12216 results for "cancer rna-seq"

in 27.21 milliseconds.

• ChIP-seq and Hodgkin lymphoma

  ChIP-seq data (H3K4Me3, H3K27Ac histone modifications) of Hodgkin lymphoma cell line L-428. Samples were processed as previously described (Sud et al., 2018). The files are in bam format, aligned to build 37 of the human genome.

  Dataset EGAD00001004322

• Genetic and Hormonal Contributions to Gene Expression in Immune Cells

  The origins of sex differences in human disease are elusive, in part because of difficulties in separating the effects of sex hormones and sex chromosomes. To isolate the effects of testosterone, estradiol, and sex chromosome complement (XX or XY) in humans, we implemented a four-state, cross-sectional study design of trans- and cisgender individuals, the former receiving exogenous testosterone or estradiol for at least a year as part of their gender-affirming medical care. This study design allowed us to compare four combinations of sex hormones and sex chromosomes in humans: XX individuals treated with exogenous testosterone (n=21), XY individuals treated with exogenous estradiol (n=13), untreated XX individuals (n=20), and untreated XY individuals (n=15). We chose to focus on the human immune system because it displays an impressively broad range of sex-differential biology. We collected blood samples from each individual and isolated PBMCs the same day. We performed 10X Genomics 3' single-cell RNA-sequencing (scRNA-seq) on PBMCs from the 69 individuals. We generated 150-bp paired end reads from a total of 358,426 cells (with an average of 48,007 reads/cell) and identified 18 distinct immune cell types. We found that testosterone, estradiol, and sex chromosome complement have unique, non-overlapping effects on PBMC cell abundances and gene expression.

  Study phs003860

• A Perioperative Study of Safusidenib in Patients with IDH1-Mutated Glioma

  10 participants with a radiological or pathological diagnosis of WHO Grade 2 lower-grade glioma (LGG) were recruited at a single center starting in December, 2022. Eligibility criteria permitted participants who had undergone prior surgery for WHO Grade 2 LGG, but excluded those with a history of prior radiation or chemotherapy.In Part A of the study, participants underwent an initial craniotomy with tumor biopsy and a lumbar puncture for cerebrospinal fluid (CSF) collection at study entry. Following sample collection, participants received safusidenib at the recommended phase 2 doses of 250 mg twice daily (b.i.d.) for a period of 22–36 days. This was followed by a second craniotomy for maximal safe tumor resection and a repeat lumbar puncture within 5 hours of the final pre-resection dose of safusidenib. Tumor, blood, and CSF samples were collected at both surgical time points for comprehensive translational research.Molecular analyses were performed on samples collected at both time points. These included pharmacokinetics (PK), targeted metabolomics, whole-genome sequencing (WGS) of tumor tissue, single-nucleus RNA sequencing (snRNA-seq), and DNA methylation profiling on all patients. Targeted metabolomics was conducted on samples from 9 participants, while spatial transcriptomics and spatial metabolomics were performed on tumor tissue from 3 participants each. Histone methylation profiling was conducted on samples from 8 participants.

  Study phs003976

• Symptom Clusters in Oncology Patients Receiving Chemotherapy

  The parent longitudinal study evaluated the symptom experience of oncology outpatients receiving chemotherapy. Patients completed questionnaires in their homes a total of six times (assessments 1 through 6). The questionnaires were timed to evaluate symptoms associated with the receipt of two cycles of chemotherapy that were administered approximately a month apart. Assessments 1 and 4 evaluated symptoms prior to the receipt of chemotherapy. Assessments 2 and 5 evaluated symptoms in the week following the administration of chemotherapy. Assessments 3 and 6 evaluated symptoms two weeks following the administration of chemotherapy. For this analysis, morning and evening fatigue data from the enrollment assessment (i.e., prior to the second or third cycle of chemotherapy) and the assessment that was done approximately 1 week after administration of chemotherapy were evaluated. Patients completed the Lee Fatigue Scale to obtain information on morning and evening fatigue severity. For the morning fatigue assessment, patients were asked to describe how they “felt over the past week when they woke up in the morning”. For the evening fatigue assessment, they were asked to describe how they felt over the past week “before they went to bed at night”. Medical records were reviewed for disease and treatment information. Epigenome assays (microarray) were completed for 1170 patients. Whole transcriptome sequencing (bulk RNA-Seq) was completed for 651 patients.

  Study phs003863

• Human Pancreatic Islet RNAseq - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004042

• Phenotyping data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004056

• GWAS data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004044

• Identification_of_cardiovascular_biomarkers_through_an_integrative_omics_approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionallyannotate index SNPs. With a large number of association signals located outside codingregions there has been an intense search among sequence variants affecting geneexpression at the transcriptional level. However, little progress has been made in mappingregulatory variants that affect protein levels at the translational or post-translational level. It isnow possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins bymass spectrometry. We have established a collaboration with a longitudinal, family-basedstudy in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295individuals) and has follow up data for 10 years (three visits). We have undertaken a pilotstudy in a focus set of 257 subjects from 79 families with the aim to integrate GWAS,transcriptomic and DNA methylation data with proteomic data on a set of 100 proteinsmeasured in PBMCs. We have already generated GWAS data using Illumina's core-exomechip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq togenerate transcriptomic data of the corresponding PBMCs.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000711

• An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

  We undertook an empirical approach to dissect the tumor microenvironment by developing a bulk tumor dissection algorithm, DisHet, and leveraging RNA-Seq data of tumorgrafts (patient-derived tumors implanted in mice), in which only the tumor cell component expands. We found that approximately 65% of previously defined immune signature genes are not abundantly expressed in the Renal Cell Carcinoma (RCC) microenvironment, and we identified more than two times as many novel immune/stromal transcripts. By using refined immune/stroma-specific genes and genomics, electronic medical record data and imaging data of 1084 RCC patients, we discovered a highly-inflamed pan-RCC subtype enriched for Treg cells, NK cells, Th1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. This inflamed subtype (IS) is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. Interestingly, IS is correlated with systemic manifestations of inflammation in patients such as thrombocytosis and anemia, whose pathogenesis were poorly defined and have been predictors of poor prognosis in RCC. Indeed, we discovered that IS is a strong predictor of poor survival. Lastly, our analyses show that tumor cells may drive stromal immune response. Overall, these data provide a missing link between the tumor cells, the tumor microenvironment, and systemic factors.

  Study EGAS00001002786

• 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

• Massively parallel single-cell B-cell receptor sequencing enables rapid discovery of diverse antigen-reactive antibodies

  Using high-throughput single-cell B-cell receptor sequencing (scBCR-seq) we obtained accurately paired full-length heavy- and light-chain variable regions from thousands of individual B cells in a massively parallel fashion. We sequenced more than 250,000 B cells from rat, mouse and human repertoires to characterize their lineages and expansion. In addition, we immunized rats with chicken ovalbumin and profiled antigen-reactive B cells from lymph nodes of immunized animals. The scBCR-seq data recovered 81% (n = 56/69) of B-cell lineages identified from hybridomas generated from the same set of B cells that were subjected to scBCR-seq. Importantly, scBCR-seq identified an additional 710 candidate lineages that were not recovered as hybridomas. We synthesized, expressed and tested 93 clones from the identified lineages and found that 99% (n = 92/93) of the clones were antigen-reactive. Our results establish scBCR-seq as a powerful tool for antibody discovery.

  Study EGAS00001003663

• miRNA Profiling of Maternal and Non-Maternal Healthy Adult Blood Plasma Using Small RNA-Sequencing

  We compared several performance characteristics of four miRNA profiling methods: small RNA-sequencing, HTG EdgeSeq, Abcam FirePlex, and NanoString nCounter. We used pools of synthetic miRNAs and extracellular RNA from healthy individuals to assess these characteristics.

  Study phs001892

• scATAC-seq and combined scRNA-seq of the human first trimester neurodevelopment

  Study EGAS00001007472

• Whole-Exome-Seq-Dataset

  Whole-Exome-Seq-Dataset

  Dataset EGAD00001000042

• whole genome seq

  20 whole genome seq

  Dataset EGAD00001004462

• ChIP-seq in KMS11 and TKO cells

  Histone chIP-seq in t(4;14) Myeloma cell line KMS11 and KMS11 cells with knock-out of translocated NSD2 allele (KMS11 TKO).

  Study EGAS50000000077

• ATAC-Seq of human CD4 Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ATAC-seq (114 samples) The final quality filtered set included 73 individuals with ATAC-seq.

  Dataset EGAD00001005002

• SF11956 snATAC Seq GBM

  IDHR132H Wildtype GBM. Male, 63 Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005406

• ATAC-seq

  ATAC-seq data. Dataset includes FASTQ files, BAM files, and analysis files with the ATAC-seq peaks determined using MACS2.

  Dataset EGAD00001008962

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads. This dataset is large and split into two parts to facilitate downloads. The Linux command line of "tar -xvf xxxx_PART1.gz" should be used to extract the individual files. For additional information regarding the genomic data associated with the study, please also see the paper companion website at https://llmpp.ccr.cancer.gov/local/DLBCL_singlecell/

  Dataset EGAD50000002490

• Medulloblastoma Cirlce-Seq

  Circle-Seq experiment.

  Dataset EGAD00001009483

• RNA sequencing of peripheral blood samples from 17 Greenlanders

  The data contain whole deep RNA sequencing of leukocytes from 17 Greenlanders. RNA was purified from peripheral blood with the PAXGene Blood miRNA Kit (Qiagen). The RNA sequencing library was prepared following the instructions of the TruSeq RNA Sample Prep Kit v2 (Illumina). For mRNA isolation and fragmentation 200 ng of total RNA was purified by oligo-dT beads. The qualified libraries were amplified on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3–cBot–HS, Illumina). The amplified flow cell was sequenced paired-end on the HiSeq 4000 System (TruSeq SBS KIT-HS V3, Illumina).

  Dataset EGAD00001003814

• Lipomatous tumors with 12q amplification

  The project concerns whole genome sequencing (short-read and long-read) and RNA-sequencing of lipomatous tumors with 12q-amplification. A subset of lipomatous tumors is driven by amplification of genes mapping to chromosome arm 12q, including the MDM2 gene. The goals of the study were to compare expression levels of genes mapping to 12q in tumors with amplification in rod-shaped or circularized chromosomes as well as to assess and compare the structural variants in those tumors. In total, 20 samples were analyzed, and the data were correlated with genomic data on bulk and single cell DNA from the same tumors. The fastq files from the tumors were uploaded to EGA.

  Study EGAS50000000062

• Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

  The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

  Study JGAS000875

• A Single Cell Atlas of Gene Regulatory Elements in the Human Heart

  Background: Cis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. Methods: We performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing, and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. Results: We defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. Conclusion: This comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

  Study phs002204