seq library was sequenced with two complete lanes on the Illumina HiSeq 2500 in the 101-bases paired-end rapid mode and aligned to hg19 using bwa.This resulted in the following coverage values (genome-wide, after deduplication, including all uniquely mapping reads):GBM103 macroH2A1: 17x H3K36me3: 20xMB59 macroH2A1: 11x H3K36me3: 11x

  Dataset EGAD00001000664

• RNA sequencing in primary inflammatory (TPP) macrophages treated with a MEK1/2 inhibitor

  This dataset comprises raw RNA sequencing from inflammatory (TPP) macrophages that were treated with the MEK inhibitor PD-0325901 (100nM or 500nM) or vehicle control (n=3 donors). MEK inhibitor or vehicle control was added on day 4 and cells were harvested on day 6 and lysed. RNA was extracted from cell lysates using an AllPrep DNA/RNA Mini Kit (Qiagen). Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NextSeq500. Raw data are provided as 50 bp paired-end Illumina reads.

  Dataset EGAD00001011337

• Oesophageal_Adenocarcinoma_Organoids_Iso_Seq

  RNA Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio RNA data will be combined with other sequencing data in order to generate accurate reference cancer genomes and study how structural variants affect gene expression

  Study EGAS00001004051

• Processed miRNA Counts for the miRNA Profiling from Indian HFrEF Cohort Dataset

  This dataset contains processed miRNA count data for the 49 Heart Failure samples profiled by miRNAseq for the Indian HFrEF Cohort from the study Integrated Transcriptomic and Regulatory RNA Profiling Reflects Complex Pathophysiology and Uncovers a Conserved Gene Signature in End Stage Heart Failure RNA-Seq data.

  Dataset EGAD50000001195

• APP p.V742L and control fibroblasts RNA-seq

  This dataset consists of 16 FASTQ file pairs containing 3` RNA-sequencing data of patient-derived fibroblasts and three age- and sex-matched control fibroblast lines (CTR1, CTR2, and CTR3). The patient and CTR1 fibroblast lines have three biological replicates, while CTR2 and CTR3 lines both have one sample. Each sample has two lanes.

  Dataset EGAD50000001825

• Single-cell RNA-seq of AML blasts pre and post culture

  This dataset contains 6 Fastq files from 3 samples (pre-culture (n=1), post culture in standard (n=1) or niche-llike (n=1) conditions) from 1 AML patient. They correspond to single-cell RNA sequencing on Illumina plateform of 3 libraries prepared with 10X Genomics gene expression V3.1 chemistry.

  Dataset EGAD00001008772

• Paired RNA-Seq data from 17 samples of different tumors

  Paired RNA sequencing data (21 runs/ 17 samples) of different tumors. The samples were prepared using the Illumina TruSeq stranded mRNA Kit. The sequencing was done on Illumina HiSeq 4000.

  Dataset EGAD00001009706

• RNA-seq data from 9 patients with peri-implantitis

  Fastq files + patients' characteristics

  Dataset EGAD50000000544

• 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

  Dataset EGAD50000000747

• RNA-Seq of SMARCB1 re-expression and HDAC+mTOR inhibition experiments in malignant rhabdoid tumor organoids

  Dataset EGAD00001006574

• University of Michigan ALS Biorepository

  We are collaborators at the University of Michigan (Ann Arbor, MI) studying amyotrophic lateral sclerosis (ALS), employing sequencing-based approaches (e.g. bulk RNA-seq of whole blood) in case-control studies.

  Dac EGAC50000000598

• RNASEQ_TALL_t_14_16_translocation

  RNA-seq results of sequenced data of patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001781

• Transcriptomic 90 patient cohort data

  This dataset includes RNA-seq data of samples from our paper.

  Dataset EGAD00001009042

• MSAT dataset

  Muscle SATellite cell study (MSAT) dataset comprises 39 samples of paired-end RNA-Seq sequences in fastq format.

  Dataset EGAD00001008984

• Whole transcriptome and whole exome sequencing of BPDCN patients

  Here, seven patients with BPDCN were characterized using RNA-seq and WXS.

  Dataset EGAD00001010314

• Biomarker data

  Biomarker data for KATHERINE: Biomarker data include RNA-seq time point, Percent of tumor content, PAM50 subtypes, normalized gene expression of ERBB2, CD8 and CD274, normalized immune signature expression.

  Dataset EGAD00001008786

• A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors

  Except for a few genes known to have oncogenic spliceforms in gastric cancer, the full scope of aberrant splicing in gastric oncogenesis remains unclear. In this study, we elucidated the alternative splicing events associated with gastric carcinogenesis and identified upstream regulators governing these events. We performed RNA-seq on 19 matched tumor/normal pairs and a panel of gastric cancer cell lines, and identified 361 tumor associated (TA) alternative splicing events (ASEs), which included known oncogenic ASEs in genes such as INSR, FGFR2, CD44 and KRAS. We further identified 8 splicing factors dysregulated in gastric tumors, the expression of which are correlated to the splice ratio of the TA ASEs. We thereby constructed a dysregulated splicing network in gastric cancer, consisting of alternative splicing changes correlated to their potential regulators. This network featured three potential regulatory modules centered around the splicing factors ESRP2, MBNL1 and PTPB1. Knockdown of each splicing factor led to the expected changes in splicing of approximately half of the ASEs assayed. Thus, dysregulation of the splicing factors indeed was the cause of many of the TA ASEs. Pathway enrichment analysis showed that genes affected by tumor associated splicing were pre-dominantly involved in cytoskeletal organization. Concordant with this, knockdown of the splicing factors regulating the TA ASEs led to the expected changes in trans-well migration activity. Thus, we have established for the first time a comprehensive splicing network that likely drives gastric tumor progression, based on which novel therapeutic targets can be identified for further evaluation.

  Study EGAS00001002256

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program - Neuroblastoma

  The goal of NCI's Pediatric In Vivo Testing Consortium (PIVOT) is to advance the development of effective treatments for pediatric cancers through preclinical in vivo testing of novel therapeutic agents. To design impactful experiments that can be rapidly translated to the clinic, PIVOT investigators require comprehensive genomic characterization of the patient-derived xenograft (PDX) models used across the consortium. This robust experimental design enhances collaboration with industry partners by providing proof-of-concept data for drugs in development. As part of this effort, neuroblastoma PDX models are being molecularly characterized to identify promising therapeutic candidates. The molecular profiling includes whole exome sequencing (WES), RNA-seq, MethylEPIC array, CytoSNP array, and DNA fingerprinting for quality control. Additionally, demographic and clinical data (e.g., diagnosis, disease site, disease status) are shared. These characterized PDX models, matched with patient tumors, guide model selection for preclinical drug testing.

  Study phs003163

• Single cell RNAseq of PBMC from bladder cancer patients

  Frozen PBMC samples containing at least 1 million cells were thawed for 1 minute at 37C and washed twice with RPMI complete media (10% FBS with glutamate and Pen/Strep). All of the samples had >80% viable cells. Sample processing for single-cell RNA-seq was done using Chromium Single Cell 3’ Library and Gel bead kit v2 (PN-120237) following manufacturer’s user guide (CG00052, 10x Genomics, Pleasanton, CA). The total cell density was used to impute the volume of single cell suspension needed in the reverse transcription (RT) master mix, aiming to achieve ~ 6,000 cells per sample. cDNAs and libraries were prepared following manufacturer’s user guide (10x Genomics). cDNA amplification and indexed libraries were prepared using 12 and 14 cycles of PCR, respectively. Libraries were profiled, quantified, and sequenced as 5’ single-cell gene expression libraries.

  Study EGAS00001004008

• Breast_cancer_topographs

  Breast cancer topography will be explored using a combination of multi-region whole geome sequencing and in-situ RNA sequencing of fixed tissue specimens.

  Study EGAS00001003698

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Study EGAS50000000741

• 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