12304 results for "cancer rna-seq"

in 24.64 milliseconds.

• Covid19 RNAseq Fastq files

  RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre-kit and sequencing on the NovaSeq 6000.

  Study EGAS00001007022

• Covid19 RNAseq BAM files

  RNA Sequencing using Illumina’s TruSeq Stranded Total RNA with RiboZero Globin depletion library pre-kit and sequencing on the NovaSeq 6000.

  Study EGAS00001007050

• Dataset for H3K27me3 ChIP-seq data for neuroblastoma cell lines (Neuroblastoma_CL)

  Dataset for H3K27me3 ChIP-seq data of 31 neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015809

• Small RNA-sequencing and RNA-sequencing data of tuberous sclerosis complex subependymal giant cell astrocytomas

  This data set contains small RNA-sequencing and RNA-sequencing data from subependymal giant cell astrocytomas (SEGA) resected from tuberous sclerosis complex patients. Small RNA-sequencing and RNA-sequencing were performed on the same set of SEGAs (n=19) and periventricular controls (n=8). For full details on library preparation and patients please refer to the paper "The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas." (PMID: 31834371 DOI: 10.1093/brain/awz370).

  Dataset EGAD00001005932

• Bulk and single-cell RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes (3 in-house and 2 commercial lines), both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein

  RNA editing is a post transcriptional mechanism that targets changes in RNA transcripts to modulate innate immune responses. We report the role of astrocyte specific, ADAR1 mediated RNA editing in neuroinflammation in Parkinson’s disease. We generated hiPSC-derived astrocytes, neurons and co-cultures and exposed them to small soluble alpha-synuclein aggregates. Oligomeric alpha-synuclein triggered an inflammatory glial state associated with TLR activation, viral responses, and cytokine secretion. This reactive state resulted in loss of neurosupportive functions, and the induction of neuronal toxicity. Notably, interferon response pathways were activated leading to upregulation, and isoform switching of the RNA deaminase enzyme, ADAR1. ADAR1 mediates A-to-I RNA editing, and increases in RNA editing were observed in inflammatory pathways in cells, as well as in post-mortem human PD brain. Aberrant, or dysregulated, ADAR1 responses and RNA editing may lead to sustained inflammatory reactive states in astrocytes triggered by alpha-synuclein aggregation, and this may drive the neuroinflammatory cascade in Parkinson’s.

  Study EGAS50000000751

• Identification of driver oncogenes in scirrhous-type gastric cancer cell lines

  Scirrhous type gastric cancer (SGC) is one of the most intractable cancer subtypes in human, and its therapeutic targets have been rarely identified to date. Exploration of somatic mutations in the SGC genome with the next generation sequencers has been hampered by low tumor contents by the markedly increased fibrous tissues. Thus, SGC cell lines may be useful resources to search for novel oncogenes in. Here we have conducted whole exome sequencing and RNA sequencing on two SGC cell lines, OCUM-8 and OCUM-9. Interestingly, most of the mutations thus identified have not been reported. In OCUM-8 cells, a novel CD44-IGF1R fusion gene is discovered, the protein product of which ligates the amino-terminus of CD44 to the transmembrane and the tyrosine-kinase domains of IGF1R. Further, both of CD44 and IGF1R are markedly amplified in the OCUM-8 genome and abundantly expressed. CD44-IGF1R has a transforming ability, and the suppression of its kinase activity leads to rapid cell death of OCUM-8. On the other hand, OCUM-9 seems to possess multiple oncogenic events in its genome. The MET gene is highly amplified, and the treatment of OCUM-9 with crizotinib, a MET inhibitor, results in cell death. Further, a novel BORCS5-ETV6 fusion gene is identified in the OCUM-9 genome. BORCS5-ETV6 possesses oncogenic activity, and suppression of its message partially inhibits cell growth. Prevalence of these novel fusion genes among SGC awaits further investigation, but we validate the significance of cell lines as appropriate reagents for detailed genomic analyses of SGC.

  Study JGAS000179

• Biallelic tumor suppressor loss and DNA repair defects in de novo small cell prostate cancer

  Small cell prostatic carcinoma (SCPC) is an aggressive pathology that is managed similar to small cell lung cancer. SCPC can evolve from prostatic adenocarcinoma in response to androgen deprivation therapy but in rare cases is present at initial cancer diagnosis. The molecular etiology of de novo SCPC is incompletely understood due to the scarcity of tumor tissue and the brief life expectancy of patients. Through a retrospective search of our regional oncology pharmacy database, we identified 18 patients diagnosed with de novo SCPC between 2004 and 2017. Ten patients had pure SCPC pathology and the remainder had some admixed adenocarcinoma foci, but all were treated with first line platinum-based chemotherapy. Median overall survival was 28 months. We performed targeted DNA sequencing, whole exome sequencing and mRNA profiling on formalin-fixed paraffin embedded archival tumor tissue. We observed frequent biallelic deletion and/or mutation of tumor suppressors TP53, RB1 and PTEN, similar to treatment related SCPC. Indeed, at the RNA level pure de novo SCPC closely resembled treatment-related SCPC. However, five patients had biallelic loss of DNA repair genes including BRCA1, BRCA2, ATM and MSH2/6: potentially underlying the high genomic instability of this rare disease variant. Two patients with pure de novo SCPC harbored ETS gene rearrangements to androgen-driven promoters, consistent with evolution of de novo SCPC from an androgen-driven ancestor. Overall, our results reveal a highly aggressive molecular landscape underlies this unusual pathologic variant, and propose opportunities for targeted therapy strategies in a disease with few treatment options.

  Study EGAS00001003007

• Colorectal cancer organoids expressing BRAF (fusion) genes

  Fusion genes may be oncogenic drivers and potential targets for personalized therapies in a variety of cancer types. The BRAF gene is frequently involved in oncogenic fusions, with fusion frequencies of 0.2-3% throughout different cancers. BRAF can be fused to a wide variety of genes, however, BRAF fusions rarely occur in the exact same gene configuration, making assessment of the fusion relevance and decision for drug treatment challenging. Here, we devised a colorectal cancer organoid-based platform to functionally characterize diverse BRAF fusions, containing various partner genes (AGAP3, DLG1 and TRIM24). We compared these BRAF fusions with respect to cellular behaviour, downstream signaling activation and response to targeted therapies. We found that 5’ partner choice of BRAF affects cellular localization and intracellular signaling capacities of the fusion genes. The DLG1-BRAF fusion gene showed distinct localization to the plasma membrane and exhibited increased levels of MAPK pathway activation under unperturbed conditions. Furthermore, the different BRAF fusions showed varying sensitivities to the targeted inhibition of ERK and BRAF, with the DLG1-BRAF fusion being the most sensitive. Additionally, RNA-sequencing identified distinct subsets of genes affected by the DLG1-BRAF fusion gene. Importantly, all fusion genes conveyed resistance to the clinically relevant EGFR/HER2/HER4-inhibitor afatinib, suggesting that BRAF fusions should be screened alongside other MAPK pathway alterations to identify mCRC patients amenable to cetuximab treatment. In summary, we developed a platform to efficiently assess molecular and cellular effects of fusion genes, and revealed that differential drug responses and distinct gene expression profiles can be induced by different BRAF fusions .

  Study EGAS00001003558

• Transcriptomic intra-tumor heterogeneity of colorectal cancer varies depending on tumor location within the colorectum

  Background; Intra-tumor heterogeneity (ITH) of colorectal cancer (CRC) complicates molecular tumor classification, such as transcriptional subtyping. Differences in cellular states, biopsy cell composition, and tumor microenvironment may all lead to ITH. Here we analyze ITH at the transcriptomic and proteomic levels to ascertain whether subtype discordance between multiregional biopsies reflects relevant biological ITH or lack of classifier robustness. Further, we study the impact of tumor location on ITH.MethodsMultiregional biopsies from stage II and III CRC tumors were analyzed by RNA sequencing (41 biopsies, 14 tumors) and multiplex immune protein analysis (89 biopsies, 29 tumors). CRC subtyping were performed using consensus molecular subtypes (CMS), CRC intrinsic subtypes (CRIS), and TUMOR types. ITH-scores and network maps were defined to determine the origin of heterogeneity. A validation cohort was used with one biopsy per tumor (162 tumors).ResultsOverall, inter-tumor transcriptional variation exceeded ITH, and subtyping calls were frequently concordant between multiregional biopsies. Still, some tumors had high ITH and were classified discordantly. Proximal tumors showed ITH related to differences in the microenvironment, while ITH within distal tumors were cancer-cell related. This subtype discordancy reflected actual molecular ITH within the tumors. The relevance of the subtypes was reflected at protein level where several inflammation markers were significantly increased in immune related transcriptional subtypes, which was verified in an independent cohort (Wilcoxon rank sum test; p<0.05).ConclusionOur transcriptomic and proteomic analyses show that the tumor location along the colorectum influence the ITH of CRC, which again influence the concordance of subtyping.

  Study EGAS00001004668

• Combined DNA Methylation and Genotyping via scTAMARA-seq (DNA)

  This dataset features single-cell DNA methylation and nuclear genotyping data obtained using the scTAMARA-seq protocol, a combination of SDR-seq and scTAM-seq. The targeted panel, 200 DNA methylation (a subset of the orginal 448 CpG targets) and 167 genotyping targets, were applied to a CD34+ enriched bone marrow sample from patient X.1. The data was generated on the Mission Bio Tapestri platform.

  Dataset EGAD00001015496

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• Genomic Characterization of Duke Melanoma Brain Metastases

  Previous work has shown that melanoma brain metastases (MBM) have a unique molecular profile compared to extracranial metastases (ECM). Description of the biology of MBM and associations between biological features and clinical outcomes will facilitate the design of rational therapies for patients with MBM. To better characterize the molecular profile of MBM, we conducted whole exome sequencing (WES) and total RNA sequencing on MBM tissues obtained from an independent cohort of 14 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations and gene expression profiles within and between cohorts. The mutational landscape and gene expression of MBM from the Duke cohort resembled those previously reported in a previously published dataset of WES and RNA sequencing in MBM and matched ECM tissues from UT MD Anderson Cancer Center (Fischer et al., 2019 30787016). Duke MBM demonstrated similar rates of mutations in genes associated with melanoma, including BRAF, NRAS, and PTEN, as the MD Anderson cohort. Immune populations in MBM were similar between Duke and MD Anderson MBM, though Duke samples demonstrated more resting CD4+ memory T cells. The ratio of M2 to M1 macrophages in the Duke cohort was similar to that of the MD Anderson cohort. In MBM, a higher M2:M1 ratio may contribute to an immune-suppressive tumor microenvironment. Sequencing data and sample attributes from MBM tissues obtained from 14 patients from Duke University Medical Center will be available through dbGaP.

  Study phs003009

• Neuroblastoma Cell Line Circle-seq

  We generated Circle-seq data for 12 neuroblastoma cell lines to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004796

• FASTQ Files for Human LV H3K27ac ChIP-seq

  This dataset contains 70 human LV H3K27ac ChIP-seq paired-end FASTQ files. The sequencing was performed using Illumina Hiseq 4000.

  Dataset EGAD00001004945

• ChIP-seq for GOF p53

  This dataset includes ChIP-seq data from two cell lines (HKCI-11 (GOFp53) and MIHA(WT p53)). All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005449

• Chip-Seq data of neuroblastoma patients

  144 sample from individuals with ALT-positive neuroblastoma tumors, chip-seq sequencing

  Dataset EGAD00001006625

• Spatial transcriptomic data of breast cancer

  Fastq files from spatial transcriptomic of breast cancer coming from 8 Breast cancer sections. Sample preparation: frozen BC samples were chosen based on tissue structure and RNA quality (RIN > 8). The “Visium Spatial Tissue Optimization Slide and Reagent Kit” (10X Genomics; #PN-1000193) was then used to optimize permeabilization conditions for BC tissues. Briefly, sections were fixed, stained and then permeabilized at different time points to capture mRNA, and the reverse transcription was performed to generate fluorescently labeled cDNA. The permeabilization time that resulted in the highest fluorescence signal with the lowest background diffusion was chosen. The best permeabilization time for BC tissue was 18 min. Cryostat sections of 10 μm of thickness were cut and placed on Visium Spatial Gene Expression slides (10X Genomics, PN-1000184). The slide was incubated for 1 min at 37°C, then fixed with methanol for 30 min at -20°C followed by Hematoxylin and Eosin (H&E) staining and images were taken under a high-resolution microscope. After imaging, the coverslip was detached by holding the slide in water and the slide was mounted in a plastic slide cassette. The spatial gene expression process, including tissue permeabilization, second strand synthesis and cDNA amplification, was performed according to the manufacturer’s instructions (10X Genomics; #CG000239). cDNA quality was next assessed using Agilent High sensitivity DNA Kit (Agilent, #5067-4626). The spatial gene libraries were constructed using Visium Spatial Library Construction Kit (10X Genomics, PN-1000184).

  Dataset EGAD50000000322

• Global RNA sequencing data of human iPSC-derived microglia from frontotemporal dementia (FTD) patients

  Global RNA sequencing was performed in RNA samples extracted from human iPSC-derived microglia from healthy controls and sporadic (non-genetic) and genetic C9orf72 hexanucleotide repeat expansion-carrying patients with FTD.

  Study EGAS50000001688

• Total RNA sequencing of fibroblasts from an unmethylated full mutation carrier (UFM2)

  Total RNA sequencing of fibroblasts from an individual with a fragile X syndrome related unmethylated full mutation (UFM2). Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000919

• Total RNA sequencing of fibroblasts from an individual with fragile X syndrome

  Total RNA sequencing of fibroblasts from an individual with a methylated CGG repeat >200x in the FMR1 5'UTR. Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000920

• Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

  Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

  Study phs001433

• 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

• H3K27Ac ChIP-seq of 9 cHL cell lines

  The dataset contains 36 ChIP-seq data for H3K27Ac and their corresponging inputs for 9 cHL cell lines. Data are raw paired-end fasq files for each histone and input, and for each cell line.

  Dataset EGAD50000001272

• scRNA and spatial-seq of human skin wound healing

  Human skin acute wound healing contains 12 samples of scRNA-seq and 16 samples of spatial transcriptomics, Human skin chronic wound data contains 9 samples scRNA-seq.

  Dataset EGAD50000000813

• ChIP-seq peaks of H3K27ac

  ChIP-seq peaks of H3K27ac. The dataset includes FASTQ files, BAM files, and analyses of the ChIP-seq peaks of H3K27ac determined using MACS2

  Dataset EGAD00001008964

• RNA sequencing data for Molecular Characterization of ETMRs

  The dataset contains two samples from one patient. As a representative FFPE tissue sample, ET174 was histologically iden- tified, targeted and microdissected with a puncher for nucleic acid extraction. RNA was extracted using the automated Maxwell system with the Maxwell 16 LEV RNA FFPE Kit (Promega), according to the manufacturer’s instructions. To evaluate FFPE RNA quality, we used the percentage of RNA fragments >200 nt fragment determination value (DV200). Only RNA samples with DV200 > 70% were included for sequencing on a NextSeq 500 (Illumina). Eight lanes have been sequenced resulting in 16 Fastq files (paired end).

  Dataset EGAD00001006209

• NanoString nCounter® PanCancer IO 360™on anti-PD1/anti-PD1+CTLA4 in patients with metastatic melanoma

  Patients with advanced melanoma were treated with standard-of-care single agent anti-PD-1 (nivolumab or pembrolizumab) or a combined anti-PD-1+anti-CTLA-4 (ipilimumab) therapy. Patients were retrospectively identified, based on formalin-fixed paraffin-embedded (FFPE) tissue availability. Total RNA was isolated from macro-dissected FFPE tissue sections using the AllPrep DNA/RNA FFPE Kit (Qiagen) or High Pure FFPET RNA Isolation Kit (Roche) according to the manufacturer’s instructions. RNA quantity was assessed on Qubit, and RNA integrity was assessed using the Tapestation system (Agilent). Total RNA samples (60ng/ul, total 200ng) were used as input for the NanoString PanCancer IO360 Panel, run on the nCounter MAX/FLEX prep station and scanner. Samples were hybridised for 20hrs, and each cartridge contained a panel standard.

  Study EGAS00001006977

• ATAC-Seq and CTCF ChIP-Seq on the OCIAML-2 cell line

  Study EGAS00001004741

• Single Cell Dissection of the Tumour Microenvironment Reveals Dynamic Interplay Shaping the Tumour Immunity Continuum in Ovarian Cancer

  Diverse tumour immune phenotypes with distinct T cell infiltration patterns result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these phenotypes remain elusive. Here, we provide a high-resolution dissection of the tumour microenvironment representative of different tumour immune phenotypes. By performing single-cell RNA sequencing (scRNAseq) of the tumour, immune, and stromal compartments from 15 ovarian cancer patients, we characterized the diverse cellular and functional phenotypes, as well as dynamic interplay within and between these components. Infiltrated and excluded tumours markedly differed from desert tumours in several tumour cell intrinsic features, including high interferon response, antigen presentation and oxidative phosphorylation. Moreover, these tumours were characterized by tumour associated macrophage (TAM)-like myeloid subsets, while desert tumours were enriched in myeloid derived suppressive cell (MDSC)-like myeloid subsets. Infiltrated and excluded tumours differed in their T cell composition and fibroblast subsets. While dysfunctional CD8+ GZMB T cells and IL1-activated fibroblasts (IL1 CAFs) were associated with infiltrated tumours, pre-dysfunctional CD8+ GZMK T cells and TGFB-activated fibroblasts (TGFB CAFs) were enriched in excluded tumours. These findings validated in bulk transcriptomic profiles of 1071 ovarian tumours and using in situ hybridization. Furthermore, our study revealed chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumour cell-T cell crosstalk via a CXC16-CXCR6 axis, stromal-immune cell crosstalk via CXCL12/14-CXCR4 signalling, and TAM-like macrophage-T cell crosstalk through CXCR3-CXCL9/10/11 signalling. Our in-depth characterization of the tumour environment and intercellular interactions provides novel insights into potential molecular mechanisms that shape the distinct biology of tumour immune phenotypes. Our findings may inform novel therapeutic strategies for potentially shifting tumours along the immunity continuum to improve clinical benefit from cancer immunotherapies.

  Study EGAS00001004935

• 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

• Whole genome sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Paired-end 150 basepair whole genome sequencing of 94 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Libraries were prepared using the Illumina® TruSeq™ DNA Nano library preparation method according to the manufacturer’s instructions at The University of Melbourne Centre for Cancer Research (UMCCR) using 200ng input DNA and a 550 base pair insert size. Samples were sequenced in separate batches on the Illumina® Nova-Seq 6000 according to manufacturer’s instructions (Illumina, USA). Included in this dataset are FASTQ format files containing raw read data, CRAM format files containing reads aligned to GRCh38, and VCF format files containing germline variants calls.

  Dataset EGAD50000000502

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• 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

• Sequencing_component_for_the_whole_genome_methylation_analysis_in_PBMCs_and_cell_subsets__pilot_study_

  DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

  Study EGAS00001000490

• 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

• 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

• 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

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

  Study EGAS00001007472

• Whole-Exome-Seq-Dataset

  Whole-Exome-Seq-Dataset

  Dataset EGAD00001000042