11979 results for "cancer rna-seq"

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• 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

• 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

• De novo modeling of chromoplectic Ewing sarcoma tumors from patient-derived mesenchymal stem cells

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic (RNA-seq) and epigenetic (ChIP-seq) hallmarks of EwS.

  Dataset EGAD50000001673

• Whole scRNA-seq from pre frontal cortex patient biopsy

  The single- cell RNA-seq prefrontal cortex sample was selected from a cohort of patients with hydrocephalus ≥18 years of age planning to undergo CSF diversion surgery either with a ventriculoperitoneal shunt placement (VP) or ventriculocisternostomy (VCS). The tissue was dissociated followed by red cell and debris removal and counting of the cells to be sequenced with (scRNA-seq; 10x Genomics kit v2). After dissociation only non neuronal cells were retrieved.

  Dataset EGAD50000001542

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226

• Citrate synthase novel variant rewires TCA cycle to promote colorectal cancer progression

  H3K4me3, IgG, and Input ChIP-seq in overexpression of pLV Control, CS-FL and CS-ΔEx4 in SW1116 cells

  Dataset EGAD00001015543

• Transcriptomic 90 patient cohort data

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

  Dataset EGAD00001009042

• Expressed fusion transcripts in rare bone tumours

  mRNA-Seq on total RNA from primary osteoblastomas and phosphaturic mesenchymal tumours, focussing on fusion transcript expression

  Dataset EGAD00001000990

• 1_fibroblasts_HD_vs_Ctrl_DMSO_Branaplam

  n=4 Ctrl and n=4 HD fibroblasts lines were treated with DMSO or 10nM Branaplam for 72h and RNA-seq was performed.

  Dataset EGAD00001008807

• 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

• 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

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• G&T-seq: parallel sequencing of the genomes and transcriptomes of single cells

  The ability to simultaneously sequence the genome and transcriptome of the same single cell offersa powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describeG&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from singlecells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot beinferred from DNA or RNA sequencing alone, including associations between DNA copy numbervariation and gene expression dosage. We further demonstrate the detection of coding interchromosomalfusions and single nucleotide variants in both the genomes and transcriptomes ofindividual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, andthe investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferredcell types and states.

  Study EGAS00001001204

• 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

• 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

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006088

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006122

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001005827

• 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

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts

  RNA-sequencing was carried out on ascetic fluid-isolated mesothelial cells from low-grade serous ovarian cancer patients, high-grade serous ovarian cancer patients, chemotherapy-treated high-grade serous ovarian cancer patients and control mesothelial cells obtained from non-oncologic patients to identify differentially expressed genes associated to mesothelial-to-mesenchymal transition process.

  Study EGAS00001003747

• clonealign: 10X genomics chromium single-cell RNA-sequencing

  10X genomics chromium single-cell RNA-sequencing of (i) patient derived triple negative breast cancer xenograft (ii) primary tumour and ascites ovarian cancer cell lines at tumour recurrence.

  Dataset EGAD00001004552

• RNA sequencing of Notch inhibitor treated HCC PDX models across timepoints

  To study the effect of Notch inhibition on the transcriptional profiles our PDX models, we generated bulk RNA-seq data for two Notch inhibition sensitive and three Notch inhibition insensitive models across multiple timepoints (8h, 24h, 48h, 7d, 17d) using anti-JAG1, anti-Notch2, anti-Notch1 or anti-gD antibodies. 3-5 samples were collected for each treatment condition, resulting in a total of 96 samples. Isolated RNA was used as input for library preparation using TruSeq RNA Sample Preparation Kit v2 (Illumina). The libraries were multiplexed and sequenced on Illumina HiSeq 2500 (Illumina) to produce FASTQ files.

  Dataset EGAD50000000737