11979 results for "cancer rna-seq"

in 14.44 milliseconds.

• WGS,RNA data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs)

  Paired WGS and RNA-Seq data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs). We performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load.

  Dataset EGAD00001006189

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• The Dynamic Immune Behavior of Primary and Metastatic Ovarian Carcinoma

  Single-cell RNA-seq data of prospectively collected normal ovarian tissue sample from 1 healthy individual and tumor tissue samples with or without chemotherapy from 19 HGSOC patients.

  Dataset EGAD50000000057

• scRNAseq sequencing reads and count matrices of murine splenocytes from diffuse large B-cell lymphoma

  Single-cell RNA-seq of 91 murine splenocytes from Bcl6tg/+ and Cd70-/-; Bcl6tg/+ diffuse large B-cell lymphoma mouse models and Cd70-/- and wild-type controls.

  Dataset EGAD00001012104

• Human normal brain single-cell

  We profiled two human fetal brainstem specimens at 17 and 19 post-conception weeks by single-cell RNA-seq using 10X Chromium Single Cell 3'. The BAM files are provided.

  Dataset EGAD00001005128

• CPM table for OAK (GO28915)

  This dataset contains counts per million for 699 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from OAK (GO28915).

  Dataset EGAD00001008629

• Count table for POPLAR (GO28753)

  This dataset contains counts for 192 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from POPLAR (GO28753).

  Dataset EGAD00001008630

• Count table for OAK (GO28915)

  This dataset contains counts for 699 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from OAK (GO28915).

  Dataset EGAD00001008628

• CPM table for POPLAR (GO28953)

  This dataset contains counts per million for 192 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from POPLAR (GO28753).

  Dataset EGAD00001008631

• Genomic Analysis of Medullary Thyroid Carcinoma

  Sequence data from two medullary thyroid carcinoma patients: WGS datasets generated from tumors and matched normal tissues and RNA-Seq from tumors are included.

  Dataset EGAD00001001618

• Transcriptomic profiles of neuroblastoma PDXs and primary tumors

  This dataset contains bam files for RNA-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft) and 3 pairs of neuroblastoma tumors at diagnosis and at relapse.

  Dataset EGAD00001003393

• Integrative genomic study of CML patients

  This dataset contains WES and RNA-Seq fastq files for 65 CML patient samples at various stages of disease progression.

  Dataset EGAD00001004179

• Whole-genome sequencing reveals genomic signatures associated with the inflammatory microenvironments in Chinese NSCLC patients

  We integrate genomic (whole-genome sequencing, WGS) and transcriptome (polyA-enriched RNA-Seq) sequencing from 90 NSCLC cases and comprehensively identified the distinct genomic features of Chinese NSCLC patients.

  Dataset EGAD00001004071

• macIDR validation data

  RNA-seq of 24 M-CSF differentiated human peripheral monocyte-derived macrophages (MDMs) activated with short exposure (3hours) to LPS, or long exposure (24 hours) to LPS, LPS with IFNγ, IFNγ, IL-4, IL-10, and dexamethasone.

  Dataset EGAD00001004584

• Gene Expression Signatures Characterized by Longitudinal Stability and Inter-Individual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

  RNA sequencing (RNAseq) of peripheral blood lymphocytes was used to develop a means to assess immune function in a way that can be used in discovery science and applied to patients individually in clinical settings. The premise is that profiles of RNA present in immune cells is reflective of the combined influence of genetic and environmental variation on immune potential of individuals and that this potential can be tapped to understand human immunity in a variety of biological contexts. CD4+ cells were isolated from fresh whole blood via positive magnetic bead selection and cell lysates were prepared using Qiazol (QIAGEN) and stored at -80ºC for 3 to 8 months. RNA was extracted in batches for cDNA library preparation and RNA-Seq. For this study, we developed standard operating procedures for handling human blood samples and determined: a) the best way to enrich for CD4+ T cells from whole blood and yield high quality RNA, b) the sensitivity of this RNA profiling strategy, and c) the reproducibility of generated immune profiles from healthy subjects. We then developed bioinformatics processes to establish immune response signatures and immune response phenotypes within cohorts of individuals.

  Study phs001512

• An integrated molecular study of 20 hepatoblastoma pairs using whole genome sequencing and RNA sequencing

  Hepatoblastoma is an uncommon malignant liver cancer occurring in infants and children. The mutant background of hepatoblastoma has not been fully demonstrated. The aim of this study is to genomically depict the mutational landscape of hepatoblastoma through an integrative analysis of whole genome sequencing and RNA sequencing of 20 hepatoblastomas from Chinese individuals.

  Study EGAS00001002772

• Studying Glioblastoma in a Human Organoid Tumor Transplantation Model

  This study comprises two complementary investigations that leverage innovative human model systems and cutting-edge molecular profiling to dissect glioblastoma (GBM) heterogeneity and tumor-microenvironment interactions. The first study uses a novel Human Organoid Tumor Transplantation (HOTT) model, in which freshly dissociated GBM tumor cells from five patients were transplanted into human embryonic stem cell-derived cortical organoids. This system enables the interrogation of tumor and microenvironment interactions in a human-specific, developmentally relevant context. Using single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq), the authors profiled over 216,000 cells, analyzing tumor heterogeneity across multiple media conditions. Ligand-receptor analysis (CellChat), immunofluorescence, and RNAScope were used to validate findings. The study revealed that the HOTT model faithfully recapitulates primary GBM cell types and microenvironmental components, and uncovered a novel bidirectional signaling axis mediated by PTPRZ1 that influences both tumor migration and cell fate in a context-dependent manner. PTPRZ1 is identified to be important for intercellular communication between tumor and microenvironmental cells, while PDGFRB, NOTCH3, HOPX, FAM107A, CLDN5, RGS5, FOXC1, SOX18 are key markers of the neurovascular progenitor that we identify to be a multipotent, restricted progenitor in GBM. Related datasets include the inclusion of immune cells in the HOTT system, termed “iHOTT”. The second study focuses on identifying and characterizing a rare but functionally potent neurovascular progenitor (NVP) population within GBM tumors. By generating a meta-atlas from seven publicly available GBM scRNA-seq datasets, the authors identified a unique tumor-derived cell population co-expressing neural progenitor and vascular markers. This population was validated in situ and in vivo through immunostaining and lineage tracing via DNA barcoding in the HOTT system. Functional knockdown of NVPs in a murine GBM model resulted in reduced cycling cells, altered tumor composition, and increased survival. Clonal analysis showed NVPs have dual potency to give rise to both neuronal and vascular-like tumor cells, contributing significantly to tumor cell diversity. Molecular technologies used across the studies include: Single-cell and single-nucleus RNA sequencing DNA barcoding and clonal lineage tracing (CellTag) Population information: Tumor samples were obtained directly from multiple GBM patients (all IDH1 wild-type, adult), including core and peripheral tumor regions. Human cortical organoids derived from human embryonic stem cells (hESCs) served as the microenvironment in the HOTT model. Principal findings include: HOTT recapitulates the heterogeneity and cell type fidelity of GBM, while enabling the study of tumor–microenvironment signaling. PTPRZ1 has opposing roles in tumor and microenvironment, influencing GBM cell migration and fate via non-catalytic mechanisms. A novel GBM neurovascular progenitor population (NVP) was identified, validated, and shown to contribute clonally to distinct tumor cell types. Elimination of NVPs in vivo reduces tumor aggressiveness and improves survival. Data to be available through dbGaP: Raw and processed single-cell and single-nucleus RNA-seq data (HOTT model and NVP studies) CellTag barcode-labeled scRNA-seq clonal lineage data Associated metadata including patient of origin, experimental condition, and sample annotations.

  Study phs003936

• GM adipose tissue study

  The Greek Metabolic (GM) adipose study was carried out in 106 individuals living in Greece and consists of genotyping data (chip), RNA-Seq and ATAC-Seq (for a subset of individuals) data from paired biopsies of Subcutaneous and Visceral adipose tissue. eQTL mapping was performed to study gene regulation and findings compared to those from adipose tissue GTEX data. The focus of this project was to study an underexplored population living in different environmental conditions in order to reveal novel regulatory effects for genes that shape complex traits and disease risk. Our results highlight the utility of modest-sized studies in adding to our understanding of the molecular basis of complex traits and to the identification of mechanisms that drive disease in specific tissues.

  Study EGAS00001007126

• RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

  Dac EGAC00001000741

• Targeted RNA sequencing of breast cancer GWAS loci

  Dataset EGAD00001004498

• Triple Negative Breast Cancer RNA Sequencing

  We propose to definitively characterise the somatic genetics of triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000390

• Proteogenomic Landscape of Squamous Cell Lung Cancer

  To provide a detailed analysis on how genomic and transcriptomic alterations related to proteome level changes in squamous cell lung cancer (SCC), we performed an integrated analysis incorporating DNA copy number, somatic mutations, expression RNA-sequencing, and expression proteomics in 108 SCC nested within clinical outcome, tumor pathology, and other clinically relevant data.

  Study phs001781

• DAC for study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer."

  This is Data Access Committee will oversee data sharing for sequence data in the EGA study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer." This dataset includes 116 bam files from whole exome sequencing on the Illumina HiSeq2500, 102 fastq files from RNA sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor/normal DNA samples and tumor RNA samples from 72 individuals with non-small cell lung cancer treated with pembrolizumab and SBRT or pembrolizumab alone on the NCT02492568 trial.

  Dac EGAC50000000202

• Integrated Somatic and Germline Molecular Properties Dictating Biological and Clinical Phenotypes in Cancer

  We performed single-nuclei matched RNA- and ATAC-sequencing of frozen biopsies from normal adjacent tissue, primary and metastatic esophageal adenocarcinoma specimens. The data was then further stratified into a tumor microenvironment and malignant compartment and was computationally analyzed to reveal cancer cell subtypes and programs driving malignancy.

  Study phs003438

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915