15070 results for "cancer studies using rna-seq"

in 16.74 milliseconds.

• WGS and RNA-Seq data from a GBM patient PT-MB9777

  WGS and RNA-Seq data from a GBM patient PT-MB9777

  Dataset EGAD00001004253

• RNA-Seq files for SJHGG study

  RNA-Seq files accompanying the paper titled "Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas".

  Dataset EGAD00001003905

• Meso RNA-seq data (SSA cell line study)

  RNA-seq data for mesothelioma cell lines after spliceostatin (SSA) or control (DMSO) treatment.

  Dataset EGAD00001001914

• Longitudinal RNA-seq in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Dataset EGAD00001002068

• NiCOL Study RNA-seq dataset

  15 samples sequenced in RNA-seq. This dataset contains their raw FASTQ data and the raw count table and the TPM count table.

  Dataset EGAD00001010912

• Cam_121 RNA-Seq data

  This dataset contains RNA-Seq data from 204 primary melanomas and 177 regional lymph nodes. More details can be found in the manuscript: "Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study"

  Dataset EGAD00001006401

• Tumor gene expression profiles for the study "TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells"

  RNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. RNA was sequenced using a capture based approach (exome capture, RNA access).

  Dataset EGAD00001003977

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Dataset EGAD00001015535

• Integrative analysis of exome-seq, RNA-seq, ATAC-seq (bulk and single-cell), and Hi-C data generated from 3-D spatially mapped samples acquired during surgical resection from 10 patients diagnosed with IDH-WT glioblastoma

  Glioblastoma (GBM), the most common primary brain cancer in adults, remains incurable with no targeted therapies approved despite decades of investigation into its molecular landscape. Treatment failure is attributed to intratumoral heterogeneity in the GBM genome and epigenome, which foster tumor evolution and selection of resistant clones. However, tumor evolution and intratumoral heterogeneity remain poorly understood on the level of the whole tumor as most studies are based on single samples per patient and lack spatial context. Here, we have used 3-D neuronavigation during surgical resection for 10 primary IDH-WT GBM patients to collect 102 samples representing maximal tumor diversity, each mapped by 3-D spatial coordinates. We have applied a strategic set of genomic and epigenomic assays spanning multiple levels of resolution to discover, orthogonally validate, and functionally assess drivers of tumor evolution and intratumoral heterogeneity. These include extrachromosomal DNA amplifications, chromothripsis events, inversions, and translocations that disrupt both the GBM genome and epigenome while generating fusion transcripts and opportunities for therapeutic intervention. We define epigenomic programs that contribute to GBM evolution and intratumoral heterogeneity, revealing their 3-D spatial patterning within whole tumors and their cell type(s) of origin in single-cell data from the same tumor samples. Notably, we distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells and discover NEUROD1, JUN/FOS, and NF1 transcription factors as key drivers of GBM evolution and growth. Collectively, these data provide unprecedented insight into GBM evolution and intratumoral heterogeneity from single-cell to whole-tumor resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.

  Study EGAS00001006785

• RNA expression profiling of neuromuscular diseases and viral diseases

  MicroRNAs (miRNAs), particularly those found in human body fluids, have been suggested as potential biomarkers. Among various body fluids, the cerebrospinal fluid (CSF) shows promise as a profiling target for diagnosis and monitoring of neurological diseases. However, relevant genome-scale studies are limited and no studies have profiled exosomal miRNAs in CSF. Therefore, we conducted a next-generation sequencing-based survey of small RNAs in the exosomal and non-exosomal (supernatant) fractions of healthy human CSF as well as serum in each donor. Our data provided the first landscape of small RNAs in CSF exosome.

  Study JGAS000064

• RNA-Seq

  RNA Sequencing

  Dataset EGAD00001001121

• BCC HHI-ICI combination therapy

  Data of advanced basal cell carcinoma patients receiving hedgehog-inhibitor and immune checkpoint-inhibitor combination treatment. The single-cell RNA-sequencing data was generated via the Parse Biosciences platform from PBMC samples of 10 patients at 4 four timepoints each. The spatial transcriptomics dataset was generated using the 10x Visium platform (+CITE-seq) and contains altogether 10 biopsies at different timepoints during treatment from 3 patients. The processed matrices with the spatial images can be downloaded from: https://zenodo.org/records/17814765

  Dataset EGAD50000002134

• Single nucleus mRNA sequencing of immune cells from diverse CNS regions in human health and diseases

  CNS nuclei were isolated from frozen specimen, stained with anti-NeuN and anti-Olig2, FACS purified (DAPI+NeuN-Olig2-), and analyzed with single nucleus RNA-seq. One batch of samples was also labelled with CMO and allows distinguishing indivudal samples within the analysis. A combined seurat object was generated to include all the analyses and samples were integrated using Harmony integration.

  Dataset EGAD50000001835

• Aligned FOS RNA sequencing data

  Total RNA-sequencing Paired-End was performed by GenomeScan (Leiden, the Netherlands) on the NovaSeq6000 platform for full-length FOS (FOS FL), truncated FOS (FOSΔ), a FOS isoform with an L376N mutation (FOS mut), untransduced fMSC (unt) and fMSC with empty pLV (pLV) at week 0, 1, 2, and 3 in triplicate (total of 60 samples). Raw RNA-seq data were processed by the RNA-seq BioWDL pipeline pipeline version 5.0.0 developed by the SASC team at LUMC, LUMC, Leiden, the Netherlands).

  Dataset EGAD50000001839

• Human melanoma samples with and without resistance to BRAF inhibitor therapy

  Human melanoma samples were collected pre, on, and progression on BRAF inhibitor therapy. RNA was extracted and run on RNA-seq. This has provided insights into different categories of BRAF inhibitor resistance mechanisms.

  Study EGAS00001000992

• RNA-seq data from Follicular Lymphoma samples

  Dataset included RNA-seq data (Two Fastq files per sample as paired end sequencing was performed) from ribosomal-depleted total RNA in 28 Follicular Lymphoma (FL) criopreserved samples to analyze long non-coding RNA and coding transcript expression profiles. Sample metadata is referred to histological groups of FL tumors (FL1-3A versus FL3B/DLBCL) either in tumor purified cell samples (N=12) as in unpurified tumor samples including normal cells of the lymph node microenvironment (N=16).

  Dataset EGAD00001004109

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumor tissue and from the blood of fifty patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumor DNA samples using two orthogonal platforms – exome capture by Roche-Nimblegen SeqCap Ez kit followed by sequencing on Roche-454 GS FLX, and exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 30x. In addition, we have used Illumina Omni Quad SNP-chips to generate genotype data at 1.14 million genomic markers. The average concordance between SNP-chip and sequence data is 99.8%.

  Study EGAS00001000249

• Prostate cancer ancestral genomic disparity

  Prostate cancer is characterised by significant global disparity; mortality rates in SubSaharan Africa are double to quadruple those in Eurasia. Hypothesising unknown interplay between genetic and non-genetic factors, tumour genome profiling envisages contributing mutational processes. Through whole-genome sequencing of treatment-naïve prostate cancer from 183 ethnically/globally distinct patients (African versus European), we generate the largest cancer genomics resource for Sub-Saharan Africa. Identifying ~2 million somatic variants, Africans carried the greatest burden. We describe a new molecular taxonomy using all mutational types and ethno39 geographic identifiers, including Asian. Defined as Global Mutational Subtypes (GMS) A–D, although Africans presented within all subtypes, we found GMS-B to be ‘African-specific’ and GMS-D ‘African-predominant’, including Admixed and European Africans. Conversely, Europeans from Australia, Africa and Brazil predominated within ‘mutationally-quiet’ and ethnically/globally ‘universal’ GMS-A, while European Australians shared a higher mutational burden with Africans in GMS45 C. GMS predicts clinical outcomes; reconstructing cancer timelines suggests four evolutionary trajectories with different mutation rates (GMS-A, low 0.968/year versus D, highest 1.315/year). Our data suggest both common genetic factors across extant populations and regional environmental factors contributing to carcinogenesis, analogous to gene-environment interaction defined here as a different effect of an environmental surrounding in persons with different ancestries or vice versa. We anticipate GMS acting as a proxy to intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

  Study EGAS00001006425

• ETMR H3K27Ac ChIPSeq

  H3K27Ac ChIP-seq DNA libraries for 5 ETMR samples were prepared using NEBNext ChIP-seq Illumina Sequencing library preparation kit. ChIP-seqlibraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ChIP-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004809

• RNA-seq analysis of midbrain dopaminergic neurons following ZFHX4 knockdown.

  We performed RNA-seq analysis on midbrain dopaminergic neurons derived from induced pluripotent stem cells following lentiviral-mediated knockdown of the transcription factor ZFHX4. Transcriptomic analysis enabled the identification of potential ZFHX4 target genes. Enrichment analysis of the differentially expressed genes was conducted to assess the biological pathways regulated by ZFHX4.

  Study EGAS50000001111

• RNA-seq analysis of BMP-stimulated glioma initiating cells

  Bone morphogenetic protein (BMP) signaling has been shown to suppress progression of glioblastoma by promoting astrocytic differentiation; however, roles of BMP signaling in cell proliferation and apoptosis of glioblastoma cells remains to be elucidated. We here performed RNA-seq analysis of glioma initiating cells to identify transcriptional target(s) of BMP.

  Study JGAS000077

• Cellular Indexing of Transcriptomes and Epitopes Sequencing (CITE-Seq) Analysis to Investigate the Impact of Granulocyte-Colony Stimulating Factor on CRISPR/Cas9 Gene Edited Human Hematopoietic Stem Cell Function

  Our research using in-vivo preclinical xenograft mouse models demonstrated that G-CSF impedes engraftment of CRISPR-Cas9 gene edited human hematopoietic stem cells (HSCs). In this CITE-seq study, we sought to investigate the mechanisms by which G-CSF negatively impacts long-term repopulating functions of CRISPR-Cas9 gene edited human HSCs. Accordingly, human CD34+ cells were obtained from a healthy volunteer and edited with Cas9 alone (Cas9 group), Cas9+AAVS1-targeting gRNA (RNP group), or Cas9+AAVS1-targeting gRNA+GSE56 (RNP/GSE56 group). Then, these edited cells were transplanted into busulfan-conditioned NSG mice, and these mice subsequently received 3 days of phosphate buffered saline (PBS) or G-CSF. Each mouse was subsequently euthanized and harvested for bone marrow cells and human CD34+cells were isolated using immunomagnetic beads. Isolated CD34+ cells from a total of 6 mice were individually stained with Total seq B CITE-seq antibodies (CD38, CD45RA, CD90, CD49f) + hashtag oligo antibodies 1, 2, 3, 4, 5 and 6. Fluorescence activated cell sorting (FACS) was used to purify ~2,500 cells from each group that were subsequently pooled for CITE-seq library preparation and sequencing. Seurat was used to demultiplex data into 6 individual groups and differential gene expression analysis was performed to evaluate the impact of G-CSF within Cas9, RNP and RNP/GSE56 groups.

  Study phs003277

• Single-cell RNA sequencing of human kidney transplant nephrectomies with chronic rejection or non-alloimmune graft injury

  This dataset contains raw single-cell RNA sequencing (scRNA-seq) data for five new kidney allograft nephrectomy samples used to construct the described in the following study: https://www.biorxiv.org/content/10.1101/2022.10.28.514222v2.full. The full description of processing is described in the manuscript. Briefly, samples were digested into a single cell suspension and run according to the 10X Genomics Chromium 5’ single cell kit (v2). Sequencing was performed using an Illumina Novaseq instrument. Samples were designated as TXN2 (EGAN00002519570, mycotic pseudoaneurysm, control dataset), TXN3 (EGAN00002235628, renal vein thrombus, control dataset), TXN5 (EGAN00002519573, chronic transplant rejection), TXN6 (EGAN00002519572, chronic pyelonephritis and renal artery stenosis, non-alloimmune graft injury dataset), TXN7 (EGAN00002519576, recurrent focal segmental glomerulosclerosis, non-alloimmune graft injury dataset).

  Dataset EGAD00001015631

• IBC RNA-seq

  RNA sequencing of IBC patients

  Dataset EGAD00001011649