11769 results for "cancer rna-seq"

in 16.43 milliseconds.

• Single-cell RNA sequencing of sorted regulatory T cells

  Single-cell RNA sequencing of flow cytometry enriched CD4+ CD127- CD25+ regulatory T cells from 8 systemic lupus erythematosus patients (SLE_001 to SLE_007, and SLE_009) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform (incl. generation of TCR libraries). Samples from patients SLE_001, SLE_002, SLE_004, SLE_006 were collected and processed on the first day of experiment (Day 1), and samples from patients SLE_003, SLE_005, SLE_007, SLE_009 on the second day of experiment (Day 2). On each day, samples were pooled and distributed to four lanes on the chromium controller. Run ID 245269 and ID 245270 identify samples sequenced on separate flow cells. Provided are raw sequencing files.

  Dataset EGAD50000000663

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Study EGAS00001004081

• RNA sequencing in blood samples of cluster headache patients

  Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Blood samples were subjected to globin reduction before sequencing.

  Study EGAS00001001918

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Illumina RNA sequencing for HLA expression qauntification

  In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology.

  Study EGAS00001004931

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• Deep RNA sequencing in CLL

  Chronic lymphocytic leukemia (CLL) is a B-cell neoplasm with a heterogeneous clinical and biological behavior. We have performed deep RNA sequencing in different subpopulations of B-lymphocytes from healthy individuals and CLL cells from a cohort of 98 patients, and characterized the CLL transcriptional landscape with unprecedented resolution. The transcriptomic architecture of CLL uncovered here refines the biological characterization of the disease and opens new perspectives for the clinical management of patients.

  Study EGAS00001000374

• Identification of High-Risk PHF19 Expressing Cells in Myeloma Single-Cell Multiomics

  The aim of this study is to identify novel subsets of cells that are associated with progression and response to treatment. In this project, we study the tumor fraction from 49 myeloma patients across stages of progression. Samples were collected from 10 smoldering multiple myeloma (SMM), 22 newly diagnosed multiple myeloma (NDMM), and 17 relapsed refractory multiple myeloma (RRMM) patients. These samples were then sorted using magnetic-activated cell sorting (MACS) for CD138+ cells that represent the tumor fraction of each sample. The CD138+ fraction then underwent whole genome sequencing (WGS), where possible, and single-cell multiomics. Single-cell multiomics can now measure scRNA-seq and scATAC-seq simultaneously, which we use in this project. Using single-cell multiomics, we will study subclonal changes in gene expression, chromatin accessibility, and identify novel regulatory relationships within myeloma tumors. Furthermore, we will apply state of the art single-cell and single-cell multiomic techniques to better identify the more high-risk components of myeloma.

  Study phs003220

• Cell-type eQTLs for single-cell Mendelian Randomisation

  The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

  Study EGAS50000000687

• Functional Variant rs9344 at 11q13.3 Regulates CCND1 Expression in Multiple Myeloma with t(11;14)

  Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). We have found the G risk allele is enriched in both healthy individuals of African ancestry and African American individuals with MM. The overall aim of this study was to identify the mechanism behind why the G allele is enriched in t(11;14) MM. To reach this goal, we performed ATAC-seq from 100,000 CD138+ tumor cells from 26 patients with MM. In addition, we performed ChIP-seq using antibodies against H3K4me1, H3K27ac and H3K4me3 from 100,000 CD138+ tumor cells from 8 patients with MM. We used these data to evaluate whether the G allele of rs9344 is associated with elevated chromatin accessibility, H3K27ac and H3K4me3 in t(11;14) MM.

  Study phs003997

• Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics

  Single-cell transcriptomics (scRNA-seq) has enabled the characterization of cell state heterogeneity and recapitulation of differentiation trajectories. However, since proteins are the main functional entities in cells, the exclusive use of mRNA measurements comes at the risk of missing important biological information. Here we leverage recent technological advances in single-cell proteomics by Mass Spectrometry (scp-MS) to generate the first scp-MS dataset of an in vivo differentiation hierarchy encompassing over 2,500 human CD34+ hematopoietic stem and progenitor cells. Through integration with scRNA-seq, we identify proteins that are important for stem cell quiescence, which were not indicated by their mRNA transcripts, and demonstrate functional expression covariance during differentiation that is only detectable on protein level. Finally, we show that modeling translation dynamics can infer cell progression during differentiation and explain 45% more protein variation from mRNA than linear correlation. Our work serves as a framework for future single-cell multi-omics studies across biological systems.

  Study EGAS00001007930

• 300BCG study: human population variation of trained immunity

  To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tuberculosis, but also triggers innate immune activation and memory. We established personal chromatin accessibility maps over a time course of BCG vaccination in the 300BCG cohort using ATAC-seq.

  Study EGAS50000000090

• Raw scRNA-seq data from B-lineage cells in the blood of celiac disease patients

  Raw scRNA-seq data from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The data was generated with the Smart-seq2 protocol and sequenced on a NextSeq500 instrument (Illumina) with 75 bp paired-end reads in high-output mode. The dataset contains R1 and R2 reads for each single cell (fastq.gz files) for cells passing quality control based on number of detected genes, reads, mitochondrial genes, reads mapping to the reference transcriptome and a productively rearranged immunoglobulin heavy chain IgA isotype reconstructed by the computational tool BraCeR. Metadata for the cells is provided in a csv file.

  Dataset EGAD50000000340

• Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

  We generated the first single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

  Study EGAS50000000735

• Histone acetylome-wide association study on tuberculosis infection

  Epigenetic mechanisms are thought to play an important role in the pathogenesis of infectious diseases. Here, we describe the first histone acetylome-wide association study (HAWAS) of an infectious disease, based on genome-wide H3K27 acetylation profiling of peripheral granulocytes and monocytes from subjects with active Mycobacterium tuberculosis (Mtb) infection and healthy controls (135 ChIP-seq datasets).

  Study EGAS00001003118

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell transcriptome sequencing and a novel bioinformatics pipeline

  We report a deconvolution and identification strategy of scRNA-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and aquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures.

  Study EGAS00001006202

• Single cell RNA-sequencing of tissues from NSCLC patients treated with chemoimmunotherapy

  Study EGAS00001006728

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Study EGAS00001007295

• Angiosarcoma RNA sequencing

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001000738

• Short-read scRNA-seq

  10x Chromium Single Cell 3′ single-cell cDNA sequencing data for adrenal tissue sampleA and sampleB.

  Dataset EGAD50000002210

• input

  Input dataset of human islets. To be used in conjuction with Cohesin and Mediator ChIP-Seq datasets.

  Dataset EGAD00001005209

• Integrated Genomic Analyses of Cutaneous T Cell Lymphomas Reveal the Molecular Bases for Disease Heterogeneity

  Cutaneous T cell lymphomas (CTCLs) are a clinically diverse collection of lymphomas of the skin-homing T cell. In the present study, we performed DNA and RNA sequencing on a cohort of CTCLs with representative samples from varying disease subtypes and stages. We characterized the landscape of putative driver genes, identified genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes. DNA and RNA sequencing was performed on 114 and 96 samples respectively. Tumor samples were obtained from University of Chicago (Chicago, IL), Northwestern University (Chicago, IL) and Yale University (New Haven, CT). 

  Study phs002456

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• RNA sequencing of periprostatic fat after a 6 month deep androgen deprivation therapy

  Androgen deprivation therapy treated patients (n=11) were recruited from an open label neoadjuvant phase II study in which patients with high-risk disease received a ‘supercastration’ regimen consisting of degarelix 240/80 mg subcutaneously every four weeks; abiraterone acetate 500 mg orally daily titrating upwards every two weeks by 250 mg to a final dose of 1000 mg daily; bicalutamide 50 mg orally daily; and prednisolone 5 mg orally twice daily for a total of 6 months (Australian New Zealand Clinical Trials Registry 12612000772842). Untreated patients with similar pre-treatment characteristics were obtained from a prospective prostatectomy biorepository22,23. Prior to ligation of the dorsal venous complex and prostate pedicles, the anterior prostate was defatted and the specimen was removed immediately, placed in a sterile container and transferred on ice for long-term storage in the vapour phase of liquid nitrogen. A total of 50–100 µg of adipose tissue was separated from fresh frozen samples stored at −160°C. RNA was isolated using the Qiagen RNeasy Lipid Tissue Mini Kit and eluted in 35 µL nuclease-free water. 0.5–1 µg of total RNA was used as the input for cDNA library synthesis using TruSeq RNA Sample Prep Kit v2 (Illumina), and libraries were constructed according to manufacturer’s instructions. Samples were sequenced on a HiSeq 2500 (Illumina) using 101 base paired-end chemistry, aiming for 50 million mapped paired-end reads per sample.

  Dataset EGAD00001004971

• WGS and WTS data of patient diagnosed with HSTCL

  WGS and WTS data of a single patient diagnosed with HSTCL. Whole-genome sequencing (WGS) was performed for the tumor-normal sample. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 4000 2x151 bp read length. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length.

  Dataset EGAD00001005229