9296 results for "cancer rna-seq"

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• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004607

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004679

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004681

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004682

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004689

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004674

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004659

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004715

• Genome and transcriptome sequence data from a metastatic pancreatic cancer patient

  Genome and transcriptome sequence data from a metastatic pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004718

• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient

  Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002567

• Genome and transcriptome sequence data from a primary unknown cancer patient

  Genome and transcriptome sequence data from a primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002569

• Genome and transcriptome sequence data from a serous endometrial cancer patient

  Genome and transcriptome sequence data from a serous endometrial cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002631

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002637

• Genome and transcriptome sequence data from a metastatic prostate cancer patient

  Genome and transcriptome sequence data from a metastatic prostate cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002638

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002639

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002643

• Genome and transcriptome sequence data from a metastatic rectal cancer patient

  Genome and transcriptome sequence data from a metastatic rectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002618

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005834

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Dataset EGAD00001005420

• HPS1 patient monocyte-derived macrophage and control macrophage RNAseq with and without infection

  4 HPS1 patient monocyte-derived macrophages and 4 controls were RNA sequenced at baseline and after Salmonella Typhimurium infection. We used paired end sequencing on an Illumina HiSeq 4000. Each sample was run on 3 lanes for sequencing depth, which we combined for our analysis.

  Dataset EGAD00001006978

• RNAseq in ASD patients and controls

  RNA sequences of a total of 24 samples, including 13 unrelated ASD patients (13 males) and 11 adult individuals of Spanish origin as controls (4 males, 7 females). The RNAseq study was conducted on a HiSeq 4000 (Illumina) and paired-end sequences were obtained (fastq files).

  Dataset EGAD00001008160

• DIPG MEK inhibition RNASeq

  RNA sequencing of Diffuse intrinsic pontine gliomas, primary patient derived DIPG cell cultures and isogenic trametinib resistant clones

  Dataset EGAD00001008212

• WGS data for 67 patient cohort

  This dataset includes WGS data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008647

• Somatic cancer gene mutation screening

  Sequencing of colorectal tumors and normal tissue using Ion AmpliSeq Cancer Hotspot Panel V2

  Dataset EGAD00001001010

• Premalignant SOX2 in ovarian cancer patients

  Whole Genome Sequencing data set for the study "Premalignant SOX2 in ovarian cancer patients"

  Dataset EGAD00001002734

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• Single cell epigenomic study of H3-K27M mutant diffuse midline glioma across age and location

  Histone 3 lysine27-to-methionine (H3-K27M) mutations most frequently occur in childhood diffuse midline gliomas (DMGs) of the pons, but are also increasingly recognized in adult DMGs. Their potential heterogeneity at different ages and midline locations are vastly understudied. Here, through dissecting the single-cell epigenomic architectures of a comprehensive cohort of patient H3-K27M DMGs, we delineate how age and anatomical location shape glioma cell-intrinsic and -extrinsic features in light of the shared driver mutation. We analyzed the open chromatin profiles of 8 tumors utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Study EGAS00001007035

• sn-RNAseq profiling of the impact of a cytokine storm model in human cardiac organoids

  We developed conditions to model conditions of diastolic dysfunction caused by inflammatory factors in human cardiac organoids. Our organoid model is based on conditions promoting maturation (Mills et al., PNAS, 2017 and Voges et al., In Revision) and incorporating human pluripotent stem cell derived cardiomyocytes, epicardial cells, fibroblasts, endothelial cells and pericytes. Following 15 days of differentiation (Voges et al., Development, 2017) we formed human cardiac organoids incorporating both our multicellular differentiation (Mills et al., PNAS, 2017) and additional endothelial cells (Voges et al., In Revision). After another 12 days of maturation in 5 days maturation medium and 5 days weaning medium (Voges et al., In Revision) human cardiac organoids were either treated with weaning medium or “cardiac cytokine storm” comprised of 100 ng/ml IFNg, 10 ng/ml IL-1 β and 10 µg/ml poly(I:C). After 48 hours human cardiac organoids were harvested and snap frozen in -80C before nuclei isolation and single nuclei RNA sequencing.Pooled hCO (~40) were homogenized in 4 mL lysis buffer (300 mM sucrose, 10 mM Tris-HCl (pH = 8), 5 mM CaCl2, 5 mM magnesium acetate, 2 mM EDTA, 0.5 mM EGTA, 1 mM DTT)(all Sigma-Aldrich) with 30 strokes of a dounce tissue grinder (Wheaton). Large pieces of hCO were allowed to settle and homogenate was passed through pre-wetted 40 µm cell strainers (Becton Dickinson). Remaining hCO material in the douncer was resuspended in 4 mL and the douncing and filtering steps were repeated twice. All steps of the homogenization were performed on ice. The filtered homogenate was centrifuged at 1500 x g for 5 min at 4oC. Nuclei pellets were then re-suspended in PBS. A fraction of resuspended nuclei were then stained with hoechst nuclear stain (1:500 dilution) and counted on a haemocytometer under fluorescent microscope.The nuclei were then re-centrifuged (1500 x g for 5 min at 4°C) and resuspended at a density to load ~5,000 nuclei per sample. Cell were loaded into the Chromium Controller (10X Genomics) for gel bead emulsion (GEM) formation. Library preparation was conducted according to the manufacturer’s recommended protocol using the Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit v3.1. Libraries were sequenced on the NextSeq 500/550 v2 (Illumina) with 150 bp reads.In the snRNA-seq we note the lower than expected percentage of non-myocytes and the loss of endothelial cells (Mills et al., PNAS, 2017 and Voges et al., In Revision), indicating the protocol requires further optimization for hCO samples.

  Study EGAS00001005174

• Human breast transcriptome analysis

  Obesity is a risk factor for the development of post-menopausal breast cancer and is associated with a worse breast cancer prognosis. Here we carried out transcriptome profiling on nontumorous breast tissue to define the molecular changes that occur related to excess body fat and adipose inflammation. A second goal was to determine if blood biomarkers reflect molecular changes in the breast. Increases in a variety of pathways linked to tumor development and progression were found. Moreover, increased expression of several drug targets including aromatase, the rate-limiting enzyme for estrogen biosynthesis, and PD-1 was observed. Various blood biomarkers that are associated with either elevated risk of breast cancer or worse prognosis were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.

  Study EGAS00001004665

• Cancer and germline exomes consisting of FASTQ paired-end reads from melanoma and lung cancer samples

  Efforts to precisely identify tumor human leukocyte antigen presented peptides (HLAp) capable of mediating T cell based tumor rejection still face important challenges. Recent reports suggest that non-canonical cancer HLAp could be immunogenic but their identification requires highly sensitive and accurate mass-spectrometry (MS)-based proteogenomics approaches. Here, we present a MS-based analytical pipeline that can precisely characterize the non-canonical HLAp repertoire, incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLAp. Albeit often at low levels and in distinct subpopulations of cells, numerous non-canonical HLAp are shared across tumors. This analytical platform holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.

  Study EGAS00001003723

• National Human Genome Research Institute Tumor Sequencing Project (TSP) - Lung Adenocarcinoma

  The Tumor Sequencing Project (TSP) Consortium is a collaboration among participants at the Baylor College of Medicine Human Genome Sequencing Center, the Broad Institute Genome Sequencing Platform, the Dana Farber Cancer Institute, the Memorial Sloan-Kettering Cancer Center, the Genome Sequencing Center and Siteman Cancer Center at Washington University, the M.D. Anderson Cancer Center and the University of Michigan Medical Center. The TSP Part A will pilot approaches to large-scale identification of genomic changes in tumors by sequencing the exonic regions of 623 genes in 188 specimens of adenocarcinoma of the lung, as well as using high density SNP genotyping arrays for high resolution identification of changes in chromosomal copy number. The TSP Part B will pilot approaches to tumor characterization of lung adenocarcinoma samples using next-generation sequencing technologies and benchmark those results against Part A data generated with ABI3730 instruments.

  Study phs000144

• Glioma International Case Control Study (GICC)

  The main goals of the GICC Study were: 1) to identify novel genetic risk variants for glioma, as well as validate variants implicated by previous genome-wide association studies of glioma; and 2) to explore biologically relevant gene-gene and gene-environment interactions in glioma susceptibility. The GICC Study includes participants from the following centers: Brigham and Women's Hospital (Boston, Massachusetts), Case Western Reserve University (Cleveland, Ohio), Columbia University (New York, New York), the Danish Cancer Society Research Centre (Copenhagen, Denmark), Duke University (Durham, North Carolina), the University of Texas MD Anderson Cancer Center (Houston, Texas), Memorial Sloan Kettering Cancer Center (New York, New York), the Mayo Clinic (Rochester, Minnesota), NorthShore HealthSystem (Chicago, Illinois), Umea University (Umea, Sweden), the University of California, San Francisco (San Francisco, California), the University of Southern California (Los Angeles, California), and the Institute of Cancer Research (London, United Kingdom).

  Study phs001319

• Methylation Profiles of Cell-Free DNA Using Nanopore Sequencing

  Epigenetic characterization of cell-free DNA (cfDNA) is an emerging approach for detecting and characterizing diseases such as cancer. We developed a strategy using nanopore-based single-molecule sequencing to measure cfDNA methylomes. This approach generated up to hundreds of millions of reads for a single cfDNA sample from cancer patients, an order of magnitude improvement over existing nanopore sequencing methods. We developed a single-molecule classifier to determine whether individual reads originated from a tumor or immune cells. Leveraging methylomes of matched tumors and immune cells, we characterized cfDNA methylomes of cancer patients for longitudinal monitoring during treatment.Control subjects consist of healthy individuals without a positive diagnosis of cancer. cfDNA was obtained through purification of plasma from blood draws. Genomic DNA (gDNA) was derived from extraction of primary tumor tissue or from leukocytes from blood draws.

  Study phs002950

• Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment

  Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

  Study EGAS00001002485

• Viral Respiratory Pathogens Genetics

  The overall purpose of this study is to investigate the host genetic factors in response to influenza virus infection, with the focus on influenza vaccination in the first substudy "Adult Influenza Vaccine Genetics" and with the focus on influenza natural infection and other acute respiratory infections (ARIs) in the second substudy "Acute Viral Respiratory Infection Genetics". In the first substudy, healthy adults were enrolled in 2008 (male cohort) and 2010 (female cohort) and immunized with seasonal influenza vaccine. In the second substudy, healthy adults were invited to enroll to be followed for acute respiratory illness through two consecutive influenza seasons 2009-2010 and 2010-2011. Peripheral blood genomic DNA samples were collected from all the subjects, and time-series RNA and serum samples were obtained pre- and post- immunization/infection. Genotyping was carried out on peripheral blood genomic DNA samples using Illumina HumanOmniExpress-12 v1 arrays. Peripheral blood RNA samples obtained at each visit were analyzed using Illumina Human HT-12 (for all the samples) and HiSeq 2000 (for 130 samples in the "Acute Viral Respiratory Infection Genetics" study). Serum specimens were tested using hemagglutination-inhibition (HAI) antibody assay for Influenza H1N1, H3N2, and Influenza B strains. A detailed description of each substudy is provided under their own pages below and via the grouping tool in the right-hand box: phs000635 Adult Influenza Vaccine Genetics phs001031 Acute Viral Respiratory Infection Genetics

  Study phs001030

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• 108 samples liver cancer and normal controls (54 pairs), whole exome sequencing

  liver cancer paired with normal controls, viral and non-viral origin

  Dataset EGAD00001006005

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Single cell sequencing of ovarian cancer

  Single cell sequencing of 12 ovarian cancer biopsies from 7 patients.

  Dataset EGAD00001006898

• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• Paired-end Whole Exome-seq analysis of multi-centric lower grade glioma

  This dataset includes Nimblegen SeqCap EZ Exome v3 data for each lesion of three patients with multicentric glioma. For two patients, each lesion was sequenced along with whole blood. For a third patient, 3 pieces from the right lesion and 4 pieces from the left were sequenced along with whole blood. In each case BAM files that have been aligned with BWA mem alignment are available.

  Dataset EGAD00001003795

• Dataset GBM 2022

  The cellular origin and differentiation status of glioblastoma by scRNA-seq

  Dataset EGAD00001008745

• Epigenomic analysis of human dopaminergic neuron differentiation reveals LBX1, NHLH1 and NR2F1/2 as necessary for lineage specification

  Sample information: The 56 samples produced in this project come from the human iPSC line GM17602 (Coriell) where a tyrosine hydroxylase-T2A-mCherry reporter was inserted. A combination of epigenetic analysis (ATAC/ChIP) along transcriptomics.

  Dataset EGAD00001009288

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [ ChIP-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000079

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [BS-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000078

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [ ChIP-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000165

• Standard epigenome mapping in human epithelial cells of the digestive and urogenital organs [BS-Seq ]

  The aim of this study is to participate in International Human Epigenome Consortium (http://ihec-epigenomes.org/), through disclosure of quality reference epigenome profiles in normal and diseased cells obtained from multiple Japanese people.

  Study JGAS000082

• Dataset for neuroendocrine_adrenal_tumor-RNA

  Rare cancer sequencing data of 145 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008862

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

  Dataset EGAD00001006888